CMS 2014 Projects (NRA (2014)


 

Andrews (CMS 2014) (2014)
Project Title:Regional Inverse Modeling in North and South America for the NASA Carbon Monitoring System

Science Team
Members:

Arlyn Andrews, NOAA Earth System Research Laboratory (Project Lead)
Lei Hu, NOAA / CIRES
Anna Michalak, Carnegie Institution for Science
John Miller, NOAA Global Monitoring Laboratory

Solicitation:NASA: Carbon Monitoring System (2014)
Precursor Projects: Andrews (CMS 2011)  
Successor Projects: Andrews (CMS 2016)  
Abstract: We propose a single follow-on proposal combining our projects North American Regional-Scale Flux Estimation and Observing System Design for the NASA Carbon Monitoring System (A. Andrews, PI) and In situ CO2-based evaluation of the Carbon Monitoring System flux product (J. Miller, PI) awarded under the 2012 CMS solicitation. Both projects leveraged available in situ measurements of CO2 and used high-resolution regional inverse modeling tools to quantify CO2 fluxes on regional scales and to investigate consistency among in situ and remote sensing datasets. Under the first project, we incorporated remote sensing measurements of CO2 into CarbonTracker-Lagrange, a NOAA-led effort to implement a regional inverse modeling framework for North America that uses footprints from a suite of Lagrangian transport models and a flexible inversion scheme with geostatistical and Bayesian capability. The inversions conducted for this project complement the CMS Flux Pilot estimates, because they are obtained for a regional domain and at higher resolution (1o), using different transport models (i.e. Lagrangian vs. Eulerian), augmented CO2 data sets (in situ and remote sensing), and using explicit matrix inversions rather than a data assimilation approach. Footprints (surface influence functions) for over 3 million ground-based, airborne, and satellite receptors were computed and are being made available to the research community. The second project used in situ atmospheric CO2 data, globally and with a South American focus, to evaluate products from the CMS Flux Pilot project. The South American component of the project focused on comparing CMS modeled CO2 concentrations with observed vertical profiles from aircraft above the Brazilian Amazon, a critically important yet under-sampled region where extensive cloud and aerosol contamination limit the usefulness of satellite data. Here we propose to refine and further develop the Lagrangian inversion framework and to complete the on-going flux inversions for North America and South America, leveraging datasets collected under the North American Carbon Program and through our partnerships with researchers in Brazil and taking into account uncertainties caused by satellite retrieval errors and model inadequacies, such as errors in simulated atmospheric transport and limitations of current inversion approaches. As detailed below, the proposed work will make heavy use of NASA assets, including TCCON and the upcoming OCO-2 XCO¬2 and chlorophyll fluorescence observations along with NASA remote sensing data products describing land cover and vegetation. We will also use and evaluate NASA model products (e.g., MERRA transport fields and the CMS Flux Product), thus strengthening links to NOAAs CarbonTracker effort and supporting the development of an integrated Carbon Monitoring System. The proposed work will develop strategies for incorporating diverse CO2 observations and quantifying fluxes at scales relevant for Monitoring, Reporting and Verification (MRV) and quantifying uncertainties of CMS products.
Project Associations:
  • CMS
CMS Primary Theme:
  • Land-Atmosphere Flux
CMS Science Theme(s):
  • Atmospheric Transport
  • Land-Atmosphere Flux
  • MRV

Participants:

Arlyn Andrews, NOAA Earth System Research Laboratory
Lei Hu, NOAA / CIRES
Anna Michalak, Carnegie Institution for Science
John Miller, NOAA Global Monitoring Laboratory

Project URL(s): None provided.
 
Data
Products:
Product Title:  Measurement Sampling Footprints: 2013 - 2015 (TCCON, OCO-2, GOSAT)
Time Period:  2007-2010; 1 July - 20 August 2012; 2015
Description:  - Quantify fluxes at scales relevant for MRV using strategies that incorporate diverse carbon dioxide observations.
Status:  Preliminary
CMS Science Theme(s):  Atmospheric Transport; Land-Atmosphere Flux; MRV
Keywords:  Flux/Movement (; anthropogenic;; terrestrial; ; atmospheric)
Spatial Extent:  North and South Americas
Spatial Resolution:  1 latitude x 1 longitude; 0.1 latitude x 0.1 longitude for subdomain centered on measurement location
Temporal Frequency:  Hourly
Input Data Products:  TCCON, OCO-2 XCO2, ACOS/GOSAT, NOAA surface and aircraft observations, Environment Canada surface CO2, Earth Networks CO2, Penn State / Ameriflux CO2, NCAR RACCOON CO2, IPEN (Brazil) in situ CO2
Algorithm/Models Used:  GEOS transport fields, STILT-WRF, STILT-BRAMS, HYSPLIT-HRRR, Geostatistical Inverse Modeling (GIM), Bayesian Inverse Modeling, NOAA CarbonTracker
Evaluation:  CMS Global Flux project (Bowman-02, Ott-01), multiple transport models, GOSAT, surface and aircraft network
Intercomparison Efforts/Gaps:  NOAA CarbonTracker
Uncertainty Estimates:  Comparison of Footprints from multiple transport models, comparison of simulated CO2 between WRF-STILT and with CMS Global Flux project Mole fraction fields (Bowman-02, Ott-01) forced by same fluxes
Uncertainty Categories:  All: ensemble, deterministic, model-data comparison, model-model comparison, data-data comparison
Application Areas:  - MRV, REDD+; - GHG emissions inventory; - Cap-and-trade program; - Land management
Relevant Policies/Programs:  US National Greenhouse Gas Inventory (NGHGI) baseline reporting to the UN Framework Convention on Climate Change (UNFCCC), Clean Air Act (CAA), U.S. Carbon Cycle Science Program (USCCSP), North American Carbon Program (NACP), North American Leaders' Declaration on Climate Change and Clean Energy (NALS)
Potential Users:  EPA, USDA, NASA (GOSAT, ACOS, & OCO-2 *Chris O'Dell* science teams), and stakeholders of any emissions verification project, other atmospheric transport modelers and inverse modelers
Stakeholders:  
Current Application Readiness Level:  5
Start Application Readiness Level:  1
Target Application Readiness Level:  9
Future Developments:  - Collaborate with CMS flux teams.
Limitations:  - Ground-based data used for optimization is sparse.; - Limited information on the fidelity of the atmospheric transport model.
Date When Product Available:  Summer 2010 available now, 2007-2010 available before Nov meeting, 2015 available with 6 month delay from real time
Assigned Data Center:  Goddard
Metadata URL(s):
Data Server URL(s):

http://www.esrl.noaa.gov/gmd/ccgg/carbontracker-lagrange/
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  CO2 Flux Estimates 2013-2015
Time Period:  2007-2010; 1 July - 20 August 2012; 2015
Description:  - Quantify fluxes at scales relevant for MRV using strategies that incorporate diverse carbon dioxide observations.
Status:  Public
CMS Science Theme(s):  Atmospheric Transport; Land-Atmosphere Flux; MRV
Keywords:  Flux/Movement (; anthropogenic;; terrestrial; ; atmospheric)
Spatial Extent:  North and South Americas
Spatial Resolution:  1 latitude x 1 longitude
Temporal Frequency:  3-hourly (will be aggregated to coarser resolution for reporting)
Input Data Products:  TCCON, OCO-2 XCO2, chlorophyll fluorescence observations, and NASA remote sensing data products on land cover and vegetation, ACOS/GOSAT, NOAA surface and aircraft observations, Environment Canada surface CO2, Earth Networks CO2, Penn State / Ameriflux CO2, NCAR RACCOON CO2, IPEN (Brazil) in situ CO2
Algorithm/Models Used:  GEOS transport fields, STILT-WRF, STILT-BRAMS, HYSPLIT-HRRR, Geostatistical Inverse Modeling (GIM), Bayesian Inverse Modeling, NOAA CarbonTracker
Evaluation:  CMS Global Flux project (Bowman-02, Ott-01), multiple transport models, GOSAT, surface and aircraft network
Intercomparison Efforts/Gaps:  NOAA CarbonTracker
Uncertainty Estimates:  Formal grid-scale uncertainty estimates from inversion and across a suite of inversions using different priors, data-weighing and assumptions
Uncertainty Categories:  All: ensemble, deterministic, model-data comparison, model-model comparison, data-data comparison
Application Areas:  - MRV, REDD+; - GHG emissions inventory; - Cap-and-trade program; - Land management
Relevant Policies/Programs:  US National Greenhouse Gas Inventory (NGHGI) baseline reporting to the UN Framework Convention on Climate Change (UNFCCC), Clean Air Act (CAA), U.S. Carbon Cycle Science Program (USCCSP), North American Carbon Program (NACP), North American Leaders' Declaration on Climate Change and Clean Energy (NALS)
Potential Users:  EPA, USDA, NASA (GOSAT, ACOS, & OCO-2 *Chris O'Dell* science teams), and stakeholders of any emissions verification project
Stakeholders:  
Current Application Readiness Level:  5
Start Application Readiness Level:  1
Target Application Readiness Level:  9
Future Developments:  - Collaborate with CMS flux teams.
Limitations:  - Ground-based data used for optimization is sparse.; - Limited information on the fidelity of the atmospheric transport model.
Date When Product Available:  Summer 2010 available now. Summer 2012 and 2007-2010 available by 31 March 2015.
Assigned Data Center:  Goddard
Metadata URL(s):

https://www.esrl.noaa.gov/gmd/ccgg/arc/?id=131
Data Server URL(s):

https://www.esrl.noaa.gov/gmd/ccgg/arc/?id=131

http://www.esrl.noaa.gov/gmd/ccgg/carbontracker-lagrange/
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Uncertainty evaluations of CMS products
Time Period:  2007-2010; 1 July - 20 August 2012; 2015
Description:  - Quantify uncertainties of CMS products.
Status:  Planned
CMS Science Theme(s):  Atmospheric Transport; Land-Atmosphere Flux; MRV
Keywords:  Uncertainties & Standard Errors
Spatial Extent:  North and South Americas
Spatial Resolution:  1 latitude x 1 longitude
Temporal Frequency:  3-hourly (will be aggregated to coarser resolution for reporting)
Input Data Products:  TCCON, OCO-2 XCO2, chlorophyll fluorescence observations, and NASA remote sensing data products on land cover and vegetation, ACOS/GOSAT, NOAA surface and aircraft observations, Environment Canada surface CO2, Earth Networks CO2, Penn State / Ameriflux CO2, NCAR RACCOON CO2, IPEN (Brazil) in situ CO2
Algorithm/Models Used:  GEOS transport fields, STILT-WRF, STILT-BRAMS, HYSPLIT-HRRR, Geostatistical Inverse Modeling (GIM), Bayesian Inverse Modeling, NOAA CarbonTracker
Evaluation:  CMS Global Flux project (Bowman-02, Ott-01), multiple transport models, GOSAT, surface and aircraft network
Intercomparison Efforts/Gaps:  NOAA CarbonTracker
Uncertainty Estimates:  Comparison between High-resolution in situ data-informed fluxes from Lagrangian inversion with CMS Global Flux project Mole Fraction fields
Uncertainty Categories:  All: ensemble, deterministic, model-data comparison, model-model comparison, data-data comparison
Application Areas:  - MRV, REDD+; - GHG emissions inventory; - Cap-and-trade program; - Land management
Relevant Policies/Programs:  US National Greenhouse Gas Inventory (NGHGI) baseline reporting to the UN Framework Convention on Climate Change (UNFCCC), Clean Air Act (CAA), U.S. Carbon Cycle Science Program (USCCSP), North American Carbon Program (NACP), North American Leaders' Declaration on Climate Change and Clean Energy (NALS)
Potential Users:  EPA, USDA, NASA (GOSAT, ACOS, & OCO-2 *Chris O'Dell* science teams), and stakeholders of any emissions verification project
Stakeholders:  
Current Application Readiness Level:  3
Start Application Readiness Level:  1
Target Application Readiness Level:  9
Future Developments:  - Collaborate with CMS flux teams.
Limitations:  - Ground-based data used for optimization is sparse.; - Limited information on the fidelity of the atmospheric transport model.
Date When Product Available:  Summer 2010 available now. Summer 2012 and 2007-2010 available by 31 March 2015.
Assigned Data Center:  GES DISC
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

 
Publications: Hu, L., Andrews, A. E., Thoning, K. W., Sweeney, C., Miller, J. B., Michalak, A. M., Dlugokencky, E., Tans, P. P., Shiga, Y. P., Mountain, M., Nehrkorn, T., Montzka, S. A., McKain, K., Kofler, J., Trudeau, M., Michel, S. E., Biraud, S. C., Fischer, M. L., Worthy, D. E. J., Vaughn, B. H., White, J. W. C., Yadav, V., Basu, S., van der Velde, I. R. 2019. Enhanced North American carbon uptake associated with El Nino. Science Advances. 5(6). DOI: 10.1126/sciadv.aaw0076

Nehrkorn, T., Eluszkiewicz, J., Wofsy, S. C., Lin, J. C., Gerbig, C., Longo, M., Freitas, S. 2010. Coupled weather research and forecasting-stochastic time-inverted lagrangian transport (WRF-STILT) model. Meteorology and Atmospheric Physics. 107(1-2), 51-64. DOI: 10.1007/s00703-010-0068-x

Yadav, V., Michalak, A. M. 2013. Improving computational efficiency in large linear inverse problems: an example from carbon dioxide flux estimation. Geoscientific Model Development. 6(3), 583-590. DOI: 10.5194/gmd-6-583-2013

Gourdji, S. M., Hirsch, A. I., Mueller, K. L., Yadav, V., Andrews, A. E., Michalak, A. M. 2010. Regional-scale geostatistical inverse modeling of North American CO<sub>2</sub> fluxes: a synthetic data study. Atmospheric Chemistry and Physics. 10(13), 6151-6167. DOI: 10.5194/acp-10-6151-2010

Gourdji, S. M., Mueller, K. L., Yadav, V., Huntzinger, D. N., Andrews, A. E., Trudeau, M., Petron, G., Nehrkorn, T., Eluszkiewicz, J., Henderson, J., Wen, D., Lin, J., Fischer, M., Sweeney, C., Michalak, A. M. 2012. North American CO<sub>2</sub> exchange: inter-comparison of modeled estimates with results from a fine-scale atmospheric inversion. Biogeosciences. 9(1), 457-475. DOI: 10.5194/bg-9-457-2012

5th NACP All-Investigators Meeting Posters (2015):
  • A Lagrangian Framework for North American Regional-Scale Flux Estimation and Observing System Design -- (Arlyn Elizabeth Andrews, Kirk Thoning, John Miller, Michael Trudeau, Pieter Tans, Marikate Mountain, Thomas Nehrkorn, Anna M Michalak, Vineet Yadav, Christopher O'Dell, Christopher Sloop, Roland Draxler, Ariel Stein, Doug Worthy) [abstract]


 

Baker (CMS 2014) (2014)
Project Title:A Global High-Resolution Atmospheric Data Assimilation System for Carbon Flux Monitoring and Verification

Science Team
Members:

David Baker, CIRA/Colorado State University (Project Lead)

Solicitation:NASA: Carbon Monitoring System (2014)
Abstract: Measurements of atmospheric CO2 concentration have provided a top-down view of the global carbon cycle, clarifying the impact of the anthropogenic fossil fuel input, and giving a rough latitudinal breakdown of the uptake of the fossil input by the oceans and land biosphere. NASA and other space agencies around the world have invested great effort in designing satellite missions to measure column-integrated CO2 concentrations from space, in hopes of getting enough spatio-temporal coverage to resolve surface CO2 fluxes at regional scales -- it is hoped that the processes driving the uptake and release of CO2 will be easier to identify at these scales, leading to better predictions of CO2 levels and global warming in the future. These CO2 measurements complement direct measurements of plant biomass nicely, since they sense the impact of other land ecosystem processes less easily measured (e.g., carbon stored below the ground in roots and soils, and carbon running off into streams and groundwater), as well as the impact of fossil fuel and biomass burning, and air-sea fluxes. Global flux inversion studies based on atmospheric measurements could thus be used as a check on the more direct measurement of plant biomass. Alternatively, they could be used as a framework for interpreting the biomass measurements in the context of the broader carbon cycle. If the flux estimates from such a system could be made at a spatial resolutions fine enough to parse the results across geopolitical boundaries, with reliable uncertainty estimates, they could be suitable for carbon trading and treaty verification purposes. The density and reliability of current satellite CO2 measurements have limited their usefulness towards this end so far, but the expected explosion of satellite CO2 data in the coming decade or two, including eventually from satellites in geosynchronous and highly-elliptic orbits rapidly scanning the land surface, should make this feasible. If CO2 fluxes must be resolved at scales of 1x1 deg or better to attribute them to individual countries reliably, then there is also a computational challenge to overcome in implementing such an inversion system: atmospheric transport models take roughly an order of magnitude longer to run each time the spatial resolution is doubled; if the resolution of the fluxes is increased from current levels (order 4x4 deg) to 1x1 deg, then the inversions should take roughly a hundred times longer to complete. Running the models at even finer scales is desirable, to come closer to the scales at which the measurements are actually made (e.g. of order 3 km2 for an OCO-2 pixel FOV). Here we propose a new inversion method that will efficiently estimate fluxes at sub-degree resolution, while at the same time producing a high-rank covariance matrix that quantifies flux uncertainty at the same scales. It solves the same Euler-Lagrange equations as the currently-used variational methods do, but does so with a direct matrix inversion rather than with an iterative descent method. The measurements are grouped into blocks, and a basis function is run through the transport model for each block, with the highest spatial resolution being coarsened as mixing spreads out the signal. The variational method is thus effectively parallelized, since the basis functions can be run on separate processors. Once the matrix inversion is done, the resulting covariance matrix may be used as a preconditioner in the standard iterative search to refine the finest scales. The rank of the covariance matrix produced by the method is limited only by the size of the matrix that can be inverted in memory, e.g. O(10,000), as compared with the O(100) matrices currently produced by ensemble Kalman filter and iterative variational methods. We test the accuracy of the uncertainties given by this covariance matrix and use it to compare the ability of different CO2-measuring satellite concepts to constrain country-scale annual mean fluxes.
Project Associations:
  • CMS
CMS Primary Theme:
  • Global Surface-Atmosphere Flux
CMS Science Theme(s):
  • Atmospheric Transport
  • Land-Atmosphere Flux
  • Ocean-Atmosphere Flux
  • Global Surface-Atmosphere Flux
  • MRV

Participants:

David Baker, CIRA/Colorado State University

Project URL(s): None provided.
 
Data
Products:
Product Title:  CO2 flux estimate uncertainties.
Time Period:  2012-2016
Description:  - Quantify carbon flux uncertainties at sub-degree resolution by producing a high-rank covariance matrix. he representer method to be used is laid out in A.F. Bennett's Inverse Modeling of the Ocean and Atmosphere, Cambridge University Press, 2002, 234 pp. (see Section 1.3 in particular.) An assessment of the ability of the representer method to speed up the flux calculation of the iterative 4Dvar method, as well as the production of a fine-resolution flux estimate using simulated data
Status:  Planned
CMS Science Theme(s):  Atmospheric Transport; Global Surface-Atmosphere Flux; Land-Atmosphere Flux; MRV; Ocean-Atmosphere Flux
Keywords:  Uncertainties & Standard Errors
Spatial Extent:  Global
Spatial Resolution:  2/3 x 5/6 (lat/lon)
Temporal Frequency:  Hourly, daily, weekly
Input Data Products:  GEOS 5.7.2 and GEOS-5 FP meteorological analyses; GOSAT and OCO-2 measurements
Algorithm/Models Used:  Bennett's representer method and the gradient-based method of Rabier and Courtier (1992)
Evaluation:  Compare the uncertainties taken from the covariance matrices of the two methods
Intercomparison Efforts/Gaps:  Compare the flux uncertainty estimates from this project with those from other flux projects (like Bowman's JPL effort) at various spatial and temporal resolutions.
Uncertainty Estimates:  Both Bennett's representer method and the gradient-based method of Rabier and Courtier (1992) produce high-rank covariance matrices representing the random errors in the estimated high-resolution fluxes
Uncertainty Categories:  The covariance matrix from the representer method is deterministic (obtained from a matrix inversion), while that from the Rabier and Courtier method is stochastic (determined from the flux differences obtained with an ensemble of randomly-perturbed observations)
Application Areas:  - MRV; - GHG emissions inventory; - Global carbon budget calculations; - Land management
Relevant Policies/Programs:  CMS Flux Pilot Project (FPP), Clean Air Act (CAA), National Climate Assessment of U.S. Global Change Research Program, Doha/Kyoto, USCCSP, Intergovernmental Panel on Climate Change (IPCC)
Potential Users:  CMS flux teams, NOAA Carbon Tracker, EPA, DOE, Group on Earth Observations (GEO)
Stakeholders:  
Current Application Readiness Level:  2
Start Application Readiness Level:  2
Target Application Readiness Level:  7
Future Developments:  We plan to let end users know of the benefits of our method, as we are able to demonstrate that in the course of the project.
Limitations:  The limitations of the method are to be assessed in the proposed work.
Date When Product Available:  The accuracy of the high-resolution uncertainties given by the representer method will be assessed by comparing them to uncertainties from the Rabier and Courtier method; this will be started in Year
Assigned Data Center:  Goddard
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  

Product Title:  CO2 flux estimates.
Time Period:  2012-2016
Description:  - Provide carbon flux estimates at sub-degree resolution using a new inversion method. The representer method to be used is laid out in A.F. Bennett's Inverse Modeling of the Ocean and Atmosphere, Cambridge University Press, 2002, 234 pp. (see Section 1.3 in particular.) An assessment of the ability of the representer method to speed up the flux calculation of the iterative 4Dvar method, as well as the production of a fine-resolution flux estimate using simulated data
Status:  Planned
CMS Science Theme(s):  Atmospheric Transport; Global Surface-Atmosphere Flux; Land-Atmosphere Flux; MRV; Ocean-Atmosphere Flux
Keywords:  Flux/Movement (; anthropogenic;; terrestrial; ; oceanic; ; atmospheric)
Spatial Extent:  Global
Spatial Resolution:  2/3 x 5/6 (lat/lon)
Temporal Frequency:  Hourly, daily, weekly
Input Data Products:  GEOS 5.7.2 and GEOS-5 FP meteorological analyses; GOSAT and OCO-2 measurements
Algorithm/Models Used:  Bennett's representer method (a direct matrix inversion) and variational data assimilation (4DVar, an iterative minimization method)
Evaluation:  Compare to a known truth in an OSSE framework
Intercomparison Efforts/Gaps:  Compare the ability of different CO2 measuring satellite concepts to constrain country-scale annual mean fluxes.
Uncertainty Estimates:  High-rank covariance matrix (see below)
Uncertainty Categories:  The covariance matrix from the representer method is deterministic (obtained from a matrix inversion), while that from the Rabier and Courtier method is stochastic (determined from the flux differences obtained with an ensemble of randomly-perturbed observations)
Application Areas:  - MRV; - GHG emissions inventory; - Global carbon budget calculations; - Land management
Relevant Policies/Programs:  CMS Flux Pilot Project (FPP), Clean Air Act (CAA), National Climate Assessment of U.S. Global Change Research Program, Doha/Kyoto, USCCSP, Intergovernmental Panel on Climate Change (IPCC)
Potential Users:  CMS flux teams, NOAA Carbon Tracker, EPA, DOE, Group on Earth Observations (GEO)
Stakeholders:  
Current Application Readiness Level:  2
Start Application Readiness Level:  2
Target Application Readiness Level:  7
Future Developments:  We plan to let end users know of the benefits of our method, as we are able to demonstrate that in the course of the project.
Limitations:  The limitations of the method are to be assessed in the proposed work.
Date When Product Available:  Projected Sept 2015
Assigned Data Center:  Goddard
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  

 
Publications: Basu, S., Baker, D. F., Chevallier, F., Patra, P. K., Liu, J., Miller, J. B. 2018. The impact of transport model differences on CO<sub>2</sub> surface flux estimates from OCO-2 retrievals of column average CO<sub>2</sub>. Atmospheric Chemistry and Physics. 18(10), 7189-7215. DOI: 10.5194/acp-18-7189-2018


 

Bowman (CMS 2014) (2014)
Project Title:Continuation of the CMS-Flux Pilot Project

Science Team
Members:

Kevin Bowman, JPL (Project Lead)
Kevin Gurney, Northern Arizona University
Daven Henze, University of Colorado
Deborah (Debbie) Huntzinger, Northern Arizona University
Junjie Liu, JPL
Dimitris Menemenlis, Jet Propulsion Laboratory

Solicitation:NASA: Carbon Monitoring System (2014)
Precursor Projects: Gunson-Pawson-Potter (2009)  
Successor Projects: Bowman (CMS 2016)  
Abstract: Dramatic increases in atmospheric CO2 from preindustrial to present day is the primary driver of climate change. The spatial origin of the CO2 growth rate and its variability is a complex function of anthropogenic, terrestrial, and oceanic processes. The tilt of industrial emissions towards developing countries has increased the uncertainty in fossil fuel emissions. Shifts in the patterns of climate variability, e.g., toward Central Pacific 'Modoki' El Ninos, can intensify the magnitude and extend of droughts, e.g., 2005 and 2010 Amazonian droughts, leading to increased fires and reduction of GPP while modulating atmosphere-ocean pCO2 exchange across entire ocean basins. In order to quantify the role of spatio-temporal patterns of anthropogenic and natural carbon fluxes in controlling atmospheric CO2, we will build upon the success of the Carbon Monitoring System Flux Pilot Project (CMS-Flux) initiated in Phase I and continued in Phase II. We propose to produce observationally-constrained and spatially-explicit 'bottom-up' estimates of anthropogenic, oceanic, and terrestrial carbon fluxes using the CMS-Flux system balanced against the observed atmospheric growth rate from 2010-2015. These estimates are a continuation of anthropogenic emissions from the Fossil Fuel Assimilation System (FFDAS), assimilated oceanic pCO2 fluxes from ECCO2-Darwin, and terrestrial ecosystem fluxes from CASA-GFED3 model and the MsTMIP ensemble models. While supported by separately funded NASA activities, these terrestrial ecosystem fluxes will be modified to be consistent with a fully balanced carbon cycle. These carbon fluxes will be subsequently updated by CMS-Flux constrained by GOSAT and OCO-2 xCO2 observations from 2010-2015. We propose to assimilate ancillary satellite observations of CO and NO2 from MOPITT and OMI into CMS-Flux in order to attribute posterior fluxes to combustion and industrial carbon fluxes, respectively. These estimates exploit the inherent capacity of CMS-Flux to assimilate both passive and chemically active atmospheric constituents within the same framework. Building upon the analysis in previous CMS-Flux estimates, we will further investigate the correlation of climate variability, especially drought, on regional carbon fluxes and how they modulate the atmospheric CO2 growth rate. Using these estimates of CO and NO2 emissions, we will attribute the variability of those carbon fluxes to combustion processes. Given the breadth of work, we expect the proposal to cost 500K/year.
Project Associations:
  • CMS
CMS Primary Theme:
  • Global Surface-Atmosphere Flux
CMS Science Theme(s):
  • Land-Atmosphere Flux
  • Ocean-Atmosphere Flux
  • Global Surface-Atmosphere Flux

Participants:

Kevin Bowman, JPL
George (Jim) Collatz, NASA GSFC - retired
Joshua Fisher, Chapman University
Kevin Gurney, Northern Arizona University
Daven Henze, University of Colorado
Deborah (Debbie) Huntzinger, Northern Arizona University
Meemong Lee, JPL
Junjie Liu, JPL
Rohit Mathur, U.S. EPA
Dimitris Menemenlis, Jet Propulsion Laboratory

Project URL(s): http://cmsflux.jpl.nasa.gov
 
Data
Products:
Product Title:  Carbon Monitoring System Carbon Flux for Fire L4 V1 (CMSFluxFire) at GES DISC
Start Date:  01/2010      End Date:  01/2013
Description:  This dataset provides the Carbon Flux for Fires.

The NASA Carbon Monitoring System (CMS) is designed to make significant contributions in characterizing, quantifying, understanding, and predicting the evolution of global carbon sources and sinks through improved monitoring of carbon stocks and fluxes. The System will use the full range of NASA satellite observations and modeling/analysis capabilities to establish the accuracy, quantitative uncertainties, and utility of products for supporting national and international policy, regulatory, and management activities. CMS will maintain a global emphasis while providing finer scale regional information, utilizing space-based and surface-based data and will rapidly initiate generation and distribution of products both for user evaluation and to inform near-term policy development and planning.
Status:  Archived
CMS Science Theme(s):  Land-Atmosphere Flux
Keywords:  
Spatial Extent:  Global
Spatial Resolution:  4 x 5
Temporal Frequency:  
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  GHG emissions inventory
Relevant Policies/Programs:  National Climate Assessment of U.S. Global Change Research Program
Potential Users:  Group on Earth Observations (GEO), CMS flux teams, EPA, NOAA, DOE Integrated Assessment (IA) and Climate and Earth System Modeling groups
Stakeholders:  
Current Application Readiness Level:  5
Start Application Readiness Level:  5
Target Application Readiness Level:  6
Future Developments:  
Limitations:  
Date When Product Available:  October 2017
Assigned Data Center:  GES DISC
Metadata URL(s):

https://acdisc.gsfc.nasa.gov/data/CMS/CMSFluxTotalprior.1/doc/README.CMS_Flux_V1.pdf
Data Server URL(s):

https://acdisc.gsfc.nasa.gov/data/CMS/CMSFluxFire.1/
Archived Data Citation:  Kevin Bowman(2017), Carbon Monitoring System Carbon Flux for Fire L4 V1, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed [Data Access Date] 10.5067/3C1Y3EJB1E7Q

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

Product Title:  Carbon Monitoring System Flux for Fossil Fuel L4 V1 (CMSFluxFossilfuel) at GES DISC
Start Date:  01/2010      End Date:  01/2013
Description:  This dataset provides the Carbon Flux for Fossil Fuel.

The NASA Carbon Monitoring System (CMS) is designed to make significant contributions in characterizing, quantifying, understanding, and predicting the evolution of global carbon sources and sinks through improved monitoring of carbon stocks and fluxes. The System will use the full range of NASA satellite observations and modeling/analysis capabilities to establish the accuracy, quantitative uncertainties, and utility of products for supporting national and international policy, regulatory, and management activities. CMS will maintain a global emphasis while providing finer scale regional information, utilizing space-based and surface-based data and will rapidly initiate generation and distribution of products both for user evaluation and to inform near-term policy development and planning.
Status:  Archived
CMS Science Theme(s):  Land-Atmosphere Flux
Keywords:  
Spatial Extent:  Global
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  5
Start Application Readiness Level:  5
Target Application Readiness Level:  6
Future Developments:  
Limitations:  
Date When Product Available:  October 2017
Assigned Data Center:  GES DISC
Metadata URL(s):

https://acdisc.gsfc.nasa.gov/data/CMS/CMSFluxTotalprior.1/doc/README.CMS_Flux_V1.pdf
Data Server URL(s):

https://acdisc.gsfc.nasa.gov/data/CMS/CMSFluxFossilfuel.1/
Archived Data Citation:  Kevin Bowman(2017), Carbon Monitoring System Flux for Fossil Fuel L4 V1, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed [Data Access Date] 10.5067/JC6BC3CPEJXQ

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

Product Title:  Carbon Monitoring System Flux for Ocean Carbon L4 V1 (CMSFluxOcean) at GES DISC
Start Date:  01/2010      End Date:  01/2013
Description:  This dataset provides the Carbon Flux for Ocean Carbon.

The NASA Carbon Monitoring System (CMS) is designed to make significant contributions in characterizing, quantifying, understanding, and predicting the evolution of global carbon sources and sinks through improved monitoring of carbon stocks and fluxes. The System will use the full range of NASA satellite observations and modeling/analysis capabilities to establish the accuracy, quantitative uncertainties, and utility of products for supporting national and international policy, regulatory, and management activities. CMS will maintain a global emphasis while providing finer scale regional information, utilizing space-based and surface-based data and will rapidly initiate generation and distribution of products both for user evaluation and to inform near-term policy development and planning.
Status:  Archived
CMS Science Theme(s):  Global Surface-Atmosphere Flux; Ocean-Atmosphere Flux
Keywords:  Flux/Movement (oceanic; atmospheric)
Spatial Extent:  Global
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  Sea level anomaly from altimeters on Jason-1, Jason-2/Ocean Surface; Topography Mission (OSTM), and Environmental Satellite (Envisat); sea surface temperature from the Advanced Microwave Scanning Radiometer-; EOS (AMSR-E); and temperature and salinity profiles from the Argo profiling floats. Global surface pCO2 (LDEO) Database of the Carbon Dioxide Information Analysis Center. GLODAP Atlas.
Algorithm/Models Used:  ECCO2-Darwin
Evaluation:  Evaluation against Takahash atlas. See Brix et al, Ocean Modeling, submitted
Intercomparison Efforts/Gaps:  Intercomparisons with Goddard NOBM. See Ott et al, JGR, in revision
Uncertainty Estimates:  Uncertainty calculated from Green's function
Uncertainty Categories:  Ensemble
Application Areas:  Ocean acidification mitigation; - Land management (riverine export)
Relevant Policies/Programs:  CMS FPP, CAA, National Climate Assessment of U.S. Global Change Research Program, Doha/Kyoto, USCCSP, Intergovernmental Panel on Climate Change (IPCC)
Potential Users:  Group on Earth Observations (GEO), Regional Greenhouse Gas Initiative (RGGI), CMS flux teams, EPA, NOAA *John Miller*, DOE Integrated Assessment (IA) and Climate and Earth System Modeling groups
Stakeholders:  Environmental Protection Agency (Point of Contact: Rohit Mathur)
Current Application Readiness Level:  5
Start Application Readiness Level:  5
Target Application Readiness Level:  6
Future Developments:  Engage EPA, carbon-climate community. Improve cmsflux.jpl.nasa.gov website
Limitations:  Model bias and drift can be challenging over short time scales. pCO2 measurements extremely limited.
Date When Product Available:  October 2017
Assigned Data Center:  GES DISC
Metadata URL(s):

https://acdisc.gsfc.nasa.gov/data/CMS/CMSFluxTotalprior.1/doc/README.CMS_Flux_V1.pdf
Data Server URL(s):

https://acdisc.gsfc.nasa.gov/data/CMS/CMSFluxOcean.1/
Archived Data Citation:  Kevin Bowman(2017), Carbon Monitoring System Flux for Ocean Carbon L4 V1, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed [Data Access Date] 10.5067/96SSC2AOLE3Z

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

Product Title:  Carbon Monitoring System Flux for Posterior Fire Carbon L4 V1 (CMSFluxFirepost) at GES DISC
Start Date:  01/2010      End Date:  01/2013
Description:  This dataset provides the Carbon Flux for Fires.

The NASA Carbon Monitoring System (CMS) is designed to make significant contributions in characterizing, quantifying, understanding, and predicting the evolution of global carbon sources and sinks through improved monitoring of carbon stocks and fluxes. The System will use the full range of NASA satellite observations and modeling/analysis capabilities to establish the accuracy, quantitative uncertainties, and utility of products for supporting national and international policy, regulatory, and management activities. CMS will maintain a global emphasis while providing finer scale regional information, utilizing space-based and surface-based data and will rapidly initiate generation and distribution of products both for user evaluation and to inform near-term policy development and planning.
Status:  Archived
CMS Science Theme(s):  Land-Atmosphere Flux
Keywords:  
Spatial Extent:  Global
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  Environmental Protection Agency (Point of Contact: Rohit Mathur)
Current Application Readiness Level:  5
Start Application Readiness Level:  5
Target Application Readiness Level:  6
Future Developments:  
Limitations:  
Date When Product Available:  October 2017
Assigned Data Center:  GES DISC
Metadata URL(s):

https://acdisc.gsfc.nasa.gov/data/CMS/CMSFluxFirepost.1/doc/README.CMS_Flux_V1.pdf
Data Server URL(s):

https://acdisc.gsfc.nasa.gov/data/CMS/CMSFluxFirepost.1/
Archived Data Citation:  Kevin Bowman(2017), Carbon Monitoring System Flux for Posterior Fire Carbon L4 V1, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed [Data Access Date] 10.5067/N3HM4V0JZVLB

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

Product Title:  Carbon Monitoring System Flux for Posterior Total Carbon L4 V1 (CMSFluxTotalpost) at GES DISC
Start Date:  01/2010      End Date:  01/2013
Description:  This dataset provides the Carbon Flux for Posterior Total Carbon.

The NASA Carbon Monitoring System (CMS) is designed to make significant contributions in characterizing, quantifying, understanding, and predicting the evolution of global carbon sources and sinks through improved monitoring of carbon stocks and fluxes. The System will use the full range of NASA satellite observations and modeling/analysis capabilities to establish the accuracy, quantitative uncertainties, and utility of products for supporting national and international policy, regulatory, and management activities. CMS will maintain a global emphasis while providing finer scale regional information, utilizing space-based and surface-based data and will rapidly initiate generation and distribution of products both for user evaluation and to inform near-term policy development and planning.
Status:  Archived
CMS Science Theme(s):  Global Surface-Atmosphere Flux; Land-Atmosphere Flux
Keywords:  Flux/Movement (; oceanic; ; atmospheric; ; anthropogenic; ; terrestrial)
Spatial Extent:  Global
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  GOSAT and OCO-2 XCO2, MOPITT CO, meteorological analysis. Input used for carbon cycle fluxes described separately.
Algorithm/Models Used:  4D-variational assimilation (Liu et al, Tellus, 2014)
Evaluation:  See CMS 2012 John Miller (Miller-J-01). Evaluated against TCCON, surface, and aircraft data.
Intercomparison Efforts/Gaps:  Intercomparisons needed against other systems.
Uncertainty Estimates:  Formal posterior uncertainty calculations -- see Liu et al, Tellus, 2014 and Bousserez et al, QJRMS, in revision
Uncertainty Categories:  Ensemble, deterministic, model-data comparison
Application Areas:  GHG emissions inventory; - Land management; - Global carbon budget calculations;
Relevant Policies/Programs:  CMS FPP, CAA, National Climate Assessment of U.S. Global Change Research Program, Doha/Kyoto, USCCSP, Intergovernmental Panel on Climate Change (IPCC)
Potential Users:  Group on Earth Observations (GEO), Regional Greenhouse Gas Initiative (RGGI), CMS flux teams, EPA, NOAA *John Miller*, DOE Integrated Assessment (IA) and Climate and Earth System Modeling groups
Stakeholders:  Environmental Protection Agency (Point of Contact: Rohit Mathur)
Current Application Readiness Level:  5
Start Application Readiness Level:  5
Target Application Readiness Level:  6
Future Developments:  Engage EPA, carbon-climate community. Improve cmsflux.jpl.nasa.gov website
Limitations:  - Atmospherically constrained fluxes have uncertainty associated with the transport model.; - Potential biases of satellite data (e.g. calibration).; - Finer temporal resolution than monthly may not be appropriate for detecting changes in fluxes.
Date When Product Available:  October 2017
Assigned Data Center:  GES DISC
Metadata URL(s):

https://acdisc.gsfc.nasa.gov/data/CMS/CMSFluxFirepost.1/doc/README.CMS_Flux_V1.pdf
Data Server URL(s):

https://acdisc.gsfc.nasa.gov/data/CMS/CMSFluxTotalpost.1/
Archived Data Citation:  Kevin Bowman(2017), Carbon Monitoring System Flux for Posterior Total Carbon L4 V1, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed [Data Access Date] 10.5067/QCBSYYY4CENP

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

Product Title:  Carbon Monitoring System Flux for Prior Total Carbon L4 V1 (CMSFluxTotalprior) at GES DISC
Start Date:  01/2010      End Date:  01/2013
Description:  This dataset provides the Carbon Flux for Prior Total Carbon.

The NASA Carbon Monitoring System (CMS) is designed to make significant contributions in characterizing, quantifying, understanding, and predicting the evolution of global carbon sources and sinks through improved monitoring of carbon stocks and fluxes. The System will use the full range of NASA satellite observations and modeling/analysis capabilities to establish the accuracy, quantitative uncertainties, and utility of products for supporting national and international policy, regulatory, and management activities. CMS will maintain a global emphasis while providing finer scale regional information, utilizing space-based and surface-based data and will rapidly initiate generation and distribution of products both for user evaluation and to inform near-term policy development and planning.
Status:  Archived
CMS Science Theme(s):  Land-Atmosphere Flux; Ocean-Atmosphere Flux
Keywords:  
Spatial Extent:  Global
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  GOSAT and OCO-2 XCO2, MOPITT CO, meteorological analysis. Input used for carbon cycle fluxes described separately.
Algorithm/Models Used:  4D-variational assimilation (Liu et al, Tellus, 2014)
Evaluation:  See CMS 2012 John Miller (Miller-J-01). Evaluated against TCCON, surface, and aircraft data.
Intercomparison Efforts/Gaps:  Intercomparisons needed against other systems.
Uncertainty Estimates:  Formal posterior uncertainty calculations -- see Liu et al, Tellus, 2014 and Bousserez et al, QJRMS, in revision
Uncertainty Categories:  Ensemble, deterministic, model-data comparison
Application Areas:  GHG emissions inventory; - Land management; - Global carbon budget calculations;
Relevant Policies/Programs:  CMS FPP, CAA, National Climate Assessment of U.S. Global Change Research Program, Doha/Kyoto, USCCSP, Intergovernmental Panel on Climate Change
Potential Users:  Group on Earth Observations (GEO), Regional Greenhouse Gas Initiative (RGGI), CMS flux teams, EPA, NOAA *John Miller*, DOE Integrated Assessment
Stakeholders:  Environmental Protection Agency (Point of Contact: Rohit Mathur)
Current Application Readiness Level:  5
Start Application Readiness Level:  5
Target Application Readiness Level:  6
Future Developments:  Engage EPA, carbon-climate community. Improve cmsflux.jpl.nasa.gov website
Limitations:  Atmospherically constrained fluxes have uncertainty associated with the transport model.; - Potential biases of satellite data (e.g. calibration).; - Finer temporal resolution than monthly may not be appropriate for detecting changes in fluxes.
Date When Product Available:  October 2017
Assigned Data Center:  GES DISC
Metadata URL(s):

https://acdisc.gsfc.nasa.gov/data/CMS/CMSFluxTotalprior.1/doc/README.CMS_Flux_V1.pdf
Data Server URL(s):

https://acdisc.gsfc.nasa.gov/data/CMS/CMSFluxTotalprior.1/
Archived Data Citation:  Kevin Bowman(2017), Carbon Monitoring System Flux for Prior Total Carbon L4 V1, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed [Data Access Date] 10.5067/F0JBNZ5QYWY6

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

Product Title:  Carbon Monitoring System Flux for Shipping, Aviation, and Chemical Sources L4 V1 (CMSFluxMISC) at GES DISC
Start Date:  01/2000      End Date:  01/2001
Description:  This dataset provides the Carbon Flux for Shipping, Aviation, and Chemical Sources.

The NASA Carbon Monitoring System (CMS) is designed to make significant contributions in characterizing, quantifying, understanding, and predicting the evolution of global carbon sources and sinks through improved monitoring of carbon stocks and fluxes. The System will use the full range of NASA satellite observations and modeling/analysis capabilities to establish the accuracy, quantitative uncertainties, and utility of products for supporting national and international policy, regulatory, and management activities. CMS will maintain a global emphasis while providing finer scale regional information, utilizing space-based and surface-based data and will rapidly initiate generation and distribution of products both for user evaluation and to inform near-term policy development and planning.
Status:  Archived
CMS Science Theme(s):  Land-Atmosphere Flux; Ocean-Atmosphere Flux
Keywords:  
Spatial Extent:  Global
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  5
Start Application Readiness Level:  5
Target Application Readiness Level:  6
Future Developments:  
Limitations:  
Date When Product Available:  October 2017
Assigned Data Center:  GES DISC
Metadata URL(s):

https://acdisc.gsfc.nasa.gov/data/CMS/CMSFluxMISC.1/doc/README.CMS_Flux_V1.pdf
Data Server URL(s):

https://acdisc.gsfc.nasa.gov/data/CMS/CMSFluxMISC.1/
Archived Data Citation:  Kevin Bowman(2017), Carbon Monitoring System Flux for Shipping, Aviation, and Chemical Sources L4 V1, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed [Data Access Date] 10.5067/RLT7JTCRJ11M

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

Product Title:  Carbon Monitoring System Flux from the Net Ecosystem Exchange L4 V1 (CMSFluxNEE) at GES DISC
Start Date:  01/2010      End Date:  01/2013
Description:  This dataset provides the Carbon Flux from the Net Ecosystem Exchange.

The NASA Carbon Monitoring System (CMS) is designed to make significant contributions in characterizing, quantifying, understanding, and predicting the evolution of global carbon sources and sinks through improved monitoring of carbon stocks and fluxes. The System will use the full range of NASA satellite observations and modeling/analysis capabilities to establish the accuracy, quantitative uncertainties, and utility of products for supporting national and international policy, regulatory, and management activities. CMS will maintain a global emphasis while providing finer scale regional information, utilizing space-based and surface-based data and will rapidly initiate generation and distribution of products both for user evaluation and to inform near-term policy development and planning.
Status:  Archived
CMS Science Theme(s):  Global Surface-Atmosphere Flux; Land-Atmosphere Flux
Keywords:  Flux/Movement (; terrestrial; ; atmospheric)
Spatial Extent:  Global
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  Seasonal/interannual phenology: monthly; GIMMS AVHRR NDVI; -Woody allocation: MODIS Vegetation Continuous ; Fields; -Vegetation class: MODIS Land Cover Type; -Seasonal/interannual burned area (daily): MODIS ; Surface Reflectance & Fire detections; MERRA.
Algorithm/Models Used:  CASA-GFED3, MsTMIP ensemble models, Sib4
Evaluation:  Evaluation against eddy-covariance measurements, atmospheric data.
Intercomparison Efforts/Gaps:  MsTMIP is an intercomparison activity.
Uncertainty Estimates:  Ensemble uncertainty, parametric uncertainty and data comparisons.
Uncertainty Categories:  Ensemble and model-data comparison
Application Areas:  GHG emissions inventory; - Land management; - Global carbon budget calculations
Relevant Policies/Programs:  CMS FPP, CAA, National Climate Assessment of U.S. Global Change Research Program, Doha/Kyoto, USCCSP, Intergovernmental Panel on Climate Change
Potential Users:  Group on Earth Observations (GEO), Regional Greenhouse Gas Initiative (RGGI), CMS flux teams, EPA, NOAA *John Miller*, DOE Integrated Assessment
Stakeholders:  Environmental Protection Agency (Point of Contact: Rohit Mathur)
Current Application Readiness Level:  5
Start Application Readiness Level:  5
Target Application Readiness Level:  6
Future Developments:  Engage EPA, carbon-climate community. Improve cmsflux.jpl.nasa.gov website
Limitations:  See Huntzinger CMS 2012, Collatz CMS 2013 for additional details.
Date When Product Available:  October 2017
Assigned Data Center:  GES DISC
Metadata URL(s):

https://acdisc.gsfc.nasa.gov/data/CMS/CMSFluxNEE.1/doc/README.CMS_Flux_V1.pdf
Data Server URL(s):

https://acdisc.gsfc.nasa.gov/data/CMS/CMSFluxNEE.1/
Archived Data Citation:  Kevin Bowman(2017), Carbon Monitoring System Flux from the Net Ecosystem Exchange L4 V1, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed [Data Access Date] 10.5067/4ACY6GOWQ7BB

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

Product Title:  Carbon Monitoring System Carbon Flux for Fire L4 V2 (CMSFluxFire) at GES DISC
Start Date:  01/2010      End Date:  01/2017     (2010-2016)
Description:  This dataset provides the Carbon Flux for Fires.

The NASA Carbon Monitoring System (CMS) is designed to make significant contributions in characterizing, quantifying, understanding, and predicting the evolution of global carbon sources and sinks through improved monitoring of carbon stocks and fluxes. The System will use the full range of NASA satellite observations and modeling/analysis capabilities to establish the accuracy, quantitative uncertainties, and utility of products for supporting national and international policy, regulatory, and management activities. CMS will maintain a global emphasis while providing finer scale regional information, utilizing space-based and surface-based data and will rapidly initiate generation and distribution of products both for user evaluation and to inform near-term policy development and planning.
Status:  Archived
CMS Science Theme(s):  Global Surface-Atmosphere Flux
Keywords:  
Spatial Extent:  Global
Spatial Resolution:  4 degrees by 5 degrees
Temporal Frequency:  Monthly
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  GES DISC
Metadata URL(s):
10.5067/HO07ZJEQBMHE
Data Server URL(s):
10.5067/HO07ZJEQBMHE
Archived Data Citation:  Kevin Bowman (2017), Carbon Monitoring System Carbon Flux for Fire L4 V2, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/HO07ZJEQBMHE

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

Product Title:  Carbon Monitoring System Carbon Flux for Fossil Fuel Prior L4 V2 (CMSFluxFossilFuelPrior) at GES DISC
Start Date:  01/2010      End Date:  01/2017
Description:  This dataset provides the Carbon Flux for Fossil Fuel Prior.

The NASA Carbon Monitoring System (CMS) is designed to make significant contributions in characterizing, quantifying, understanding, and predicting the evolution of global carbon sources and sinks through improved monitoring of carbon stocks and fluxes. The System will use the full range of NASA satellite observations and modeling/analysis capabilities to establish the accuracy, quantitative uncertainties, and utility of products for supporting national and international policy, regulatory, and management activities. CMS will maintain a global emphasis while providing finer scale regional information, utilizing space-based and surface-based data and will rapidly initiate generation and distribution of products both for user evaluation and to inform near-term policy development and planning.
Status:  Archived
CMS Science Theme(s):  Global Surface-Atmosphere Flux
Keywords:  
Spatial Extent:  Global
Spatial Resolution:  4 x 5 degrees
Temporal Frequency:  Monthly
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  GES DISC
Metadata URL(s):
10.5067/JHP9Q8DBRQCB
Data Server URL(s):
10.5067/JHP9Q8DBRQCB
Archived Data Citation:  Kevin Bowman (2020), Carbon Monitoring System Carbon Flux for Fossil Fuel Prior L4 V2, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/JHP9Q8DBRQCB

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

Product Title:  Carbon Monitoring System Carbon Flux for Ocean Prior L4 V2 (CMSFluxOceanPrior) at GES DISC
Start Date:  01/2010      End Date:  01/2017     (2010-2016)
Description:  This dataset provides the Carbon Flux for Ocean Carbon Prior.

The NASA Carbon Monitoring System (CMS) is designed to make significant contributions in characterizing, quantifying, understanding, and predicting the evolution of global carbon sources and sinks through improved monitoring of carbon stocks and fluxes. The System will use the full range of NASA satellite observations and modeling/analysis capabilities to establish the accuracy, quantitative uncertainties, and utility of products for supporting national and international policy, regulatory, and management activities. CMS will maintain a global emphasis while providing finer scale regional information, utilizing space-based and surface-based data and will rapidly initiate generation and distribution of products both for user evaluation and to inform near-term policy development and planning.
Status:  Archived
CMS Science Theme(s):  Global Surface-Atmosphere Flux
Keywords:  
Spatial Extent:  Global
Spatial Resolution:  4 x 5 degrees
Temporal Frequency:  Monthly
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  GES DISC
Metadata URL(s):
10.5067/MYWVXT4RWQO3
Data Server URL(s):
10.5067/MYWVXT4RWQO3
Archived Data Citation:  Kevin Bowman (2017), Carbon Monitoring System Carbon Flux for Ocean Prior L4 V2, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/MYWVXT4RWQO3

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

Product Title:  Carbon Monitoring System Carbon Flux from the Net Biome Exchange L4 V2 (CMSFluxNBE) at GES DISC
Start Date:  01/2010      End Date:  01/2017     (2010-2016)
Description:  This dataset provides the Carbon Flux from the Net Biome Exchange.

The NASA Carbon Monitoring System (CMS) is designed to make significant contributions in characterizing, quantifying, understanding, and predicting the evolution of global carbon sources and sinks through improved monitoring of carbon stocks and fluxes. The System will use the full range of NASA satellite observations and modeling/analysis capabilities to establish the accuracy, quantitative uncertainties, and utility of products for supporting national and international policy, regulatory, and management activities. CMS will maintain a global emphasis while providing finer scale regional information, utilizing space-based and surface-based data and will rapidly initiate generation and distribution of products both for user evaluation and to inform near-term policy development and planning.
Status:  Archived
CMS Science Theme(s):  Global Surface-Atmosphere Flux
Keywords:  
Spatial Extent:  Global
Spatial Resolution:  4 x 5 degrees
Temporal Frequency:  Monthly
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  GES DISC
Metadata URL(s):
10.5067/ZQQ4M53CP6L2
Data Server URL(s):
10.5067/ZQQ4M53CP6L2
Archived Data Citation:  Kevin Bowman (2020), Carbon Monitoring System Carbon Flux from the Net Biome Exchange L4 V2, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/ZQQ4M53CP6L2

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

Product Title:  Carbon Monitoring System Carbon Flux from the Net Biome Exchange Prior L4 V2 (CMSFluxNBEPrior) at GES DISC
Start Date:  01/2010      End Date:  01/2017     (2010-2016)
Description:  This dataset provides the Carbon Flux from the Net Biome Exchange Prior.

The NASA Carbon Monitoring System (CMS) is designed to make significant contributions in characterizing, quantifying, understanding, and predicting the evolution of global carbon sources and sinks through improved monitoring of carbon stocks and fluxes. The System will use the full range of NASA satellite observations and modeling/analysis capabilities to establish the accuracy, quantitative uncertainties, and utility of products for supporting national and international policy, regulatory, and management activities. CMS will maintain a global emphasis while providing finer scale regional information, utilizing space-based and surface-based data and will rapidly initiate generation and distribution of products both for user evaluation and to inform near-term policy development and planning.
Status:  Archived
CMS Science Theme(s):  Global Surface-Atmosphere Flux
Keywords:  
Spatial Extent:  Global
Spatial Resolution:  4 degrees by 5 degrees
Temporal Frequency:  Monthly
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
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Assigned Data Center:  GES DISC
Metadata URL(s):
10.5067/3DVX5KRI8AYL
Data Server URL(s):
10.5067/3DVX5KRI8AYL
Archived Data Citation:  Kevin Bowman (2020), Carbon Monitoring System Carbon Flux from the Net Biome Exchange Prior L4 V2, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/3DVX5KRI8AYL

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

Product Title:  Carbon Monitoring System Carbon Flux Total L4 V2 (CMSFluxTotal) at GES DISC
Start Date:  01/2010      End Date:  01/2017
Description:  This dataset provides the Carbon Flux for Posterior Total Carbon.

The NASA Carbon Monitoring System (CMS) is designed to make significant contributions in characterizing, quantifying, understanding, and predicting the evolution of global carbon sources and sinks through improved monitoring of carbon stocks and fluxes. The System will use the full range of NASA satellite observations and modeling/analysis capabilities to establish the accuracy, quantitative uncertainties, and utility of products for supporting national and international policy, regulatory, and management activities. CMS will maintain a global emphasis while providing finer scale regional information, utilizing space-based and surface-based data and will rapidly initiate generation and distribution of products both for user evaluation and to inform near-term policy development and planning.
Status:  Archived
CMS Science Theme(s):  Global Surface-Atmosphere Flux
Keywords:  
Spatial Extent:  Global
Spatial Resolution:  4 degrees by 5 degrees
Temporal Frequency:  Monthly
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Algorithm/Models Used:  
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Current Application Readiness Level:  
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Target Application Readiness Level:  
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Limitations:  
Date When Product Available:  
Assigned Data Center:  GES DISC
Metadata URL(s):
10.5067/71F2I0PR2ISD
Data Server URL(s):
10.5067/71F2I0PR2ISD
Archived Data Citation:  Kevin Bowman (2020), Carbon Monitoring System Carbon Flux Total L4 V2, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/71F2I0PR2ISD

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

 
Publications: Bowman, K. W., Liu, J., Bloom, A. A., Parazoo, N. C., Lee, M., Jiang, Z., Menemenlis, D., Gierach, M. M., Collatz, G. J., Gurney, K. R., Wunch, D. 2017. Global and Brazilian Carbon Response to El Nino Modoki 2011-2010. Earth and Space Science. 4(10), 637-660. DOI: 10.1002/2016EA000204

Liu, J., Bowman, K. W., Lee, M. 2016. Comparison between the Local Ensemble Transform Kalman Filter (LETKF) and 4D-Var in atmospheric CO 2 flux inversion with the Goddard Earth Observing System-Chem model and the observation impact diagnostics from the LETKF. Journal of Geophysical Research: Atmospheres. 121(21), 13,066-13,087. DOI: 10.1002/2016JD025100

Liu, J., Bowman, K. W., Schimel, D. S., Parazoo, N. C., Jiang, Z., Lee, M., Bloom, A. A., Wunch, D., Frankenberg, C., Sun, Y., O'Dell, C. W., Gurney, K. R., Menemenlis, D., Gierach, M., Crisp, D., Eldering, A. 2017. Contrasting carbon cycle responses of the tropical continents to the 2015-2016 El Nino. Science. 358(6360). DOI: 10.1126/science.aam5690

Liu, J., Bowman, K. W., Schimel, D., Parazoo, N. C., Jiang, Z., Lee, M., Bloom, A. A., Wunch, D., Frankenberg, C., Sun, Y., O'Dell, C. W., Gurney, K. R., Menemenlis, D., Gierach, M., Crisp, D., Eldering, A. 2018. Response to Comment on "Contrasting carbon cycle responses of the tropical continents to the 2015-2016 El Nino". Science. 362(6418), eaat1211. DOI: 10.1126/science.aat1211

Liu, J., Bowman, K., Parazoo, N. C., Bloom, A. A., Wunch, D., Jiang, Z., Gurney, K. R., Schimel, D. 2018. Detecting drought impact on terrestrial biosphere carbon fluxes over contiguous US with satellite observations. Environmental Research Letters. 13(9), 095003. DOI: 10.1088/1748-9326/aad5ef

Ott, L. E., Pawson, S., Collatz, G. J., Gregg, W. W., Menemenlis, D., Brix, H., Rousseaux, C. S., Bowman, K. W., Liu, J., Eldering, A., Gunson, M. R., Kawa, S. R. 2015. Assessing the magnitude of CO2flux uncertainty in atmospheric CO2records using products from NASA's Carbon Monitoring Flux Pilot Project. Journal of Geophysical Research: Atmospheres. 120(2), 734-765. DOI: 10.1002/2014JD022411

Schwalm, C. R., Huntzinger, D. N., Fisher, J. B., Michalak, A. M., Bowman, K., Ciais, P., Cook, R., El-Masri, B., Hayes, D., Huang, M., Ito, A., Jain, A., King, A. W., Lei, H., Liu, J., Lu, C., Mao, J., Peng, S., Poulter, B., Ricciuto, D., Schaefer, K., Shi, X., Tao, B., Tian, H., Wang, W., Wei, Y., Yang, J., Zeng, N. 2015. Toward "optimal" integration of terrestrial biosphere models. Geophysical Research Letters. 42(11), 4418-4428. DOI: 10.1002/2015GL064002

Liu, J., Bowman, K. 2016. A method for independent validation of surface fluxes from atmospheric inversion: Application to CO 2. Geophysical Research Letters. 43(7), 3502-3508. DOI: 10.1002/2016GL067828

Worden, J. R., Turner, A. J., Bloom, A., Kulawik, S. S., Liu, J., Lee, M., Weidner, R., Bowman, K., Frankenberg, C., Parker, R., Payne, V. H. 2015. Quantifying lower tropospheric methane concentrations using GOSAT near-IR and TES thermal IR measurements. Atmospheric Measurement Techniques. 8(8), 3433-3445. DOI: 10.5194/amt-8-3433-2015

Liu, J., Bowman, K. W., Henze, D. K. 2015. Source-receptor relationships of column-average CO2and implications for the impact of observations on flux inversions. Journal of Geophysical Research: Atmospheres. 120(10), 5214-5236. DOI: 10.1002/2014JD022914

Zhang, X., Gurney, K. R., Rayner, P., Liu, Y., Asefi-Najafabady, S. 2014. Sensitivity of simulated CO<sub>2</sub> concentration to regridding of global fossil fuel CO<sub>2</sub> emissions. Geoscientific Model Development. 7(6), 2867-2874. DOI: 10.5194/gmd-7-2867-2014

Asefi-Najafabady, S., Rayner, P. J., Gurney, K. R., McRobert, A., Song, Y., Coltin, K., Huang, J., Elvidge, C., Baugh, K. 2014. A multiyear, global gridded fossil fuel CO2emission data product: Evaluation and analysis of results. Journal of Geophysical Research: Atmospheres. 119(17), 10,213-10,231. DOI: 10.1002/2013JD021296

Archived Data Citations: Kevin Bowman(2017), Carbon Monitoring System Flux for Posterior Fire Carbon L4 V1, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed [Data Access Date] 10.5067/N3HM4V0JZVLB

Kevin Bowman(2017), Carbon Monitoring System Flux for Shipping, Aviation, and Chemical Sources L4 V1, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed [Data Access Date] 10.5067/RLT7JTCRJ11M

Kevin Bowman(2017), Carbon Monitoring System Flux from the Net Ecosystem Exchange L4 V1, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed [Data Access Date] 10.5067/4ACY6GOWQ7BB

Kevin Bowman(2017), Carbon Monitoring System Flux for Posterior Total Carbon L4 V1, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed [Data Access Date] 10.5067/QCBSYYY4CENP

Kevin Bowman(2017), Carbon Monitoring System Flux for Prior Total Carbon L4 V1, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed [Data Access Date] 10.5067/F0JBNZ5QYWY6

Kevin Bowman(2017), Carbon Monitoring System Carbon Flux for Fire L4 V1, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed [Data Access Date] 10.5067/3C1Y3EJB1E7Q

Kevin Bowman(2017), Carbon Monitoring System Flux for Fossil Fuel L4 V1, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed [Data Access Date] 10.5067/JC6BC3CPEJXQ

Kevin Bowman(2017), Carbon Monitoring System Flux for Ocean Carbon L4 V1, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed [Data Access Date] 10.5067/96SSC2AOLE3Z

Kevin Bowman (2020), Carbon Monitoring System Carbon Flux from the Net Biome Exchange Prior L4 V2, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/3DVX5KRI8AYL

Kevin Bowman (2017), Carbon Monitoring System Carbon Flux for Ocean Prior L4 V2, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/MYWVXT4RWQO3

Kevin Bowman (2020), Carbon Monitoring System Carbon Flux from the Net Biome Exchange L4 V2, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/ZQQ4M53CP6L2

Kevin Bowman (2017), Carbon Monitoring System Carbon Flux for Fire L4 V2, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/HO07ZJEQBMHE

Kevin Bowman (2020), Carbon Monitoring System Carbon Flux Total L4 V2, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/71F2I0PR2ISD

Kevin Bowman (2020), Carbon Monitoring System Carbon Flux for Fossil Fuel Prior L4 V2, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/JHP9Q8DBRQCB

2015 NASA Carbon Cycle & Ecosystems Joint Science Workshop Poster(s)
  • Surface CO2 flux estimation and validation for 2010 and 2011 from CMS-Flux   --   (Junjie Liu, Kevin W Bowman, Michelle Gierach, George James Collatz, Meemong Lee, Kevin Robert Gurney, John Miller, Dimitris Menemenlis, Nicolas Bousserez)   [abstract]
5th NACP All-Investigators Meeting Posters (2015):
  • Diagnosing Atmospheric Transport Uncertainty in CMS-Flux and WRF Simulations -- (Martha Butler, Thomas Lauvaux, Junjie Liu, Kenneth James Davis, Kevin W Bowman) [abstract]   [poster]


 

Fatoyinbo (CMS 2014) (2014)
Project Title:Total Carbon Estimation in African Mangroves and Coastal Wetlands in Preparation for REDD and Blue Carbon Credits

Science Team
Members:

Temilola (Lola) Fatoyinbo, NASA GSFC (Project Lead)
David Lagomasino, East Carolina University

Solicitation:NASA: Carbon Monitoring System (2014)
Successor Projects: Fatoyinbo (CMS 2016)  
Abstract: Coastal Blue Carbon ecosystems such as mangroves, salt marshes and seagrass beds have the highest total carbon densities of all ecosystems. Although they only represent 3% of the total forest area, carbon emissions from mangrove destruction at current rates could be equivalent to 10% of carbon emissions from deforestation. The high carbon sequestration coupled with the high risk of destruction make mangroves a prime candidate for carbon mitigation initiatives such as the United Nations Collaborative Programme on Reducing Emissions from Deforestation and Degradation in Developing Countries (UN-REDD and REDD+). In mangroves especially, the extreme difficulty of the terrain has hindered the establishment of sufficient field plots needed to accurately measure carbon on the scale necessary to relate remotely sensed measurements with field measurements at accuracies of 10% to 20% as required for Monitoring, Reporting and Verification (MRV) activities. Furthermore, there is a large gap in knowledge in African mangrove ecosystems. We propose to develop a Mangrove Total Carbon Monitoring system in Gabon, Tanzania and Mozambique, three countries that are investing heavily in scientific and logistical aspects of developing MRV systems, through cooperation of the local governments and scientific institutions with international organizations such as the WWF, the UN-REDD programme, USAID, SilvaCarbon and Global Earth Observations-Forest Carbon Tracking (GEO-FCT). In Mozambique and Tanzania, The East Africa Carbon Mangrove Project was recently initiated by the US Forest Service on behalf of USAID to address carbon cycle issues relative to mangroves. The Zambezi River delta in Mozambique has been selected by WWF Mozambique and implemented by the US Forest Service as a baseline study on carbon stocks in mangroves to provide the basis for inclusion of mangroves in the Mozambique national REDD+ strategy. Through its strategic plan, Le Gabon Emergent, the Government of Gabon has committed to pursue sustainable development and a Gabon Forest Carbon Assessment has been initialized across the country. As part of these 3 initiatives there will be airborne lidar data acquired and made available in mangrove sites in all three countries. We will use a suite of commercial off-the-shelf datasets to estimate forest biomass, extend and cover change over time, including airborne LiDAR, Synthetic Aperture Radar (SAR) and Very High Resolution optical (VHR). Our proposed methodology takes into account that most MRV systems require repeated measurements of carbon stocks and acquiring airborne lidar data on a regular timeframe is costly and impractical. Thus we propose to use commercial spaceborne data from optical sensors as well as Synthetic Aperture Radar (SAR) missions. We will to use the most advanced 3-D remote sensing technology - Polarimetric Interferometric SAR or Pol-InSAR - as an operational technology that can augment, or even replace, costly acquisitions of Lidar data for MRV activities. We propose a 3D mapping methodology to quantitatively characterize forest structure and extent as well as change over time and to inform the field measurements site stratification and location. Our research strategy consists in using the airborne lidar to upscale field estimates of biomass to a larger scale and enable validation of TanDEM-X derived estimates of canopy height and biomass. We will develop a present day mangrove extent map using Landsat, SAR (ALOS-2) and Very high Resolution commercial optical data then adapt global forest change mapping algorithms to include mangrove forests and develop a timeseries of mangrove change in all three countries from 1990 to the present day. Finally we will coordinate a Mangrove Carbon Working Group composed of in-country and US experts to coordinate, disseminate and inform field, remote sensing and GIS experts on the use and generation of the data products from this study.
CMS Primary Theme:
  • Land Biomass
CMS Science Theme(s):
  • Land Biomass
  • Land-Atmosphere Flux
  • Land-Ocean Flux
  • Decision Support
  • MRV

Participants:

Temilola (Lola) Fatoyinbo, NASA GSFC
David Lagomasino, East Carolina University
Mwita Mangora, University of Dar es Salaam Institute of Marine Sciences
Aurelie Shapiro, World Wildlife Fund
Marc (Mac) Simard, Jet Propulsion Laboratory / Caltech
Carl Trettin, U.S. Forest Service Southern Research Station
Jan-Willem van Bochove, United Nations Environment Programme World Conservation Monitoring Centre
Eliakimu Zahabu, Sokoine University of Agriculture

Project URL(s): None provided.
 
Data
Products:
Product Title:  Mangrove forest biomass estimates.
Time Period:  2013-2015
Description:  - Develop a Mangrove Total Carbon Monitoring System in Gabon, Tanzania, and Mozambique.; - Provide estimates of forest biomass using a suite of COTS datasets.
Status:  Planned
CMS Science Theme(s):  Land Biomass; MRV
Keywords:  Carbon Stocks (; terrestrial)
Spatial Extent:  Gabon, Tanzania, and Mozambique
Spatial Resolution:  1m to 12 m
Temporal Frequency:  Single Product 2013/2014
Input Data Products:  Airborne Lidar (commercial COTS aircraft), Synthetic Aperture Radar (SAR), Very High Resolution optical (VHR), TanDEM-X Polarimetric Interferometric SAR (Pol-InSAR), field measurements.
Algorithm/Models Used:  Pol-InSAR
Evaluation:  Validate TanDEM-X derived estimates of canopy height and biomass with Lidar and Field.
Intercomparison Efforts/Gaps:  Comparison of Biomass and height estimates to those produced by Fatoyinbo and Simard (2013) and Hutchinson (2013)
Uncertainty Estimates:  Uncertainties estimated from model-data comparisons (Modeled Biomass - measured biomass)
Uncertainty Categories:  Ensemble and Model-Data Comparison
Application Areas:  - MRV, REDD+; - Forest inventory; - Land management; - Watershed protection plans
Relevant Policies/Programs:  REDD+, Le Gabon Emergent, Gabon Forest Carbon Assessment, Silvacarbon, GEO-FCT
Potential Users:  Forestry departments of Gabon, Tanzania, and Mozambique, WWF *Aurelie Shapiro*, USAID, USFS, Conservation International *Emily Pidgeon*, UNEP-WCMC, University Eduardo Mondlane
Stakeholders:  Gabon Space Agency (AGEOS); Omar Bongo University; US Forest Service (Point of Contact: Carl Trettin: ctrettin@fs.fed.us); US Forest Service (Point of Contact: Carl Trettin ctrettin@fs.fed.us)
Current Application Readiness Level:  5
Start Application Readiness Level:  3
Target Application Readiness Level:  6
Future Developments:  - Coordinate a Mangrove carbon working Group composed of in-country and US experts to Coordinate, disseminate, and Inform field, remote sensing, and GIS experts on the Use and generation of the data products from this project.
Limitations:  Not all of the uncertainties have been identified and quantified.
Date When Product Available:  Mozambique 2016, Tanzania 2016, Gabon 2017
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:9.54000 East Longitude:39.49000
North Latitude:0.38330 South Latitude:-25.95000

Product Title:  Mangrove forest cover change maps.
Time Period:  1990-2015
Description:  - Develop a time series of mangrove change in all three countries from 1990 to present day.
Status:  Planned
CMS Science Theme(s):  Land Biomass; Land-Atmosphere Flux; Land-Ocean Flux; MRV
Keywords:  Disturbance (land cover change)
Spatial Extent:  Gabon, Tanzania, and Mozambique
Spatial Resolution:  30 m
Temporal Frequency:  Annually 1990-2014
Input Data Products:  Landsat, SAR (ALOS-2), and VHR commercial optical data
Algorithm/Models Used:  Global forest change mapping algorithms
Evaluation:  Validate Landsat/SAR change with VHR optical data and field measurements
Intercomparison Efforts/Gaps:  Comparison of change with available regional and global change products such as Hansen et al, 2013.
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  - MRV, REDD+; - Forest inventory; - Land management; - Watershed protection plans
Relevant Policies/Programs:  REDD+, Le Gabon Emergent, Gabon Forest Carbon Assessment, Silvacarbon, GEO-FCT
Potential Users:  Forestry departments of Gabon, Tanzania, and Mozambique, WWF *Aurelie Shapiro*, USAID, USFS, Conservation International *Emily Pidgeon*, UNEP-WCMC, University Eduardo Mondlane
Stakeholders:  Gabon Space Agency (AGEOS); Omar Bongo University; University of Dar es Salaam Institute of Marine Sciences (Point of Contact: Mwita Mangora mmangora@yahoo.com); US Forest Service (Point of Contact: Carl Trettin: ctrettin@fs.fed.us); US Forest Service (Point of Contact: Carl Trettin ctrettin@fs.fed.us)
Current Application Readiness Level:  6
Start Application Readiness Level:  6
Target Application Readiness Level:  7
Future Developments:  - Coordinate a Mangrove carbon working Group composed of in-country and US experts to Coordinate, disseminate, and Inform field, remote sensing, and GIS experts on the Use and generation of the data products from this project.
Limitations:  Not all of the uncertainties have been identified and quantified.
Date When Product Available:  2016
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:9.54000 East Longitude:39.49000
North Latitude:0.38330 South Latitude:-25.95000

Product Title:  Mangrove forest extent maps.
Time Period:  1990-2015
Description:  - Provide Mangrove Forest extent maps using a suite of COTS datasets.
Status:  Planned
CMS Science Theme(s):  Land Biomass; MRV
Keywords:  Ecosystem Composition & Structure (forest extent)
Spatial Extent:  Gabon, Tanzania, and Mozambique
Spatial Resolution:  30 m
Temporal Frequency:  Single Product 2013/2014
Input Data Products:  Landsat, SAR (ALOS-2), and VHR commercial optical data
Algorithm/Models Used:  Land cover Classification algorithms
Evaluation:  Validate Landsat/SAR extent with VHR optical data and field measurements
Intercomparison Efforts/Gaps:  Comparison of Extent maps with Global products by Giri (2011) and Spalding (2011)
Uncertainty Estimates:  Uncertainties estimated from model-data comparisons (mapped Extent - field validation/VHR data)
Uncertainty Categories:  Model-Data Comparison
Application Areas:  - MRV, REDD+; - Forest inventory; - Land management; - Watershed protection plans
Relevant Policies/Programs:  REDD+, Le Gabon Emergent, Gabon Forest Carbon Assessment, Silvacarbon, GEO-FCT
Potential Users:  Forestry departments of Gabon, Tanzania, and Mozambique, WWF *Aurelie Shapiro*, USAID, USFS, Conservation International *Emily Pidgeon*, UNEP-WCMC, University Eduardo Mondlane
Stakeholders:  Gabon Space Agency (AGEOS); Omar Bongo University; University of Dar es Salaam Institute of Marine Sciences (Point of Contact: Mwita Mangora mmangora@yahoo.com); US Forest Service (Point of Contact: Carl Trettin: ctrettin@fs.fed.us); US Forest Service (Point of Contact: Carl Trettin ctrettin@fs.fed.us); World Wildlife Fund (Point of Contact: Aurelie Shapiro, aurelie.shapiro@wwf.de)
Current Application Readiness Level:  6
Start Application Readiness Level:  6
Target Application Readiness Level:  7
Future Developments:  - Coordinate a Mangrove carbon working Group composed of in-country and US experts to Coordinate, disseminate, and Inform field, remote sensing, and GIS experts on the Use and generation of the data products from this project.
Limitations:  Not all of the uncertainties have been identified and quantified.
Date When Product Available:  Mozambique 2015, Tanzania 2016, Gabon 2017
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:9.54000 East Longitude:39.49000
North Latitude:0.38330 South Latitude:-25.95000

Product Title:  CMS: Mangrove Canopy Characteristics and Land Cover Change, Tanzania, 1990-2014
Start Date:  01/1990      End Date:  12/2014     (1990-2014)
Description:  This data set provides canopy height, land cover change, and stand age estimates for mangrove forests in the Rufiji River Delta in Tanzania. The estimates were derived from a canopy height model (CHM) using TanDEM-X imagery and Polarimetric SAR interferometry (Pol-InSAR) techniques. Landsat imagery circa 1990 and circa 2014 was used to estimate stand age between 1994 and 2014 and for forest land cover change modeling.
Status:  Archived
CMS Science Theme(s):  Land Biomass
Keywords:  Disturbance (land cover change)
Spatial Extent:  Rufiji River Delta in Tanzania
Spatial Resolution:  Canopy height (12-m x 12-m), Land cover change (30-m x 30-m), stand age (30-m x 30-m)
Temporal Frequency:  One time estimate
Input Data Products:  Landsat, TanDEM-X imagery and Polarimetric SAR interferometry (Pol-InSAR) techniques
Algorithm/Models Used:  Global forest change mapping algorithms, canopy height model (CHM)
Evaluation:  Validate Landsat/SAR change with VHR optical data and field measurements.
Intercomparison Efforts/Gaps:  Comparison of change with available regional and global change products such as Hansen et al, 2013.
Uncertainty Estimates:  A +/- 2 m uncertainty was used for the canopy height estimates. This uncertainty was determined through previous studies. Google Earth imagery was also used extensively as an additional reference for the circa 2014 land cover classification, but not for the circa 1990 classification, as no imagery was available for this area for any date prior to 2009. A static +/- 1 year uncertainty was used for the stand age modeling.
Uncertainty Categories:  
Application Areas:  - MRV, REDD+; - Forest inventory; - Land management; - Watershed protection plans; - Climate mitigation and adaptation plans
Relevant Policies/Programs:  REDD+, Le Gabon Emergent, Gabon Forest Carbon Assessment, Silvacarbon, GEO-FCT
Potential Users:  Forestry departments of Gabon, Tanzania, and Mozambique, WWF *Aurelie Shapiro*, USAID, USFS, Conservation International *Emily Pidgeon*, UNEP-WCMC, University Eduardo Mondlane
Stakeholders:  Tanzania Forest Service; University of Dar es Salaam Institute of Marine Sciences (Point of Contact: Mwita Mangora mmangora@yahoo.com); US Forest Service (Point of Contact: Carl Trettin: ctrettin@fs.fed.us); US Forest Service (Point of Contact: Carl Trettin ctrettin@fs.fed.us)
Current Application Readiness Level:  6
Start Application Readiness Level:  6
Target Application Readiness Level:  7
Future Developments:  - Coordinate a Mangrove carbon working Group composed of in-country and US experts to Coordinate, disseminate, and Inform field, remote sensing, and GIS experts on the Use and generation of the data products from this project.
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1377
Data Server URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1377
Archived Data Citation:  Lagomasino, D., T. Fatoyinbo, S. Lee, E. Feliciano, C. Trettin, and M.C. Hansen. 2017. CMS: Mangrove Canopy Characteristics and Land Cover Change, Tanzania, 1990-2014. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1377

Bounding Coordinates:
West Longitude:39.19000 East Longitude:39.50000
North Latitude:-7.51000 South Latitude:-8.04000

Product Title:  CMS: Mangrove Canopy Height Estimates from Remote Imagery, Zambezi Delta, Mozambique
Start Date:  10/2011      End Date:  05/2014     (2011-2014)
Description:  This data set provides high resolution canopy height estimates for mangrove forests in the Zambezi Delta, Mozambique, Africa. The estimates were derived from three separate canopy height models (CHM) using airborne Lidar data, stereophotogrammetry with WorldView 1 imagery, and Interferometric-Synthetic Aperture Radar (In-SAR) techniques with TanDEM-X imagery. The data cover the period 2011-10-14 to 2014-05-06.
Status:  Archived
CMS Science Theme(s):  Land Biomass; MRV
Keywords:  canopy height; carbon stocks; biomass
Spatial Extent:  Zambezi River Delta, Mozambique
Spatial Resolution:  1m x 1m and 12m x 12m
Temporal Frequency:  One time estimate
Input Data Products:  Airborne Lidar (commercial COTS aircraft), Synthetic Aperture Radar (SAR), Very High Resolution optical (VHR), TanDEM-X Polarimetric Interferometric SAR (Pol-InSAR), field measurements
Algorithm/Models Used:  Pol-InSAR; Ames Stereopipeline
Evaluation:  General statistics including the mean, median, and standard deviations were determined for each of the CHMs. A comparative analysis was performed using root-mean-square-error (RMSE). The airborne CHM was used as a reference to assess the spaceborne CHMs. Canopies over 10-m were accurately predicted by all CHMs while the distributions of canopy height were best predicted by the VHR CHM.
Intercomparison Efforts/Gaps:  Comparison of Biomass and height estimates to those produced by Fatoyinbo and Simard (2013) and Hutchinson (2013)
Uncertainty Estimates:  Uncertainties estimated from model-data comparisons (Modeled height - measured height)
Uncertainty Categories:  Ensemble and Model-Data Comparison
Application Areas:  MRV, REDD+; - Forest inventory; - Land management; - Watershed protection plan
Relevant Policies/Programs:  REDD+, Le Gabon Emergent, Gabon Forest Carbon Assessment, Silvacarbon, GEO-FCT
Potential Users:  US Forest Service, Forestry departments of Gabon, Tanzania, and Mozambique, WWF *Aurelie Shapiro*, USAID, USFS, Conservation International *Emily Pidgeon*, UNEP-WCMC, University Eduardo Mondlane
Stakeholders:  University of Dar es Salaam Institute of Marine Sciences (Point of Contact: Mwita Mangora mmangora@yahoo.com); US Forest Service (Point of Contact: Carl Trettin: ctrettin@fs.fed.us)
Current Application Readiness Level:  6
Start Application Readiness Level:  5
Target Application Readiness Level:  7
Future Developments:  Complete mangrove canopy height estimates for the entire countries of Mozambique, Tanzania, and Gabon at 12m spatial resolution. Coordinate a Mangrove Carbon Working Group composed of in-country and US experts to coordinate, disseminate, and inform field, remote sensing, and GIS experts on the use and generation of the data products from this project.
Limitations:  Not all of the uncertainties have been identified and quantified.
Date When Product Available:  February 2017
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1357
Data Server URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1357
Archived Data Citation:  Lagomasino, D., T. Fatoyinbo, S. Lee, E. Feliciano, M. Simard, and C. Trettin. 2016. CMS: Mangrove Canopy Height Estimates from Remote Imagery, Zambezi Delta, Mozambique. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1357

Bounding Coordinates:
West Longitude:36.12000 East Longitude:36.34000
North Latitude:-18.63000 South Latitude:-18.92000

Product Title:  CMS: Mangrove Canopy Height from High-resolution Stereo Image Pairs, Mozambique, 2012
Start Date:  09/2012      End Date:  09/2012     (2012)
Description:  This data set provides canopy height estimates for mangrove forests at 0.6 x 0.6 m resolution in three study sites located in southeastern Mozambique, Africa: two sites on Inhaca Island and one in the Maputo Elephant Reserve, located in the southern province of Maputo for September, 2012. The estimates were derived from WorldView1 (WV-1) very high resolution (VHR) stereo images processed using the Ames Stereo Pipeline (ASP) digital surface model (DSM) tool.
Status:  Archived
CMS Science Theme(s):  Land Biomass; MRV
Keywords:  canopy height; carbon stocks; biomass
Spatial Extent:  Three sites in southern province of Maputo, Mozambique
Spatial Resolution:  0.6 m x 0.6 m
Temporal Frequency:  One time estimate
Input Data Products:  The estimates were derived from WorldView1 (WV-1) very high resolution (VHR) stereo images processed using the Ames Stereo Pipeline (ASP) digital surface model (DSM) tool.
Algorithm/Models Used:  Ames Stereo Pipeline (ASP) digital surface model (DSM) tool
Evaluation:  Canopy height estimated from VHR were compared to local field surveys and shuttle radar topography mission (SRTM) data collected in 2000 and 2014 to identify bias and errors. The VHR estimates were also compared to canopy height derived from coarse radar altimetry data collected from the shuttle radar topography mission (SRTM) in 2000, and SRTM 30-m data released in 2014.
Intercomparison Efforts/Gaps:  Comparison of Biomass and height estimates to those produced by Fatoyinbo and Simard (2013) and Hutchinson (2013)
Uncertainty Estimates:  Uncertainties estimated from model-data comparisons (Modeled height - measured height)
Uncertainty Categories:  Ensemble and Model-Data Comparison
Application Areas:  MRV, REDD+; - Forest inventory; - Land management; - Watershed protection plan
Relevant Policies/Programs:  REDD+, Le Gabon Emergent, Gabon Forest Carbon Assessment, Silvacarbon, GEO-FCT
Potential Users:  US Forest Service, Forestry departments of Gabon, Tanzania, and Mozambique, WWF *Aurelie Shapiro*, USAID, USFS, Conservation International *Emily Pidgeon*, UNEP-WCMC, University Eduardo Mondlane
Stakeholders:  University of Dar es Salaam Institute of Marine Sciences (Point of Contact: Mwita Mangora mmangora@yahoo.com); US Forest Service (Point of Contact: Carl Trettin: ctrettin@fs.fed.us)
Current Application Readiness Level:  6
Start Application Readiness Level:  5
Target Application Readiness Level:  7
Future Developments:  Complete mangrove canopy height estimates for the entire countries of Mozambique, Tanzania, and Gabon at 12m spatial resolution. Coordinate a Mangrove Carbon Working Group composed of in-country and US experts to coordinate, disseminate, and inform field, remote sensing, and GIS experts on the use and generation of the data products from this project.
Limitations:  Not all of the uncertainties have been identified and quantified.
Date When Product Available:  June 2016
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1327
Data Server URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1327
Archived Data Citation:  Lagomasino, D., and T. Fatoyinbo. 2016. CMS: Mangrove Canopy Height from High-resolution Stereo Image Pairs, Mozambique, 2012. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1327

Bounding Coordinates:
West Longitude:32.81000 East Longitude:33.00000
North Latitude:-25.98000 South Latitude:-26.39000

Product Title:  Mangrove Canopy Height
Time Period:  2011 - 2014
Description:  Develop mangrove canopy height estimates using a suite of COTS datasets. Canopy height data will then be used to derive otherproduct derivatives such as land cover change and biomass.
Status:  Planned
CMS Science Theme(s):  Land Biomass; MRV
Keywords:  canopy height; carbon stocks; biomass
Spatial Extent:  Gabon, Tanzania, Mozambique
Spatial Resolution:  1 m to 12 m
Temporal Frequency:  Single Product - dependant on time/date of satellite acquisition
Input Data Products:  Airborne Lidar (commercial COTS aircraft), Synthetic Aperture Radar (SAR), Very High Resolution optical (VHR), TanDEM-X Polarimetric Interferometric SAR (Pol-InSAR), field measurements.
Algorithm/Models Used:  Pol-InSAR; Ames Stereopipeline
Evaluation:  Validate TanDEM-X and VHR derived estimates of canopy height and biomass with Lidar and Field.
Intercomparison Efforts/Gaps:  Comparison of Biomass and height estimates to those produced by Fatoyinbo and Simard (2013) and Hutchinson (2013)
Uncertainty Estimates:  Uncertainties estimated from model-data comparisons (Modeled height - measured height)
Uncertainty Categories:  Ensemble and Model-Data Comparison
Application Areas:  MRV, REDD+; - Forest inventory; - Land management; - Watershed protection plan
Relevant Policies/Programs:  REDD+, Le Gabon Emergent, Gabon Forest Carbon Assessment, Silvacarbon, GEO-FCT
Potential Users:  US Forest Service, Forestry departments of Gabon, Tanzania, and Mozambique, WWF *Aurelie Shapiro*, USAID, USFS, Conservation International *Emily Pidgeon*, UNEP-WCMC, University Eduardo Mondlane
Stakeholders:  Gabon Space Agency (AGEOS); Omar Bongo University; University of Dar es Salaam Institute of Marine Sciences (Point of Contact: Mwita Mangora mmangora@yahoo.com); US Forest Service (Point of Contact: Carl Trettin: ctrettin@fs.fed.us); US Forest Service (Point of Contact: Carl Trettin ctrettin@fs.fed.us)
Current Application Readiness Level:  6
Start Application Readiness Level:  5
Target Application Readiness Level:  7
Future Developments:  Coordinate a Mangrove carbon working Group composed of in-country and US experts to Coordinate, disseminate, and Inform field, remote sensing, and GIS experts on the Use and generation of the data products from this project.
Limitations:  Not all of the uncertainties have been identified and quantified.
Date When Product Available:  July 2016
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1327

http://dx.doi.org/10.3334/ORNLDAAC/1357
Data Server URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1327

http://dx.doi.org/10.3334/ORNLDAAC/1357
Archived Data Citation:  
Bounding Coordinates:
West Longitude:9.54000 East Longitude:39.49000
North Latitude:0.38330 South Latitude:-25.95000

Product Title:  CMS: Aboveground Biomass for Mangrove Forest, Zambezi River Delta, Mozambique
Start Date:  09/2012      End Date:  05/2014     (Field measurements were made in September and October of 2012 and 2013. LiDAR measurements were taken on a single day: May 5, 2014)
Description:  This dataset provides several estimates of aboveground biomass from various regressions and allometries for mangrove forest in the Zambezi River Delta, Mozambique. Plot level estimates of aboveground biomass are based on extensive tree biophysical measurements from field campaigns conducted in September and October of 2012 and 2013. Aboveground biomass estimates for the larger area of mangrove coverage within the delta are based on (1) the plot level data and (2) canopy structure data derived from airborne LiDAR surveys in 2014. The high-resolution canopy height model for the delta region derived from the airborne LiDAR data is also included.
Status:  Archived
CMS Science Theme(s):  Land Biomass; MRV
Keywords:  Carbon Stocks (; terrestrial)
Spatial Extent:  Mangrove forested land of the Zambezi River Delta, Mozambique
Spatial Resolution:  1 m
Temporal Frequency:  Seasonal
Input Data Products:  Airborne Lidar, and field measurements. LiDAR data was acquired by Land Resources International (Pietermaritzburg, South Africa). The airborne survey comprised an approximate area of 115 km2 in the Zambezi Delta region, Mozambique, with a point density that ranged between 5 - 7 points per m2 (Lagomasino et al., 2016).
Algorithm/Models Used:  Field-based canopy height and carbon stock estimates were inventoried using a stratified random sampling design that took into account forest canopy height classes determined from the Mozambique mangrove canopy height data product derived from SRTM and GLAS data (Fatoyinbo et al., 2008). Total aboveground biomass (AGB) was estimated using the generalized Komiyama et al. (2005) mangrove allometry, the pantropical Chave et al. (2005) allometry, and the site-specific Njana et al. (2015) allometry derived for Tanzania as there is no site-specific published allometry for the Zambezi region.
Evaluation:  
Intercomparison Efforts/Gaps:  Comparison of field and LiDAR height metrics showed that the airborne survey data was highly correlated with field estimates of forest canopy height at the plot level across the entire range of sampled canopy heights. The strongest correlation between field and airborne survey metrics were found between LiDAR H100, LH, and Field H100, with 93% accuracy prediction between the airborne and field survey metrics.
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  - MRV REDD+; - Forest inventory; - Land management; - Watershed protection plans
Relevant Policies/Programs:  REDD+, Silvacarbon, GEO-FCT
Potential Users:  US Forest Service, Forestry department Mozambique, WWF, USAID, Conservation International, UNEP-WCMC, University Eduardo Mondlane
Stakeholders:  
Current Application Readiness Level:  5
Start Application Readiness Level:  3
Target Application Readiness Level:  6
Future Developments:  
Limitations:  The dataset authors advise that the Njana Power-based AGB map (njana_power_agb.tif) provides the most accurate estimates of AGB for this region as it is based on an allometric equation specific to East African mangrove forest, takes into account tree height, and has the highest range of input diameter at breast height and height measurements.
Date When Product Available:  August 25 2017
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1522
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1522
Archived Data Citation:  Fatoyinbo, T., E. Feliciano, D. Lagomasino, S. Lee, and C. Trettin. 2017. CMS: Aboveground Biomass for Mangrove Forest, Zambezi River Delta, Mozambique. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1522

Bounding Coordinates:
West Longitude:36.15000 East Longitude:36.29000
North Latitude:-18.79000 South Latitude:-18.90000

Product Title:  CMS: LiDAR Data for Mangrove Forests in the Zambezi River Delta, Mozambique, 2014
Start Date:  05/2014      End Date:  05/2014     (one sampling date)
Description:  This data set provides high-resolution LiDAR point cloud data collected during surveys over mangrove forests in the Zambezi River Delta in Mozambique in May 2014. The data are arranged into 144 1- by 1-km tiles.
Status:  Archived
CMS Science Theme(s):  Land Biomass; MRV
Keywords:  Carbon Stocks (; terrestrial)
Spatial Extent:  Mangrove forested land of the Zambezi River Delta, Mozambique
Spatial Resolution:  < 1 meter
Temporal Frequency:  one time sampling
Input Data Products:  Airborne LiDAR data was acquired on May 5, 2014 by Land Resources International (Pietermaritzburg, South Africa). The airborne survey comprised an approximate area of 115 km2 in the Zambezi Delta region, Mozambique, with a point density that ranged between 5 and 7 points per m2 (Lagomasino et al., 2016). The data were processed in Global Mapper and arranged into 144 1-km2 tiles for distribution with this data package.
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  - MRV REDD+; - Forest inventory; - Land management; - Watershed protection plans
Relevant Policies/Programs:  REDD+, Silvacarbon, GEO-FCT
Potential Users:  US Forest Service, Forestry department Mozambique, WWF, USAID, Conservation International, UNEP-WCMC, University Eduardo Mondlane
Stakeholders:  
Current Application Readiness Level:  5
Start Application Readiness Level:  3
Target Application Readiness Level:  6
Future Developments:  
Limitations:  
Date When Product Available:  August 25 2017
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1521
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1521
Archived Data Citation:  Fatoyinbo, T., and C. Trettin. 2017. CMS: LiDAR Data for Mangrove Forests in the Zambezi River Delta, Mozambique, 2014. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1521

Bounding Coordinates:
West Longitude:36.15000 East Longitude:36.29000
North Latitude:-18.79000 South Latitude:-18.89000

Product Title:  Global Mangrove Distribution, Aboveground Biomass, and Canopy Height
Start Date:  01/2000      End Date:  08/2014
Description:  This dataset characterizes the global distribution, biomass, and canopy height of mangrove-forested wetlands based on remotely sensed and in situ field measurement data. Estimates of (1) mangrove aboveground biomass (AGB), (2) maximum canopy height (height of the tallest tree), and (3) basal-area weighted height (individual tree heights weighted in proportion to their basal area) for the nominal year 2000 were derived across a 30-meter resolution global mangrove ecotype extent map using remotely-sensed canopy height measurements and region-specific allometric models. Also provided are (4) in situ field measurement data for selected sites across a wide variety of forest structures (e.g., scrub, fringe, riverine and basin) in mangrove ecotypes of the global equatorial region. Within designated plots, selected trees were identified to species and diameter at breast height (DBH) and tree height was measured using a laser rangefinder or clinometer. Tree density (the number of stems) can be estimated for each plot and expressed per unit area. These data were used to derive plot-level allometry among AGB, basal area weighted height (Hba), and maximum canopy height (Hmax) and to validate the remotely sensed estimates.
Status:  Archived
CMS Science Theme(s):  Land Biomass; MRV
Keywords:  
Spatial Extent:  Global within a circum-equatorial band from 31 degrees north to 39 degrees south
Spatial Resolution:  
Temporal Frequency:  One-time estimates for nominal year 2000
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1665
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1665
Archived Data Citation:  Simard, M., T. Fatoyinbo, C. Smetanka, V.H. Rivera-monroy, E. Castaneda, N. Thomas, and T. Van der stocken. 2019. Global Mangrove Distribution, Aboveground Biomass, and Canopy Height. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1665

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:31.00000 South Latitude:-39.00000

Product Title:  CMS: Mangrove Forest Cover Extent and Change across Major River Deltas, 2000-2016
Start Date:  01/2000      End Date:  12/2016
Description:  This dataset provides estimates of mangrove extent for 2016, and mangrove change (gain or loss) from 2000 to 2016, in major river delta regions of eight countries: Bangladesh, Gabon, Jamaica, Mozambique, Peru, Senegal, Tanzania, and Vietnam. For mangrove extent, a combination of Landsat 8 OLI, Sentinel-1 C-SAR, and Shuttle Radar Topography Mission (SRTM) elevation data were used to create country-wide maps of mangrove landcover extent at a 30-m resolution. For mangrove change, the global mangrove map for 2000 (Giri et al., 2010) was used as the baseline. Normalized Difference Vegetation Indices (NDVI) were calculated for every cloud- and shadow-free pixel in the Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 OLI collection and used to create an NDVI anomaly from 2000 to 2016. Areas of change (loss or gain) occurred at the extremes of the cumulative anomalies.
Status:  Archived
CMS Science Theme(s):  Land Biomass; MRV
Keywords:  
Spatial Extent:  Gabon, Mozambique, Tanzania, Peru, Senegal, Jamaica
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1670
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1670
Archived Data Citation:  Lagomasino, D., T. Fatoyinbo, S. Lee, E. Feliciano, C. Trettin, A. Shapiro, and M. Mwita. 2019. CMS: Mangrove Forest Cover Extent and Change across Major River Deltas, 2000-2016. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1670

Bounding Coordinates:
West Longitude:-82.00000 East Longitude:107.03000
North Latitude:22.50000 South Latitude:-28.00000

 
Publications: Fatoyinbo, T., Feliciano, E. A., Lagomasino, D., Lee, S. K., Trettin, C. 2018. Estimating mangrove aboveground biomass from airborne LiDAR data: a case study from the Zambezi River delta. Environmental Research Letters. 13(2), 025012. DOI: 10.1088/1748-9326/aa9f03

Lagomasino, D., Fatoyinbo, T., Lee, S., Feliciano, E., Trettin, C., Shapiro, A., Mangora, M. M. 2019. Measuring mangrove carbon loss and gain in deltas. Environmental Research Letters. 14(2), 025002. DOI: 10.1088/1748-9326/aaf0de

Simard, M., Fatoyinbo, L., Smetanka, C., Rivera-Monroy, V. H., Castaneda-Moya, E., Thomas, N., Van der Stocken, T. 2018. Mangrove canopy height globally related to precipitation, temperature and cyclone frequency. Nature Geoscience. 12(1), 40-45. DOI: 10.1038/s41561-018-0279-1

Lagomasino, D., Fatoyinbo, T., Lee, S., Simard, M. 2015. High-resolution forest canopy height estimation in an African blue carbon ecosystem. Remote Sensing in Ecology and Conservation. 1(1), 51-60. DOI: 10.1002/rse2.3

Lee, S., Fatoyinbo, T. E. 2015. TanDEM-X Pol-InSAR Inversion for Mangrove Canopy Height Estimation. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 8(7), 3608-3618. DOI: 10.1109/JSTARS.2015.2431646

Lagomasino, D., Fatoyinbo, T., Lee, S., Feliciano, E., Trettin, C., Simard, M. 2016. A Comparison of Mangrove Canopy Height Using Multiple Independent Measurements from Land, Air, and Space. Remote Sensing. 8(4), 327. DOI: 10.3390/rs8040327

Archived Data Citations: Lagomasino, D., T. Fatoyinbo, S. Lee, E. Feliciano, M. Simard, and C. Trettin. 2016. CMS: Mangrove Canopy Height Estimates from Remote Imagery, Zambezi Delta, Mozambique. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1357

Lagomasino, D., and T. Fatoyinbo. 2016. CMS: Mangrove Canopy Height from High-resolution Stereo Image Pairs, Mozambique, 2012. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1327

Lagomasino, D., T. Fatoyinbo, S. Lee, E. Feliciano, C. Trettin, and M.C. Hansen. 2017. CMS: Mangrove Canopy Characteristics and Land Cover Change, Tanzania, 1990-2014. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1377

Fatoyinbo, T., and C. Trettin. 2017. CMS: LiDAR Data for Mangrove Forests in the Zambezi River Delta, Mozambique, 2014. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1521

Fatoyinbo, T., E. Feliciano, D. Lagomasino, S. Lee, and C. Trettin. 2017. CMS: Aboveground Biomass for Mangrove Forest, Zambezi River Delta, Mozambique. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1522

Simard, M., T. Fatoyinbo, C. Smetanka, V.H. Rivera-monroy, E. Castaneda, N. Thomas, and T. Van der stocken. 2019. Global Mangrove Distribution, Aboveground Biomass, and Canopy Height. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1665

Lagomasino, D., T. Fatoyinbo, S. Lee, E. Feliciano, C. Trettin, A. Shapiro, and M. Mwita. 2019. CMS: Mangrove Forest Cover Extent and Change across Major River Deltas, 2000-2016. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1670

Outreach Activities: NASA Earth Observatory Image of the Day: Below the Mangrove Canopy
June 1, 2017

NASA Earth Observatory Notes from the field: Mangrove Carbon With a Grain of Salt
March 22, 2017

NASA Earth Science News Team: NASA, Partner Space Agencies Measure Forests In Gabon
Feb 25, 2016

2015 NASA Carbon Cycle & Ecosystems Joint Science Workshop Poster(s)
  • Mangrove Canopy height and biomass estimates from TanDEM-X and WorldView Stereo photogrammetry   --   (Temilola E. Fatoyinbo, SeungKuk Lee, David Lagomasino, Marc Simard, Carl Trettin, Matthew Hansen, John Poulsen)   [abstract]


 

Ganguly (CMS 2014) (2014)
Project Title:Reducing Uncertainties in Satellite-Derived Forest Aboveground Biomass Estimates Using a High Resolution Forest Cover Map

Science Team
Members:

Sangram Ganguly, Rhombus Power Inc. (Project Lead)
Cristina Milesi, NASA ARC
Ramakrishna (Rama) Nemani, NASA ARC
Taejin Park, NASA Ames Research Center / BAERI

Solicitation:NASA: Carbon Monitoring System (2014)
Abstract: Several studies to date have provided an extensive knowledge base for estimating forest aboveground biomass (AGB) and recent advances in space-based modeling of the 3-D canopy structure, combined with canopy reflectance measured by passive optical sensors and radar backscatter, are providing improved satellite-derived AGB density mapping for large scale carbon monitoring applications. A key limitation in forest AGB estimation from remote sensing, however, is the large uncertainty in forest cover estimates from the coarse-to-medium resolution satellite-derived land cover maps (present resolution is limited to 30-m of the USGS NLCD Program). As part of our CMS Phase II activities, we have demonstrated the use of Landsat-based estimates of Leaf Area Index and ICESat Geoscience Laser Altimeter System (GLAS) derived canopy heights for estimating AGB at a 30-m spatial resolution, which compare relatively well with inventory based plot level estimates. However, uncertainties in forest cover estimates at the Landsat scale result in high uncertainties for AGB estimation, predominantly in heterogeneous forest and urban landscapes. We have successfully tested an approach using a machine learning algorithm and High-Performance-Computing with NAIP air-borne imagery data for mapping tree cover at 1-m over California and Maryland. In a comparison with high resolution LiDAR data available over selected regions in the two states, we found our results to be promising both in terms of accuracy as well as our ability to scale nationally. In this project, we propose to estimate forest cover for the continental US at spatial resolution of 1-m in support of reducing uncertainties in the AGB estimation. The generated 1-m forest cover map will be aggregated to the Landsat spatial grid to demonstrate differences in AGB estimates (pixel-level AGB density, total AGB at aggregated scales like ecoregions and counties) when using a native 30-m forest cover map versus a 30-m map derived from a higher resolution dataset. The process will also be complemented with a LiDAR derived AGB estimate at the 30-m scale to aid in true validation. The proposed work will substantially contribute to filling the gaps in ongoing NASA CMS research and help quantifying the errors and uncertainties in NASA CMS products.
Project Associations:
  • CMS
CMS Primary Theme:
  • Land Biomass
CMS Science Theme(s):
  • Land Biomass

Participants:

Sangram Ganguly, Rhombus Power Inc.
Subodh Kalia, Bay Area Environmental Research Institute
Cristina Milesi, NASA ARC
Ramakrishna (Rama) Nemani, NASA ARC
Taejin Park, NASA Ames Research Center / BAERI

Project URL(s): None provided.
 
Data
Products:
Product Title:  Aboveground biomass at Landsat scale and Lidar-derived biomass maps.
Time Period:  2000-2012
Description:  - Provide aboveground biomass estimates.; - Compare differences between pixel-level AGB density and total AGB at aggregated scales like ecoregions and counties.
Status:  Planned
CMS Science Theme(s):  Land Biomass
Keywords:  Carbon Stocks (; terrestrial)
Spatial Extent:  CONUS
Spatial Resolution:  30 m
Temporal Frequency:  Yearly
Input Data Products:  Landsat Leaf Area Index, ICESat GLAS, NAIP airborne imagery data, G-LiHT lidar
Algorithm/Models Used:  machine learning algorithm (deep belief networks)
Evaluation:  AGB uncertainty
Intercomparison Efforts/Gaps:  - Compare between a native 30-m forest cover map versus a 30-m map derived from a higher resolution dataset. Compare with Lidar derived tree cover.
Uncertainty Estimates:  AGB uncertainty propagation using monte carlo error propagation model.
Uncertainty Categories:  ensemble, model-data
Application Areas:  - Forest inventory; - Land management, Fire Management
Relevant Policies/Programs:  FIA, National Climate Assessment, IPCC
Potential Users:  CMS land biomass product developers, USFS
Stakeholders:  
Current Application Readiness Level:  2
Start Application Readiness Level:  1
Target Application Readiness Level:  5
Future Developments:  State-wide AGB maps to be ready by 2015 Spring
Limitations:  None
Date When Product Available:  California AGB map available. Rest of the states: 2015 Spring
Assigned Data Center:  ORNL DAAC
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  

Product Title:  Tree cover maps.
Time Period:  2010-2012
Description:  - Provide tree cover estimate for the continental U.S.; - Reduce uncertainties in the aboveground (AGB) biomass estimation.
Status:  Planned
CMS Science Theme(s):  Land Biomass
Keywords:  Ecosystem Composition & Structure (forest cover)
Spatial Extent:  CONUS
Spatial Resolution:  1 m
Temporal Frequency:  Yearly
Input Data Products:  Landsat Leaf Area Index, ICESat GLAS, National Agriculture Imagery Program (NAIP) airborne imagery data, G-LiHT lidar
Algorithm/Models Used:  machine learning algorithm (deep belief networks)
Evaluation:  classification accuracy.
Intercomparison Efforts/Gaps:  - Compare between a native 30-m forest cover map versus a 30-m map derived from the 1-m tree cover data. Compare with Lidar derived tree cover data.
Uncertainty Estimates:  Detailed propagation of error analysis for both field and remote sensing steps. Conditional Random Fields for estimating pixel specific uncertainty in tree cover.
Uncertainty Categories:  ensemble, model- data
Application Areas:  - Forest inventory; - Land management, Fire Management, Land Cover Change
Relevant Policies/Programs:  FIA, National Climate Assessment, IPCC
Potential Users:  CMS land biomass product developers, USFS
Stakeholders:  
Current Application Readiness Level:  2
Start Application Readiness Level:  1
Target Application Readiness Level:  5
Future Developments:  Tree cover map ready by 2015 spring
Limitations:  Continuous Yearly Sampling (dependent on aerial NAIP imagery) - epoch level possible
Date When Product Available:  California Data already available. Rest of the states: 2015 Spring
Assigned Data Center:  ORNL DAAC
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  

 
Publications: Basu, S., Ganguly, S., Mukhopadhyay, S., DiBiano, R., Karki, M., Nemani, R. 2015. DeepSat. Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems. DOI: 10.1145/2820783.2820816

Basu, S., Karki, M., Ganguly, S., DiBiano, R., Mukhopadhyay, S., Gayaka, S., Kannan, R., Nemani, R. 2016. Learning Sparse Feature Representations Using Probabilistic Quadtrees and Deep Belief Nets. Neural Processing Letters. 45(3), 855-867. DOI: 10.1007/s11063-016-9556-4

Boyda, E., Basu, S., Ganguly, S., Michaelis, A., Mukhopadhyay, S., Nemani, R. R. 2017. Deploying a quantum annealing processor to detect tree cover in aerial imagery of California. PLOS ONE. 12(2), e0172505. DOI: 10.1371/journal.pone.0172505

Choi, S., Kempes, C. P., Park, T., Ganguly, S., Wang, W., Xu, L., Basu, S., Dungan, J. L., Simard, M., Saatchi, S. S., Piao, S., Ni, X., Shi, Y., Cao, C., Nemani, R. R., Knyazikhin, Y., Myneni, R. B. 2016. Application of the metabolic scaling theory and water-energy balance equation to model large-scale patterns of maximum forest canopy height. Global Ecology and Biogeography. 25(12), 1428-1442. DOI: 10.1111/geb.12503

Basu, s., M. Karki, S. Ganguly, R. DiBiano, S. Mukhopadhyay, R. Nemani.2015. Learning Sparse Feature Representations using Probabilistic Quadtrees and Deep Belief Nets, European Symposium on Artificial Neural Networks, ESANN 2015 https://www.elen.ucl.ac.be/esann/proceedings/papers.php?ann=2015

Basu, S., Ganguly, S., Nemani, R. R., Mukhopadhyay, S., Zhang, G., Milesi, C., Michaelis, A., Votava, P., Dubayah, R., Duncanson, L., Cook, B., Yu, Y., Saatchi, S., DiBiano, R., Karki, M., Boyda, E., Kumar, U., Li, S. 2015. A Semiautomated Probabilistic Framework for Tree-Cover Delineation From 1-m NAIP Imagery Using a High-Performance Computing Architecture. IEEE Transactions on Geoscience and Remote Sensing. 53(10), 5690-5708. DOI:
10.1109/TGRS.2015.2428197

Zhang, G., Ganguly, S., Nemani, R. R., White, M. A., Milesi, C., Hashimoto, H., Wang, W., Saatchi, S., Yu, Y., Myneni, R. B. 2014. Estimation of forest aboveground biomass in California using canopy height and leaf area index estimated from satellite data. Remote Sensing of Environment. 151, 44-56. DOI: 10.1016/j.rse.2014.01.025

2015 NASA Carbon Cycle & Ecosystems Joint Science Workshop Poster(s)
  • G-LiHT: Multi-Sensor Airborne Image Data from Denali to the Yucatan   --   (Bruce Cook, Lawrence A Corp, Douglas Morton, Joel McCorkel)   [abstract]   [poster]


 

Greenberg (CMS 2014) (2014)
Project Title:Reducing Uncertainties in Estimating California's Forest Carbon Stocks

Science Team
Members:

Jonathan Greenberg, University of Nevada (Project Lead)

Solicitation:NASA: Carbon Monitoring System (2014)
Successor Projects: Greenberg (CMS 2016)  
Abstract: We propose to create a prototype Carbon Monitoring System (CMS) for the state of California, with the goal of estimating the mean tree-sequestered above-ground biomass AGB) using various remote sensing techniques for the period of 2005 to 2015 at 30m resolution, and determine the spatially explicit uncertainty in these estimates. One of the key characteristics of this CMS will be a detailed propagation of error analysis for both the field and remote sensing steps. We will investigate and compare state-of-the-art AGB estimation approaches applied to commercial LiDAR and Worldview-2, as well as dense time series of Landsat 4 8 imagery. The CMS will be developed with future-proofing in mind: new techniques, as they become available, will be easily integrated into the system and fused with previous techniques. All models and data products will be released under open content/open source licenses to maximize the utility of the research to the wider community.
Project Associations:
  • CMS
CMS Primary Theme:
  • Land Biomass
CMS Science Theme(s):
  • Land Biomass

Participants:

Jonathan Greenberg, University of Nevada
Carlos Ramirez Reyes, USDA Forest Service
Michele Slaton, USDA Forest Service

Project URL(s): None provided.
 
Data
Products:
Product Title:  LiDAR-Derived Aboveground Biomass and Uncertainty for California Forests, 2005-2014
Start Date:  01/2005      End Date:  12/2014     (2005-2015)
Description:  This dataset provides estimates of aboveground biomass and spatially explicit uncertainty from 53 airborne LiDAR surveys of locations throughout California between 2005 and 2014. Aboveground biomass was estimated by performing individual tree crown detection and applying a customized "remote sensing aware" allometric equation to these individual trees. Aboveground biomass estimates and their uncertainties for each study area are provided in per-tree and gridded format. The canopy height models used for the tree detection and biomass estimation are also provided.
Status:  Archived
CMS Science Theme(s):  Land Biomass
Keywords:  Carbon Stocks (; terrestrial)
Spatial Extent:  California
Spatial Resolution:  Shapfiles: one polygon feature per tree canopy GeoTIFFs: 30-m (AGB, uncertainty, coefficient of variation) and 25-cm (CHM)
Temporal Frequency:  Mixture: Lidar and WV-2, 1-off; Landsat: 16 day
Input Data Products:  Commercial Lidar, Worldview-2, Landsat 4-8 time series, field measurements
Algorithm/Models Used:  Individual tree crown recognition, time series analysis, machine learning
Evaluation:  FIA plot validation
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  Bayesian hierarchical modeling approach: full propagation of error
Uncertainty Categories:  
Application Areas:  - Fire management; - Forest inventory; - Land management
Relevant Policies/Programs:  
Potential Users:  USDA FS *Carlos Ramirez*
Stakeholders:  
Current Application Readiness Level:  2
Start Application Readiness Level:  2
Target Application Readiness Level:  4
Future Developments:  - The carbon monitoring system will be designed so that new techniques, as they become available, will be easily integrated into the system and fused with previous techniques.; - All models and data products will be released under open content/open source
Limitations:  
Date When Product Available:  July 2018
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1537
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1537
Archived Data Citation:  Xu, Q., A. Man, M.M. Fredrickson, Z. Hou, J. Pitkanen, B. Wing, C. Ramirez, B. Li, and J. Greenberg. 2018. LiDAR-Derived Aboveground Biomass and Uncertainty for California Forests, 2005-2014. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1537

Bounding Coordinates:
West Longitude:-123.75000 East Longitude:-117.74000
North Latitude:41.98000 South Latitude:34.05000

Product Title:  CMS: Vegetative Lifeform Cover from Landsat SR for CONUS, 1984-2018
Start Date:  01/1984      End Date:  12/2018     (1984-01-01 to 2018-01-01)
Description:  This dataset contains estimates of percent cover of tree, shrub, herb, and other (non-vegetation) lifeform classes and uncertainties for the conterminous U.S. (CONUS). The estimates were derived using quantile regression forest models and indicate the percent of ground covered by a vertical projection of each lifeform class ranging from 0 to 100 percent. Model input data included Landsat surface reflectance (SR) data and 165 airborne LiDAR datasets covering eight of the eleven terrestrial biomes of the conterminous U.S. and Alaska. Eighty-six of the LiDAR acquisitions are part of the NASA Goddard's LiDAR, Hyperspectral, and Thermal Imager (G-LiHT) airborne imager data collection; the remaining 79 sites were acquired by the National Science Foundation's National Ecological Observatory Network Airborne Observation Platform (NEON AOP). Acquisitions were selected based on the availability of the SR data for each G-LiHT and NEON dataset. The data are annual estimates from 1984 to 2018 and were tiled (425 tiles) using the CONUS Landsat Analysis Ready Data (ARD) grid scheme. Data are provided in GeoTIFF format.
Status:  Archived
CMS Science Theme(s):  Land Biomass
Keywords:  Land Biomass
Spatial Extent:  conterminous United States
Spatial Resolution:  30 m
Temporal Frequency:  annual
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1809
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1809
Archived Data Citation:  Parra, A., and J.A. Greenberg. 2021. CMS: Vegetative Lifeform Cover from Landsat SR for CONUS, 1984-2018. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1809

Bounding Coordinates:
West Longitude:-126.71000 East Longitude:-65.06000
North Latitude:50.66000 South Latitude:23.27000

 
Publications: Xu, Q., Man, A., Fredrickson, M., Hou, Z., Pitkanen, J., Wing, B., Ramirez, C., Li, B., Greenberg, J. A. 2018. Quantification of uncertainty in aboveground biomass estimates derived from small-footprint airborne LiDAR. Remote Sensing of Environment. 216, 514-528. DOI: 10.1016/j.rse.2018.07.022

Archived Data Citations: Xu, Q., A. Man, M.M. Fredrickson, Z. Hou, J. Pitkanen, B. Wing, C. Ramirez, B. Li, and J. Greenberg. 2018. LiDAR-Derived Aboveground Biomass and Uncertainty for California Forests, 2005-2014. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1537

Parra, A., and J.A. Greenberg. 2021. CMS: Vegetative Lifeform Cover from Landsat SR for CONUS, 1984-2018. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1809


 

Hudak (CMS 2014) (2014)
Project Title:Prototyping A Methodology To Develop Regional-Scale Forest Aboveground Biomass Carbon Maps Predicted From Landsat Time Series, Trained From Field and Lidar Data Collections, And Independently Validated With FIA Data

Science Team
Members:

Andrew (Andy) Hudak, USDA Forest Service (Project Lead)
Robert Kennedy, Oregon State University

Solicitation:NASA: Carbon Monitoring System (2014)
Successor Projects: Hudak (CMS 2018)  
Abstract: Current Monitoring Reporting and Verification (MRV) needs cannot be met by using only available NASA satellite data products, but must be integrated with commercial off-the-shelf technologies. The exceptional sensitivity of commercial, airborne scanning lidar data to forest canopy structure has made it the best remote sensing technology for predicting vegetation attributes, including biomass. We propose to use multiple, landscape-level lidar datasets, previously acquired in conjunction with project-level field plot datasets for model calibration/validation, to predict aboveground biomass stores across representative vegetation types in the northwestern USA. The predicted biomass maps will serve as training area for upscaling biomass carbon predictions to the regional level, as predicted from Landsat time series imagery processed through LandTrendr. Regional maps will be validated with FIA data summarized at the county level, along with error statistics. Bias between biomass predictions and FIA observations summarized for the representative vegetation types will be quantified, and bias corrections applied, with the goal of maintaining a transparent record of bias corrections at the county level. We envision a lidar and field plot database that can continue to be updated as new project-level forest inventory data are collected. This strategy will actively engage forest managers by utilizing existing data collected by and maintained by land managers of the US Forest Service (USFS) and other public and private stakeholders. Our chosen study region is the northwestern USA, where multiple commercial lidar and field plot datasets exist, LandTrendr data products are farthest along in the production line, and steep environmental gradient provide an exceptional diversity in vegetation types. The cumulative area of LiDAR collections across multiple ownerships in the northwestern USA has reached the point that land managers of the USFS and other stakeholders need to develop a strategy for how to utilize LiDAR for improved regional inventory, and because these inventories are the initial conditions for simulation modeling of future conditions, the strategy will result in more accurate estimates of projected conditions. We have assembled and consistently processed field plot and lidar datasets at >21 landscape-level project areas distributed along a broad climate gradient across the northwestern USA from temperate rainforest to cold desert. We propose to employ imputation as our predictive modeling strategy because it assigns actual ground observations at representative sample locations, to unsampled locations. Further, imputation modeling is firmly ensconced within the forest management community, and has been used for decades to assign stand attributes from reference stands to target stands. Therefore, forest and rangeland managers of the USFS and other major public and private land management stakeholders will have little difficulty buying in to our proposed methodology, and would benefit enormously by making more effective use of available LiDAR and ground inventory data. Fortunately, the USFS has also developed a carbon management capability with greater utility to local forest managers: the carbon accounting tool of the Forest Vegetation Simulator (FVS) (http://www.fs.fed.us/fmsc/fvs/). FVS remains freely available, is now open source (Open-FVS), is approved by the American Carbon Registry to estimate carbon stock changes, and provides the option of climate change projections using Climate-FVS. Our chosen modeling methods and tools lend themselves to transparency and verifiability. Our goal is to develop a prototype CMS that works with acceptable accuracy, objectivity, transparency, and reproducibility in the northwestern USA, it will be ready for replication and application elsewhere in the USA, and globally with ties to SilvaCarbon and REDD+.
Measurement Approaches:
  • Remote Sensing
Project Associations:
  • CMS
CMS Primary Theme:
  • Land Biomass
CMS Science Theme(s):
  • Land Biomass
  • Decision Support
  • MRV

Participants:

Renate Bush, U.S. Forest Service Region 1
Mark Corrao, Northwest Management, Inc.
Michael (Mike) Falkowski, NASA Headquarters
Patrick Fekety, Colorado State University
Nancy Glenn, Boise State University
Andrew (Andy) Hudak, USDA Forest Service
Robert Kennedy, Oregon State University
Sanford Moss, U.S. Forest Service Region 4
Jim Muckenhoupt, U.S. Forest Service Region 6
Alistair Smith, University of Idaho
Christopher (Chris) Woodall, USDA Forest Service

Project URL(s): https://www.fs.fed.us/rmrs/projects/prototyping-methodology-map-regional-aboveground-biomass-carbon-lidar-and-landsat-image
 
Data
Products:
Product Title:  Annual Aboveground Biomass Maps for Forests in the Northwestern USA, 2000-2016
Start Date:  01/2000      End Date:  12/2016     (2000-2016)
Description:  This dataset provides annual maps of aboveground biomass (AGB, Mg/ha) for forests in Washington, Oregon, Idaho, and western Montana, USA, for the years 2000-2016, at a spatial resolution of 30 meters. Tree measurements were summarized with the Fire and Fuels Extension of the Forest Vegetation Simulator (FFE-FVS) to estimate AGB in field plots contributed by stakeholders, then lidar was used to predict plot-level AGB using the Random Forests machine learning algorithm. The machine learning outputs were used to predict AGB from Landsat time series imagery processed through LandTrendr, climate metrics generated from 30-year climate normals, and topographic metrics generated from a 30-m Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM). The non-forested pixels were masked using the PALSAR 2009 forest/nonforest mask.
Status:  Archived
CMS Science Theme(s):  Decision Support; Land Biomass; MRV
Keywords:  Carbon Stocks (pool: terrestrial), Flux/Movement (terrestrial), Ecosystem Composition and Structure (forest cover, forest/non-forest), Disturbance (forest structure change)
Spatial Extent:  Northwestern U.S. (WA, OR, ID)
Spatial Resolution:  30 m nominally,
Temporal Frequency:  Annual
Input Data Products:  Commercial airborne lidar data, field plot datasets, LandTrendr (Landsat time series), climate metrics derived from 1961-1990 normals, topographic metrics derived from void-filled 30 m SRTM digital elevation model, Simard et al. (2011) global canopy height product
Algorithm/Models Used:  LandTrendr, Random Forests regression modeling
Evaluation:  Regional maps will be calibrated with FIA plot data
Intercomparison Efforts/Gaps:  Comparison to Kennedy et al. GNN-derived aboveground biomass carbon maps in WA and OR
Uncertainty Estimates:  Maps (30 m resolution) of standard deviation from the random forest model as a measure of precision; Comparison to independent FIA estimates as a measure of bias.
Uncertainty Categories:  Ensemble (e.g. stochastic); Model-Data Comparison; Model-Model Comparison
Application Areas:  - MRV; - Cap and trade; - Land management
Relevant Policies/Programs:  NACP, USCCSP, UNFCCC, NGHGI, SilvaCarbon, REDD+
Potential Users:  Federal land management agencies (e.g., US Forest Service), state land and other public and private forest managers
Stakeholders:  Confederated Tribes of the Colville Reservation (Point of Contact: Cody Desautel, cody.desautel@colvilletribes.com); Mason, Bruce & Girard, Inc. (Point of Contact: pgould@masonbruce.com); Northwest Management, Inc. (Point of Contact: Mark Corrao, mcorrao@nmi2.com); The Nature Conservancy (Point of Contact: Ryan Haugo, rhaugo@TNC.ORG); U.S. Forest Service Region 4 (Point of Contact: Jed Gregory, jed.gregory@usda.gov); U.S. Forest Service Region 6 (Point of Contact: Jim Muckenhoupt, jim.muckenhoupt@usda.gov); USFS Region 1 (Point of Contact: Renate Bush, renate.bush@usda.gov); Washington Department of Natural Resources (Point of Contact: Luke Rogers, lwrogers@uw.edu)
Current Application Readiness Level:  5
Start Application Readiness Level:  4
Target Application Readiness Level:  7
Future Developments:  Phase 2 (funded) will expand spatially to entire U.S. West and temporally to 1984-2020
Limitations:  Local inaccuracies can be caused by the choice of Forest/Non-Forest mask used; we used a F/NF mask independently derived from 2009 PALSAR data and publicly available
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1719
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1719
Archived Data Citation:  Fekety, P.A., and A.T. Hudak. 2019. Annual Aboveground Biomass Maps for Forests in the Northwestern USA, 2000-2016. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1719

Bounding Coordinates:
West Longitude:-127.52000 East Longitude:-110.31000
North Latitude:50.79000 South Latitude:39.81000

Product Title:  CMS: Pinyon-Juniper Forest Live Aboveground Biomass, Great Basin, USA, 2000-2016
Start Date:  01/2000      End Date:  12/2016     (2000-2016)
Description:  This dataset provides annual maps of live aboveground tree biomass (Mg/ha) for pinyon-juniper forests across the Great Basin of the Western USA for the years 2000-2016 at a spatial resolution of 30 meters. Biomass estimates are limited to areas of the Great Basin defined as a pinyon-juniper ecosystem type by the 2016 Landfire Existing Vegetation Type map. The estimates of biomass were based on a linear relationship with pinyon-juniper canopy cover and crown-based allometrics developed from field data in Nevada and Idaho. Canopy cover was estimated from remote sensing by using annual composites of Landsat imagery, which were temporally segmented with the LandTrendr algorithm, along with biologically-relevant climate variables, and topographic indices in a Random Forest regression model. Models of canopy cover were trained from semi-automatic extraction of tree crowns from 2011 - 2013 high resolution imagery (1 m) from the National Agriculture Imagery Program, which were validated with photo interpretation. Maps of the standard deviation of biomass estimates from decision trees in the Random Forest model are provided as an indicator of uncertainty. Biomass estimates were calibrated to estimates from the Forest Inventory and Analysis program (FIA) on an annual basis and corrections applied.
Status:  Archived
CMS Science Theme(s):  Land Biomass
Keywords:  Carbon Stocks (terrestrial), Flux/Movement (terrestrial), Ecosystem Composition and Structure (forest cover, forest/non-forest), Disturbance (forest structure change)
Spatial Extent:  Great Basin of North America
Spatial Resolution:  30 x 30 m
Temporal Frequency:  Annual
Input Data Products:  Landsat time series, gridded 30-year climate normals, topography derived from the National Elevation Dataset
Algorithm/Models Used:  LandTrendr, Random Forest, Spatial Wavelet Analysis
Evaluation:  Field-based estimates from the SageSTEP and Forest Inventory and Analysis programs
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  Maps of standard deviation from the random forest model. Comparisons to SageSTEP and FIA.
Uncertainty Categories:  ensemble and model-data comparison
Application Areas:  MRV, Land management, Cap-and-trade
Relevant Policies/Programs:  US National Greenhouse Gas Inventory (NGHGI) baseline reporting to the UN Framework Convention on Climate Change (UNFCCC), U.S. Carbon Cycle Science Program (USCCSP), North American Carbon Program (NACP)
Potential Users:  USFS, BLM, EPA, stakeholders in land management
Stakeholders:  The Nature Conservancy (Point of Contact: Ryan Haugo, rhaugo@TNC.ORG); U.S. Forest Service Region 4 (Point of Contact: Jed Gregory, jed.gregory@usda.gov)
Current Application Readiness Level:  5
Start Application Readiness Level:  3
Target Application Readiness Level:  7
Future Developments:  - Continued methods development - Share results with forest service partners
Limitations:  - Some exclusion of areas with low tree cover and prior disturbance
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1755
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1755
Archived Data Citation:  Filippelli, S.K., M.J. Falkowski, A.T. Hudak, and P.A. Fekety. 2020. CMS: Pinyon-Juniper Forest Live Aboveground Biomass, Great Basin, USA, 2000-2016. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1755

Bounding Coordinates:
West Longitude:-123.90000 East Longitude:-109.31000
North Latitude:47.12000 South Latitude:33.93000

Product Title:  LiDAR Derived Forest Aboveground Biomass Maps, Northwestern USA, 2002-2016
Start Date:  01/2002      End Date:  12/2016     (2002 through 2016)
Description:  This dataset provides maps of aboveground forest biomass (AGB) of living trees and standing dead trees in Mg/ha across portions of Northwestern United States, including Washington, Oregon, Idaho, and Montana, at a spatial resolution of 30 m. Forest inventory data were compiled from 29 stakeholders that had overlapping lidar imagery. The collection totaled 3805 field plots with lidar imagery for 176 collections acquired between 2002 and 2016. Plot-level AGB estimates were calculated from tree measurements using the default allometric equations found in the Fire Fuels Extension (FFE) of the Forest Vegetation Simulator (FVS). The random forest algorithm was used to model AGB from lidar height and density metrics that were generated from the lidar returns within fixed-radius field plot footprints, gridded climate metrics obtained from the Climate-FVS Ready Data Server, and topographic estimates extracted from Shuttle Radar Topography Mission (SRTM) 1 Arc-Second Global elevation rasters. AGB was then mapped from the same lidar metrics gridded across the extent of the lidar collections at 30-m resolution. The standard deviation of estimated AGB of the terminal nodes from the random forest predictions was also mapped to show pixel-level model uncertainty. Note that the AGB estimates are, for the most part, a single snapshot in time and that the forest conditions are not necessarily representative of the larger study area.
Status:  Archived
CMS Science Theme(s):  Land Biomass
Keywords:  
Spatial Extent:  Northwestern United States: Washington, Oregon, Idaho, and part of western Montana
Spatial Resolution:  30 m
Temporal Frequency:  annual
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  Confederated Tribes of the Colville Reservation (Point of Contact: Cody Desautel, cody.desautel@colvilletribes.com); Mason, Bruce & Girard, Inc. (Point of Contact: pgould@masonbruce.com); Northwest Management, Inc. (Point of Contact: Mark Corrao, mcorrao@nmi2.com); The Nature Conservancy (Point of Contact: Ryan Haugo, rhaugo@TNC.ORG); U.S. Forest Service Region 4 (Point of Contact: Jed Gregory, jed.gregory@usda.gov); U.S. Forest Service Region 6 (Point of Contact: Jim Muckenhoupt, jim.muckenhoupt@usda.gov); USFS Region 1 (Point of Contact: Renate Bush, renate.bush@usda.gov); Washington Department of Natural Resources (Point of Contact: Luke Rogers, lwrogers@uw.edu)
Current Application Readiness Level:  5
Start Application Readiness Level:  5
Target Application Readiness Level:  7
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1766
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1766
Archived Data Citation:  Fekety, P.A., and A.T. Hudak. 2020. LiDAR Derived Forest Aboveground Biomass Maps, Northwestern USA, 2002-2016. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1766

Bounding Coordinates:
West Longitude:-125.58000 East Longitude:-112.28000
North Latitude:49.35000 South Latitude:41.66000

Product Title:  Tree and stand attributes for "A carbon monitoring system for mapping regional, annual aboveground biomass across the northwestern USA"
Start Date:  01/2002      End Date:  12/2017     (These data were collected between 2002 and 2017)
Description:  These data represent a portion of the forest inventory data used in Hudak et al. (in review) "A carbon monitoring system for mapping regional, annual aboveground biomass across the northwestern USA". This study used forest inventory data located in lidar units along with Landsat data, topographic metrics, and climate metrics to create maps of forested biomass across the northwestern USA (Washington, Oregon, Idaho, and western Montana.) The data requirements for inclusion in this study included: 1. fixed-area plots, 2. plots centers were recorded using a global navigation satellite system receiver (e.g., a GPS receiver) capable of differential correction, and 3. plots were located in a lidar unit where tree data were collected within 3 years of the lidar collection. A shapefile of the lidar units can be found in Fekety and Hudak (2020, https://doi.org/10.3334/ORNLDAAC/1766). The forest inventory data presented here (n = 2,680 plots) include all data that could be made publicly available and have been compiled from numerous existing datasets. The forest inventory data were collected using project-specific sampling plans and therefore these data have been formatted to be read by the Forest Vegetation Simulator (FVS; https://www.fs.fed.us/fvs/). The forest inventory data in this dataset were collected between 2002 and 2017 and located in Idaho, Oregon, and Washington, USA.
Status:  Archived
CMS Science Theme(s):  Land Biomass
Keywords:  
Spatial Extent:  Idaho, Oregon, and Washington, USA.
Spatial Resolution:  Inventories so measurements on an individual tree level
Temporal Frequency:  
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  Washington Department of Natural Resources (Point of Contact: Luke Rogers, lwrogers@uw.edu)
Current Application Readiness Level:  5
Start Application Readiness Level:  4
Target Application Readiness Level:  7
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  USFS Research Data Archive
Metadata URL(s):

https://doi.org/10.2737/RDS-2020-0026
Data Server URL(s):

https://doi.org/10.2737/RDS-2020-0026
Archived Data Citation:  Fekety, P.A., A.T. Hudak and B.C. Bright. 2020. Tree and stand attributes for 'A carbon monitoring system for mapping regional, annual aboveground biomass across the northwestern USA'. Fort Collins, CO: Forest Service Research Data Archive. DOI: 10.2737/RDS-2020-0026.

Bounding Coordinates:
West Longitude:-124.42690 East Longitude:-115.02440
North Latitude:48.98967 South Latitude:42.10223

 
Publications: Fekety, P. A., Crookston, N. L., Hudak, A. T., Filippelli, S. K., Vogeler, J. C., Falkowski, M. J. 2020. Hundred year projected carbon loads and species compositions for four National Forests in the northwestern USA. Carbon Balance and Management. 15(1). DOI: 10.1186/s13021-020-00140-9

Fekety, P. A., Falkowski, M. J., Hudak, A. T. 2015. Temporal transferability of LiDAR-based imputation of forest inventory attributes. Canadian Journal of Forest Research. 45(4), 422-435. DOI: 10.1139/cjfr-2014-0405

Fekety, P. A., Falkowski, M. J., Hudak, A. T., Jain, T. B., Evans, J. S. 2018. Transferability of Lidar-derived Basal Area and Stem Density Models within a Northern Idaho Ecoregion. Canadian Journal of Remote Sensing. 44(2), 131-143. DOI: 10.1080/07038992.2018.1461557

Fekety, P. A., Sadak, R. B., Sauder, J. D., Hudak, A. T., Falkowski, M. J. 2019. Predicting forest understory habitat for Canada lynx using LIDAR data. Wildlife Society Bulletin. 43(4), 619-629. DOI: 10.1002/wsb.1018

Filippelli, S. K., Falkowski, M. J., Hudak, A. T., Fekety, P. A., Vogeler, J. C., Khalyani, A. H., Rau, B. M., Strand, E. K. 2020. Monitoring pinyon-juniper cover and aboveground biomass across the Great Basin. Environmental Research Letters. 15(2), 025004. DOI: 10.1088/1748-9326/ab6785

Fusco, E. J., Rau, B. M., Falkowski, M., Filippelli, S., Bradley, B. A. 2019. Accounting for aboveground carbon storage in shrubland and woodland ecosystems in the Great Basin. Ecosphere. 10(8). DOI: 10.1002/ecs2.2821

Hudak, A. T., Fekety, P. A., Kane, V. R., Kennedy, R. E., Filippelli, S. K., Falkowski, M. J., Tinkham, W. T., Smith, A. M. S., Crookston, N. L., Domke, G. M., Corrao, M. V., Bright, B. C., Churchill, D. J., Gould, P. J., McGaughey, R. J., Kane, J. T., Dong, J. 2020. A carbon monitoring system for mapping regional, annual aboveground biomass across the northwestern USA. Environmental Research Letters. 15(9), 095003. DOI: 10.1088/1748-9326/ab93f9

Sanchez-Lopez, N., Boschetti, L., Hudak, A. 2018. Semi-Automated Delineation of Stands in an Even-Age Dominated Forest: A LiDAR-GEOBIA Two-Stage Evaluation Strategy. Remote Sensing. 10(10), 1622. DOI: 10.3390/rs10101622

Sanchez-Lopez, N., Boschetti, L., Hudak, A. T. 2019. Reconstruction of the disturbance history of a temperate coniferous forest through stand-level analysis of airborne LiDAR data. Forestry: An International Journal of Forest Research. DOI: 10.1093/forestry/cpz048

Stitt, J. M., Hudak, A. T., Silva, C. A., Vierling, L. A., Vierling, K. T. 2021. Characterizing individual tree-level snags using airborne lidar-derived forest canopy gaps within closed-canopy conifer forests. Methods in Ecology and Evolution. 13(2), 473-484. DOI: 10.1111/2041-210X.13752

Stitt, J. M., Hudak, A. T., Silva, C. A., Vierling, L. A., Vierling, K. T. 2022. Evaluating the Use of Lidar to Discern Snag Characteristics Important for Wildlife. Remote Sensing. 14(3), 720. DOI: 10.3390/rs14030720

Tinkham, W. T., Mahoney, P. R., Hudak, A. T., Domke, G. M., Falkowski, M. J., Woodall, C. W., Smith, A. M. 2018. Applications of the United States Forest Inventory and Analysis dataset: a review and future directions. Canadian Journal of Forest Research. 48(11), 1251-1268. DOI: 10.1139/cjfr-2018-0196

Deo, R. K., Froese, R. E., Falkowski, M. J., Hudak, A. T. 2016. Optimizing Variable Radius Plot Size and LiDAR Resolution to Model Standing Volume in Conifer Forests. Canadian Journal of Remote Sensing. 42(5), 428-442. DOI: 10.1080/07038992.2016.1220826

Archived Data Citations: Fekety, P.A., and A.T. Hudak. 2019. Annual Aboveground Biomass Maps for Forests in the Northwestern USA, 2000-2016. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1719

Filippelli, S.K., M.J. Falkowski, A.T. Hudak, and P.A. Fekety. 2020. CMS: Pinyon-Juniper Forest Live Aboveground Biomass, Great Basin, USA, 2000-2016. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1755

Fekety, P.A., A.T. Hudak and B.C. Bright. 2020. Tree and stand attributes for 'A carbon monitoring system for mapping regional, annual aboveground biomass across the northwestern USA'. Fort Collins, CO: Forest Service Research Data Archive. DOI: 10.2737/RDS-2020-0026.

Fekety, P.A., and A.T. Hudak. 2020. LiDAR Derived Forest Aboveground Biomass Maps, Northwestern USA, 2002-2016. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1766

2015 NASA Carbon Cycle & Ecosystems Joint Science Workshop Poster(s)
  • Developing an Ecoregion-level Imputation Model From LiDAR-derived Biomass Maps   --   (Andrew Thomas Hudak, Patrick A Fekety, Michael J Falkowski, Robert E Kennedy, Alistair Matthew Stuart Smith)   [abstract]


 

Hurtt (CMS 2014) (2014)
Project Title:High-Resolution Carbon Monitoring and Modeling: Continuing Prototype Development and Deployment

Science Team
Members:

George Hurtt, University of Maryland (Project Lead)
Philip (Phil) DeCola, University of Maryland
Katelyn Dolan, University of Maryland
Ralph Dubayah, University of Maryland

Solicitation:NASA: Carbon Monitoring System (2014)
Precursor Projects: Dubayah (CMS 2013)  
Successor Projects: Hurtt (CMS 2016)  
Abstract: The overall goal of our project is the continuing development of a framework for estimating high-resolution carbon stocks and dynamics and future carbon sequestration potential using remote sensing and ecosystem modeling linked with existing field observation systems such as the USFS Forest Inventory. In particular, we seek to demonstrate an approach that provides the basis for the rapid expansion from Maryland to nearby states, and which additionally enables the monitoring of annualized changes in stocks through time at fine spatial resolution. We believe this build-out is possible today and is a critical step in the development of a national CMS. Specifically we will address the following objectives: (1) Improve our existing methodology for carbon stock estimation and uncertainty based on lessons learned from our Phase 2 study; (2) Provide wall-to-wall, high-resolution estimates of carbon stocks and their uncertainties for the 3-state region of Pennsylvania, Delaware and Maryland; (3) Initialize and run a prognostic ecosystem model for carbon at high-spatial resolution over multiple eastern states; (4) Validate national biomass maps using Forest Inventory and Analysis (FIA) data and high-resolution biomass maps over an expanded domain; (5) Develop and test methods for monitoring changes in carbon stocks through time using repeat lidar data, satellite imagery, forest inventory data, and remote sensing driven mechanistic modeling; (6) Demonstrate MRV efficacy to meet stakeholder needs in our 3-state region, and a vision for future national-scale deployment. Our work has followed a logical expansion of effort, from proof-of concept starting with just two counties in our Phase 1 pilot study, to an entire state (24 counties) in Phase 2. This research has emphatically demonstrated the feasibility of large-scale mapping using airborne lidar. We propose to build on these efforts to encompass another qualitative increase in spatial extent, new MRV-relevant product prototyping, and a vision for future operational deployment of MRV systems that are responsive to local, national and international interests in management and policy.
Project Associations:
  • CMS
CMS Primary Theme:
  • Land Biomass
CMS Science Theme(s):
  • Land Biomass
  • Land-Atmosphere Flux
  • Decision Support
  • MRV

Participants:

Elliott Campbell, Maryland Department of Natural Resources
Michelle Canick, The Nature Conservancy
Hong-Hanh Chu, Massachusetts Executive Office of Energy & Environmental Affairs
Greg Czarnecki, Pennsylvania DCNR Bureau of Forestry
Philip (Phil) DeCola, University of Maryland
Katelyn Dolan, University of Maryland
Ralph Dubayah, University of Maryland
Rob Feldt, Maryland Forest Service
Suzanne Hagell, New York State Department of Environmental Conservation, Office of Climate Change
George Hurtt, University of Maryland
Jimmy Kroon, Delaware Forest Service
Shawn Lehman, Pennsylvania DCNR Bureau of Forestry
Bennet Leon, Vermont Department of Environmental Conservation
Jeffrey Mapes, New York State Department of Environmental Conservation, Office of Climate Change
Valeria Morales, University of Maryland
Charles Murphy, Baltimore City Recreation & Parks
Anna Ngai, The Regional Greenhouse Gas Initiative (RGGI)
Robert O'Connor, Massachusetts Executive Office of Energy & Environmental Affairs
Nathan Randolph, Baltimore City Recreation & Parks
Jared Snyder, New York State Department of Environmental Conservation, Office of Climate Change
Kari St. Laurent, Delaware DNREC
Don Strebel, Versar, Inc.
Kevin Townsend, Blue Source

Project URL(s): None provided.
 
Data
Products:
Product Title:  High-density canopy maps of afforestation areas, along with estimates of biomass sequestered since project initiation
Time Period:  Variable based on Lidar acquisition dates (2004-2015)
Description:  - Produce estimates of biomass accumulation on afforestation sites
Status:  Planned
CMS Science Theme(s):  Land Biomass; MRV
Keywords:  Sink (; terrestrial)
Spatial Extent:  Maryland and Pennsylvania
Spatial Resolution:  30 m
Temporal Frequency:  Once
Input Data Products:  New lidar flights over afforestation areas
Algorithm/Models Used:  Linear regression models, Random Forests/BMA
Evaluation:  Field based estimates of biomass accumulation in afforestation areas
Intercomparison Efforts/Gaps:  Intercompare remote-sensing based method with field-based estimates
Uncertainty Estimates:  - Pixel-level uncertainty estimates for local scale biomass map ;
Uncertainty Categories:  model-data comparison, model-model comparison
Application Areas:  - MRV; - Land management ; - Forest inventory
Relevant Policies/Programs:  FIA, Federal Land Policy and Management Act (FLPMA), Maryland Greenhouse Gas Emissions Reduction Act Plan, Maryland Climate Action Plan, Chesapeake Bay TMDL, Maryland Forest Preservation Act, Maryland No Net Forest Loss Act; Improved FIA method over urban forests
Potential Users:  Afforestation projects
Stakeholders:  Blue Soure; Maryland DNR; PA DCNR; RGGI
Current Application Readiness Level:  5
Start Application Readiness Level:  5
Target Application Readiness Level:  9
Future Developments:  
Limitations:  
Date When Product Available:  By 2017
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Maps of aboveground biomass change
Time Period:  Variable based on Lidar acquisition dates (2004-2015)
Description:  - Produce mapped changes in above Ground biomass for Maryland
Status:  Planned
CMS Science Theme(s):  Land Biomass; Land-Atmosphere Flux; MRV
Keywords:  Flux/Movement (; terrestrial; ; atmospheric)
Spatial Extent:  Maryland
Spatial Resolution:  30 m
Temporal Frequency:  Once
Input Data Products:  Discrete return lidar (obtained from USGS/Department of Natural Resources/individual counties), Landsat disturbance
Algorithm/Models Used:  Linear regression models, Random Forests/BMA
Evaluation:  
Intercomparison Efforts/Gaps:  Intercompare empirical model estimates and process model estimates;
Uncertainty Estimates:  - Pixel-level uncertainty estimates for local scale biomass map ;
Uncertainty Categories:  model-data comparison, model-model comparison
Application Areas:  - MRV; - Land management ; - Forest inventory
Relevant Policies/Programs:  FIA, Federal Land Policy and Management Act (FLPMA), Maryland Greenhouse Gas Emissions Reduction Act Plan, Maryland Climate Action Plan, Chesapeake Bay TMDL, Maryland Forest Preservation Act, Maryland No Net Forest Loss Act; Improved FIA method over urban forests
Potential Users:  Maryland Department of Natural Resources (DNR) Forest Service, Maryland Public Service Commission, Delaware Forest Service, Delaware DNREC, Pennsylvania DCNR Bureau of Forestry, USFS, DOE, EPA, RGGI, Blue Source, LLC, Chesapeake Conservancy, Pinchot Institute, private landowners, county GIS departments, national and global entities that want to validate top down products
Stakeholders:  Blue Soure; Delaware DNR; Maryland DNR; PA DCNR; RGGI
Current Application Readiness Level:  5
Start Application Readiness Level:  5
Target Application Readiness Level:  9
Future Developments:  
Limitations:  
Date When Product Available:  By 2017
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Prognostic ecosystem model (ED) based maps of carbon stocks and flux.
Time Period:  Variable based on Lidar acquisition dates (2004-2015)
Description:  - Initialize and run a prognostic ecosystem model for carbon at high-spatial resolution over multiple eastern states.
Status:  Planned
CMS Science Theme(s):  Land Biomass; MRV
Keywords:  Carbon Stocks (; terrestrial); ; Flux/Movement (; anthropogenic; ; terrestrial; ; atmospheric)
Spatial Extent:  Pennsylvania, Delaware, and Maryland
Spatial Resolution:  90 m
Temporal Frequency:  Once
Input Data Products:  Discrete return lidar (obtained from USGS/Department of Natural Resources/individual counties), Landsat disturbance
Algorithm/Models Used:  Ecosystem Demography Model
Evaluation:  New field plots to validate biomass estimates; cross validation with empirical biomass maps over domain
Intercomparison Efforts/Gaps:  Intercompare empirical model estimates and process model estimates;
Uncertainty Estimates:  
Uncertainty Categories:  model-data comparison, model-model comparison
Application Areas:  - MRV; - Land management ; - Forest inventory
Relevant Policies/Programs:  FIA, Federal Land Policy and Management Act (FLPMA), Maryland Greenhouse Gas Emissions Reduction Act Plan, Maryland Climate Action Plan, Chesapeake Bay TMDL, Maryland Forest Preservation Act, Maryland No Net Forest Loss Act; Improved FIA method over urban forests
Potential Users:  Maryland Department of Natural Resources (DNR) Forest Service, Maryland Public Service Commission, Delaware Forest Service, Delaware DNREC, Pennsylvania DCNR Bureau of Forestry, USFS, DOE, EPA, RGGI, Blue Source, LLC, Chesapeake Conservancy, Pinchot Institute, private landowners, county GIS departments, national and global entities that want to validate top down products
Stakeholders:  Blue Soure; Delaware DNR; Maryland DNR; PA DCNR; RGGI
Current Application Readiness Level:  5
Start Application Readiness Level:  5
Target Application Readiness Level:  9
Future Developments:  
Limitations:  
Date When Product Available:  By 2017
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Canopy Height and Biomass from LiDAR Surveys at La Selva, Costa Rica, 1998 and 2005
Start Date:  03/1998      End Date:  03/2005     (The data represents vegetation as measured in March 1998 and March 2005.)
Description:  This data set contains land-use, canopy height, and aboveground carbon estimates derived from LiDAR data collected at La Selva Biological Station in Costa Rica in March 1998 and March 2005. The data are provided as GeoTIFFs (.tif) of 100-m (1-ha) resolution. A look-up table is provided that relates modeled changes in height to changes in stand characteristics (including age and carbon content). The data were used to test the accuracy and scale-dependency of high-resolution predictions of vegetation dynamics and carbon flux by the Ecosystem Demography (ED). The ED model is an individual-based terrestrial ecosystem model that predicts both ecosystem structure and corresponding ecosystem fluxes from climate, soil, and land-use inputs.
Status:  Archived
CMS Science Theme(s):  Land Biomass; MRV
Keywords:  canopy height,forest biomass, lidar
Spatial Extent:  La Selva Biological Station in Costa Rica
Spatial Resolution:  100 meter (1 ha)
Temporal Frequency:  Discrete measurements
Input Data Products:  Laser Vegetation Imaging Sensor (LVIS), Land cover data, IKONOS satellite imagery
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  Carbon cycle scientists
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  April 2016
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1312
Data Server URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1312
Archived Data Citation:  Hurtt, G.C., R.Q. Thomas, J. Fisk, R.O. Dubayah, and S.L. Sheldon. 2016. Canopy Height and Biomass from LiDAR Surveys at La Selva, Costa Rica, 1998 and 2005. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1312

Bounding Coordinates:
West Longitude:-84.05000 East Longitude:-84.00000
North Latitude:10.45000 South Latitude:10.40000

Product Title:  CMS: LiDAR-derived Tree Canopy Cover for States in the Northeast USA
Start Date:  01/2008      End Date:  08/2014     (2008)
Description:  This data set provides high-resolution (1-m) tree canopy cover for states in the Northeast USA. State-level canopy cover data are currently available for Pennsylvania (data for nominal year 2008), Delaware (2014), and Maryland (2013). The data were derived with a rules-based expert system which facilitated integration of leaf-on LiDAR and imagery data into a single classification workflow, exploiting the spectral, height, and spatial information contained in the datasets. Additional states will be added as data processing is completed.
Status:  Archived
CMS Science Theme(s):  Land Biomass; MRV
Keywords:  
Spatial Extent:  Pennsylvania, Delaware and MarylandUSA
Spatial Resolution:  1 m
Temporal Frequency:  One time estimate for each state
Input Data Products:  County-level 2006-2008 LiDAR point cloud data, building polygon data obtained from certain counties, and 2010 leaf-on imagery from the NAIP
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  Pennsylvania Climate Change Act, TreeVitalize Program, Enhance Penn's Woods Program, Greenways Program, Pennsylvania Natural Heritage Program, Pennsylvania Forest Action Plan
Potential Users:  Pennsylvania DCNR Bureau of Forestry, USFS, DOE, EPA, RGGI, private landowners, county GIS departments,national and global entities that want to validate top down products
Stakeholders:  
Current Application Readiness Level:  8
Start Application Readiness Level:  5
Target Application Readiness Level:  9
Future Developments:  
Limitations:  
Date When Product Available:  July 2016
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1334
Data Server URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1334
Archived Data Citation:  O'Neil-Dunne, J. 2019. CMS: LiDAR-derived Tree Canopy Cover for States in the Northeast USA. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1334

Bounding Coordinates:
West Longitude:-81.14000 East Longitude:-74.15000
North Latitude:43.10000 South Latitude:37.71000

Product Title:  Forest Aboveground Biomass and Carbon Sequestration Potential for Maryland, USA
Start Date:  01/2011      End Date:  12/2011     (nominal year 2011)
Description:  This dataset provides 90-m resolution maps of estimated forest aboveground biomass (Mg/ha) for nominal year 2011 and projections of carbon sequestration potential for the state of Maryland. Estimated biomass and sequestration potential were computed using the Ecosystem Demography (ED) model, which integrates data from multiple sources, including: climate variables from the North American Regional Reanalysis (NARR) Product, soil variables from the Soil Survey Geographic Database (SSURGO), land cover variables from airborne lidar, the National Agriculture Imagery Program (NAIP) and the National Land Cover Database (NLCD), and vegetation parameters from the Forest Inventory and Analysis (FIA) Program.
Status:  Archived
CMS Science Theme(s):  Land Biomass
Keywords:  
Spatial Extent:  State of Maryland
Spatial Resolution:  90 m grid cells
Temporal Frequency:  nominal year 2011
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  8
Start Application Readiness Level:  5
Target Application Readiness Level:  9
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1660
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1660
Archived Data Citation:  Hurtt, G.C., M. Zhao, R. Sahajpal, A. Armstrong, R. Birdsey, E. Campbell, K. Dolan, R.O. Dubayah, J.P. Fisk, S. Flanagan, C. Huang, W. Huang, K. Johnson, R. Lamb, L. Ma, R. Marks, D. O'Leary III, J. O'Neil-Dunne, A. Swatantran, and H. Tang. 2019. Forest Aboveground Biomass and Carbon Sequestration Potential for Maryland, USA. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1660

Bounding Coordinates:
West Longitude:-79.52000 East Longitude:-75.05000
North Latitude:39.81000 South Latitude:37.83000

Product Title:  LiDAR Derived Biomass, Canopy Height, and Cover for New England Region, USA, 2015
Start Date:  01/2010      End Date:  12/2015     (2010-2015)
Description:  This dataset provides 30 m gridded estimates of aboveground biomass density (AGBD), forest canopy height, and tree canopy coverage for the New England Region of the U.S., including the state of Maine, Vermont, New Hampshire, Massachusetts, Connecticut, and Rhode Island, for the nominal year 2015. It is based on inputs from 1 m resolution Leaf-off LiDAR data collected from 2010 through 2015, high-resolution leaf-on agricultural imagery, and FIA plot-level measurements. Canopy height and tree cover were derived directly from LiDAR data while AGBD was estimated by statistical models that link remote sensing data and FIA plots at the pixel level. Error in AGBD was calculated at the 90% confidence interval. This approach can directly contribute to the formation of a cohesive forest carbon accounting system at national and even international levels, especially via future integrations with NASA's spaceborne LiDAR missions.
Status:  Archived
CMS Science Theme(s):  Land Biomass
Keywords:  
Spatial Extent:  Connecticut, New Hampshire, Massachusetts, Maine, Rhode Island, Vermont, U.S.
Spatial Resolution:  30 m
Temporal Frequency:  Annual and for the nominal year 2015
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  7
Start Application Readiness Level:  5
Target Application Readiness Level:  9
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1854
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1854
Archived Data Citation:  Tang, H., L. Ma, A.J. Lister, J. O'Neil-Dunne, J. Lu, R. Lamb, R.O. Dubayah, and G.C. Hurtt. 2021. LiDAR Derived Biomass, Canopy Height, and Cover for New England Region, USA, 2015. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1854

Bounding Coordinates:
West Longitude:-74.80000 East Longitude:-66.36000
North Latitude:46.76000 South Latitude:39.96000

 
Publications: Datta, A., Banerjee, S., Finley, A. O., Hamm, N. A. S., Schaap, M. 2016. Nonseparable dynamic nearest neighbor Gaussian process models for large spatio-temporal data with an application to particulate matter analysis. The Annals of Applied Statistics. 10(3). DOI: 10.1214/16-AOAS931

Dolan, K. A., Hurtt, G. C., Flanagan, S. A., Fisk, J. P., Sahajpal, R., Huang, C., Page, Y. L., Dubayah, R., Masek, J. G. 2017. Disturbance Distance: quantifying forests' vulnerability to disturbance under current and future conditions. Environmental Research Letters. 12(11), 114015. DOI: 10.1088/1748-9326/aa8ea9

Finley, A. O., Banerjee, S., E.Gelfand, A. 2015. spBayesfor Large Univariate and Multivariate Point-Referenced Spatio-Temporal Data Models. Journal of Statistical Software. 63(13). DOI: 10.18637/jss.v063.i13

Finley, A. O., Banerjee, S., Weiskittel, A. R., Babcock, C., Cook, B. D. 2014. Dynamic spatial regression models for space-varying forest stand tables. Environmetrics. 25(8), 596-609. DOI: 10.1002/env.2322

Huang, W., Dolan, K., Swatantran, A., Johnson, K., Tang, H., O'Neil-Dunne, J., Dubayah, R., Hurtt, G. 2019. High-resolution mapping of aboveground biomass for forest carbon monitoring system in the Tri-State region of Maryland, Pennsylvania and Delaware, USA. Environmental Research Letters. 14(9), 095002. DOI: 10.1088/1748-9326/ab2917

Hurtt, G., Zhao, M., Sahajpal, R., Armstrong, A., Birdsey, R., Campbell, E., Dolan, K., Dubayah, R., Fisk, J. P., Flanagan, S., Huang, C., Huang, W., Johnson, K., Lamb, R., Ma, L., Marks, R., O'Leary, D., O'Neil-Dunne, J., Swatantran, A., Tang, H. 2019. Beyond MRV: high-resolution forest carbon modeling for climate mitigation planning over Maryland, USA. Environmental Research Letters. 14(4), 045013. DOI: 10.1088/1748-9326/ab0bbe

Itter, M. S., Finley, A. O., D'Amato, A. W., Foster, J. R., Bradford, J. B. 2017. Variable effects of climate on forest growth in relation to climate extremes, disturbance, and forest dynamics. Ecological Applications. 27(4), 1082-1095. DOI: 10.1002/eap.1518

Johnson, K. D., Birdsey, R., Cole, J., Swatantran, A., O'Neil-Dunne, J., Dubayah, R., Lister, A. 2015. Integrating LIDAR and forest inventories to fill the trees outside forests data gap. Environmental Monitoring and Assessment. 187(10). DOI: 10.1007/s10661-015-4839-1

Johnson, K. D., Birdsey, R., Finley, A. O., Swantaran, A., Dubayah, R., Wayson, C., Riemann, R. 2014. Integrating forest inventory and analysis data into a LIDAR-based carbon monitoring system. Carbon Balance and Management. 9(1). DOI: 10.1186/1750-0680-9-3

Johnson, K. D., Domke, G. M., Russell, M. B., Walters, B., Hom, J., Peduzzi, A., Birdsey, R., Dolan, K., Huang, W. 2017. Estimating aboveground live understory vegetation carbon in the United States. Environmental Research Letters. 12(12), 125010. DOI: 10.1088/1748-9326/aa8fdb

Riemann, R., Liknes, G., O'Neil-Dunne, J., Toney, C., Lister, T. 2016. Comparative assessment of methods for estimating tree canopy cover across a rural-to-urban gradient in the mid-Atlantic region of the USA. Environmental Monitoring and Assessment. 188(5). DOI: 10.1007/s10661-016-5281-8

Tang, H., Ma, L., Lister, A., O'Neill-Dunne, J., Lu, J., Lamb, R. L., Dubayah, R., Hurtt, G. 2021. High-resolution forest carbon mapping for climate mitigation baselines over the RGGI region, USA. Environmental Research Letters. 16(3), 035011. DOI: 10.1088/1748-9326/abd2ef

Finley, A. O., Banerjee, S., Zhou, Y., Cook, B. D., Babcock, C. 2017. Joint hierarchical models for sparsely sampled high-dimensional LiDAR and forest variables. Remote Sensing of Environment. 190, 149-161. DOI: 10.1016/j.rse.2016.12.004

Datta, A., Banerjee, S., Finley, A. O., Gelfand, A. E. 2016. On nearest-neighbor Gaussian process models for massive spatial data. WIREs Computational Statistics. 8(5), 162-171. DOI: 10.1002/wics.1383

Salazar, E., Hammerling, D., Wang, X., Sanso, B., Finley, A. O., Mearns, L. O. 2016. Observation-based blended projections from ensembles of regional climate models. Climatic Change. 138(1-2), 55-69. DOI: 10.1007/s10584-016-1722-1

Babcock, C., Finley, A. O., Cook, B. D., Weiskittel, A., Woodall, C. W. 2016. Modeling forest biomass and growth: Coupling long-term inventory and LiDAR data. Remote Sensing of Environment. 182, 1-12. DOI: 10.1016/j.rse.2016.04.014

Datta, A., Banerjee, S., Finley, A. O., Gelfand, A. E. 2016. Hierarchical Nearest-Neighbor Gaussian Process Models for Large Geostatistical Datasets. Journal of the American Statistical Association. 111(514), 800-812. DOI: 10.1080/01621459.2015.1044091

Flanagan, S., Hurtt, G., Fisk, J., Sahajpal, R., Hansen, M., Dolan, K., Sullivan, J., Zhao, M. 2016. Potential Vegetation and Carbon Redistribution in Northern North America from Climate Change. Climate. 4(1), 2. DOI: 10.3390/cli4010002

Hurtt, G. C., Thomas, R. Q., Fisk, J. P., Dubayah, R. O., Sheldon, S. L. 2016. The Impact of Fine-Scale Disturbances on the Predictability of Vegetation Dynamics and Carbon Flux. PLOS ONE. 11(4), e0152883. DOI: 10.1371/journal.pone.0152883

Babcock, C., Finley, A. O., Bradford, J. B., Kolka, R., Birdsey, R., Ryan, M. G. 2015. LiDAR based prediction of forest biomass using hierarchical models with spatially varying coefficients. Remote Sensing of Environment. 169, 113-127. DOI: 10.1016/j.rse.2015.07.028

Hamm, N. A. S., Finley, A. O., Schaap, M., Stein, A. 2015. A spatially varying coefficient model for mapping PM10 air quality at the European scale. Atmospheric Environment. 102, 393-405. DOI: 10.1016/j.atmosenv.2014.11.043

Huang, W., Swatantran, A., Johnson, K., Duncanson, L., Tang, H., O'Neil Dunne, J., Hurtt, G., Dubayah, R. 2015. Local discrepancies in continental scale biomass maps: a case study over forested and non-forested landscapes in Maryland, USA. Carbon Balance and Management. 10(1). DOI: 10.1186/s13021-015-0030-9

Junttila, V., Kauranne, T., Finley, A. O., Bradford, J. B. 2015. Linear Models for Airborne-Laser-Scanning-Based Operational Forest Inventory With Small Field Sample Size and Highly Correlated LiDAR Data. IEEE Transactions on Geoscience and Remote Sensing. 53(10), 5600-5612. DOI: 10.1109/TGRS.2015.2425916

Archived Data Citations: Hurtt, G.C., R.Q. Thomas, J. Fisk, R.O. Dubayah, and S.L. Sheldon. 2016. Canopy Height and Biomass from LiDAR Surveys at La Selva, Costa Rica, 1998 and 2005. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1312

O'Neil-Dunne, J. 2019. CMS: LiDAR-derived Tree Canopy Cover for States in the Northeast USA. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1334

Hurtt, G.C., M. Zhao, R. Sahajpal, A. Armstrong, R. Birdsey, E. Campbell, K. Dolan, R.O. Dubayah, J.P. Fisk, S. Flanagan, C. Huang, W. Huang, K. Johnson, R. Lamb, L. Ma, R. Marks, D. O'Leary III, J. O'Neil-Dunne, A. Swatantran, and H. Tang. 2019. Forest Aboveground Biomass and Carbon Sequestration Potential for Maryland, USA. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1660

Tang, H., L. Ma, A.J. Lister, J. O'Neil-Dunne, J. Lu, R. Lamb, R.O. Dubayah, and G.C. Hurtt. 2021. LiDAR Derived Biomass, Canopy Height, and Cover for New England Region, USA, 2015. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1854

Outreach Activities: NASA has a traveling display called the Hyperwall consisting of a wall of multiple high definition screens displaying high resolution images simultaneously. View the Hyperwall presentation for this project

2015 NASA Carbon Cycle & Ecosystems Joint Science Workshop Poster(s)
  • High-Resolution Carbon Monitoring and Modeling: Continuing Prototype Development and Deployment   --   (George Hurtt, Richard Birdsey, Molly Elizabeth Brown, Philip DeCola, Katelyn Dolan, Ralph Dubayah, Vanessa Marie Escobar, Andrew Finley, Chang Huang, Kristofer Johnson, Jarlath O'Neil-Dunne, Maosheng Zhao)   [abstract]
  • Integrating Lidar Canopy Height and Landsat-based Forest Disturbance History with Ecosystem Demography Model for Carbon Change Estimation, A Case in Charles County, Maryland   --   (Maosheng Zhao, Chengquan Huang, George Hurtt, Ralph Dubayah, Justin Fisk, Anu Swatantran, Wenli Huang, Hao Tang)   [abstract]


 

Jacob (CMS 2014) (2014)
Project Title:High-Resolution Constraints on North American and Global Methane Sources Using Satellites

Science Team
Members:

Daniel Jacob, Harvard University (Project Lead)
Kevin Bowman, JPL

Solicitation:NASA: Carbon Monitoring System (2014)
Successor Projects: Jacob (CMS 2016)  
Abstract: Our proposal will focus on the exploitation of GOSAT and TROPOMI data to better constrain anthropogenic and natural methane emissions at high resolution (0.25x0.33 deg) in North America and globally at (2x2.5 deg). Our work takes advantage of previous integration with CMS-Flux that uses a consistent 4DVAR capability and wetland emissions driven by common biogeochemical models and data. Products generated from this proposal will be used in collaboration with EPA scientists in integrating the information from bottom-up and top-down constraints on emissions. We anticipate a budget request of $300 K per year for three years.
Project Associations:
  • CMS
CMS Primary Theme:
  • Land-Atmosphere Flux
CMS Science Theme(s):
  • Atmospheric Transport
  • Land-Atmosphere Flux
  • Decision Support
  • MRV

Participants:

Ramon Alvarez, Environmental Defense Fund
Kevin Bowman, JPL
Ritesh Gautam, Environmental Defense Fund
Steven Hamburg, Environmental Defense Fund
William (Bill) Irving, U.S. EPA Climate Change Division
Daniel Jacob, Harvard University
Joannes Maasakkers, SRON Netherlands Institute for Space Research
Michael (Mike) Moran, Environment and Climate Change Canada (ECCC)
Claudia (Claudia Octaviano) Octaviano Villasana, Mexican National Institute of Ecology and Climate Change (INECC Mexico)
Ben Ratner, Environmental Defense Fund
Alexander Turner, University of California
Melissa Weitz, U.S. EPA Climate Change Division

Project URL(s): None provided.
 
Data
Products:
Product Title:  CMS: Global 0.5-deg Wetland Methane Emissions and Uncertainty (WetCHARTs v1.0)
Start Date:  01/2001      End Date:  12/2015     (2001-2015)
Description:  This data set provides global monthly wetland methane (CH4) emissions and uncertainty data products derived from an ensemble of multiple terrestrial biosphere models, wetland extent scenarios, and CH4:C temperature dependencies. The data are at 0.5 by 0.5-degree resolution. Two model output data products are included in WetCHARTs v1.0: an output from the full ensemble for 2009-2010 and an output from a limited subset for 2001-2015. The intended use of the products is as a process-informed wetland CH4 emission and uncertainty data set for atmospheric chemistry and transport modelling (WetCHARTs).
Status:  Archived
CMS Science Theme(s):  Atmospheric Transport; Global Surface-Atmosphere Flux; Land-Atmosphere Flux
Keywords:  Flux/Movement; Uncertainties & Standard Errors
Spatial Extent:  Global
Spatial Resolution:  0.5 x 0.5
Temporal Frequency:  Monthly
Input Data Products:  Multiple terrestrial biosphere models, wetland extent scenarios and CH4:C temperature dependencies
Algorithm/Models Used:  
Evaluation:  The mean full ensemble and mean extended ensemble wetland emissions data were compared against a range of independent wetland CH4 regional emission estimates.
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  Use in atmospheric chemical transport models (WetCHARTs version 1.0); MRV; GHG emissions inventory; Watershed protection plans; Air quality protection; Land management and conservation
Relevant Policies/Programs:  Global Climate Change and Clean Air Initiative of the US State Department, Global Methane Initiative of the US EPA
Potential Users:  Air quality agencies at national level (e.g. EPA), industry groups (e.g. American Petroleum Institute), US State Department
Stakeholders:  
Current Application Readiness Level:  9
Start Application Readiness Level:  3
Target Application Readiness Level:  9
Future Developments:  
Limitations:  
Date When Product Available:  June 2017
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1502
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1502
Archived Data Citation:  Bloom, A.A., K. Bowman, M. Lee, A.J. Turner, R. Schroeder, J.R. Worden, R.J. Weidner, K.C. McDonald, and D.J. Jacob. 2017. CMS: Global 0.5-deg Wetland Methane Emissions and Uncertainty (WetCHARTs v1.0). ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1502

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

Product Title:  Methane (CH4) Flux for Canadian Oil/Gas Systems L4 V1 (CMS_CH4_FLX_CA) at GES DISC
Start Date:  01/2013      End Date:  01/2014     (2013)
Description:  This data set (CMS_CH4_FLX_CA) contains the yearly average methane (CH4) flux for Canada's oil and gas systems based on a bottom up calculation of oil/gas emissions reported by ICF International in 2013. A related data set (CMS_CH4_FLX_MX) contains the yearly average methane (CH4) flux for Mexico's oil and gas systems based on a bottom up calculation of oil/gas emissions reported by the Mexican Petrolium Institute in 2010. The Canadian emissions are concentrated in Alberta (gas production and processing) and the Mexican emissions are concentrated along the east coast (oil production). More details about the observations, algorithm, and scientific findings are described in Sheng et al. 2017.

The NASA Carbon Monitoring System (CMS) is designed to make significant contributions in characterizing, quantifying, understanding, and predicting the evolution of global carbon sources and sinks through improved monitoring of carbon stocks and fluxes. The System will use the full range of NASA satellite observations and modeling/analysis capabilities to establish the accuracy, quantitative uncertainties, and utility of products for supporting national and international policy, regulatory, and management activities. CMS will maintain a global emphasis while providing finer scale regional information, utilizing space-based and surface-based data and will rapidly initiate generation and distribution of products both for user evaluation and to inform near-term policy development and planning.
Status:  Archived
CMS Science Theme(s):  Atmospheric Transport; Land-Atmosphere Flux; MRV
Keywords:  Source (; anthropogenic; terrestrial)
Spatial Extent:  Canada
Spatial Resolution:  0.1 x 0.1
Temporal Frequency:  1 year
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  - MRV; - GHG emissions inventory; - Air quality protection
Relevant Policies/Programs:  
Potential Users:  Air quality agencies at national level, industry groups, US State Department
Stakeholders:  EDF (Point of Contact: Ritesh Gautam, Daniel Zavala); EPA (Point of Contact: Bill Irving and his group in the Climate Change Division)
Current Application Readiness Level:  9
Start Application Readiness Level:  1
Target Application Readiness Level:  9
Future Developments:  
Limitations:  
Date When Product Available:  July 2017
Assigned Data Center:  GES DISC
Metadata URL(s):

https://acdisc.gsfc.nasa.gov/data/CMS/CMS_CH4_FLX_CA.1/doc/README.CMS_CH4_FLX_CAMX_V1.pdf
Data Server URL(s):

https://disc.gsfc.nasa.gov/datasets/CMS_CH4_FLX_CA_V1/summary?keywords=CMS
Archived Data Citation:  Jianxiong Sheng & Daniel Jacob(2016), Methane (CH4) Flux for Canada's Oil/Gas Systems L4 V1, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed [Data Access Date] 10.5067/6K2DW26DXETZ

Bounding Coordinates:
West Longitude:-142.05000 East Longitude:-47.05000
North Latitude:69.95000 South Latitude:40.05000

Product Title:  Methane (CH4) Flux for Mexican Oil/Gas Systems L4 V1 (CMS_CH4_FLX_MX) at GES DISC
Start Date:  01/2010      End Date:  01/2011     (2010)
Description:  This data set (CMS_CH4_FLX_MX) contains the yearly average methane (CH4) flux for Mexico's oil and gas systems based on a bottom up calculation of oil/gas emissions reported by the Mexican Petrolium Institute in 2010. A related data set (CMS_CH4_FLX_CA) contains the yearly average methane (CH4) flux for Canada's oil and gas systems based on a bottom up calculation of oil/gas emissions reported by ICF International in 2013. The Mexican emissions are concentrated along the east coast (oil production) and the Canadian emissions are concentrated in Alberta (gas production and processing). More details about the observations, algorithm, and scientific findings are described in Sheng et al. 2017.

The NASA Carbon Monitoring System (CMS) is designed to make significant contributions in characterizing, quantifying, understanding, and predicting the evolution of global carbon sources and sinks through improved monitoring of carbon stocks and fluxes. The System will use the full range of NASA satellite observations and modeling/analysis capabilities to establish the accuracy, quantitative uncertainties, and utility of products for supporting national and international policy, regulatory, and management activities. CMS will maintain a global emphasis while providing finer scale regional information, utilizing space-based and surface-based data and will rapidly initiate generation and distribution of products both for user evaluation and to inform near-term policy development and planning.
Status:  Archived
CMS Science Theme(s):  Atmospheric Transport; Land-Atmosphere Flux; MRV
Keywords:  Source (; anthropogenic; terrestrial)
Spatial Extent:  Mexico
Spatial Resolution:  0.1 x 0.1
Temporal Frequency:  1 year
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  - MRV; - GHG emissions inventory; - Air quality protection
Relevant Policies/Programs:  
Potential Users:  Air quality agencies at national level, industry groups, US State Department
Stakeholders:  EDF (Point of Contact: Ritesh Gautam, Daniel Zavala); EPA (Point of Contact: Bill Irving and his group in the Climate Change Division)
Current Application Readiness Level:  9
Start Application Readiness Level:  1
Target Application Readiness Level:  9
Future Developments:  
Limitations:  
Date When Product Available:  July 2017
Assigned Data Center:  GES DISC
Metadata URL(s):

https://acdisc.gsfc.nasa.gov/data/CMS/CMS_CH4_FLX_MX.1/doc/README.CMS_CH4_FLX_CAMX_V1.pdf
Data Server URL(s):

https://disc.gsfc.nasa.gov/datasets/CMS_CH4_FLX_MX_V1/summary?keywords=CMS
Archived Data Citation:  Jianxiong Sheng & Daniel Jacob(2016), Methane (CH4) Flux for Mexico's Oil/Gas Systems L4 V1, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed [Data Access Date] 10.5067/RZAQB50RV3BS

Bounding Coordinates:
West Longitude:-119.05000 East Longitude:-84.95000
North Latitude:33.95000 South Latitude:13.05000

Product Title:  Gridded National Inventory of U.S. Methane Emissions
Time Period:  2012
Description:  We present a gridded inventory of US anthropogenic methane emissions with 0.1 0.1 spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 US Environmental Protection Agency (EPA) Inventory of US Greenhouse Gas Emissions and Sinks (GHGI) for 2012. The EPA inventory is available only as national totals for different source types. We use a wide range of databases at the state, county, local, and point source level to disaggregate the inventory and allocate the spatial and temporal distribution of emissions for individual source types.
Status:  Public
CMS Science Theme(s):  Atmospheric Transport; Land-Atmosphere Flux; MRV
Keywords:  Source (; anthropogenic; terrestrial)
Spatial Extent:  CONUS
Spatial Resolution:  0.1 x 0.1
Temporal Frequency:  monthly and 8-day averages
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  national methane inventory reports to UNFCCC
Potential Users:  methane researchers, EPA, state agencies
Stakeholders:  EDF (Point of Contact: Ritesh Gautam, Daniel Zavala); EPA (Point of Contact: Bill Irving and his group in the Climate Change Division)
Current Application Readiness Level:  9
Start Application Readiness Level:  3
Target Application Readiness Level:  9
Future Developments:  
Limitations:  
Date When Product Available:  
Metadata URL(s):

https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions
Data Server URL(s):

https://www.epa.gov/ghgemissions/gridded-2012-methane-emissions
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  CMS: Global 0.5-deg Wetland Methane Emissions and Uncertainty (WetCHARTs v1.3.1)
Start Date:  01/2001      End Date:  12/2019     (2001-2019)
Description:  This dataset provides global monthly wetland methane (CH4) emissions estimates at 0.5 by 0.5-degree resolution for the period 2001-2019 that were derived from an ensemble of multiple terrestrial biosphere models, wetland extent scenarios, and CH4:C temperature dependencies that encompass the main sources of uncertainty in wetland CH4 emissions. There are 18 model configurations. WetCHARTs v1.3.1 is an updated product of WetCHARTs v1.0 Extended Ensemble. Three new features in the updated version include (1) the model output data is updated from 2001-2015 to 2001-2019, (2) the model drivers are replaced from using ERA-interim to ERA5 reanalysis data, and (3) the Global Lakes and Wetlands Database (GLWD) wetland extent definitions have been adjusted for the 50-100% Wetland, 25-50% Wetland, and Wetland Complex (0-25% Wetland) categories. The intended use of this product is as a process-informed wetland CH4 emission data set for atmospheric chemistry and transport modeling. Users can compare estimates by model configuration to explore variability and sensitivity with respect to ensemble members
Status:  Archived
CMS Science Theme(s):  Land-Atmosphere Flux
Keywords:  methane; wetlands
Spatial Extent:  Global
Spatial Resolution:  0.5 degrees
Temporal Frequency:  Monthly
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1915
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1915
Archived Data Citation:  Bloom, A.A., K.W. Bowman, M. Lee, A.J. Turner, R. Schroeder, J.R. Worden, R.J. Weidner, K.C. McDonald, and D.J. Jacob. 2021. CMS: Global 0.5-deg Wetland Methane Emissions and Uncertainty (WetCHARTs v1.3.1). ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1915

Bounding Coordinates:
West Longitude:-179.75000 East Longitude:179.75000
North Latitude:89.75000 South Latitude:-89.75000

 
Publications: Ma, S., Worden, J. R., Bloom, A. A., Zhang, Y., Poulter, B., Cusworth, D. H., Yin, Y., Pandey, S., Maasakkers, J. D., Lu, X., Shen, L., Sheng, J., Frankenberg, C., Miller, C. E., Jacob, D. J. 2021. Satellite Constraints on the Latitudinal Distribution and Temperature Sensitivity of Wetland Methane Emissions. AGU Advances. 2(3). DOI: 10.1029/2021AV000408

Parker, R. J., Boesch, H., McNorton, J., Comyn-Platt, E., Gloor, M., Wilson, C., Chipperfield, M. P., Hayman, G. D., Bloom, A. A. 2018. Evaluating year-to-year anomalies in tropical wetland methane emissions using satellite CH4 observations. Remote Sensing of Environment. 211, 261-275. DOI: 10.1016/j.rse.2018.02.011

Sheng, J., Jacob, D. J., Maasakkers, J. D., Sulprizio, M. P., Zavala-Araiza, D., Hamburg, S. P. 2017. A high-resolution (0.1deg x 0.1deg) inventory of methane emissions from Canadian and Mexican oil and gas systems. Atmospheric Environment. 158, 211-215. DOI: 10.1016/j.atmosenv.2017.02.036

Turner, A. J., Frankenberg, C., Wennberg, P. O., Jacob, D. J. 2017. Ambiguity in the causes for decadal trends in atmospheric methane and hydroxyl. Proceedings of the National Academy of Sciences. 114(21), 5367-5372. DOI: 10.1073/pnas.1616020114

Zhang, Y., Gautam, R., Pandey, S., Omara, M., Maasakkers, J. D., Sadavarte, P., Lyon, D., Nesser, H., Sulprizio, M. P., Varon, D. J., Zhang, R., Houweling, S., Zavala-Araiza, D., Alvarez, R. A., Lorente, A., Hamburg, S. P., Aben, I., Jacob, D. J. 2020. Quantifying methane emissions from the largest oil-producing basin in the United States from space. Science Advances. 6(17). DOI: 10.1126/sciadv.aaz5120

Maasakkers, J. D., Jacob, D. J., Sulprizio, M. P., Turner, A. J., Weitz, M., Wirth, T., Hight, C., DeFigueiredo, M., Desai, M., Schmeltz, R., Hockstad, L., Bloom, A. A., Bowman, K. W., Jeong, S., Fischer, M. L. 2016. Gridded National Inventory of U.S. Methane Emissions. Environmental Science & Technology. 50(23), 13123-13133. DOI: 10.1021/acs.est.6b02878

Turner, A. J., Jacob, D. J., Benmergui, J., Wofsy, S. C., Maasakkers, J. D., Butz, A., Hasekamp, O., Biraud, S. C. 2016. A large increase in U.S. methane emissions over the past decade inferred from satellite data and surface observations. Geophysical Research Letters. 43(5), 2218-2224. DOI: 10.1002/2016gl067987

Turner, A. J., Jacob, D. J., Wecht, K. J., Maasakkers, J. D., Lundgren, E., Andrews, A. E., Biraud, S. C., Boesch, H., Bowman, K. W., Deutscher, N. M., Dubey, M. K., Griffith, D. W. T., Hase, F., Kuze, A., Notholt, J., Ohyama, H., Parker, R., Payne, V. H., Sussmann, R., Sweeney, C., Velazco, V. A., Warneke, T., Wennberg, P. O., Wunch, D. 2015. Estimating global and North American methane emissions with high spatial resolution using GOSAT satellite data. Atmospheric Chemistry and Physics. 15(12), 7049-7069. DOI: 10.5194/acp-15-7049-2015

Turner, A. J., Jacob, D. J. 2015. Balancing aggregation and smoothing errors in inverse models. Atmospheric Chemistry and Physics. 15(12), 7039-7048. DOI: 10.5194/acp-15-7039-2015

Archived Data Citations: Jianxiong Sheng & Daniel Jacob(2016), Methane (CH4) Flux for Canada's Oil/Gas Systems L4 V1, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed [Data Access Date] 10.5067/6K2DW26DXETZ

Bloom, A.A., K. Bowman, M. Lee, A.J. Turner, R. Schroeder, J.R. Worden, R.J. Weidner, K.C. McDonald, and D.J. Jacob. 2017. CMS: Global 0.5-deg Wetland Methane Emissions and Uncertainty (WetCHARTs v1.0). ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1502

Jianxiong Sheng & Daniel Jacob(2016), Methane (CH4) Flux for Mexico's Oil/Gas Systems L4 V1, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed [Data Access Date] 10.5067/RZAQB50RV3BS

Bloom, A.A., K.W. Bowman, M. Lee, A.J. Turner, R. Schroeder, J.R. Worden, R.J. Weidner, K.C. McDonald, and D.J. Jacob. 2021. CMS: Global 0.5-deg Wetland Methane Emissions and Uncertainty (WetCHARTs v1.3.1). ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1915

Outreach Activities: NASA has a traveling display called the Hyperwall consisting of a wall of multiple high definition screens displaying high resolution images simultaneously. View the Hyperwall presentation for this project

5th NACP All-Investigators Meeting Posters (2015):
  • A gridded (0.1x0.1), monthly resolved version of the US EPA national methane emissions inventory for use as a priori and reference in methane source inversions -- (Joannes D Maasakkers, Daniel J Jacob, Melissa P Sulprizio, Melissa Weitz, Tom Wirth, Cate Hight, Bill Irving, Alexis A Bloom, Alexander J Turner) [abstract]


 

Lohrenz (CMS 2014) (2014)
Project Title:An Integrated Terrestrial-Coastal Ocean Observation and Modeling Framework for Carbon Management Decision Support

Science Team
Members:

Steven (Steve) Lohrenz, University of Massachusetts (Project Lead)
Hanqin Tian, Schiller Institute for Integrated Science and Society, Boston College

Solicitation:NASA: Carbon Monitoring System (2014)
Abstract: The NASA Carbon Monitoring System effort seeks to apply satellite remote sensing resources along with observational and modeling capabilities to improve monitoring of carbon stocks and fluxes, particularly as they contribute to the development of Monitoring, Reporting and Verification (MRV) system capabilities. Our prior NASA-funded research employs a combination of models and remotely-sensed and in situ observations to develop georeferenced products and associated uncertainties for land-ocean exchange of carbon, air-sea exchanges of carbon dioxide, and coastal to open ocean exchanges of carbon. A major aspect of this project has been to establish and populate geospatial portals for sharing and analysis of carbon datasets and products. The primary region of study has been the Mississippi River watershed and northern Gulf of Mexico. The unique nature of our approach, coupling models of terrestrial and ocean ecosystem dynamics and associated carbon processes, allows for assessment of how societal and human-related land use, land use change and forestry (LULUCF) and climate-related change affect terrestrial carbon storage and fluxes, as well as export of materials through watersheds to the coastal margins. Here, we propose to extend the domain of our observational and integrated terrestrial-ocean ecosystem model system to include the southeastern U.S. and South Atlantic Bight. In addition to land-ocean and sea-atmosphere exchanges, we will utilize satellite observations together with the capabilities of the terrestrial ecosystem model to characterize and quantify terrestrial carbon storage and fluxes, including land-atmosphere fluxes of both carbon dioxide and methane. Our approach will include assembling model products along with associated uncertainties and errors in a geospatial framework that will facilitate decision support for carbon and land use management. Objectives of the proposed research include the following: 1) Expand the spatial domain of our observational and integrated modeling approach to include the Mississippi River basin and southeastern U.S., and examine terrestrial carbon storage and fluxes including characterization and quantification of biomass and carbon stocks in and land-atmosphere, land-ocean, and sea-atmosphere fluxes of carbon dioxide and methane; 2) Examine different LULUCF scenarios within the terrestrial domain and different climate scenarios to assess effectiveness of carbon management strategies; 3) Engage with other CMS projects and stakeholders (e.g., USDA, National Climate Assessment, etc.) to identify user needs related to carbon management and MRV activities, modify and expand the scope of information based on user feedback, and explore possible transition of prototype products to fully operational status. The Application Readiness Level of our prior CMS project was rated as ARL-4 (Initial Implementation and Verification in Laboratory Environment), with the potential to advance to ARL-6 (Demonstration in a Relevant Environment). A goal of this proposed research will be to advance this capability to ARL-7 (Application of Prototype in Partners Operational Decision Making Environment). Our proposed effort will aid in the effective implementation of MRV approaches, which require an understanding of the contributions of individual forest and other ecotypes beyond local to regional and national scale carbon processes. Furthermore, our proposed effort will aid in governance and decision support related to carbon management, including the ability to evaluate different LULUCF scenarios in the context of changing climate conditions. Extended impacts of forest and other land use management strategies on carbon storage and transport, including in soils and into watersheds and coastal margins will be assessed. Finally, this information will be readily accessible as a geo-referenced product to support operational needs of stakeholders.
Measurement Approaches:
  • Remote Sensing
  • In Situ Measurements
  • Modeling
Project Associations:
  • CMS
CMS Primary Theme:
  • Land-Ocean Flux
CMS Science Theme(s):
  • Land Biomass
  • Land-Atmosphere Flux
  • Ocean-Atmosphere Flux
  • Land-Ocean Flux
  • Decision Support
  • MRV

Participants:

Wei-Jun Cai, University of Delaware
Ruoying He, North Carolina State University & Fathom Science
Steven (Steve) Lohrenz, University of Massachusetts
Benjamin Pfeil, Surface Ocean Carbon Atlas (SOCAT)
Gyami Shrestha, Lynker Corporation
Hanqin Tian, Schiller Institute for Integrated Science and Society, Boston College

Project URL(s): http://omgsrv1.meas.ncsu.edu:8080/thredds/sabgom_catalog.html
http://www.gulfcarbon.org
 
Data
Products:
Product Title:  Partial pressure (or fugacity) of carbon dioxide, salinity and other variables collected from Surface underway observations using Carbon dioxide (CO2) gas analyzer, Shower head chamber equilibrator for autonomous carbon dioxide (CO2) measurement and other instruments from the USS BOLD in the Gulf of Mexico from 2006-06-06 to 2006-09-11 (NCEI Accession 0117493)
Start Date:  06/2006      End Date:  09/2006     (1904-present, present-2099 (projected))
Description:  NODC Accession 0117493 includes Surface underway, chemical, meteorological and physical data collected from USS BOLD in the Gulf of Mexico from 2006-06-06 to 2006-09-11. These data include BAROMETRIC PRESSURE, Partial pressure (or fugacity) of carbon dioxide - water, SALINITY and SEA SURFACE TEMPERATURE. The instruments used to collect these data include Carbon dioxide (CO2) gas analyzer and Shower head chamber equilibrator for autonomous carbon dioxide (CO2) measurement.

These data were collected by Wei-Jun Cai, Wei-Jen Huang and Yongchen Wang of University of Georgia; School of Marine Programs as part of the Coastal_UG_Gulf_of_Mexico_2006 data set. CDIAC assigned the following cruise ID(s) to this data set: 31B520060606 (GM0606) and 31B520060906 (GM0609).

The Global Coastal Carbon Data Project data includes the bottle (discrete) and surface (underway) carbon-related measurements from coastal research cruises, the data from time series cruises and coastal moorings. The coastal regions data are very important for the understanding of carbon cycle on the continental margins.
Status:  Archived
CMS Science Theme(s):  MRV; Ocean-Atmosphere Flux
Keywords:  Flux/Movement (; oceanic; ; atmospheric)
Spatial Extent:  Southeastern U.S. and South Atlantic Bight
Spatial Resolution:  5 km
Temporal Frequency:  Monthly
Input Data Products:  Various
Algorithm/Models Used:  DLEM, SABGOM, ROMS, other
Evaluation:  MODIS, AVHRR, VIIRS, and other satellites, ship-based observations, NOAA Ocean Acidification monitoring program
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  We will focus on quantifying the estimation errors and uncertainties induced by modeling algorithms, model parameters, input data and the coupling between land and ocean models. Formal assessment of uncertainty in coupled land surface-ocean models includes several steps: (1) identification of the output(s) of interests, (2) identification of a limited set of input parameters to which outputs are most sensitive, and that may vary depending on the output of interest, (3) development of the distributions for inputs and their correlation structure, (4) design and evaluation of a Monte Carlo experiment. The input parameters exhibiting the highest model sensitivity will be identified and studied in more detail.
Uncertainty Categories:  ensemble
Application Areas:  - ocean acidification mitigation and carbon management
Relevant Policies/Programs:  NACP, National Climate Assessment of U.S. Global Change Research Program, NASA Coastal Carbon Synthesis, Carbon North America (CarboNA), Coastal Zone Management Act, Clean Water Act (CWA), US-Mexico Bilateral Framework on Clean Energy and Climate Change (US-Mexico Bilateral)
Potential Users:  NOAA, US Global Change Research Program
Stakeholders:  NASA SeaBASS Database (Point of Contact: Joel Scott, joel.scott@nasa.gov); NOAA Ocean Acidification Program (Point of Contact: Libby Jewett, libby.jewett@noaa.gov and Dwight Gledhill, dwight.gledhill@noaa.gov); Surface Ocean Carbon Atlas (SOCAT) (Point of Contact: Benjamin Pfeil, benjamin.pfeil@gfi.uib.no)
Current Application Readiness Level:  6
Start Application Readiness Level:  4
Target Application Readiness Level:  7
Future Developments:  None at this time
Limitations:  Limited by reliability of estimated ocean boundary condition; model validation limited by number of in situ observations; satellite comparisons constrained by cloud coverage and continuity of ocean color imagery
Date When Product Available:  June 2012
Assigned Data Center:  CDIAC
Metadata URL(s):

https://cdiac.ess-dive.lbl.gov/ftp/oceans/UG_GoM_UW_Data//2006.data/GM0606_Meta.html

https://cdiac.ess-dive.lbl.gov/ftp/oceans/UG_GoM_UW_Data//2006.data/GM0609_Meta.html
Data Server URL(s):

https://cdiac.ess-dive.lbl.gov/ftp/oceans/UG_GoM_UW_Data//2006.data/

http://omgsrv1.meas.ncsu.edu:8080/ocean-circulation/carbon.jsp
Archived Data Citation:  Cai, W.-J., Y. Wang, and W.-J. Huang. 2012. Sea Surface pCO2 measurements in the Gulf of Mexico during the Ocean Survey Vessel Bold cruises in 2006. http://cdiac.ornl.gov/ftp/oceans/UG_GoM_UW_Data/2006.data. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, US Department of Energy, Oak Ridge, Tennessee. DOI: 10.3334/CDIAC/OTG.UG_GOM_UW_2006.

Xue, Z., R. He, K. Fennel, W. J. Cai, S. Lohrenz, W. J. Huang, H. Tian, W. Ren, and Z. Zang (2016), Modeling pCO2 variability in the Gulf of Mexico, Biogeosciences, 13(15), 4359-4377, DOI: 10.5194/bg-13-4359-2016

Bounding Coordinates:
West Longitude:-93.43010 East Longitude:-87.33980
North Latitude:30.23490 South Latitude:28.17990

Product Title:  Spatial patterns of carbon and other products in the Gulf of Mexico and South Atlantic Bight
Description:  Map-based visualization of monthly ocean physical conditions and processes and carbon and other biogeochemical properties in the Gulf of Mexico and South Atlantic Bight from 2005-2010
Status:  Public
CMS Science Theme(s):  Land Biomass; Land-Atmosphere Flux; Land-Ocean Flux; MRV; Ocean-Atmosphere Flux
Keywords:  Evaluation & User Interfaces
Spatial Extent:  
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  - MRV; - Land management; - Watershed protection plans; - Ocean acidification mitigation and carbon management
Relevant Policies/Programs:  NACP, National Climate Assessment of U.S. Global Change Research Program, NASA Coastal Carbon Synthesis, Carbon North America (CarboNA), Coastal Zone Management Act, Clean Water Act (CWA), US-Mexico Bilateral Framework on Clean Energy and Climate Change (US-Mexico Bilateral)
Potential Users:  USDA, EPA (Mississippi River/Gulf of Mexico Watershed Nutrient Task Force), NOAA, USGS, US Global Change Research Program, CMS terrestrial flux teams
Stakeholders:  NASA SeaBASS Database (Point of Contact: Joel Scott, joel.scott@nasa.gov); NOAA Ocean Acidification Program (Point of Contact: Libby Jewett, libby.jewett@noaa.gov and Dwight Gledhill, dwight.gledhill@noaa.gov)
Current Application Readiness Level:  5
Start Application Readiness Level:  4
Target Application Readiness Level:  7
Future Developments:  None at this time
Limitations:  Model projections are dependent on reliability of climate and land use scenarios
Date When Product Available:  Variable
Metadata URL(s):
Data Server URL(s):

http://omgsrv1.meas.ncsu.edu:8080/ocean-circulation/carbon.jsp
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Gulf of Mexico carbon and bio-optical measurements
Start Date:  01/2009
Description:  Satellite Assessment of CO2 Distribution, Variability and Flux and Understanding of Control Mechanisms in a River Dominated Ocean Margin
Status:  Archived
CMS Science Theme(s):  
Keywords:  
Spatial Extent:  
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  NOAA, US Global Change Research Program
Stakeholders:  
Current Application Readiness Level:  6
Start Application Readiness Level:  4
Target Application Readiness Level:  7
Future Developments:  
Limitations:  
Date When Product Available:  September 2014
Assigned Data Center:  SeaBASS
Metadata URL(s):
Data Server URL(s):

https://seabass.gsfc.nasa.gov/experiment/GulfCarbon
Archived Data Citation:  Lohrenz, S. E., W.-J. Cai, S. Chakraborty, W.-J. Huang, K. Martin, X. Chen. Phytoplankton pigment, optical properties and CTD data from the Gulf of Mexico during the R/V Cape Hatteras cruises in 2009 and 2010. http://seabass.gsfc.nasa.gov/seabasscgi/data.cgi?experiment=GulfCarbon. DOI: 10.5067/SeaBASS/GULFCARBON/DATA001

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

Product Title:  Partial pressure (or fugacity) of carbon dioxide, salinity and other variables collected from underway - surface observations using Carbon dioxide (CO2) gas analyzer, Shower head chamber equilibrator for autonomous carbon dioxide (CO2) measurement and other instruments from the CAPE HATTERAS in the Gulf of Mexico from 2009-01-09 to 2010-03-21 (NCEI Accession 0115765)
Start Date:  01/2009      End Date:  03/2010
Description:  NODC Accession 0115765 includes chemical, meteorological, physical and underway - surface data collected from CAPE HATTERAS in the Gulf of Mexico from 2009-01-09 to 2010-03-21. These data include BAROMETRIC PRESSURE, CARBON DIOXIDE - AIR, Partial pressure (or fugacity) of carbon dioxide, SALINITY and SEA SURFACE TEMPERATURE. The instruments used to collect these data include Carbon dioxide (CO2) gas analyzer and Shower head chamber equilibrator for autonomous carbon dioxide (CO2) measurement.

These data were collected by Wei-Jun Cai of University of Delaware; College of Earth, Ocean, and Environment; School of Marine Science and Policy as part of the Coastal_Cape Hatteras_GM_0901, Coastal_Cape_Hatteras_GM_0904, Coastal_Cape_Hatteras_GM_0907 and Coastal_Cape_Hatteras_GM_1003 data set. CDIAC assigned the following cruise ID(s) to this data set: 32KZ20090109, 32KZ20090420, 32KZ20090719 and 32KZ20100311.

The Global Coastal Carbon Data Project data includes the bottle (discrete) and surface (underway) carbon-related measurements from coastal research cruises, the data from time series cruises and coastal moorings. The coastal regions data are very important for the understanding of carbon cycle on the continental margins.
Status:  Archived
CMS Science Theme(s):  
Keywords:  
Spatial Extent:  
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  NOAA, US Global Change Research Program
Stakeholders:  NOAA Ocean Acidification Program (Point of Contact: Libby Jewett, libby.jewett@noaa.gov and Dwight Gledhill, dwight.gledhill@noaa.gov)
Current Application Readiness Level:  6
Start Application Readiness Level:  4
Target Application Readiness Level:  7
Future Developments:  
Limitations:  
Date When Product Available:  December 2013
Assigned Data Center:  CDIAC
Metadata URL(s):

https://cdiac.ess-dive.lbl.gov/ftp/oceans/Cape_Hatteras_GM/
Data Server URL(s):

https://cdiac.ess-dive.lbl.gov/ftp/oceans/Cape_Hatteras_GM/
Archived Data Citation:  Cai, W.-J., Y. Wang and W.-J. Huang. 2014. Sea surface pCO2 survey in the Gulf of Mexico during the R/V Cape Hatteras cruises in 2009 and 2010. http://cdiac.ess-dive.lbl.gov/ftp/oceans/Cape_Hatteras_GM/. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, US Department of Energy, Oak Ridge, Tennessee. DOI: 10.3334/CDIAC/OTG.Cape_Hatteras_GM

Bounding Coordinates:
West Longitude:-93.81698 East Longitude:-87.98232
North Latitude:30.35972 South Latitude:27.53240

Product Title:  Partial pressure (or fugacity) of carbon dioxide, salinity and SEA SURFACE TEMPERATURE collected from Surface underway observations using Carbon dioxide (CO2) gas analyzer, Shower head chamber equilibrator for autonomous carbon dioxide (CO2) measurement and other instruments from the USS BOLD in the Gulf of Mexico from 2007-05-02 to 2007-08-24 (NCEI Accession 0117500)
Start Date:  05/2007      End Date:  08/2007
Description:  NODC Accession 0117500 includes Surface underway, chemical and physical data collected from USS BOLD in the Gulf of Mexico from 2007-05-02 to 2007-08-24. These data include Partial pressure (or fugacity) of carbon dioxide - water, SALINITY and SEA SURFACE TEMPERATURE. The instruments used to collect these data include Carbon dioxide (CO2) gas analyzer and Shower head chamber equilibrator for autonomous carbon dioxide (CO2) measurement.

These data were collected by Wei-Jun Cai, Wei-Jen Huang and Yongchen Wang of University of Georgia; School of Marine Programs as part of the Coastal_UG_Gulf_of_Mexico_2007 data set. CDIAC assigned the following cruise ID(s) to this data set: 31B520070502 (GM0705) and 31B520070818 (GM0708).

The Global Coastal Carbon Data Project data includes the bottle (discrete) and surface (underway) carbon-related measurements from coastal research cruises, the data from time series cruises and coastal moorings. The coastal regions data are very important for the understanding of carbon cycle on the continental margins.
Status:  Archived
CMS Science Theme(s):  
Keywords:  
Spatial Extent:  
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  NOAA, US Global Change Research Program
Stakeholders:  NOAA Ocean Acidification Program (Point of Contact: Libby Jewett, libby.jewett@noaa.gov and Dwight Gledhill, dwight.gledhill@noaa.gov)
Current Application Readiness Level:  6
Start Application Readiness Level:  4
Target Application Readiness Level:  7
Future Developments:  
Limitations:  
Date When Product Available:  June 2012
Assigned Data Center:  CDIAC
Metadata URL(s):

https://cdiac.ess-dive.lbl.gov/ftp/oceans/UG_GoM_UW_Data/2007.data/GM0705_Meta.html

https://cdiac.ess-dive.lbl.gov/ftp/oceans/UG_GoM_UW_Data/2007.data/GM0708_Meta.html
Data Server URL(s):

https://cdiac.ess-dive.lbl.gov/ftp/oceans/UG_GoM_UW_Data/2007.data/
Archived Data Citation:  Cai, W.-J., Y. Wang, and W.-J. Huang. 2012. Sea Surface pCO2 measurements in the Gulf of Mexico during the Ocean Survey Vessel Bold cruises in 2007.

http://cdiac.ornl.gov/ftp/oceans/UG_GoM_UW_Data/2007.data.

Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, US Department of Energy, Oak Ridge, Tennessee. DOI: 10.3334/CDIAC/OTG.UG_GOM_UW_2007

Bounding Coordinates:
West Longitude:-93.42999 East Longitude:-87.29086
North Latitude:30.27041 South Latitude:28.17926

Product Title:  CMS: Simulated Physical-Biogeochemical Data, SABGOM Model, Gulf of Mexico, 2005-2010
Start Date:  01/2005      End Date:  12/2010
Description:  This dataset contains monthly mean ocean surface physical and biogeochemical data for the Gulf of Mexico simulated by the South Atlantic Bight and Gulf of Mexico (SABGOM) model on a 5-km grid from 2005 to 2010. The simulated data include ocean surface salinity, temperature, dissolved inorganic nitrogen (DIN), dissolved inorganic carbon (DIC), partial pressure of CO2 (pCO2), air-sea CO2 flux, surface currents, and primary production. The SABGOM model is a coupled physical-biogeochemical model for studying circulation and biochemical cycling for the entire Gulf of Mexico to achieve an improved understanding of marine ecosystem variations and their relations with three-dimensional ocean circulation in a gulf-wide context.
Status:  Archived
CMS Science Theme(s):  MRV; Ocean Biomass; Ocean-Atmosphere Flux
Keywords:  Flux/Movement (oceanic; atmospheric)
Spatial Extent:  South Atlantic Bight and Gulf of Mexico
Spatial Resolution:  5 km
Temporal Frequency:  monthly
Input Data Products:  Model inputs included: NCEPs high-resolution combined model and assimilated atmospheric dataset (North American Regional Reanalysis, www.cdc.noaa.gov) Open boundary conditions for ocean model (temperature, salinity, water level, and velocity) from a data-assimilative global ocean circulation model (HYCOM/NCODA) Observed freshwater and terrestrial nutrient input from 63 major rivers (Aulenbach et al., 2007; Milliman and Farnsworth, 2011; Fuentes-Yaco et al., 2001; and Nixon, 1996) Monthly model outputs of water, NO3, NH4, and alkalinity from the Dynamic Land Ecosystem Model (DLEM)) were used as riverine inputs To account for riverine inputs, a climatological monthly alkalinity time series was constructed by averaging all available US Geological Survey (USGS) observations for each major river, including the Mississippi, Atchafalaya, Mobile, and Brazos in the GoM. Because direct riverine DIC measurements were not available, riverine DIC inputs using the corresponding alkalinity value plus 50 were approximated (Xue et al., 2016).
Algorithm/Models Used:  The model outputs provided in this data set are the monthly mean ocean surface physical and biogeochemical data for the Gulf of Mexico on a 5-km grid from 2005 to 2010. The simulated data include ocean surface salinity, temperature, dissolved inorganic nitrogen (DIN), dissolved inorganic carbon (DIC), partial pressure of CO2 (pCO2), air-sea CO2 flux, surface currents, and primary production.
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  Modeled data were validated against ship-based measurements from sea surface pCO2 database compiled by the LamontDoherty Earth Observatory, > 180 000 data points in the Gulf over 20052010, (Takahashi et al., 2015), and ship-based measurements (> 78 000 data points) from Huang et al. (2015). For the analysis, the GOM was divided into the five subregions: Mexico Shelf (MX), Western Gulf of Mexico Shelf (WGoM), Northern Gulf of Mexico Shelf (NGoM), West Florida Shelf (WF), and open ocean. The data points falling in each of the subregions was first grouped by a 10-day temporal binning and then spatially averaged to get a mean value for each subregion. Agreement between model and observations was better during spring, fall, and winter, than during summer. The model overestimated pCO2 in June 2006, August 2007, and July 2009. Refer to Xue et al. (2016) for additional details.
Uncertainty Categories:  ensemble
Application Areas:  - Ocean acidification mitigation and carbon management; marine ecosystem variations; climate change studies; and marine carbon cycle studies
Relevant Policies/Programs:  NACP, National Climate Assessment of U.S. Global Change Research Program, NASA Coastal Carbon Synthesis, Carbon North America (CarboNA), Coastal Zone Management Act, Clean Water Act (CWA), US-Mexico Bilateral Framework on Clean Energy and Climate Change (US-Mexico Bilateral)
Potential Users:  NOAA, US Global Change Research Program
Stakeholders:  
Current Application Readiness Level:  6
Start Application Readiness Level:  4
Target Application Readiness Level:  7
Future Developments:  
Limitations:  
Date When Product Available:  November 2017
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://daac.ornl.gov/CMS/guides/CMS_SABGOM_Model_Simulations.html
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1510
Archived Data Citation:  He, R., and Z. Xue. 2017. CMS: Simulated Physical-Biogeochemical Data, SABGOM Model, Gulf of Mexico, 2005-2010. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1510

Bounding Coordinates:
West Longitude:-100.43000 East Longitude:-68.19000
North Latitude:39.37000 South Latitude:13.16000

Product Title:  Ocean Surface pCO2 and Air-Sea CO2 Flux in the Northern Gulf of Mexico, 2006-2010
Start Date:  01/2006      End Date:  01/2011
Description:  This dataset provides 1 km gridded monthly estimates of surface ocean partial pressure of CO2 (pCO2) and air-sea flux of CO2 (CO2 flux) for the northern Gulf of Mexico for the period 2006 through 2010. Estimates of pCO2 were derived from MODIS/Aqua satellite imagery in combination with ship-based observations. Estimates of CO2 flux were derived from estimates of seawater pCO2, wind fields, and atmospheric pCO2.
Status:  Archived
CMS Science Theme(s):  Ocean-Atmosphere Flux
Keywords:  
Spatial Extent:  Northern Gulf of Mexico
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  USDA, EPA (Mississippi River/Gulf of Mexico Watershed Nutrient Task Force), NOAA, USGS, US Global Change Research Program, CMS terrestrial flux teams
Stakeholders:  NOAA Ocean Acidification Program (Point of Contact: Libby Jewett, libby.jewett@noaa.gov and Dwight Gledhill, dwight.gledhill@noaa.gov); US Global Change Research Program (Point of Contact: Nancy Cavallaro, USDA; Kathy Hibbard, NASA; Gyami Shrestha, US Carbon Cycle Science Program)
Current Application Readiness Level:  6
Start Application Readiness Level:  4
Target Application Readiness Level:  7
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1668
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1668
Archived Data Citation:  Lohrenz, S.E., W.J. Cai, S. Chakraborty, R. He, and H. Tian. 2019. Ocean Surface pCO2 and Air-Sea CO2 Flux in the Northern Gulf of Mexico, 2006-2010. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1668

Bounding Coordinates:
West Longitude:-96.00000 East Longitude:-86.00000
North Latitude:32.00000 South Latitude:25.00000

Product Title:  Export and Leaching of Carbon and Nitrogen from Mississippi River Basin, 1901-2099
Start Date:  01/1901      End Date:  12/2099     (1901-2099)
Description:  This dataset provides estimates for export and leaching of dissolved inorganic carbon (DIC), dissolved organic carbon (DOC), total organic carbon (TOC), particulate organic carbon (POC), ammonium (NH4+), nitrate (NO3-), and total organic nitrogen (TON) from the Mississippi River Basin (MRB) to the Gulf of Mexico. The estimates are provided for a historical period of 1901-2014, and a future period of 2010-2099 (carbon estimates only) under two scenarios of high and low levels of population growth, economy, and energy consumption, respectively. The estimates are from the Dynamic Land Ecosystem Model 2.0 (DLEM 2.0). These data are applicable to studying how changes in multiple environmental factors (e.g., fertilizer application, land-use changes, climate variability, atmospheric CO2, and N deposition) affect the dynamics of leaching and export to the Gulf of Mexico.
Status:  Archived
CMS Science Theme(s):  Land-Ocean Flux
Keywords:  carbon; nitrogen
Spatial Extent:  Mississippi River Basin
Spatial Resolution:  Carbon data are 5 arc minute; nitrogen data are 7.5 arc minute
Temporal Frequency:  annual
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  USDA, EPA (Mississippi River/Gulf of Mexico Watershed Nutrient Task Force), NOAA, USGS, US Global Change Research Program, CMS terrestrial flux teams
Stakeholders:  
Current Application Readiness Level:  6
Start Application Readiness Level:  3,4
Target Application Readiness Level:  7
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1699
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1699
Archived Data Citation:  Tian, H., S.E. Lohrenz, S. Pan, W.J. Cai, and R. He. 2019. Export and Leaching of Carbon and Nitrogen from Mississippi River Basin, 1901-2099. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1699

Bounding Coordinates:
West Longitude:-126.00000 East Longitude:-62.00000
North Latitude:53.00000 South Latitude:24.50000

Product Title:  CMS: Annual Estimates of Global Riverine Nitrous Oxide Emissions, 1900-2016
Start Date:  01/1900      End Date:  12/2016     (1900-2016)
Description:  This dataset provides modeled estimates of annual nitrous oxide (N2O) emissions at a coarse geographic scale (0.5 x 0.5 degree) for two sets of global rivers and streams covering the period of 1900-2016. Emissions (g N2O-N/yr) are provided for higher-order rivers and streams (4th order). The estimates were derived from a water transport model, the Model for Scale Adaptive River Transport (MOSART), coupled with the Dynamic Land Ecosystem Model (DLEM) to link hydrology and ecosystem processes pertaining to N2O flux and transport. Factors driving the model included climate, land use and land cover, and nitrogen inputs (i.e., fertilizer, deposition, manure, and sewage). Nitrogen discharges from streams and rivers to the ocean were calibrated from observations from 50 river basins across the globe.
Status:  Archived
CMS Science Theme(s):  Ocean-Atmosphere Flux
Keywords:  
Spatial Extent:  Global
Spatial Resolution:  0.5 x 0.5 degrees
Temporal Frequency:  Annual
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1791
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1791
Archived Data Citation:  Yao, Y., and H. Tian. 2021. CMS: Annual Estimates of Global Riverine Nitrous Oxide Emissions, 1900-2016. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1791

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:88.50000 South Latitude:-88.50000

 
Publications: Chakraborty, S., Lohrenz, S. E., Gundersen, K. 2017. Photophysiological and light absorption properties of phytoplankton communities in the river-dominated margin of the northern G ulf of M exico. Journal of Geophysical Research: Oceans. 122(6), 4922-4938. DOI: 10.1002/2016JC012092

Fennel, K., Alin, S., Barbero, L., Evans, W., Bourgeois, T., Cooley, S., Dunne, J., Feely, R. A., Hernandez-Ayon, J. M., Hu, C., Hu, X., Lohrenz, S., Muller-Karger, F., Najjar, R., Robbins, L., Russell, J., Shadwick, E., Siedlecki, S., Steiner, N., Turk, D., Vlahos, P., Wang, Z. A. 2018. Chapter 16: Coastal Ocean and Continental Shelves. Second State of the Carbon Cycle Report DOI: 10.7930/soccr2.2018.ch16

Fennel, K., Alin, S., Barbero, L., Evans, W., Bourgeois, T., Cooley, S., Dunne, J., Feely, R. A., Hernandez-Ayon, J. M., Hu, X., Lohrenz, S., Muller-Karger, F., Najjar, R., Robbins, L., Shadwick, E., Siedlecki, S., Steiner, N., Sutton, A., Turk, D., Vlahos, P., Wang, Z. A. 2019. Carbon cycling in the North American coastal ocean: a synthesis. Biogeosciences. 16(6), 1281-1304. DOI: 10.5194/bg-16-1281-2019

Hurtt, G. C., Andrews, A., Bowman, K., Brown, M. E., Chatterjee, A., Escobar, V., Fatoyinbo, L., Griffith, P., Guy, M., Healey, S. P., Jacob, D. J., Kennedy, R., Lohrenz, S., McGroddy, M. E., Morales, V., Nehrkorn, T., Ott, L., Saatchi, S., Sepulveda Carlo, E., Serbin, S. P., Tian, H. 2022. The NASA Carbon Monitoring System Phase 2 synthesis: scope, findings, gaps and recommended next steps. Environmental Research Letters. 17(6), 063010. DOI: 10.1088/1748-9326/ac7407

Lohrenz, S. E., Cai, W., Chakraborty, S., Huang, W., Guo, X., He, R., Xue, Z., Fennel, K., Howden, S., Tian, H. 2018. Satellite estimation of coastal pCO2 and air-sea flux of carbon dioxide in the northern Gulf of Mexico. Remote Sensing of Environment. 207, 71-83. DOI: 10.1016/j.rse.2017.12.039

Lu, C., Yu, Z., Tian, H., Hennessy, D. A., Feng, H., Al-Kaisi, M., Zhou, Y., Sauer, T., Arritt, R. 2018. Increasing carbon footprint of grain crop production in the US Western Corn Belt. Environmental Research Letters. 13(12), 124007. DOI: 10.1088/1748-9326/aae9fe

Lu, C., Zhang, J., Tian, H., Crumpton, W. G., Helmers, M. J., Cai, W., Hopkinson, C. S., Lohrenz, S. E. 2020. Increased extreme precipitation challenges nitrogen load management to the Gulf of Mexico. Communications Earth & Environment. 1(1). DOI: 10.1038/s43247-020-00020-7

Najjar, R. G., Herrmann, M., Alexander, R., Boyer, E. W., Burdige, D. J., Butman, D., Cai, W., Canuel, E. A., Chen, R. F., Friedrichs, M. A. M., Feagin, R. A., Griffith, P. C., Hinson, A. L., Holmquist, J. R., Hu, X., Kemp, W. M., Kroeger, K. D., Mannino, A., McCallister, S. L., McGillis, W. R., Mulholland, M. R., Pilskaln, C. H., Salisbury, J., Signorini, S. R., St-Laurent, P., Tian, H., Tzortziou, M., Vlahos, P., Wang, Z. A., Zimmerman, R. C. 2018. Carbon Budget of Tidal Wetlands, Estuaries, and Shelf Waters of Eastern North America. Global Biogeochemical Cycles. 32(3), 389-416. DOI: 10.1002/2017GB005790

Poulter, B., Bousquet, P., Canadell, J. G., Ciais, P., Peregon, A., Saunois, M., Arora, V. K., Beerling, D. J., Brovkin, V., Jones, C. D., Joos, F., Gedney, N., Ito, A., Kleinen, T., Koven, C. D., McDonald, K., Melton, J. R., Peng, C., Peng, S., Prigent, C., Schroeder, R., Riley, W. J., Saito, M., Spahni, R., Tian, H., Taylor, L., Viovy, N., Wilton, D., Wiltshire, A., Xu, X., Zhang, B., Zhang, Z., Zhu, Q. 2017. Global wetland contribution to 2000-2012 atmospheric methane growth rate dynamics. Environmental Research Letters. 12(9), 094013. DOI: 10.1088/1748-9326/aa8391

Ren, W., Tian, H., Cai, W., Lohrenz, S. E., Hopkinson, C. S., Huang, W., Yang, J., Tao, B., Pan, S., He, R. 2016. Century-long increasing trend and variability of dissolved organic carbon export from the Mississippi River basin driven by natural and anthropogenic forcing. Global Biogeochemical Cycles. 30(9), 1288-1299. DOI: 10.1002/2016GB005395

Ren, W., Tian, H., Tao, B., Yang, J., Pan, S., Cai, W., Lohrenz, S. E., He, R., Hopkinson, C. S. 2015. Large increase in dissolved inorganic carbon flux from the Mississippi River to Gulf of Mexico due to climatic and anthropogenic changes over the 21st century. Journal of Geophysical Research: Biogeosciences. 120(4), 724-736. DOI: 10.1002/2014JG002761

Tian, H., Xu, R., Pan, S., Yao, Y., Bian, Z., Cai, W., Hopkinson, C. S., Justic, D., Lohrenz, S., Lu, C., Ren, W., Yang, J. 2020. Long-Term Trajectory of Nitrogen Loading and Delivery From Mississippi River Basin to the Gulf of Mexico. Global Biogeochemical Cycles. 34(5). DOI: 10.1029/2019GB006475

Yu, Z., Lu, C., Cao, P., Tian, H. 2018. Long-term terrestrial carbon dynamics in the Midwestern United States during 1850-2015: Roles of land use and cover change and agricultural management. Global Change Biology. 24(6), 2673-2690. DOI: 10.1111/gcb.14074

Zhang, B., Tian, H., Lu, C., Chen, G., Pan, S., Anderson, C., Poulter, B. 2017. Methane emissions from global wetlands: An assessment of the uncertainty associated with various wetland extent data sets. Atmospheric Environment. 165, 310-321. DOI: 10.1016/j.atmosenv.2017.07.001

Benway, H. M., Alin, S. R., Boyer, E., Cai, W., Coble, P. G., Cross, J. N., Friedrichs, M. A. M., Goni, M., Griffith, P., Herrmann, M., Lohrenz, S. E., Mathis, J. T., McKinley, G. A., Najjar, R. G., Pilskaln, C. H., Siedlecki, S. A., Smith, R. A. 2016. A science plan for carbon cycle research in North American coastal waters. Report of the Coastal CARbon Synthesis (CCARS) community workshop, August 19-21, 2014 DOI: 10.1575/1912/7777

Tian, H., Lu, C., Ciais, P., Michalak, A. M., Canadell, J. G., Saikawa, E., Huntzinger, D. N., Gurney, K. R., Sitch, S., Zhang, B., Yang, J., Bousquet, P., Bruhwiler, L., Chen, G., Dlugokencky, E., Friedlingstein, P., Melillo, J., Pan, S., Poulter, B., Prinn, R., Saunois, M., Schwalm, C. R., Wofsy, S. C. 2016. The terrestrial biosphere as a net source of greenhouse gases to the atmosphere. Nature. 531(7593), 225-228. DOI: 10.1038/nature16946

Salisbury, J., Vandemark, D., Jonsson, B., Balch, W., Chakraborty, S., Lohrenz, S., Chapron, B., Hales, B., Mannino, A., Mathis, J., Reul, N., Signorini, S., Wanninkhof, R., Yates, K. 2015. How Can Present and Future Satellite Missions Support Scientific Studies that Address Ocean Acidification? Oceanography. 25(2), 108-121. DOI: 10.5670/oceanog.2015.35

Yang, Q., Tian, H., Li, X., Ren, W., Zhang, B., Zhang, X., Wolf, J. 2016. Spatiotemporal patterns of livestock manure nutrient production in the conterminous United States from 1930 to 2012. Science of The Total Environment. 541, 1592-1602. DOI: 10.1016/j.scitotenv.2015.10.044

Huang, W., Cai, W., Wang, Y., Hu, X., Chen, B., Lohrenz, S. E., Chakraborty, S., He, R., Brandes, J., Hopkinson, C. S. 2015. The response of inorganic carbon distributions and dynamics to upwelling-favorable winds on the northern Gulf of Mexico during summer. Continental Shelf Research. 111, 211-222. DOI: 10.1016/j.csr.2015.08.020

Yang, J., Tian, H., Tao, B., Ren, W., Pan, S., Liu, Y., Wang, Y. 2015. A growing importance of large fires in conterminous United States during 1984-2012. Journal of Geophysical Research: Biogeosciences. 120(12), 2625-2640. DOI: 10.1002/2015JG002965

Xue, Z., He, R., Fennel, K., Cai, W., Lohrenz, S., Huang, W., Tian, H., Ren, W., Zang, Z. 2016. Modeling &lt;i&gt;p&lt;/i&gt;CO&lt;sub&gt;2&lt;/sub&gt; variability in the Gulf of Mexico. Biogeosciences. 13(15), 4359-4377. DOI: 10.5194/bg-13-4359-2016

Tian, H., Ren, W., Yang, J., Tao, B., Cai, W., Lohrenz, S. E., Hopkinson, C. S., Liu, M., Yang, Q., Lu, C., Zhang, B., Banger, K., Pan, S., He, R., Xue, Z. 2015. Climate extremes dominating seasonal and interannual variations in carbon export from the Mississippi River Basin. Global Biogeochemical Cycles. 29(9), 1333-1347. DOI: 10.1002/2014GB005068

Chakraborty, S., Lohrenz, S. 2015. Phytoplankton community structure in the river-influenced continental margin of the northern Gulf of Mexico. Marine Ecology Progress Series. 521, 31-47. DOI: 10.3354/meps11107

Huang, W., Cai, W., Wang, Y., Lohrenz, S. E., Murrell, M. C. 2015. The carbon dioxide system on the Mississippi River-dominated continental shelf in the northern Gulf of Mexico: 1. Distribution and air-sea CO2flux. Journal of Geophysical Research: Oceans. 120(3), 1429-1445. DOI: 10.1002/2014JC010498

Tian, H., Yang, Q., Najjar, R. G., Ren, W., Friedrichs, M. A. M., Hopkinson, C. S., Pan, S. 2015. Anthropogenic and climatic influences on carbon fluxes from eastern North America to the Atlantic Ocean: A process-based modeling study. Journal of Geophysical Research: Biogeosciences. 120(4), 757-772. DOI: 10.1002/2014JG002760

Zhang, C., Tian, H., Pan, S., Lockaby, G., Chappelka, A. 2014. Multi-factor controls on terrestrial carbon dynamics in urbanized areas. Biogeosciences. 11(24), 7107-7124. DOI: 10.5194/bg-11-7107-2014

Archived Data Citations: Cai, W.-J., Y. Wang, and W.-J. Huang. 2012. Sea Surface pCO2 measurements in the Gulf of Mexico during the Ocean Survey Vessel Bold cruises in 2006. http://cdiac.ornl.gov/ftp/oceans/UG_GoM_UW_Data/2006.data. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, US Department of Energy, Oak Ridge, Tennessee. DOI: 10.3334/CDIAC/OTG.UG_GOM_UW_2006. Xue, Z., R. He, K. Fennel, W. J. Cai, S. Lohrenz, W. J. Huang, H. Tian, W. Ren, and Z. Zang (2016), Modeling pCO2 variability in the Gulf of Mexico, Biogeosciences, 13(15), 4359-4377, DOI: 10.5194/bg-13-4359-2016

Lohrenz, S. E., W.-J. Cai, S. Chakraborty, W.-J. Huang, K. Martin, X. Chen. Phytoplankton pigment, optical properties and CTD data from the Gulf of Mexico during the R/V Cape Hatteras cruises in 2009 and 2010. http://seabass.gsfc.nasa.gov/seabasscgi/data.cgi?experiment=GulfCarbon. DOI: 10.5067/SeaBASS/GULFCARBON/DATA001

Cai, W.-J., Y. Wang and W.-J. Huang. 2014. Sea surface pCO2 survey in the Gulf of Mexico during the R/V Cape Hatteras cruises in 2009 and 2010. http://cdiac.ess-dive.lbl.gov/ftp/oceans/Cape_Hatteras_GM/. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, US Department of Energy, Oak Ridge, Tennessee. DOI: 10.3334/CDIAC/OTG.Cape_Hatteras_GM

Cai, W.-J., Y. Wang, and W.-J. Huang. 2012. Sea Surface pCO2 measurements in the Gulf of Mexico during the Ocean Survey Vessel Bold cruises in 2007. http://cdiac.ornl.gov/ftp/oceans/UG_GoM_UW_Data/2007.data. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, US Department of Energy, Oak Ridge, Tennessee. DOI: 10.3334/CDIAC/OTG.UG_GOM_UW_2007

He, R., and Z. Xue. 2017. CMS: Simulated Physical-Biogeochemical Data, SABGOM Model, Gulf of Mexico, 2005-2010. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1510

Lohrenz, S.E., W.J. Cai, S. Chakraborty, R. He, and H. Tian. 2019. Ocean Surface pCO2 and Air-Sea CO2 Flux in the Northern Gulf of Mexico, 2006-2010. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1668

Tian, H., S.E. Lohrenz, S. Pan, W.J. Cai, and R. He. 2019. Export and Leaching of Carbon and Nitrogen from Mississippi River Basin, 1901-2099. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1699

Yao, Y., and H. Tian. 2021. CMS: Annual Estimates of Global Riverine Nitrous Oxide Emissions, 1900-2016. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1791

2015 NASA Carbon Cycle & Ecosystems Joint Science Workshop Poster(s)
  • Ocean margins as an increasing sink for the atmospheric carbon dioxide   --   (Wei-Jun Cai, Goulven Laruelle, Xinping Hu, Pierre Regnier)   [abstract]
  • Contemporary and projected lateral carbon fluxes from North America to Oceans: A process-based modeling study   --   (Hanqin Tian, Qichun Yang, Wei Ren, Chaoqun Lu, Bowen Zhang, Shufen Pan, Bo Tao, Steven Lohrenz, Wei-Jun Cai, Ruoying He, Marjorie Friedrichs, Raymond Najjar)   [abstract]
5th NACP All-Investigators Meeting Posters (2015):
  • Integrated Observation and Modeling of Carbon Cycle Processes Across Terrestrial-Coastal Interfaces: Reducing Uncertainties and Enhancing Linkages to Decision Support -- (Steven Lohrenz, Hanqin Tian, Wei-Jun Cai, Ruoying He) [abstract]   [poster]
  • Contemporary and projected lateral carbon fluxes from North America to Oceans: A process-based modeling study -- (Hanqin Tian, Qichun Yang, Bowen Zhang, Jia Yang, Shufen Pan, Wei Ren, Chaoqun Lu, Bo Tao, Steven Lohrenz, Wei-Jun Cai, Ruoying He, Marjorie Friedrichs, Raymond Najjar) [abstract]


 

Morton (CMS 2014) (2014)
Project Title:Long-Term Carbon Consequences of Amazon Forest Degradation

Science Team
Members:

Douglas (Doug) Morton, NASA GSFC (Project Lead)

Solicitation:NASA: Carbon Monitoring System (2014)
Abstract: Four decades of deforestation, forest degradation, and agricultural use have fundamentally altered remaining forest fragments along the arc of deforestation in southern Amazonia. Forest carbon stocks in these frontier forests remain poorly characterized by existing forest inventory data or moderate resolution (0.25-1 km2) satellite data products. Nonetheless, these frontier landscapes retain clues to historic forest carbon emissions and the legacy of forest degradation from logging and fire. Improving our understanding of the long-term carbon consequences of forest degradation is essential for efforts to Reduce Emissions from Deforestation and Forest Degradation and enhance forest carbon stocks (REDD+). The level of emphasis on forest degradation in monitoring, reporting, and verification (MRV) of REDD+ activities in Amazonia fundamentally depends on the magnitude of net carbon emissions from logging, fire, and forest fragmentation. We propose to conduct detailed analyses of forest carbon stocks and land cover transitions in three frontier forest regions in the Peruvian and Brazilian Amazon. The proposed study combines contemporary forest inventory data and extensive airborne lidar surveys with time series of Landsat data to evaluate landscape patterns of forest carbon stocks. Our major emphasis is the variety of forest carbon loss trajectories from different intensities and frequencies of forest degradation. We selected three frontier regions to evaluate the mosaic of forest ages and conditions from logging, fire, and forest fragmentation in old (Santarm, Par, Brazil), established (Feliz Natal, Mato Grosso, Brazil), and young frontier forests (Colonel Portillo, Ucayali, Peru). Key research themes include 1) long-term changes in forest structure and carbon stocks from forest degradation; 2) lidar-biomass relationships in degraded forests; and 3) full carbon accounting of forest emissions, including deforestation, degradation, and secondary forest dynamics. The proposed research addresses the two priority areas in the Carbon Monitoring System (CMS) solicitation (A.7). Specifically, we will use airborne lidar data from commercial off-the-shelf sensors, collected under separate funding from USAID and the US Department of State, to characterize Amazon forest structure and biomass and prototype MRV capabilities for intact and degraded forest types. Improving estimates of carbon losses from forest degradation is a key priority for NASA CMS and SilvaCarbon (Peru is a SilvaCarbon country), and a major impediment to progress on REDD+. Research activities will further develop methodologies to combine field measurements, airborne scanning lidar data, and satellite observations in support of REDD+ MRV. Finally, study results will provide validation datasets for ICESat-2 and proposed lidar missions under NASAs Earth Venture program (EVi-2 and EVs-2). The proposed effort leverages four sources of existing support. Field measurements and airborne lidar data for study sites in the Brazilian and Peruvian Amazon will be acquired under separate funding from USAID, US Department of State, SilvaCarbon, and the Brazilian Conselho Nacional de Desenvolvimento Cientfico e Tecnolgico (CNPq). PI Morton is an unfunded collaborator on these existing projects, including his recent selection as a Cincia sem Fronteiras (Science Without Borders) Fellow by CNPq for 2014-2017. Additional funding for the proposed research through CMS would leverage these field and lidar data collections to address priority science areas for CMS and enhance the international impact of research activities supported by USAID and SilvaCarbon.
CMS Primary Theme:
  • Land Biomass
CMS Science Theme(s):
  • Land Biomass
  • Land-Atmosphere Flux
  • Decision Support
  • MRV

Participants:

Christine Dragisic, U.S. Department of State
Douglas (Doug) Morton, NASA GSFC

Project URL(s): None provided.
 
Data
Products:
Product Title:  LiDAR Surveys over Selected Forest Research Sites, Brazilian Amazon, 2008-2018
Start Date:  01/2008      End Date:  12/2018     (June 2008-Aug 2018)
Description:  This dataset provides the complete catalog of point cloud data collected during LiDAR surveys over selected forest research sites across the Amazon rainforest in Brazil between 2008 and 2018 for the Sustainable Landscapes Brazil Project. Flight lines were selected to overfly key field research sites in the Brazilian states of Acre, Amazonas, Bahia, Goias, Mato Grosso, Para, Rondonia, Santa Catarina, and Sao Paulo. The point clouds have been georeferenced, noise-filtered, and corrected for misalignment of overlapping flight lines. They are provided in 1 km2 tiles. The data were collected to measure forest canopy structure across Amazonian landscapes to monitor the effects of selective logging on forest biomass and carbon balance, and forest recovery over time.
Status:  Archived
CMS Science Theme(s):  Land Biomass; Land-Atmosphere Flux; MRV
Keywords:  Ecosystem Composition and Structure
Spatial Extent:  Selected areas of the Amazon Basin and other regions in Brazil
Spatial Resolution:  ~ 10 points per m2 provided in 1 km2 tiles over key field research sites
Temporal Frequency:  single acquisition over most sites (multiple acquisition over some sites)
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  1
Start Application Readiness Level:  1
Target Application Readiness Level:  1
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1644
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1644
Archived Data Citation:  dos-Santos, M.N., M.M. Keller, and D.C. Morton. 2019. LiDAR Surveys over Selected Forest Research Sites, Brazilian Amazon, 2008-2018. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1644

Bounding Coordinates:
West Longitude:-68.30000 East Longitude:-39.06000
North Latitude:-1.58000 South Latitude:-26.70000

Product Title:  Estimates of degradation carbon losses from logging and fire in Amazon forests Mato Grosso Brazil
Start Date:  01/1985      End Date:  12/2014     (1985-2014 ( lidar was collected between 2013 and 2015))
Description:  Here, we used a purposeful sample of high-density airborne lidar to capture a broad range of degraded and intact forest conditions in the southern Brazilian Amazon. For each forest stand, we combined degradation history information from annual time series of Landsat data with airborne lidar data to characterize canopy structure and estimate aboveground carbon density (ACD) using a lidar-biomass model specifically developed for frontier forests in the Brazilian Amazon (Longo et al 2016) Our study directly targets a lingering data gap for REDD+ (Andrade et al 2017) by quantifying the rates of ACD recovery over 1- to 15-year time horizons following a broad range of degradation pathways, including sequential impacts of logging and burning. These time-varying emissions estimates, or emissions factors, can be combined with activity data on the extent of forest degradation to establish REDD+ baselines; confirm the relative contributions from fire, logging, and regeneration to regional net forest carbon emissions; and estimate the consequences to mitigation targets if degradation remains omitted from greenhouse gas accounting. We combined Landsat time series and airborne lidar data to quantify variability in forest structure and ACD across gradients of degradation type, frequency, severity, and timing. Degradation history for areas with lidar coverage was characterized using a two-tiered classification approach
Status:  Public
CMS Science Theme(s):  Land Biomass; Land-Atmosphere Flux; MRV
Keywords:  Disturbance
Spatial Extent:  southern Mato Grosso, Brazil
Spatial Resolution:  30 m
Temporal Frequency:  Annually
Input Data Products:  Landsat time series
Algorithm/Models Used:  
Evaluation:  Multi-temporal lidar and field inventory data will be used to validate estimates of forest cover change
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  Uncertainty in the rates of deforestation and forest degradation will be assessed using high-resolution data
Uncertainty Categories:  data-data comparisons; model-data comparisons
Application Areas:  - MRV, REDD+; - Forest inventory; - GHG emissions inventory; - Land management
Relevant Policies/Programs:  REDD+, SilvaCarbon, Science Without Borders, Global Carbon Project, GFED
Potential Users:  INPE, Embrapa, USAID, US State Department, global carbon cycle community
Stakeholders:  National Wildlife Federation (Point of Contact: Barbara Bramble, bramble@nwf.org)
Current Application Readiness Level:  3
Start Application Readiness Level:  3
Target Application Readiness Level:  6
Future Developments:  
Limitations:  
Date When Product Available:  
Metadata URL(s):

https://iopscience.iop.org/article/10.1088/1748-9326/aac331/data

http://geoinfo.cnpm.embrapa.br/
Data Server URL(s):

https://iopscience.iop.org/article/10.1088/1748-9326/aac331/data

http://geoinfo.cnpm.embrapa.br/
Archived Data Citation:  
Bounding Coordinates:
West Longitude:-55.20000 East Longitude:-54.02000
North Latitude:-11.86700 South Latitude:-12.38000

Product Title:  Lidar-biomass models for intact, degraded, and secondary forests across the Brazilian Amazon
Start Date:  09/2011      End Date:  08/2015     (lidar was collected between 2012 and 2015 field data was collected between 2011 and 2015)
Description:  Here we investigated biomass variability in intact and degraded Amazon forest types using the largest integrated inventory plot and airborne lidar data set assembled to date for the Brazilian Amazon. Field samples and coincident lidar acquisitions specifically targeted degraded forest types in order to develop and calibrate a general model of carbon stocks for the Brazilian Amazon that captures different levels of forest degradation and recovery. This data product contains a summary with properties derived from all field plots, along with airborne-lidar derived metrics, the above-ground carbon density estimates from both field inventory plots and airborne lidar, and their uncertainties. A header is included in the file, and contains the variable description and units. Data are presented in a txt file with detailed documentation available in a pdf file.
Status:  Public
CMS Science Theme(s):  Land Biomass; MRV
Keywords:  Carbon Stocks (; terrestrial)
Spatial Extent:  18 study areas across the Brazilian Amazon
Spatial Resolution:  field inventory plots were approx 0.25 ha lidar metrics were computed on a 50 x 50 m grid
Temporal Frequency:  one time sampling for each study area
Input Data Products:  Commercial airborne Lidar, forest inventory data
Algorithm/Models Used:  Multivariate Regression
Evaluation:  Multi-temporal lidar and field inventory data will be used to validate regression models of carbon stocks in intact, degraded, and secondary forest types
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  Uncertainty in lidar-biomass relationships for degraded forests, effects of wood density variability in forest carbon stock estimates
Uncertainty Categories:  data-data comparisons; model-data comparisons
Application Areas:  - MRV, REDD+; - Forest inventory; - GHG emissions inventory; - Land management
Relevant Policies/Programs:  REDD+, SilvaCarbon, Science Without Borders, Global Carbon Project, GFED
Potential Users:  INPE, Embrapa, USAID, US State Department, global carbon cycle community
Stakeholders:  
Current Application Readiness Level:  3
Start Application Readiness Level:  3
Target Application Readiness Level:  6
Future Developments:  
Limitations:  
Date When Product Available:  
Metadata URL(s):

https://agupubs.onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002%2F2016GB005465&file=gbc20478-sup-0001-supplementary.pdf
Data Server URL(s):

https://agupubs.onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002%2F2016GB005465&file=gbc20478-sup-0002-supplementary.txt

https://www.paisagenslidar.cnptia.embrapa.br/webgis/
Archived Data Citation:  
Bounding Coordinates:
West Longitude:-67.98330 East Longitude:-46.83330
North Latitude:-1.61670 South Latitude:-13.08330

Product Title:  Secondary vegetation extent, age, and net carbon uptake in the Brazilian Amazon between 1985 and 2017.
Start Date:  01/1985      End Date:  12/2017     (1985-2017)
Description:  - Generate estimates of Annual Forest carbon emissions for each frontier landscape, including deforestation, degradation, and secondary Forest dynamics.
Status:  Public
CMS Science Theme(s):  Land Biomass; MRV
Keywords:  Carbon Stocks (; terrestrial)
Spatial Extent:  The Brazilian Amazon
Spatial Resolution:  30 m
Temporal Frequency:  Annually
Input Data Products:  Landsat time series
Algorithm/Models Used:  
Evaluation:  Multi-temporal lidar and field inventory data will be used to validate estimates of secondary forest extent
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  land cover validation
Uncertainty Categories:  data-data comparisons
Application Areas:  - MRV, REDD+; - Forest inventory; - GHG emissions inventory; - Land management
Relevant Policies/Programs:  REDD+, SilvaCarbon, Science Without Borders, Global Carbon Project, GFED
Potential Users:  INPE, Embrapa, USAID, US State Department, global carbon cycle community
Stakeholders:  National Wildlife Federation (Point of Contact: Barbara Bramble, bramble@nwf.org); Union of Concerned Scientists (Point of Contact: Sharon Smith)
Current Application Readiness Level:  3
Start Application Readiness Level:  3
Target Application Readiness Level:  6
Future Developments:  
Limitations:  
Date When Product Available:  2017
Metadata URL(s):

http://geoinfo.cnpm.embrapa.br/
Data Server URL(s):

https://floreser.users.earthengine.app/view/floreser
Archived Data Citation:  
Bounding Coordinates:
West Longitude:-68.00000 East Longitude:-46.00000
North Latitude:-1.00000 South Latitude:-13.00000

Product Title:  Forest Inventory and Biophysical Measurements, Brazilian Amazon, 2009-2018
Start Date:  01/2009      End Date:  12/2018     (2009-01-01 to 2018-12-31)
Description:  This dataset provides the complete catalog of forest inventory and biophysical measurements collected over selected forest research sites across the Amazon rainforest in Brazil between 2009 and 2018 for the Sustainable Landscapes Brazil Project. This dataset includes measurements for diameter at breast height (DBH), commercial tree height, and total tree height for forest inventories. Also included for each tree are the family, common and scientific names, coordinates, canopy position, crown radius, and for dead trees, the decomposition status. Aboveground biomass estimate is available for selected sites. The data are provided in comma-separated values (CSV) and shapefile formats. Sampling methodology for each site and year is described in companion files.
Status:  Archived
CMS Science Theme(s):  Land Biomass
Keywords:  Land Biomass
Spatial Extent:  Selected areas of the Amazon Basin and other regions in Brazil
Spatial Resolution:  Point data
Temporal Frequency:  Varies by site. Some sites were sampled once, and others were resampled in following years.
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/2007
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/2007
Archived Data Citation:  dos-Santos, M.N., M.M. Keller, E.R. Pinage, and D.C. Morton. 2022. Forest Inventory and Biophysical Measurements, Brazilian Amazon, 2009-2018. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/2007

Bounding Coordinates:
West Longitude:-67.98000 East Longitude:-46.83000
North Latitude:-1.50000 South Latitude:-13.09000

 
Publications: Andela, N., Morton, D. C., Giglio, L., Chen, Y., van der Werf, G. R., Kasibhatla, P. S., DeFries, R. S., Collatz, G. J., Hantson, S., Kloster, S., Bachelet, D., Forrest, M., Lasslop, G., Li, F., Mangeon, S., Melton, J. R., Yue, C., Randerson, J. T. 2017. A human-driven decline in global burned area. Science. 356(6345), 1356-1362. DOI: 10.1126/science.aal4108

Bustamante, M. M. C., Roitman, I., Aide, T. M., Alencar, A., Anderson, L. O., Aragao, L., Asner, G. P., Barlow, J., Berenguer, E., Chambers, J., Costa, M. H., Fanin, T., Ferreira, L. G., Ferreira, J., Keller, M., Magnusson, W. E., Morales-Barquero, L., Morton, D., Ometto, J. P. H. B., Palace, M., Peres, C. A., Silverio, D., Trumbore, S., Vieira, I. C. G. 2015. Toward an integrated monitoring framework to assess the effects of tropical forest degradation and recovery on carbon stocks and biodiversity. Global Change Biology. 22(1), 92-109. DOI: 10.1111/gcb.13087

Eitel, J. U., Hofle, B., Vierling, L. A., Abellan, A., Asner, G. P., Deems, J. S., Glennie, C. L., Joerg, P. C., LeWinter, A. L., Magney, T. S., Mandlburger, G., Morton, D. C., Muller, J., Vierling, K. T. 2016. Beyond 3-D: The new spectrum of lidar applications for earth and ecological sciences. Remote Sensing of Environment. 186, 372-392. DOI: 10.1016/j.rse.2016.08.018

Leitold, V., Morton, D. C., Longo, M., dos-Santos, M. N., Keller, M., Scaranello, M. 2018. El Nino drought increased canopy turnover in Amazon forests. New Phytologist. 219(3), 959-971. DOI: 10.1111/nph.15110

Morton, D. C. 2016. A satellite perspective. Nature Climate Change. 6(4), 346-348. DOI: 10.1038/nclimate2978

Morton, D. C., Rubio, J., Cook, B. D., Gastellu-Etchegorry, J., Longo, M., Choi, H., Hunter, M., Keller, M. 2016. Amazon forest structure generates diurnal and seasonal variability in light utilization. Biogeosciences. 13(7), 2195-2206. DOI: 10.5194/bg-13-2195-2016

Noojipady, P., Morton, C. D., Macedo, N. M., Victoria, C. D., Huang, C., Gibbs, K. H., Bolfe, L. E. 2017. Forest carbon emissions from cropland expansion in the Brazilian Cerrado biome. Environmental Research Letters. 12(2), 025004. DOI: 10.1088/1748-9326/aa5986

Nunes, S., Oliveira, L., Siqueira, J., Morton, D. C., Souza, C. M. 2020. Unmasking secondary vegetation dynamics in the Brazilian Amazon. Environmental Research Letters. 15(3), 034057. DOI: 10.1088/1748-9326/ab76db

Rangel Pinage, E., Keller, M., Duffy, P., Longo, M., dos-Santos, M., Morton, D. 2019. Long-Term Impacts of Selective Logging on Amazon Forest Dynamics from Multi-Temporal Airborne LiDAR. Remote Sensing. 11(6), 709. DOI: 10.3390/rs11060709

Rappaport, D. I., Morton, D. C., Longo, M., Keller, M., Dubayah, R., dos-Santos, M. N. 2018. Quantifying long-term changes in carbon stocks and forest structure from Amazon forest degradation. Environmental Research Letters. 13(6), 065013. DOI: 10.1088/1748-9326/aac331

Longo, M., Keller, M., dos-Santos, M. N., Leitold, V., Pinage, E. R., Baccini, A., Saatchi, S., Nogueira, E. M., Batistella, M., Morton, D. C. 2016. Aboveground biomass variability across intact and degraded forests in the Brazilian Amazon. Global Biogeochemical Cycles. 30(11), 1639-1660. DOI: 10.1002/2016GB005465

Archived Data Citations: dos-Santos, M.N., M.M. Keller, and D.C. Morton. 2019. LiDAR Surveys over Selected Forest Research Sites, Brazilian Amazon, 2008-2018. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1644

dos-Santos, M.N., M.M. Keller, E.R. Pinage, and D.C. Morton. 2022. Forest Inventory and Biophysical Measurements, Brazilian Amazon, 2009-2018. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/2007

2015 NASA Carbon Cycle & Ecosystems Joint Science Workshop Poster(s)
  • G-LiHT: Multi-Sensor Airborne Image Data from Denali to the Yucatan   --   (Bruce Cook, Lawrence A Corp, Douglas Morton, Joel McCorkel)   [abstract]   [poster]


 

Ott (CMS 2014) (2014)
Project Title:GEOS-Carb II: Delivering Carbon Flux and Concentration Products Based on the GEOS Modeling System

Science Team
Members:

Lesley Ott, NASA GSFC GMAO (Project Lead)
George (Jim) Collatz, NASA GSFC - retired
Stephan (Randy) Kawa, NASA GSFC
Tomohiro (Tom) Oda, USRA
Benjamin (Ben) Poulter, NASA GSFC

Solicitation:NASA: Carbon Monitoring System (2014)
Precursor Projects: Gunson-Pawson-Potter (2009)  
Successor Projects: Ott (CMS 2016)  
Abstract: This proposal is to extend NASA GSFCs contributions to the Carbon Monitoring System (CMS) from the Flux Pilot Project and CMS Phase One. The proposed work will draw on the capabilities of NASAs Goddard Earth Observing System (GEOS) models to deliver mature flux and concentration data products in support of CMS objectives. The proposed work consists of four main components: (i) production of observationally constrained atmosphere-ocean and atmosphere-land biosphere fluxes and uncertainties for the past decade; (ii) generation of atmospheric forward model ensembles to quantify errors in atmospheric CO2 simulations due to both flux and transport uncertainty; (iii) incorporation of GOSAT, OCO-2, and in situ observations to produce high-resolution global atmospheric CO and CO2 concentration reanalyses; (iv) evaluation of the sensitivity of inversion flux estimates to assumptions of prior flux uncertainty and transport uncertainty using multiple inversion methodologies. A central component of these efforts is the use of meteorological forcing provided by NASAs Modern Era Retrospective-analysis for Research and Applications 2 (MERRA-2) to produce a consistent picture of the interactions between weather, climate, and the carbon cycle. Flux estimates will be improved through improvements in input datasets and process representation and new methods of uncertainty quantification will be employed to deliver reliable flux estimates with associated uncertainties. Land biosphere fluxes from the CASA-GFED model, currently funded separately, will be further updated here to utilize new vegetation fluorescence, MERRA-2 soil moisture, and fire products. The ocean, land, and fossil fuel flux uncertainties will be propagated forward in the GEOS Model, version 5 (GEOS-5) to examine their impact on calculated CO2 mixing ratios and comparisons with observations. An ensemble of GEOS-5 simulations with perturbations to subgrid transport processes will be used to quantify the impact of transport uncertainty. These uncertainty estimates and fluxes will be combined with satellite and in situ CO and CO2 observations to produce realistic trace gas reanalyses for use by the carbon monitoring community. Finally, we will examine the issue of error propagation through multiple inversion modeling frameworks to better understand the constraint placed on carbon flux by existing and future atmospheric CO2 measurements. All products will be hosted on NASAs Global Modeling and Assimilation Office (GMAO) servers with simple download and visualization options provided through GMAOs website.
Project Associations:
  • CMS
CMS Primary Theme:
  • Global Surface-Atmosphere Flux
CMS Science Theme(s):
  • Atmospheric Transport
  • Land-Atmosphere Flux
  • Ocean-Atmosphere Flux
  • Global Surface-Atmosphere Flux
  • MRV

Participants:

Abhishek Chatterjee, NASA JPL
George (Jim) Collatz, NASA GSFC - retired
Stephan (Randy) Kawa, NASA GSFC
Tomohiro (Tom) Oda, USRA
Lesley Ott, NASA GSFC GMAO
Benjamin (Ben) Poulter, NASA GSFC

Project URL(s): None provided.
 
Data
Products:
Product Title:  GEOS-Carb Atmospheric CO Reanalysis - Column concentrations
Start Date:  01/2009      End Date:  12/2016     (2009-2016)
Description:  - Provide CO and CO2 reanalysis
Status:  Preliminary
CMS Science Theme(s):  Atmospheric Transport; Global Surface-Atmosphere Flux
Keywords:  Carbon Stocks (; atmospheric)
Spatial Extent:  Global
Spatial Resolution:  0.5 x 0.5
Temporal Frequency:  Daily
Input Data Products:  MERRA-2, CO from MOPITT/IASI/AIRS, CO2 from TCCON, GOSAT, OCO-2, surface flask network
Algorithm/Models Used:  GEOS-5
Evaluation:  Comparison against independent aircraft obs
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  Comparison against independent data, analysis of innovation statistics
Uncertainty Categories:  deterministic and model-data comparison
Application Areas:  - GHG emissions inventory; - Global carbon budget calculations
Relevant Policies/Programs:  CMS FPP, USCCSP, IPCC
Potential Users:  CMS flux teams, USGS, EPA, NOAA, GCP, and others who want to run carbon cycle models.
Stakeholders:  
Current Application Readiness Level:  3,4
Start Application Readiness Level:  3,4
Target Application Readiness Level:  5
Future Developments:  - Continue refining assimilation techniques using Evaluation and validation efforts.
Limitations:  Data sparsity, unknown error characteristics, measurement error
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

Product Title:  GEOS-Carb Atmospheric CO2 Uncertainty due to Transport
Time Period:  2003-2016
Description:  - Provide simulated atmospheric CO and CO2 concentrations and associated uncertainties

This work builds on earlier work and Previous products available at GMAO ftp site ftp://gmaoftp.gsfc.nasa.gov/pub/data/lott/CMS_monthly_average/
Status:  Preliminary
CMS Science Theme(s):  Atmospheric Transport; Global Surface-Atmosphere Flux
Keywords:  Carbon Stocks (; atmospheric)
Spatial Extent:  Global
Spatial Resolution:  0.5 x 0.5
Temporal Frequency:  Daily
Input Data Products:  MERRA-2, NOBM, ODIAC, CASA-GFED fluxes
Algorithm/Models Used:  GEOS-5
Evaluation:  Comparison against surface, aircraft, TCCON, GOSAT, OCO-2, MOPITT
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  Incorporate flux uncertainty estimates; ensembles with altered model physics to evaluate transport error
Uncertainty Categories:  deterministic and ensemble
Application Areas:  - GHG emissions inventory; - Global carbon budget calculations
Relevant Policies/Programs:  CMS FPP, USCCSP, IPCC
Potential Users:  CMS flux teams, USGS, EPA, NOAA, GCP, and others who want to run carbon cycle models.
Stakeholders:  
Current Application Readiness Level:  5
Start Application Readiness Level:  5
Target Application Readiness Level:  6,7
Future Developments:  - Continue improving estimates using Evaluation and validation efforts.
Limitations:  Transport uncertainty remains difficult to quantify, validation datasets do not provide global coverage or sufficient information on vertical gradients
Date When Product Available:  CO and CO2 simulations using best available fluxes by 9/15, simulations using updated fluxes and with uncertainty estimates by 9/16, updated 9/17
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  GEOS-Carb NOBM Monthly Ocean Fluxes
Time Period:  2003-2016
Description:  Provide ocean-atmosphere flux estimates.; - Quantify uncertainties.

This work builds on earlier efforts and we have made the results from those efforts available:
Gregg, W. and C. Rousseaux. 2013. CMS- Flux Pilot Project Ocean-Atmosphere Fluxes 2003- 2012 NOBM Model. Data set. Available online from the GMAO ftp site: ftp://gmaoftp.gsfc.nasa.gov/pub/data/NOBM/FCO2/
Status:  Preliminary
CMS Science Theme(s):  Global Surface-Atmosphere Flux; Ocean-Atmosphere Flux
Keywords:  Flux/Movement (; oceanic; ; atmospheric); ; Uncertainties & Standard Errors
Spatial Extent:  Global
Spatial Resolution:  0.5 x 0.5
Temporal Frequency:  Monthly
Input Data Products:  NASA's Modern Era Retrospective-analysis for Research and Applications 2 (MERRA-2), MODIS/VIIRS Chlorophyll, VIIRS Particulate Inorganic Carbon, OCO-2/GOSAT
Algorithm/Models Used:  NASA Ocean Biogeochemical Model (NOBM), Modular Ocean Model (MOM), GEOS-5
Evaluation:  Comparison with in situ database (LDEO), comparison with SOCAT derived flux estimates, atmospheric CO2 measurements (in situ, aircraft, OCO-2, GOSAT)
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  Quantify uncertainty due to atmospheric CO2 forcing, comparison with LDEO, SOCAT estimates. Impact of meteorological reanalyses already quantified.
Uncertainty Categories:  deterministic and model-data comparison
Application Areas:  ; - Global carbon budget calculations; - Ocean changes
Relevant Policies/Programs:  CMS FPP, USCCSP, IPCC
Potential Users:  CMS flux teams, USGS, EPA, NOAA, GCP, and others who want to run carbon cycle models.
Stakeholders:  
Current Application Readiness Level:  5
Start Application Readiness Level:  5
Target Application Readiness Level:  6,7
Future Developments:  - Continue improving the model using Evaluation and validation efforts.
Limitations:  Difficult to assess in Southern Ocean due to sparse data coverage
Date When Product Available:  2003-2012 Fluxes already available, Improved 2003-2015 fluxes with uncertainty estimates provided 9/16, Updated through 2016 9/17
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  GEOS-Carb ODIAC Monthly Fossil Fuel Emissions and Uncertainty
Time Period:  2003-2016
Description:  - Quantify uncertainties of fossil fuel emissions estimates

cite as Oda, T. 2014. Odiac emissions dataset. Data available from the ODIAC website: http://www.odiac.org/
Status:  Preliminary
CMS Science Theme(s):  Global Surface-Atmosphere Flux; Land-Atmosphere Flux; MRV
Keywords:  Source (; anthropogenic;); ; Uncertainties & Standard Errors
Spatial Extent:  Global
Spatial Resolution:  0.5 x 0.5
Temporal Frequency:  Yearly
Input Data Products:  CDIAC and EDGAR emissions inventories, DMSP/VIIRS night lights,
Algorithm/Models Used:  ODIAC
Evaluation:  Comparison against other emissions inventories, surface and column atmospheric CO2 observations
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  Comparison against other emissions inventories; application of differing literature estimates of national FF uncertainty, seasonality, disaggregation method
Uncertainty Categories:  deterministic and model-model comparison
Application Areas:  - GHG emissions inventory; - Global carbon budget calculations
Relevant Policies/Programs:  CMS FPP, USCCSP, IPCC
Potential Users:  CMS flux teams, USGS, EPA, NOAA, GCP, and others who want to run carbon cycle models.
Stakeholders:  
Current Application Readiness Level:  5
Start Application Readiness Level:  5
Target Application Readiness Level:  6,7
Future Developments:  - Continue improving estimates using Evaluation and validation efforts.
Limitations:  Emissions estimates difficult to validate at fine spatial scales, particularly in developing regions
Date When Product Available:  Emissions data available online; Uncertainty estimates to be delivered 9/16, updated 9/17
Metadata URL(s):
Included with data products
Data Server URL(s):

http://odiac.org/dataset.html
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  GEOS-Carb CASA-GFED 3-hourly Ecosystem Exchange Fluxes 0.5 degree x 0.625 degree V2 (GEOS_CASAGFED_3H_NEE) at GES DISC
Start Date:  01/2003      End Date:  12/2016     (2003-2016)
Description:  This product provides 3 hourly average net ecosystem exchange (NEE) and gross ecosystem exchange (GEE)
of Carbon derived from the Carnegie-Ames-Stanford-Approach – Global Fire Emissions Database version 3 (CASA-
GFED3) model.

The NASA Carbon Monitoring System (CMS) is designed to make significant contributions in characterizing, quantifying, understanding, and predicting the evolution of global carbon sources and sinks through improved monitoring of carbon stocks and fluxes. The System will use the full range of NASA satellite observations and modeling/analysis capabilities to establish the accuracy, quantitative uncertainties, and utility of products for supporting national and international policy, regulatory, and management activities. CMS will maintain a global emphasis while providing finer scale regional information, utilizing space-based and surface-based data and will rapidly initiate generation and distribution of products both for user evaluation and to inform near-term policy development and planning.
Status:  Archived
CMS Science Theme(s):  Land-Atmosphere Flux
Keywords:  NEE; NEP; GEE; Fire emissions; Heterotrophic respiration
Spatial Extent:  Global
Spatial Resolution:  0.5 degree x 0.625 degre
Temporal Frequency:  monthly, containing values every 3 hours
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  GES DISC
Metadata URL(s):
10.5067/5MQJ64JTBQ40
Data Server URL(s):
10.5067/5MQJ64JTBQ40
Archived Data Citation:  Lesley Ott (2020), GEOS-Carb CASA-GFED 3-hourly Ecosystem Exchange Fluxes 0.5 degree x 0.625 degree, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/5MQJ64JTBQ40

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

Product Title:  GEOS-Carb CASA-GFED Daily Fire and Fuel Emissions 0.5 degree x 0.5 degree V2 (GEOS_CASAGFED_D_FIRE) at GES DISC
Start Date:  01/2003      End Date:  12/2016     (2003-2016)
Description:  This product provides Daily average wildfire emissions (FIRE) and
fuel wood burning emissions (FUEL) derived from the Carnegie-Ames-Stanford-Approach – Global Fire Emissions Database version 3 (CASA-
GFED3) model.

The NASA Carbon Monitoring System (CMS) is designed to make significant contributions in characterizing, quantifying, understanding, and predicting the evolution of global carbon sources and sinks through improved monitoring of carbon stocks and fluxes. The System will use the full range of NASA satellite observations and modeling/analysis capabilities to establish the accuracy, quantitative uncertainties, and utility of products for supporting national and international policy, regulatory, and management activities. CMS will maintain a global emphasis while providing finer scale regional information, utilizing space-based and surface-based data and will rapidly initiate generation and distribution of products both for user evaluation and to inform near-term policy development and planning.
Status:  Archived
CMS Science Theme(s):  Land-Atmosphere Flux
Keywords:  Fire emissions
Spatial Extent:  Global
Spatial Resolution:  0.5 degree by 0.5 degree
Temporal Frequency:  daily
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  GES DISC
Metadata URL(s):
10.5067/IYZIZJ8ZFZHU
Data Server URL(s):
10.5067/IYZIZJ8ZFZHU
Archived Data Citation:  Lesley Ott (2020), GEOS-Carb CASA-GFED Daily Fire and Fuel Emissions 0.5 degree x 0.5 degree, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/IYZIZJ8ZFZHU

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

Product Title:  GEOS-Carb CASA-GFED Monthly Fire Fuel NPP Rh NEE Fluxes 0.5 degree x 0.5 degree V2 (GEOS_CASAGFED_M_FLUX) at GES DISC
Start Date:  01/2003      End Date:  12/2016     (2003-2016)
Description:  This product provides Monthly average Net Primary Production (NPP), heterotrophic respiration (Rh), wildfire emissions (FIRE), and
fuel wood burning emissions (FUEL) derived from the Carnegie-Ames-Stanford-Approach – Global Fire Emissions Database version 3 (CASA-
GFED3) model.

The NASA Carbon Monitoring System (CMS) is designed to make significant contributions in characterizing, quantifying, understanding, and predicting the evolution of global carbon sources and sinks through improved monitoring of carbon stocks and fluxes. The System will use the full range of NASA satellite observations and modeling/analysis capabilities to establish the accuracy, quantitative uncertainties, and utility of products for supporting national and international policy, regulatory, and management activities. CMS will maintain a global emphasis while providing finer scale regional information, utilizing space-based and surface-based data and will rapidly initiate generation and distribution of products both for user evaluation and to inform near-term policy development and planning.
Status:  Archived
CMS Science Theme(s):  Land-Atmosphere Flux
Keywords:  NPP; NEE; Fire
Spatial Extent:  Global
Spatial Resolution:  0.5 degrees by 0.625 degrees
Temporal Frequency:  3 hourly
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  GES DISC
Metadata URL(s):
10.5067/FZU47Y00Q79U
Data Server URL(s):
10.5067/FZU47Y00Q79U
Archived Data Citation:  Lesley Ott (2020), GEOS-Carb CASA-GFED Monthly Fire Fuel NPP Rh NEE Fluxes 0.5 degree x 0.5 degree, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/FZU47Y00Q79U

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

Product Title:  GEOS-Carb CASA-GFED Monthly Fire Fuel NPP Rh NEE Fluxes 0.5 degree x 0.5 degree V3 (GEOS_CASAGFED_M_FLUX) at GES DISC
Start Date:  01/2003      End Date:  12/2017     (2003-2017)
Description:  This product provides Monthly average Net Primary Production (NPP), heterotrophic respiration (Rh), wildfire emissions (FIRE), and
fuel wood burning emissions (FUEL) derived from the Carnegie-Ames-Stanford-Approach – Global Fire Emissions Database version 3 (CASA-
GFED3) model.

The NASA Carbon Monitoring System (CMS) is designed to make significant contributions in characterizing, quantifying, understanding, and predicting the evolution of global carbon sources and sinks through improved monitoring of carbon stocks and fluxes. The System will use the full range of NASA satellite observations and modeling/analysis capabilities to establish the accuracy, quantitative uncertainties, and utility of products for supporting national and international policy, regulatory, and management activities. CMS will maintain a global emphasis while providing finer scale regional information, utilizing space-based and surface-based data and will rapidly initiate generation and distribution of products both for user evaluation and to inform near-term policy development and planning.
Status:  Archived
CMS Science Theme(s):  Land-Atmosphere Flux
Keywords:  GPP;Fire
Spatial Extent:  Global
Spatial Resolution:  0.5 degree by 0.5 degree
Temporal Frequency:  monthly
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  GES DISC
Metadata URL(s):
10.5067/03147VMJE8J9
Data Server URL(s):
10.5067/03147VMJE8J9
Archived Data Citation:  Lesley Ott (2020), GEOS-Carb CASA-GFED Monthly Fire Fuel NPP Rh NEE Fluxes 0.5 degree x 0.5 degree, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/03147VMJE8J9

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

Product Title:  GEOS-Carb CASA-GFED 3-hourly Ecosystem Exchange Fluxes 0.5 degree x 0.625 degree V3 (GEOS_CASAGFED_3H_NEE) at GES DISC
Start Date:  01/2003      End Date:  12/2017     (2003-2017)
Description:  This product provides 3 hourly average net ecosystem exchange (NEE) and gross ecosystem exchange (GEE)
of Carbon derived from the Carnegie-Ames-Stanford-Approach – Global Fire Emissions Database version 3 (CASA-
GFED3) model.

The NASA Carbon Monitoring System (CMS) is designed to make significant contributions in characterizing, quantifying, understanding, and predicting the evolution of global carbon sources and sinks through improved monitoring of carbon stocks and fluxes. The System will use the full range of NASA satellite observations and modeling/analysis capabilities to establish the accuracy, quantitative uncertainties, and utility of products for supporting national and international policy, regulatory, and management activities. CMS will maintain a global emphasis while providing finer scale regional information, utilizing space-based and surface-based data and will rapidly initiate generation and distribution of products both for user evaluation and to inform near-term policy development and planning.
Status:  Archived
CMS Science Theme(s):  Land-Atmosphere Flux
Keywords:  NPP;NEE;GEE
Spatial Extent:  Global
Spatial Resolution:  0.5 degrees x 0.625 degrees
Temporal Frequency:  3-hourly
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  GES DISC
Metadata URL(s):
10.5067/VQPRALE26L20
Data Server URL(s):
10.5067/VQPRALE26L20
Archived Data Citation:  Lesley Ott (2020), GEOS-Carb CASA-GFED 3-hourly Ecosystem Exchange Fluxes 0.5 degree x 0.625 degree, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/VQPRALE26L20

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

Product Title:  GEOS-Carb CASA-GFED Daily Fire and Fuel Emissions 0.5 degree x 0.5 degree V3 (GEOS_CASAGFED_D_FIRE) at GES DISC
Start Date:  01/2003      End Date:  12/2017     (2003-2016)
Description:  This product provides Daily average wildfire emissions (FIRE) and
fuel wood burning emissions (FUEL) derived from the Carnegie-Ames-Stanford-Approach – Global Fire Emissions Database version 3 (CASA-
GFED3) model.

The NASA Carbon Monitoring System (CMS) is designed to make significant contributions in characterizing, quantifying, understanding, and predicting the evolution of global carbon sources and sinks through improved monitoring of carbon stocks and fluxes. The System will use the full range of NASA satellite observations and modeling/analysis capabilities to establish the accuracy, quantitative uncertainties, and utility of products for supporting national and international policy, regulatory, and management activities. CMS will maintain a global emphasis while providing finer scale regional information, utilizing space-based and surface-based data and will rapidly initiate generation and distribution of products both for user evaluation and to inform near-term policy development and planning.
Status:  Archived
CMS Science Theme(s):  Land-Atmosphere Flux
Keywords:  Fire
Spatial Extent:  Global
Spatial Resolution:  0.5 degree x 0.5 degree
Temporal Frequency:  daily
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  GES DISC
Metadata URL(s):
10.5067/7TQL49XLIMBD
Data Server URL(s):
10.5067/7TQL49XLIMBD
Archived Data Citation:  Lesley Ott (2020), GEOS-Carb CASA-GFED Daily Fire and Fuel Emissions 0.5 degree x 0.5 degree, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/7TQL49XLIMBD

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

Product Title:  GEOS-Carb Atmospheric CO Reanalysis - 3D concentrations
Start Date:  01/2009      End Date:  12/2016     (2009-2016)
Description:  
Status:  Preliminary
CMS Science Theme(s):  Atmospheric Transport; Global Surface-Atmosphere Flux
Keywords:  Carbon Stocks (; atmospheric)
Spatial Extent:  Global
Spatial Resolution:  0.5 x 0.5 degrees
Temporal Frequency:  daily
Input Data Products:  MERRA-2, CO from MOPITT/IASI/AIRS, CO2 from TCCON, GOSAT, OCO-2, surface flask network
Algorithm/Models Used:  GEOS-5
Evaluation:  Comparison against independent aircraft observations
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  Comparison against independent data, analysis of innovation statistics
Uncertainty Categories:  deterministic and model-data comparison
Application Areas:  GHG emissions inventory; - Global carbon budget calculations
Relevant Policies/Programs:  CMS FPP, USCCSP, IPCC
Potential Users:  CMS flux teams, USGS, EPA, NOAA, GCP, and others who want to run carbon cycle models.
Stakeholders:  
Current Application Readiness Level:  3,4
Start Application Readiness Level:  3,4
Target Application Readiness Level:  5
Future Developments:  Continue refining assimilation techniques using Evaluation and validation efforts.
Limitations:  Data sparsity, unknown error characteristics, measurement error
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

Product Title:  GEOS-Carb Atmospheric CO Reanalysis - Emissions
Start Date:  01/2009      End Date:  12/2016     (2009-2018)
Description:  
Status:  Preliminary
CMS Science Theme(s):  Atmospheric Transport; Global Surface-Atmosphere Flux
Keywords:  Carbon Stocks (; atmospheric)
Spatial Extent:  global
Spatial Resolution:  0.5 x 0.5 degrees
Temporal Frequency:  daily
Input Data Products:  MERRA-2, CO from MOPITT/IASI/AIRS, CO2 from TCCON, GOSAT, OCO-2, surface flask network
Algorithm/Models Used:  GEOS-5
Evaluation:  Comparison against independent aircraft observations
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  Comparison against independent data, analysis of innovation statistics
Uncertainty Categories:  deterministic and model-data comparison
Application Areas:  GHG emissions inventory; - Global carbon budget calculations
Relevant Policies/Programs:  CMS FPP, USCCSP, IPCC
Potential Users:  CMS flux teams, USGS, EPA, NOAA, GCP, and others who want to run carbon cycle models.
Stakeholders:  
Current Application Readiness Level:  3,4
Start Application Readiness Level:  3,4
Target Application Readiness Level:  5
Future Developments:  Continue refining assimilation techniques using Evaluation and validation efforts.
Limitations:  Data sparsity, unknown error characteristics, measurement error
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

Product Title:  GEOS-Carb Atmospheric CO Reanalysis - Surface concentrations
Start Date:  01/2009      End Date:  12/2016     (2009-2016)
Description:  
Status:  Preliminary
CMS Science Theme(s):  Atmospheric Transport; Global Surface-Atmosphere Flux
Keywords:  Carbon Stocks (; atmospheric)
Spatial Extent:  Global
Spatial Resolution:  0.5 x 0.5 degrees
Temporal Frequency:  daily
Input Data Products:  MERRA-2, CO from MOPITT/IASI/AIRS, CO2 from TCCON, GOSAT, OCO-2, surface flask network
Algorithm/Models Used:  GEOS-5
Evaluation:  Comparison against independent aircraft observations
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  Comparison against independent data, analysis of innovation statistics
Uncertainty Categories:  deterministic and model-data comparison
Application Areas:  GHG emissions inventory; - Global carbon budget calculations
Relevant Policies/Programs:  CMS FPP, USCCSP, IPCC
Potential Users:  CMS flux teams, USGS, EPA, NOAA, GCP, and others who want to run carbon cycle models.
Stakeholders:  
Current Application Readiness Level:  3,4
Start Application Readiness Level:  3,4
Target Application Readiness Level:  5
Future Developments:  Continue refining assimilation techniques using Evaluation and validation efforts.
Limitations:  Data sparsity, unknown error characteristics, measurement error
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

Product Title:  GEOS-Carb Atmospheric CO2 Reanalysis - 3D concentrations
Start Date:  01/2009      End Date:  12/2016     (2009-2016)
Description:  
Status:  Preliminary
CMS Science Theme(s):  Atmospheric Transport; Global Surface-Atmosphere Flux
Keywords:  Carbon Stocks (; atmospheric)
Spatial Extent:  Global
Spatial Resolution:  0.5 degree by 0.5 degree
Temporal Frequency:  Daily
Input Data Products:  MERRA-2, CO from MOPITT/IASI/AIRS, CO2 from TCCON, GOSAT, OCO-2, surface flask network
Algorithm/Models Used:  GEOS-5
Evaluation:  Comparison against independent aircraft observations
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  Comparison against independent data, analysis of innovation statistics
Uncertainty Categories:  deterministic and model-data comparison
Application Areas:  GHG emissions inventory; - Global carbon budget calculations
Relevant Policies/Programs:  CMS FPP, USCCSP, IPCC
Potential Users:  CMS flux teams, USGS, EPA, NOAA, GCP, and others who want to run carbon cycle models.
Stakeholders:  
Current Application Readiness Level:  3,4
Start Application Readiness Level:  3,4
Target Application Readiness Level:  5
Future Developments:  Continue refining assimilation techniques using Evaluation and validation efforts.
Limitations:  Data sparsity, unknown error characteristics, measurement error
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

Product Title:  GEOS-Carb Atmospheric CO2 Reanalysis - Emissions
Start Date:  01/2009      End Date:  12/2016     (2009-2016)
Description:  
Status:  Preliminary
CMS Science Theme(s):  Atmospheric Transport; Global Surface-Atmosphere Flux
Keywords:  Carbon Stocks (; atmospheric)
Spatial Extent:  Global
Spatial Resolution:  0.5 degree by 0.5 degree
Temporal Frequency:  Daily
Input Data Products:  MERRA-2, CO from MOPITT/IASI/AIRS, CO2 from TCCON, GOSAT, OCO-2, surface flask network
Algorithm/Models Used:  GEOS-5
Evaluation:  Comparison against independent aircraft observations
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  Comparison against independent data, analysis of innovation statistics
Uncertainty Categories:  deterministic and model-data comparison
Application Areas:  GHG emissions inventory; - Global carbon budget calculations
Relevant Policies/Programs:  CMS FPP, USCCSP, IPCC
Potential Users:  CMS flux teams, USGS, EPA, NOAA, GCP, and others who want to run carbon cycle models.
Stakeholders:  
Current Application Readiness Level:  3,4
Start Application Readiness Level:  3,4
Target Application Readiness Level:  
Future Developments:  Continue refining assimilation techniques using Evaluation and validation efforts.
Limitations:  Data sparsity, unknown error characteristics, measurement error
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

Product Title:  GEOS-Carb Atmospheric CO2 Reanalysis - Surface concentrations
Start Date:  01/2009      End Date:  12/2016     (2009-2016)
Description:  
Status:  Preliminary
CMS Science Theme(s):  Atmospheric Transport; Global Surface-Atmosphere Flux
Keywords:  Carbon Stocks (; atmospheric)
Spatial Extent:  Global
Spatial Resolution:  0.5 x 0.5 degrees
Temporal Frequency:  daily
Input Data Products:  MERRA-2, CO from MOPITT/IASI/AIRS, CO2 from TCCON, GOSAT, OCO-2, surface flask network
Algorithm/Models Used:  GEOS-5
Evaluation:  Comparison against independent aircraft observations
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  Comparison against independent data, analysis of innovation statistics
Uncertainty Categories:  deterministic and model-data comparison
Application Areas:  GHG emissions inventory; Global carbon budget calculations
Relevant Policies/Programs:  CMS FPP, USCCSP, IPCC
Potential Users:  CMS flux teams, USGS, EPA, NOAA, GCP, and others who want to run carbon cycle models.
Stakeholders:  
Current Application Readiness Level:  3,4
Start Application Readiness Level:  3,4
Target Application Readiness Level:  5
Future Developments:  Continue refining assimilation techniques using Evaluation and validation efforts.
Limitations:  Data sparsity, unknown error characteristics, measurement error
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

Product Title:  GEOS-Carb Atmospheric CO2 Reanalysis - Column concentrations
Start Date:  01/2009      End Date:  12/2016     (2009-2016)
Description:  
Status:  Preliminary
CMS Science Theme(s):  Atmospheric Transport; Global Surface-Atmosphere Flux
Keywords:  Carbon Stocks (; atmospheric)
Spatial Extent:  Global
Spatial Resolution:  0.5 x 0.5 degrees
Temporal Frequency:  daily
Input Data Products:  MERRA-2, CO from MOPITT/IASI/AIRS, CO2 from TCCON, GOSAT, OCO-2, surface flask network
Algorithm/Models Used:  GEOS-5
Evaluation:  Comparison against independent aircraft observations
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  Comparison against independent data, analysis of innovation statistics
Uncertainty Categories:  deterministic and model-data comparison
Application Areas:  GHG emissions inventory; - Global carbon budget calculations
Relevant Policies/Programs:  CMS FPP, USCCSP, IPCC
Potential Users:  CMS flux teams, USGS, EPA, NOAA, GCP, and others who want to run carbon cycle models.
Stakeholders:  
Current Application Readiness Level:  3,4
Start Application Readiness Level:  3,4
Target Application Readiness Level:  5
Future Developments:  Continue refining assimilation techniques using Evaluation and validation efforts.
Limitations:  Data sparsity, unknown error characteristics, measurement error
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:90.00000 South Latitude:-90.00000

 
Publications: Wang, J. S., Kawa, S. R., Collatz, G. J., Sasakawa, M., Gatti, L. V., Machida, T., Liu, Y., Manyin, M. E. 2018. A global synthesis inversion analysis of recent variability in CO&lt;sub&gt;2&lt;/sub&gt; fluxes using GOSAT and in situ observations. Atmospheric Chemistry and Physics. 18(15), 11097-11124. DOI: 10.5194/acp-18-11097-2018

Gregg, W. W., N. W. Casey, and C. S. Rousseaux, 2013, Global surface ocean carbon estimates in a model forced by MERRA, NASA Technical Report Series on Global Modeling and Data Assimilation, NASA TM-2013-104606, Vol. 31, 39 pp.

Gregg, W. W., Casey, N. W., Rousseaux, C. S. 2014. Sensitivity of simulated global ocean carbon flux estimates to forcing by reanalysis products. Ocean Modelling. 80, 24-35. DOI: 10.1016/j.ocemod.2014.05.002

Ott, L. E., Pawson, S., Collatz, G. J., Gregg, W. W., Menemenlis, D., Brix, H., Rousseaux, C. S., Bowman, K. W., Liu, J., Eldering, A., Gunson, M. R., Kawa, S. R. 2015. Assessing the magnitude of CO2flux uncertainty in atmospheric CO2records using products from NASA's Carbon Monitoring Flux Pilot Project. Journal of Geophysical Research: Atmospheres. 120(2), 734-765. DOI: 10.1002/2014JD022411

Oda, T., Maksyutov, S. 2011. A very high-resolution (1 kmx1 km) global fossil fuel CO&lt;sub&gt;2&lt;/sub&gt; emission inventory derived using a point source database and satellite observations of nighttime lights. Atmospheric Chemistry and Physics. 11(2), 543-556. DOI: 10.5194/acp-11-543-2011

Archived Data Citations: Lesley Ott (2020), GEOS-Carb CASA-GFED 3-hourly Ecosystem Exchange Fluxes 0.5 degree x 0.625 degree, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/5MQJ64JTBQ40

Lesley Ott (2020), GEOS-Carb CASA-GFED Monthly Fire Fuel NPP Rh NEE Fluxes 0.5 degree x 0.5 degree, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/03147VMJE8J9

Lesley Ott (2020), GEOS-Carb CASA-GFED Daily Fire and Fuel Emissions 0.5 degree x 0.5 degree, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/IYZIZJ8ZFZHU

Lesley Ott (2020), GEOS-Carb CASA-GFED Daily Fire and Fuel Emissions 0.5 degree x 0.5 degree, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/7TQL49XLIMBD

Lesley Ott (2020), GEOS-Carb CASA-GFED Monthly Fire Fuel NPP Rh NEE Fluxes 0.5 degree x 0.5 degree, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/FZU47Y00Q79U

Lesley Ott (2020), GEOS-Carb CASA-GFED 3-hourly Ecosystem Exchange Fluxes 0.5 degree x 0.625 degree, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/VQPRALE26L20

Outreach Activities: NASA has a traveling display called the Hyperwall consisting of a wall of multiple high definition screens displaying high resolution images simultaneously. View the Hyperwall presentation for this project


 

Walker (CMS 2014) (2014)
Project Title:Direct Measurement of Aboveground Carbon Dynamics in Support of Large-Area CMS Development

Science Team
Members:

Wayne Walker, Woodwell Climate Research Center (Project Lead)

Solicitation:NASA: Carbon Monitoring System (2014)
Abstract: In response to the implications that high uncertainties associated with traditional approaches to forest carbon accounting have, not only for the credibility of REDD+, but also for the advancement of biospheric modeling and carbon cycle science, the main goal of this research is to investigate the potential for annual changes in the aboveground carbon density (ACD) of forests to be estimated directly, consistently, and with measurable accuracy across large areas using an array of existing commercial off-the-shelf and NASA remote sensing assets. The geographic focus is the country of Mexico where members of the proposal team have been working closely with the Mexican government since 2011 to assist in advancing their forest monitoring capacity as part of a USAID-supported project to Reduce Emissions from Deforestation and Forest Degradation in Mexico (USAID/M-REDD). The specific objectives are to: (1) Quantify the certainty with which extensive field, off-the-shelf airborne LiDAR, and MODIS satellite data can be used synergistically to estimate wall-to-wall changes in ACD at a resolution of 500 m across Mexico over a 15-year period (2001-2015). This objective expands on the work of Baccini et al. (2012) who successfully combined field, ICESat GLAS LiDAR, and MODIS optical data sets for single-epoch mapping of pantropical ACD. Here we replace spaceborne GLAS LiDAR with off-the-shelf airborne LiDAR and combine time-series mapping with change-point analysis to enable annual ACD change estimation, (2) Quantify the certainty with which extensive field, off-the-shelf airborne LiDAR, and VIIRS satellite data can be used synergistically to estimate wall-to-wall changes in ACD at a resolution of 375 m across Mexico over 5-year period (2012-2016). As NASA’s second-generation moderate-resolution imaging radiometer, VIIRS extends and improves upon MODIS; yet the performance of VIIRS data for large-area ACD and ACD change mapping, has not been demonstrated, (3) Quantify the certainty with which extensive field, off-the-shelf airborne LiDAR, and Landsat 5-8 satellite data can be used synergistically to estimate wall-to-wall changes in ACD for the Mexican states of Chihuahua, Oaxaca, Campeche, Yucatan, and Quintana Roo over a 15-year period (2001-2015). While acknowledging the increasing demand for large-area ACD estimates at resolutions ranging from 10s to 100s of meters, we seek to more closely examine Landsat performance, particularly the inverse relationship that appears to exist between resolution and accuracy, and (4) Conduct an independent accuracy assessment of the ACD change products produced in Objectives 1-3 as well as of derivative estimates of gross emissions. We will leverage permanent plot data from the Mexico National Inventory of Forest and Soil (INFyS), intensive field and micrometeorological measurements from the Mexico network of eddy covariance flux towers (MexFlux), and deforestation data from Hansen et al. (2013), among other data sources. The ACD change products we propose to produce here represent a fundamentally new way of quantifying carbon fluxes that will significantly reduce uncertainty while leading to a more complete understanding of terrestrial carbon cycling. Unlike conventional approaches, which focus on deforestation leaving degradation unaccounted for, the proposed approach provides for a unique estimates of gross emissions at the pixel level, integrating losses due to deforestation, degradation, and other disturbances with gains due to growth. The work is expected to transform operational carbon accounting and, in doing so, drive the science, and ultimately the policy, forward. Within Mexico itself, the opportunity exists, not only to impact MRV system development at the national level through the involvement of proposal team members in the USAID/M-REDD project, but also at the jurisdictional level through relationships with the GCF and member states Chiapas and Campeche.
Project Associations:
  • CMS
CMS Primary Theme:
  • Land Biomass
CMS Science Theme(s):
  • Land Biomass
  • Land-Atmosphere Flux
  • Decision Support
  • MRV

Participants:

Alessandro (Ale) Baccini, Boston University
Wayne Walker, Woodwell Climate Research Center

Project URL(s): None provided.
 
Data
Products:
Product Title:  Accuracy assessment of the aboveground carbon density change products and derivative estimates of gross emissions.
Description:  - Conduct an independent accuracy assessment of the aboveground carbon density change products produced As well As of derivative estimates of gross emissions.
Status:  Planned
CMS Science Theme(s):  Land Biomass; Land-Atmosphere Flux; MRV
Keywords:  Evaluation & User Interfaces
Spatial Extent:  Mexico
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  Carbon density change maps
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  - MRV, REDD+; - Forest inventory; - GHG emissions inventory; - Land management
Relevant Policies/Programs:  REDD+, SilvaCarbon, Governors' Climate and Forests Task Force (GCF), US-Mexico Bilateral, NALS, Doha/Kyoto, NACP, CarboNA
Potential Users:  USAID, Chiapas and Campeche jurisdictional governments
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  At least one applications workshop + meetings with Mexican stakeholders and collaborators.
Limitations:  
Date When Product Available:  Q3/2017
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Maps of wall-to-wall changes in aboveground carbon density.
Time Period:  2001-2015
Description:  - Quantify the certainty with which extensive field, off-the-shelf airborne Lidar, and MODIS satellite data can be used synergistically to estimate wall-to-wall changes in aboveground carbon density.
Status:  Planned
CMS Science Theme(s):  Land Biomass; Land-Atmosphere Flux; MRV
Keywords:  Flux/Movement (; terrestrial; ; atmospheric)
Spatial Extent:  Mexico
Spatial Resolution:  500 m
Temporal Frequency:  Annual
Input Data Products:  field measurements, off-the-shelf airborne Lidar), MODIS. Airborne LiDAR includes 2013 G-LiHT and 2014 M-REDD, which include transects of varying length and width as well as wall-to-wall quadrats spanning the entire country.
Algorithm/Models Used:  Temporal change-point algorithm being developed in house for publication at a later date.
Evaluation:  Independent field data, flux tower data, Hansen et al. (2013).
Intercomparison Efforts/Gaps:  Intercomparisons will be conducted among the three primary products described here (i.e., MODIS, VIIRS, Landsat). No other are planned.
Uncertainty Estimates:  Uncertainty will be quantified at the pixel level.
Uncertainty Categories:  Ensemble/model-data comparison
Application Areas:  - MRV, REDD+; - Forest inventory; - GHG emissions inventory; - Land management
Relevant Policies/Programs:  REDD+, SilvaCarbon, Governors' Climate and Forests Task Force (GCF), US-Mexico Bilateral, NALS, Doha/Kyoto, NACP, CarboNA
Potential Users:  USAID, Chiapas and Campeche jurisdictional governments
Stakeholders:  
Current Application Readiness Level:  4
Start Application Readiness Level:  2
Target Application Readiness Level:  6,7
Future Developments:  At least one applications workshop + meetings with Mexican stakeholders and collaborators.
Limitations:  It remains difficult to attribute cause to changes in carbon density; however, approaches to addressing this issue are also being investigated.
Date When Product Available:  Q4/2016
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Maps of wall-to-wall changes in aboveground carbon density.
Time Period:  2012-2016
Description:  - Quantify the certainty with which extensive field, off-the-shelf airborne Lidar, and VIIRS satellite data can be used synergistically to estimate wall-to-wall changes in aboveground carbon density.
Status:  Planned
CMS Science Theme(s):  Land Biomass; Land-Atmosphere Flux; MRV
Keywords:  Flux/Movement (; terrestrial; ; atmospheric)
Spatial Extent:  Mexico
Spatial Resolution:  375 m
Temporal Frequency:  Annual
Input Data Products:  field measurements, off-the-shelf airborne Lidar, VIIRS. Airborne LiDAR includes 2013 G-LiHT and 2014 M-REDD, which include transects of varying length and width as well as wall-to-wall quadrats spanning the entire country.
Algorithm/Models Used:  Temporal change-point algorithm being developed in house for publication at a later date.
Evaluation:  Independent field data, flux tower data, Hansen et al. (2013).
Intercomparison Efforts/Gaps:  Intercomparisons will be conducted among the three primary products described here (i.e., MODIS, VIIRS, Landsat). No other are planned.
Uncertainty Estimates:  Uncertainty will be quantified at the pixel level.
Uncertainty Categories:  Ensemble/model-data comparison
Application Areas:  - MRV, REDD+; - Forest inventory; - GHG emissions inventory; - Land management
Relevant Policies/Programs:  REDD+, SilvaCarbon, Governors' Climate and Forests Task Force (GCF), US-Mexico Bilateral, NALS, Doha/Kyoto, NACP, CarboNA
Potential Users:  USAID, Chiapas and Campeche jurisdictional governments
Stakeholders:  
Current Application Readiness Level:  3
Start Application Readiness Level:  2
Target Application Readiness Level:  6,7
Future Developments:  At least one applications workshop + meetings with Mexican stakeholders and collaborators.
Limitations:  It remains difficult to attribute cause to changes in carbon density; however, approaches to addressing this issue are also being investigated.
Date When Product Available:  Q4/2016
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Maps of wall-to-wall changes in aboveground carbon density.
Time Period:  2001-2015
Description:  - Quantify the certainty with which extensive field, off-the-shelf airborne Lidar, and Landsat 5-8 satellite data can be used synergistically to estimate wall-to-wall changes in aboveground carbon density.
Status:  Planned
CMS Science Theme(s):  Land Biomass; Land-Atmosphere Flux; MRV
Keywords:  Flux/Movement (; terrestrial; ; atmospheric)
Spatial Extent:  Mexican states of Chihuahua, Oaxaca, Campeche, Yucatan, and Quintana Roo
Spatial Resolution:  30 - 250 m
Temporal Frequency:  Annual
Input Data Products:  field measurements, off-the-shelf airborne Lidar, Landsat 5-8. Airborne LiDAR includes 2013 G-LiHT and 2014 M-REDD, which include transects of varying length and width as well as wall-to-wall quadrats spanning the entire country.
Algorithm/Models Used:  Temporal change-point algorithm being developed in house for publication at a later date.
Evaluation:  Independent field data, flux tower data, Hansen et al. (2013).
Intercomparison Efforts/Gaps:  Intercomparisons will be conducted among the three primary products described here (i.e., MODIS, VIIRS, Landsat). No other are planned.
Uncertainty Estimates:  Uncertainty will be quantified at the pixel level.
Uncertainty Categories:  Ensemble/model-data comparison
Application Areas:  - MRV, REDD+; - Forest inventory; - GHG emissions inventory; - Land management
Relevant Policies/Programs:  REDD+, SilvaCarbon, Governors' Climate and Forests Task Force (GCF), US-Mexico Bilateral, NALS, Doha/Kyoto, NACP, CarboNA
Potential Users:  USAID, Chiapas and Campeche jurisdictional governments
Stakeholders:  
Current Application Readiness Level:  3
Start Application Readiness Level:  2
Target Application Readiness Level:  6,7
Future Developments:  At least one applications workshop + meetings with Mexican stakeholders and collaborators.
Limitations:  It remains difficult to attribute cause to changes in carbon density; however, approaches to addressing this issue are also being investigated.
Date When Product Available:  Q4/2016
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Aboveground Biomass Change for Amazon Basin, Mexico, and Pantropical Belt, 2003-2016
Start Date:  01/2003      End Date:  12/2016     (2003 through 2016)
Description:  This dataset provides gridded estimates of aboveground biomass (AGB) for live dry woody vegetation density in the form of both stock for the baseline year 2003 and annual change in stock from 2003 to 2016. Data are at a spatial resolution of approximately 500 m (463.31 m; 21.47 ha) for three geographies: the biogeographical limit of the Amazon Basin, the country of Mexico, and a Pantropical belt from 40 degrees North to 30 degrees South latitudes. Estimates were derived from a multi-step modeling approach that combined field measurements with co-located LiDAR data from NASA ICESat Geoscience Laser Altimeter System (GLAS) to calibrate a machine-learning (ML) algorithm that generated spatially explicit annual estimates of AGB density. ML inputs included a suite of satellite and ancillary spatial predictor variables compiled as wall-to-wall raster mosaics, including MODIS products, WorldClim climate variables reflecting current (1960-1990) climatic conditions, and SoilGrids soil variables. The 14-year time series was analyzed at the grid cell (~500 m) level with a change point-fitting algorithm to quantify annual losses and gains in AGB. Estimates of AGB and change can be used to derive total losses, gains, and the net change in aboveground carbon density over the study period as well as annual estimates of carbon stock.
Status:  Archived
CMS Science Theme(s):  Land Biomass; Land-Atmosphere Flux
Keywords:  
Spatial Extent:  Mexico, Amazon Basin, Pantropics
Spatial Resolution:  variable ~500 m (463.31 m; 21.47 ha)
Temporal Frequency:  Annual
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1824
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1824
Archived Data Citation:  Baccini, A., W. Walker, L.E. Carvalho, M.K. Farina, K.K. Solvik, and D. Sulla-Menashe. 2021. Aboveground Biomass Change for Amazon Basin, Mexico, and Pantropical Belt, 2003-2016. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1824

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:40.00000 South Latitude:-30.00000

 
Publications: Baccini, A., Walker, W., Carvalho, L., Farina, M., Houghton, R. A. 2019. Response to Comment on "Tropical forests are a net carbon source based on aboveground measurements of gain and loss". Science. 363(6423). DOI: 10.1126/science.aat1205

Baccini, A., Walker, W., Carvalho, L., Farina, M., Sulla-Menashe, D., Houghton, R. A. 2017. Tropical forests are a net carbon source based on aboveground measurements of gain and loss. Science. 358(6360), 230-234. DOI: 10.1126/science.aam5962

Walker, W. S., Gorelik, S. R., Baccini, A., Aragon-Osejo, J. L., Josse, C., Meyer, C., Macedo, M. N., Augusto, C., Rios, S., Katan, T., de Souza, A. A., Cuellar, S., Llanos, A., Zager, I., Mirabal, G. D., Solvik, K. K., Farina, M. K., Moutinho, P., Schwartzman, S. 2020. The role of forest conversion, degradation, and disturbance in the carbon dynamics of Amazon indigenous territories and protected areas. Proceedings of the National Academy of Sciences. 117(6), 3015-3025. DOI: 10.1073/pnas.1913321117

Archived Data Citations: Baccini, A., W. Walker, L.E. Carvalho, M.K. Farina, K.K. Solvik, and D. Sulla-Menashe. 2021. Aboveground Biomass Change for Amazon Basin, Mexico, and Pantropical Belt, 2003-2016. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1824


 

Williams (CMS 2014) (2014)
Project Title:Translating Forest Change to Carbon Emissions/Removals Linking Disturbance Products, Biomass Maps, and Carbon Cycle Modeling in a Comprehensive Carbon Monitoring Framework

Science Team
Members:

Christopher (Chris) Williams, Clark University (Project Lead)
Huan Gu, Clark University
Benjamin (Ben) Poulter, NASA GSFC

Solicitation:NASA: Carbon Monitoring System (2014)
Abstract: Protecting forest carbon storage and uptake is central to national and international polices aimed at mitigating climate change. The success of such policies relies on high quality, accurate reporting (Tier 3) that earns the greatest financial value of carbon credits and hence incentivizes forest conservation and protection. Methods for Tier 3 Measuring, Reporting, and Verification (MRV) to assess carbon stocks and fluxes over time and for large areas (national to sub-national) are still in development. They generally involve some combination of direct remote sensing, ground based inventorying, and computer modeling, but have tended to emphasize assessments of live aboveground carbon stocks with a less clear connection to the real target of MRV which is carbon emissions and removals. Most existing methods are also largely ambiguous as to the mechanisms that underlie carbon accumulation, and many have limited capacity for forecasting carbon dynamics over time. This projects core objective is to build new capacity for a more thorough approach by advancing our existing carbon stock and flux monitoring framework (Williams et al. 2012, 2013) to deliver a new tool for Tier 3 MRV, decision support, and forecasting, all with process-specificity. The proposed methodology begins with extending our existing framework by providing a more detailed family of carbon flux and stock trajectories, and mapping them to a 1x1 km scale for the conterminous US based on new and emerging data products. A number of improvements to the framework are proposed (Tasks 1 to 5), designed to further characterize the attributes of forested pixels beyond the regionally-defined strata used in our prior work (forest type, site productivity, and age) to now also include pre-disturbance biomass, disturbance type, and disturbance severity attributes based on recently developed RS-derived biomass maps (e.g. Kellndorfer et al. 2012, Saatchi et al. 2013), and Landsat-derived disturbance products linked to the NAFD project. Flux and stock trajectories will also be adjusted to account for any growth enhancements we may detect from detailed analysis FIA data (Task 6). Accounting of the fate of harvested wood products will be added (Task 7) to prepare the framework for more complete assessment of the forest sector carbon balance. We will then map carbon fluxes and stocks by assigning values from modeled trajectories to forest attributes defined at a pixel scale (Task 8). The improved framework will be applied for Tier 3 MRV, yielding regional and country-scale annual carbon fluxes and stocks from 1990 to 2011 (Task 9). It will also be applied in a forecasting mode to test carbon implications of likely management and natural disturbance scenarios (Task 10).
Project Associations:
  • CMS
CMS Primary Theme:
  • Land Biomass
CMS Science Theme(s):
  • Land Biomass
  • Land-Atmosphere Flux
  • Decision Support
  • MRV

Participants:

Grant Domke, USDA Forest Service
Huan Gu, Clark University
Benjamin (Ben) Poulter, NASA GSFC
Christopher (Chris) Williams, Clark University

Project URL(s): None provided.
 
Data
Products:
Product Title:  Forest Carbon Stocks and Fluxes After Disturbance, Southeastern USA, 1990-2010
Start Date:  01/1986      End Date:  12/2010     (1990-2010)
Description:  This dataset provides estimates of forest carbon stocks and fluxes in the form of aboveground woody biomass (AGB) and net ecosystem productivity (NEP), as a function of the number of years since the most recent disturbance (i.e., stand age) for forests in the southeastern USA at a 30 m resolution for the benchmark years 1990, 2000, and 2010. The study area includes: Virginia, North Carolina, South Carolina, Georgia, and Florida. Estimates were derived from an inventory-constrained version of the Carnegie-Ames-Stanford Approach (CASA) carbon cycle process model that accounts for disturbance processes as a function of years since disturbance for each combination of forest type, site productivity, and pre-disturbance biomass. Also provided are the core CASA model data inputs including: the year of the most recent disturbance according to the North American Forest Dynamics (NAFD), the Aerial Detection Survey (ADS), and the Monitoring Trends in Burn Severity (MTBS) data products; the type of disturbance; biomass estimates from the year 2000 according to the National Biomass and Carbon Dataset (NBCD); forest type group; a site productivity classification; and the number of years since stand-replacing disturbance, which is akin to forest stand age.
Status:  Archived
CMS Science Theme(s):  Land Biomass; Land-Atmosphere Flux
Keywords:  
Spatial Extent:  Southeastern USA
Spatial Resolution:  30 m
Temporal Frequency:  annual data for selected years
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
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Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1728
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1728
Archived Data Citation:  Gu, H., C.A. Williams, N. Hasler, and Y. Zhou. 2019. Forest Carbon Stocks and Fluxes After Disturbance, Southeastern USA, 1990-2010. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1728

Bounding Coordinates:
West Longitude:-89.01000 East Longitude:-71.28000
North Latitude:40.89000 South Latitude:23.23000

Product Title:  NAFD-ATT Forest Canopy Cover Loss from Landsat, CONUS, 1986-2010
Start Date:  06/1986      End Date:  09/2010     (1986-2010)
Description:  Characterizing the cause of forest canopy changes through time is fundamental to understanding current and future forest functions. A better understanding of forest dynamics can help build linkages between patterns and processes. The North American Forest Dynamics (NAFD) products provided in this dataset predict characteristics related to the cause of forest canopy cover losses for the conterminous United States (CONUS) derived from Landsat images for the period 1986-2010. The characteristics are summarized in four separate data layers. The first layer labels the type of change event (stable-no change, removals, fire, stress, wind, conversion, other), the second labels the year of the event, the third and fourth layers measure dominance and diversity, measures of qualitative confidence metrics derived from the model predictions. For each pixel the maps depict the greatest magnitude event occurring between 1986-2010.
Status:  Archived
CMS Science Theme(s):  Land Biomass
Keywords:  
Spatial Extent:  CONUS
Spatial Resolution:  30 m
Temporal Frequency:  A composited single event layer combining all events 1986-2010
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
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Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1799
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1799
Archived Data Citation:  Schleeweis, K., G.G. Moisen, C. Toney, T.A. Schroeder, C. Huang, E.A. Freeman, S.N. Goward, and J.L. Dungan. 2020. NAFD-ATT Forest Canopy Cover Loss from Landsat, CONUS, 1986-2010. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1799

Bounding Coordinates:
West Longitude:-128.03000 East Longitude:-65.20000
North Latitude:51.68000 South Latitude:22.69000

Product Title:  Forest Carbon Stocks and Fluxes from the NFCMS, Conterminous USA, 1990-2010
Start Date:  01/1986      End Date:  12/2010     (1986-01-01 to 2010-12-31 (this period covers the input data))
Description:  This dataset, derived from the National Forest Carbon Monitoring System (NFCMS), provides estimates of forest carbon stocks and fluxes in the form of aboveground woody biomass (AGB), total live biomass, total ecosystem carbon, aboveground coarse woody debris (CWD), and net ecosystem productivity (NEP) as a function of the number of years since the most recent disturbance (i.e., stand age) for forests of the conterminous U.S. at a 30 m resolution for the benchmark years 1990, 2000, and 2010. The data were derived from an inventory-constrained version of the Carnegie-Ames-Stanford Approach (CASA) carbon cycle process model that accounts for disturbance processes for each combination of forest type, site productivity, and pre-disturbance biomass. Also provided are the core model data inputs including the year of the most recent disturbance according to the North American Forest Dynamics (NAFD) and the Monitoring Trends in Burn Severity (MTBS) data products; the type of disturbance; biomass estimates from the year 2000 according to the National Biomass and Carbon Dataset (NBCD); forest-type group; a site productivity classification; and the number of years since stand-replacing disturbance. The data are useful for a wide range of applications including monitoring and reporting recent dynamics of forest carbon across the conterminous U.S., assessment of recent trends with attribution to disturbance and regrowth drivers, conservation planning, and assessment of climate change mitigation opportunities within the forest sector.
Status:  Archived
CMS Science Theme(s):  Land Biomass; Land-Atmosphere Flux; MRV
Keywords:  Flux/Movement (; anthropogenic; ; atmospheric); ; Disturbance (agent; severity); ; Carbon Stocks (; terrestrial)
Spatial Extent:  Conterminous U.S. divided into nine regions
Spatial Resolution:  30 m
Temporal Frequency:  Annual data for the selected years of 1990, 2000, and 2010
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1829
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1829
Archived Data Citation:  Williams, C.A., N. Hasler, H. Gu, and Y. Zhou. 2020. Forest Carbon Stocks and Fluxes from the NFCMS, Conterminous USA, 1990-2010. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1829

Bounding Coordinates:
West Longitude:-127.69000 East Longitude:-65.73000
North Latitude:50.37000 South Latitude:23.19000

 
Publications: Fargione, J. E., Bassett, S., Boucher, T., Bridgham, S. D., Conant, R. T., Cook-Patton, S. C., Ellis, P. W., Falcucci, A., Fourqurean, J. W., Gopalakrishna, T., Gu, H., Henderson, B., Hurteau, M. D., Kroeger, K. D., Kroeger, T., Lark, T. J., Leavitt, S. M., Lomax, G., McDonald, R. I., Megonigal, J. P., Miteva, D. A., Richardson, C. J., Sanderman, J., Shoch, D., Spawn, S. A., Veldman, J. W., Williams, C. A., Woodbury, P. B., Zganjar, C., Baranski, M., Elias, P., Houghton, R. A., Landis, E., McGlynn, E., Schlesinger, W. H., Siikamaki, J. V., Sutton-Grier, A. E., Griscom, B. W. 2018. Natural climate solutions for the United States. Science Advances. 4(11). DOI: 10.1126/sciadv.aat1869

Gu, H., Williams, C. A., Hasler, N., Zhou, Y. 2019. The Carbon Balance of the Southeastern U.S. Forest Sector as Driven by Recent Disturbance Trends. Journal of Geophysical Research: Biogeosciences. 124(9), 2786-2803. DOI: 10.1029/2018JG004841

Keenan, T. F., Williams, C. A. 2018. The Terrestrial Carbon Sink. Annual Review of Environment and Resources. 43(1), 219-243. DOI: 10.1146/annurev-environ-102017-030204

Schleeweis, K. G., Moisen, G. G., Schroeder, T. A., Toney, C., Freeman, E. A., Goward, S. N., Huang, C., Dungan, J. L. 2020. US National Maps Attributing Forest Change: 1986-2010. Forests. 11(6), 653. DOI: 10.3390/f11060653

Williams, C. A., Gu, H., Jiao, T. 2021. Climate impacts of U.S. forest loss span net warming to net cooling. Science Advances. 7(7). DOI: 10.1126/sciadv.aax8859

Zhou, Y., Williams, C. A., Hasler, N., Gu, H., Kennedy, R. 2021. Beyond biomass to carbon fluxes: application and evaluation of a comprehensive forest carbon monitoring system. Environmental Research Letters. 16(5), 055026. DOI: 10.1088/1748-9326/abf06d

Gu, H., Williams, C. A., Ghimire, B., Zhao, F., Huang, C. 2016. High-resolution mapping of time since disturbance and forest carbon flux from remote sensing and inventory data to assess harvest, fire, and beetle disturbance legacies in the Pacific Northwest. Biogeosciences. 13(22), 6321-6337. DOI: 10.5194/bg-13-6321-2016

Williams, C. A., Gu, H., MacLean, R., Masek, J. G., Collatz, G. J. 2016. Disturbance and the carbon balance of US forests: A quantitative review of impacts from harvests, fires, insects, and droughts. Global and Planetary Change. 143, 66-80. DOI: 10.1016/j.gloplacha.2016.06.002

Archived Data Citations: Williams, C.A., N. Hasler, H. Gu, and Y. Zhou. 2020. Forest Carbon Stocks and Fluxes from the NFCMS, Conterminous USA, 1990-2010. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1829

Gu, H., C.A. Williams, N. Hasler, and Y. Zhou. 2019. Forest Carbon Stocks and Fluxes After Disturbance, Southeastern USA, 1990-2010. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1728

Schleeweis, K., G.G. Moisen, C. Toney, T.A. Schroeder, C. Huang, E.A. Freeman, S.N. Goward, and J.L. Dungan. 2020. NAFD-ATT Forest Canopy Cover Loss from Landsat, CONUS, 1986-2010. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1799

2015 NASA Carbon Cycle & Ecosystems Joint Science Workshop Poster(s)
  • Continental-Scale Carbon Budget Impacts of Forest Disturbances by Fires, Insects, and Harvests in the US: Mean, Variability, Uncertainty, and Trend   --   (Huan Gu, Christopher A Williams, George James Collatz, Jeffrey Masek, Bardan Ghimire, Gretchen Moisen)   [abstract]


 

Windham-Myers (CMS 2014) (2014)
Project Title:Linking Satellite and Soil Data to Validate Coastal Wetland 'Blue Carbon' Inventories: Upscaled Support for Developing MRV and REDD+ Protocols

Science Team
Members:

Lisamarie Windham-Myers, United States Geological Survey (Project Lead)
Kristin Byrd, USGS
James Holmquist, Smithsonian Environmental Research Center
Marc (Mac) Simard, Jet Propulsion Laboratory / Caltech

Solicitation:NASA: Carbon Monitoring System (2014)
Successor Projects: Holmquist (CMS 2018)  
Abstract: The NASA Carbon Monitoring System (CMS) is poised to fill a missing gap in blue carbon accounting by providing 1) a national-scale data framework to integrate and extrapolate field measurements that support national GHG inventory requirements, and 2) testing data needs for quantification of stock-based changes in coastal wetland sediments (soil) and vegetation for eventual REDD+ eligibility. We propose to develop a verifiable carbon (C) monitoring protocol appropriate for national policy and market interventions. Our approach is to refine Landsat-based land cover change data from NOAAs Coastal Change Analysis Program, with C-relevant attributes from finer scale NASA-derived spectral and RADAR data, as well as broadly available field-data from partner agencies. Synthesizing previously-collected data for 6 sentinel sites along representative coasts of the U.S., we will refine and validate an IPCC-relevant, temporally-explicit (1992-2011) accounting method for coastal wetland C stocks and annual fluxes. Our approach leverages a recent surge in research on the key processes that regulate soil C accumulation in tidal wetlands, which we propose can be captured at large spatial scales using remotely sensed data and GIS modeling. Net annual C flux into tidal wetland soils is largely a function of vertical accretion due to organic accumulation with sea level rise, or C losses due to oxidation and erosion. Dated soil cores (137Cs, 210Pb) provide quantification of C stocks and long-term rates of net C accretion or loss. The IPCC default value for soil C sequestration in tidal wetlands is 140 g/m2/yr, but rates in U.S. tidal wetlands range from 20-800 g C /m2/yr. The greatest uncertainty in current blue carbon inventory approaches arises from categorical upscaling, or distributing point data through the estuarine landscape. Both the updated USFWS National Wetland Inventory (NWI) and NOAAs Landsat-based C-CAP program provide current and historic national distributions of estuarine intertidal wetlands. As linked with USDA SSURGO dataset, the raster-based Landsat-derived C-CAP land cover maps will be used as the primary spatial dataset for tidal wetland distribution and initial estimates of U.S. coastal wetland GHG annual inventories. Field data provide both a) attributes in a land cover model (tide gauges, elevation) and b) validation datasets (soil cores, biomass, salinity, methane fluxes). While analyses are focused on 6 sites, these field-based data are broadly available across the U.S. through partner agencies such as NOAA, Smithsonian, NSF, EPA, USFWS, and Louisianas CRMS databases. One goal will be to determine the price of precision or extent to which finer habitat classifications (hydrology, salinity, sea-level rise) continue to inform C accounting with greater accuracy. Remotely-sensed data products will be derived from ongoing NASA Earth Observations, specifically Landsat, Aquarius, PRISM, ALOS-2, UAVSAR, and HICO. Where available, airborne datasets (AVIRIS, AirSWOT) may illustrate the value of future satellite missions (HyspIRI, SWOT) for wetland C accounting. This project will provide a fundamental data platform to aid the U.S. in quantifying emissions and removals in response to the IPCC Wetlands Supplement (2014) as requested to support the national report in 2017. We recognize that MRV in coastal wetlands will require both remote sensing and field-based data to hindcast and continue monitoring C emissions and removals. Critical products will include network building, data compilation, algorithm development, and MRV error analyses across a series of data-driven scales. Our intensive site validation supports testable indices for accurate C flux accounting, and thus meets several CMS goals such as 1) future application at continental scales, 2) model testing of key drivers of coastal C sequestration and 3) intercomparison and collaboration with associated NASA-supported coastal C cycling research and scenario testing.
Project Associations:
  • CMS
CMS Primary Theme:
  • Land Biomass
CMS Science Theme(s):
  • Land Biomass
  • Land-Atmosphere Flux
  • Land-Ocean Flux
  • Decision Support
  • MRV

Participants:

Kristin Byrd, USGS
Stephen (Steve) Crooks, Silvestrum Climate Associates
Rusty Feagin, Texas A&M University
James Holmquist, Smithsonian Environmental Research Center
Marc (Mac) Simard, Jet Propulsion Laboratory / Caltech
Ariana Sutton-Grier, UMD Earth System Science Interdisciplinary Center (ESSIC)
Lisamarie Windham-Myers, United States Geological Survey
Tom Wirth, Environmental Protection Agency

Project URL(s): None provided.
 
Data
Products:
Product Title:  Accounting methodology for coastal wetland carbon stocks and fluxes.
Time Period:  1992-2011
Description:  - Develop a verifiable IPCC-relevant, temporally-explicit coastal wetland carbon monitoring protocol appropriate for national policy and market interventions.
Status:  Planned
CMS Science Theme(s):  Land Biomass; Land-Atmosphere Flux; Land-Ocean Flux; MRV
Keywords:  Carbon Stocks (; inland & coastal water;; terrestrial); ; Flux/Movement (; terrestrial;; inland & coastal water;; oceanic;; atmospheric)
Spatial Extent:  CONUS
Spatial Resolution:  30 m
Temporal Frequency:  Once
Input Data Products:  Landsat-based land cover change data (NLCD) from NOAA's Coastal Change Analysis Program, LIDAR data, USFWS National Wetland Inventory, USDA Soil Survey Geographic Database (SSURGO), relevant tide gauges within regions
Algorithm/Models Used:  GIS modeling
Evaluation:  Field data provide both:; 1. attributes in a land cover model (tidal gauges, elevation); 2. validation datasets (soil cores, biomass, salinity, methane fluxes).
Intercomparison Efforts/Gaps:  30 m vs. 250 m (MODIS): comparison with Najjar synthesis (Rusty Feagin)to determine which attribute results in a large discrepancy
Uncertainty Estimates:  MRV error analyses that reduce uncertainty that arise from categorical upscaling, or distributing point data through the estuarine landscape.
Uncertainty Categories:  All: ensemble, deterministic, model-data comparison, model-model comparison, data-data comparison
Application Areas:  - MRV, REDD+; - GHG emissions inventory; - Watershed protection plans; - Land management
Relevant Policies/Programs:  REDD+, NGHGI, Global Methane Initiative of the US EPA, Blue Carbon Initiative, Coastal Wetland Planning, Protection, and Restoration Act, NOAA Habitat Restoration Monitoring
Potential Users:  EPA *Tom Wirth*, NOAA, USFWS, Louisiana Coastal Wetlands Conservation and Restoration Task Force, USDA, Council for Environmental Cooperation, voluntary and regulatory carbon markets
Stakeholders:  EPA (Point of Contact: Tom Wirth)
Current Application Readiness Level:  1
Start Application Readiness Level:  1
Target Application Readiness Level:  6
Future Developments:  
Limitations:  Existing data availability and quality
Date When Product Available:  Jul-16
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Estimates of coastal wetland carbon fluxes.
Time Period:  1992-2011
Description:  - Quantify coastal wetland carbon fluxes.
Status:  Planned
CMS Science Theme(s):  Land-Atmosphere Flux; Land-Ocean Flux; MRV
Keywords:  Flux/Movement (; terrestrial;; inland & coastal water;; oceanic;; atmospheric)
Spatial Extent:  6 sentinel sites along representative coasts of the U.S. (Pudget Sound, San Francisco Bay, Barataria coast of Louisiana, Everglades, Chesapeake Bay, Cape Cod)
Spatial Resolution:  30 m
Temporal Frequency:  Once
Input Data Products:  dated soil cores (137Cs, 210Pb), Landsat-based land cover change data from NOAA's Coastal Change Analysis Program, NASA-derived spectral and radar data (i.e. Landsat, Aquarius, PRISM, ALOS-2, UAVSAR, and HICO), NASA airborne datasets (i.e. AVIRIS, AirSWOT), USFWS National Wetland Inventory, USDA Soil Survey Geographic Database (SSURGO), broadly available field-data from partner agencies (i.e. NOAA, Smithsonian, National Science Foundation, EPA, USFWS, and Louisiana's Coastwide Reference Monitoring System (CRMS), LIDAR
Algorithm/Models Used:  Marsh Equilibrium Model (MEMO), developed by Jim Morris
Evaluation:  data scalar evaluation: stepwise regression approach to test if incorporation of finer details about temperature, salinity, etc. improves results)
Intercomparison Efforts/Gaps:  comparison with IPCC default values
Uncertainty Estimates:  MRV error analyses that reduce uncertainty that arise from categorical upscaling, or distributing point data through the estuarine landscape.
Uncertainty Categories:  All: ensemble, deterministic, model-data comparison, model-model comparison, data-data comparison
Application Areas:  - MRV, REDD+; - GHG emissions inventory; - Watershed protection plans; - Land management
Relevant Policies/Programs:  REDD+, NGHGI, Global Methane Initiative of the US EPA, Blue Carbon Initiative, Coastal Wetland Planning, Protection, and Restoration Act, NOAA Habitat Restoration Monitoring
Potential Users:  EPA *Tom Wirth*, NOAA, USFWS, Louisiana Coastal Wetlands Conservation and Restoration Task Force, USDA, Council for Environmental Cooperation, voluntary and regulatory carbon markets
Stakeholders:  
Current Application Readiness Level:  1
Start Application Readiness Level:  1
Target Application Readiness Level:  6
Future Developments:  
Limitations:  Existing data availability and quality
Date When Product Available:  Jul-17
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  MRV error analyses across a series of data-driven scales.
Time Period:  1992-2011
Description:  - Quantify uncertainties.; - Determine price of precision or extent to which finer habitat classifications (hydrology, salinity, sea-level rise) continue to inform carbon accounting with greater accuracy.
Status:  Planned
CMS Science Theme(s):  Land Biomass; Land-Atmosphere Flux; Land-Ocean Flux; MRV
Keywords:  Evaluation & User Interfaces
Spatial Extent:  6 sentinel sites along representative coasts of the U.S. (Pudget Sound, San Francisco Bay, Barataria coast of Louisiana, Everglades, Chesapeake Bay, Cape Cod)
Spatial Resolution:  30 m
Temporal Frequency:  Once
Input Data Products:  dated soil cores (137Cs, 210Pb), Landsat-based land cover change data from NOAA's Coastal Change Analysis Program, NASA-derived spectral and radar data (i.e. Landsat, Aquarius, PRISM, ALOS-2, UAVSAR, and HICO), NASA airborne datasets (i.e. AVIRIS, AirSWOT), USFWS National Wetland Inventory, USDA Soil Survey Geographic Database (SSURGO), broadly available field-data from partner agencies (i.e. NOAA, Smithsonian, National Science Foundation, EPA, USFWS, and Louisiana's Coastwide Reference Monitoring System (CRMS), LIDAR
Algorithm/Models Used:  Statistical software coupled with GIS
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  All: ensemble, deterministic, model-data comparison, model-model comparison, data-data comparison
Application Areas:  - MRV, REDD+; - GHG emissions inventory; - Watershed protection plans; - Land management
Relevant Policies/Programs:  REDD+, NGHGI, Global Methane Initiative of the US EPA, Blue Carbon Initiative, Coastal Wetland Planning, Protection, and Restoration Act, NOAA Habitat Restoration Monitoring
Potential Users:  EPA *Tom Wirth*, NOAA, USFWS, Louisiana Coastal Wetlands Conservation and Restoration Task Force, USDA, Council for Environmental Cooperation, voluntary and regulatory carbon markets
Stakeholders:  EPA (Point of Contact: Tom Wirth)
Current Application Readiness Level:  1
Start Application Readiness Level:  1
Target Application Readiness Level:  6
Future Developments:  
Limitations:  Existing data availability and quality
Date When Product Available:  Jul-17
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Accuracy and Precision of Tidal Wetland Soil Carbon Mapping in the Conterminous United States: Public Soil Carbon Data Release Version 1
Start Date:  01/1990      End Date:  12/2017     (1990-2017)
Description:  This product is a spatially explicit database totaling 1959 soil cores from 49 different studies across CONUS. The dataset was dominated by estuarine emergent wetlands (n = 1533), but also contained tidal palustrine emergent (n = 157), estuarine forested and scrub/shrub (n = 46), and tidal palustrine forested and scrub/shrub (n = 87). 134 cores did not have enough accompanying meta-data for us to make this distinction. The empirical dataset was spatially representative with 18 of the 22 coastal CONUS states included. Variables reported include, site location, sampling methodology, soil bulk density, soil organic matter fraction, soil carbon fraction and dominant vegetation at sampling site.
Status:  Archived
CMS Science Theme(s):  Land Biomass; MRV
Keywords:  coastal carbon; wetlands
Spatial Extent:  CONUS
Spatial Resolution:  
Temporal Frequency:  collection of individual studies
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  EPA (Point of Contact: Tom Wirth)
Current Application Readiness Level:  8
Start Application Readiness Level:  1
Target Application Readiness Level:  9
Future Developments:  
Limitations:  
Date When Product Available:  June 2018
Assigned Data Center:  Smithsonian Institution CCRCN
Metadata URL(s):

https://repository.si.edu/handle/10088/35684
Data Server URL(s):

https://repository.si.edu/handle/10088/35684
Archived Data Citation:  James R Holmquist, Windham-Myers, Lisamarie, Bliss, Norman, Crooks, Stephen, Morris, James T, Megonigal, J Patrick, Troxler, Tiffany, Weller, Donald, Callaway, John, Drexler, Judith, Ferner, Matthew C, Gonneea, Meagan E, Kroeger, Kevin D, Schile-Beers, Lisa, Woo, Isa, Buffington, Kevin, Boyd, Brandon M, Breithaupt, Joshua, Brown, Lauren N, Dix, Nicole, Hice, Lyndie, Horton, Benjamin P, MacDonald, Glen M, Moyer, Ryan P, Reay, William, Shaw, Timothy, Smith, Erik, Smoak, Joseph M, Sommerfield, Christopher, Thorne, Karen, Velinsky, David, Watson, Elizabeth, Wilson Grimes, Kristen, Woodrey, Mark. (2018). [Dataset:] Accuracy and Precision of Tidal Wetland Soil Carbon Mapping in the Conterminous United States: Public Soil Carbon Data Release Version 1. Smithsonian Institution. DOI: 10.25572/ccrcn/10088/35684. [Date Accessed].

Bounding Coordinates:
West Longitude:-124.00000 East Longitude:-69.87000
North Latitude:47.97000 South Latitude:24.17000

Product Title:  Green Vegetation Fraction High-Resolution Maps for Selected US Tidal Marshes, 2015
Start Date:  09/2013      End Date:  08/2015     (2013-2015)
Description:  This dataset provides 30m resolution maps of the fraction of green vegetation within tidal marshes for six estuarine regions of the conterminous United States: Cape Cod, MA; Chesapeake Bay, MD; Everglades, FL; Mississippi Delta, LA; San Francisco Bay, CA; and Puget Sound, WA. Maps were derived from a 1m classification of 2013 to 2015 National Agriculture Imagery Program (NAIP) images as tidal marsh green vegetation, non-vegetation, and open water. Using this high-resolution map, the percent of each class within Landsat pixel extents was calculated to produce a 30m fraction of green vegetation map for each region.
Status:  Archived
CMS Science Theme(s):  Land Biomass
Keywords:  
Spatial Extent:  
Spatial Resolution:  30 x 30 m pixels
Temporal Frequency:  one time sampling for each site
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  1
Start Application Readiness Level:  1
Target Application Readiness Level:  6
Future Developments:  
Limitations:  
Date When Product Available:  December 2018
Assigned Data Center:  ORNL DAAC
Metadata URL(s):
doi.org/10.3334/ORNLDAAC/1608
Data Server URL(s):
doi.org/10.3334/ORNLDAAC/1608
Archived Data Citation:  Ballanti, L., and K.B. Byrd. 2018. Green Vegetation Fraction High-Resolution Maps for Selected US Tidal Marshes, 2015. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1608

Bounding Coordinates:
West Longitude:-122.75000 East Longitude:-69.93000
North Latitude:47.12000 South Latitude:25.08000

Product Title:  Vegetation and Open Water High-Resolution Maps for Selected US Tidal Marshes, 2015
Start Date:  09/2013      End Date:  08/2015     (2013-2015)
Description:  This dataset provides maps of tidal marsh green vegetation, non-vegetation, and open water for six estuarine regions of the conterminous United States: Cape Cod, MA; Chesapeake Bay, MD, Everglades, FL; Mississippi Delta, LA; San Francisco Bay, CA; and Puget Sound, WA. Maps were derived from current National Agriculture Imagery Program data (2013-2015) using object-based classification for estuarine and palustrine emergent tidal marshes as indicated by a modified NOAA Coastal Change Analysis Program (C-CAP) map. These 1m resolution maps were used to calculate the fraction of green vegetation within 30m Landsat pixels for the same tidal marsh regions and these data are provided in a related dataset.
Status:  Archived
CMS Science Theme(s):  Land Biomass
Keywords:  
Spatial Extent:  
Spatial Resolution:  1m resolution of veg greeness 30 m resolution of site boundaries
Temporal Frequency:  one time sampling per site
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  1
Start Application Readiness Level:  1
Target Application Readiness Level:  6
Future Developments:  
Limitations:  
Date When Product Available:  December 2018
Assigned Data Center:  ORNL DAAC
Metadata URL(s):
doi.org/10.3334/ORNLDAAC/1609
Data Server URL(s):
doi.org/10.3334/ORNLDAAC/1609
Archived Data Citation:  Ballanti, L., and K.B. Byrd. 2018. Vegetation and Open Water High-Resolution Maps for Selected US Tidal Marshes, 2015. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1609

Bounding Coordinates:
West Longitude:-122.73000 East Longitude:-69.93000
North Latitude:47.12000 South Latitude:24.92000

Product Title:  Tidal Wetland Soil Carbon Stocks for the Conterminous United States, 2006-2010
Start Date:  01/2006      End Date:  12/2010     (2006 through 2010)
Description:  This dataset provides modeled estimates of soil carbon stocks for tidal wetland areas of the Conterminous United States (CONUS) for the period 2006-2010. Wetland areas were determined using both 2006-2010 Coastal Change Analysis Program (C-CAP) raster maps and the National Wetlands Inventory (NWI) vector data. All 30 x 30-meter C-CAP pixels were extracted that are coded as estuarine emergent, scrub/shrub, or forested in either 2006 or 2010. A soil database for model fitting and validation was compiled from 49 different studies with spatially explicit empirical depth profile data and associated metadata, totaling 1,959 soil cores from 18 of the 22 coastal states. Reported estimates of carbon stocks were derived with modeling approaches that included (1) applying a single average carbon stock value from the compiled soil core data, (2) applying models fit using the empirical data and applied spatially using soil, vegetation and salinity maps, (3) relying on independently generated soil carbon maps from The United States Department of Agriculture (USDA)'s Soil Survey Geographic Database (SSURGO), and the NWI that intersected with mapped tidal wetlands, and (4) using a version of SSURGO bias-corrected for bulk density. Comparisons of uncertainty, precision, and accuracy among these four approaches are also provided.
Status:  Archived
CMS Science Theme(s):  Land Biomass; MRV
Keywords:  Carbon Stocks (; inland & coastal water;; terrestrial)
Spatial Extent:  Tidal wetlands of the conterminous United States
Spatial Resolution:  30-m
Temporal Frequency:  One-time estimate
Input Data Products:  20062010 Coastal Change Analysis Program (C-CAP) raster maps; National Wetlands Inventory (NWI) vector data; Soil maps from SSURGO
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  For models fit using a randomized subset of the empirical data, uncertainty was quantified in two phases, a validation stage in which we tested uncertainty in the model, and an application phase in which uncertainty was tested in the final mapped product. See Holmquist et al. (2018) for additional details.
Uncertainty Categories:  
Application Areas:  carbon accounting purposes
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  EPA (Point of Contact: Tom Wirth)
Current Application Readiness Level:  8
Start Application Readiness Level:  1
Target Application Readiness Level:  9
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1612
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1612
Archived Data Citation:  Holmquist, J.R., L. Windham-Myers, N. Bliss, S. Crooks, J.T. Morris, P.J. Megonigal, T. Troxler, D. Weller, J. Callaway, J. Drexler, M.C. Ferner, M.E. Gonneea, K. Kroeger, L. Schile-beers, I. Woo, K. Buffington, B.M. Boyd, J. Breithaupt, L.N. Brown, N. Dix, L. Hice, B.P. Horton, G.M. Macdonald, R.P. Moyer, W. Reay, T. Shaw, E. Smith, J.M. Smoak, C. Sommerfield, K. Thorne, D. Velinsky, E. Watson, K. Grimes, and M. Woodrey. 2019. Tidal Wetland Soil Carbon Stocks for the Conterminous United States, 2006-2010. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1612

Bounding Coordinates:
West Longitude:-127.97000 East Longitude:-65.27000
North Latitude:48.24000 South Latitude:22.73000

Product Title:  Tidal Wetlands Soil Organic Carbon and Estuarine Characteristics, USA, 1972-2015
Start Date:  01/1972      End Date:  12/2015     (annual estimates)
Description:  This dataset provides a synthesis of soil organic carbon (SOC) estimates and a variety of other environmental information from tidal wetlands within estuaries in the conterminous United States for the period 1972-2015. The data were compiled from several existing data resources and include the following: soil organic carbon stock estimates, the proportion of the catchment area containing the wetlands that is barren, tidal wetland area, nontidal wetland land, open water, saltwater zone, mixed zone, agricultural, urban, forest, and wetland areas, land elevation, ocean salinity, sea surface temperature, ocean dissolved inorganic phosphorus, estuary latitude, longitude, depth, perimeter, salinity, and estuary volume, river flow, carbon, nitrogen, and phosphorus river flux, sediment organic carbon content, windspeed, mean temperature, daily and mean precipitation, frost days, and the population within each catchment. Estuaries were also classified to one of six typological categories. Coastal locations were determined by natural environmental and political divisions within the US. The data were used to investigate how tidal wetland soil organic carbon density is distributed across the continental US among various coastal locations, estuarine typologies, vegetation types, water regimes, and management regimes, and to identify whether SOC density is correlated with different environmental variables. The analytical results are not included with this dataset.
Status:  Archived
CMS Science Theme(s):  Land Biomass; MRV
Keywords:  Carbon Stocks (; inland & coastal water;; terrestrial)
Spatial Extent:  Estuaries and coastal areas in the Continental US
Spatial Resolution:  varied
Temporal Frequency:  annual
Input Data Products:  dated soil cores (137Cs, 210Pb), Landsat-based land cover change data from NOAA's Coastal Change Analysis Program, NASA-derived spectral and radar data (i.e. Landsat, Aquarius, PRISM, ALOS-2, UAVSAR, and HICO), NASA airborne datasets (i.e. AVIRIS, AirSWOT), USFWS National Wetland Inventory, USDA Soil Survey Geographic Database (SSURGO), broadly available field-data from partner agencies (i.e. NOAA, Smithsonian, National Science Foundation, EPA, USFWS, and Louisiana's Coastwide Reference Monitoring System (CRMS), LIDAR
Algorithm/Models Used:  GIS modeling that have at least one model based on SSURGO (Bliss, 2003 model)
Evaluation:  data scalar evaluation: stepwise regression approach to test if incorporation of finer details about temperature, salinity, etc. improves results)
Intercomparison Efforts/Gaps:  30 m vs. 250 m (MODIS): comparison with Najjar synthesis (Rusty Feagin)to determine which attribute results in a large discrepancy
Uncertainty Estimates:  MRV error analyses that reduce uncertainty that arise from categorical upscaling, or distributing point data through the estuarine landscape.
Uncertainty Categories:  All: ensemble, deterministic, model-data comparison, model-model comparison, data-data comparison
Application Areas:  - MRV, REDD+; - GHG emissions inventory; - Watershed protection plans; - Land management
Relevant Policies/Programs:  REDD+, NGHGI, Global Methane Initiative of the US EPA, Blue Carbon Initiative, Coastal Wetland Planning, Protection, and Restoration Act, NOAA Habitat Restoration Monitoring
Potential Users:  EPA *Tom Wirth*, NOAA, USFWS, Louisiana Coastal Wetlands Conservation and Restoration Task Force, USDA, Council for Environmental Cooperation, voluntary and regulatory carbon markets
Stakeholders:  
Current Application Readiness Level:  6
Start Application Readiness Level:  1
Target Application Readiness Level:  6
Future Developments:  
Limitations:  Existing data availability and quality
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1742
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1742
Archived Data Citation:  Hinson, A.L., R.A. Feagin, and M. Eriksson. 2019. Tidal Wetlands Soil Organic Carbon and Estuarine Characteristics, USA, 1972-2015. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1742

Bounding Coordinates:
West Longitude:-124.39000 East Longitude:-67.05000
North Latitude:47.82000 South Latitude:25.19000

Product Title:  Coastal Wetland Elevation and Carbon Flux Inventory with Uncertainty, USA, 2006-2011
Start Date:  01/2006      End Date:  12/2011     (2006-2011)
Description:  This dataset provides maps of coastal wetland carbon and methane fluxes and coastal wetland surface elevation from 2006 to 2011 at 30 m resolution for coastal wetlands of the conterminous United States. Total coastal wetland carbon flux per year per pixel was calculated by combining maps of wetland type and change with soil, biomass, and methane flux data from a literature review. Uncertainty in carbon flux was estimated from 10,000 iterations of a Monte Carlo analysis. In addition to the uncertainty analysis, this dataset also provides a probabilistic map of the extent of tidal elevation, as well as the geospatial files used to create that surface, and a land cover and land cover change map of the coastal zone from 2006 to 2011 with accompanying estimated median soil, biomass, methane, and total CO2 equivalent annual fluxes, each with reported 95% confidence intervals, at 30 m resolution. Land cover was quantified using the Coastal Change Analysis Program (C-CAP), a Landsat-based land cover mapping product.
Status:  Archived
CMS Science Theme(s):  Land Biomass; Land-Atmosphere Flux
Keywords:  
Spatial Extent:  Oceanic coastal regions of the Continental United States
Spatial Resolution:  30 m (300 m for tide gauge datum transformation and uncertainty layers)
Temporal Frequency:  annual
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  EPA (Point of Contact: Tom Wirth)
Current Application Readiness Level:  8
Start Application Readiness Level:  1
Target Application Readiness Level:  9
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1650
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1650
Archived Data Citation:  Holmquist, J.R., L. Windham-Myers, B. Bernal, K.B. Byrd, S. Crooks, M.E. Gonneea, N. Herold, S.H. Knox, K. Kroeger, J. Mccombs, P.J. Megonigal, L. Meng, J.T. Morris, A.E. Sutton-grier, T. Troxler, and D. Weller. 2019. Coastal Wetland Elevation and Carbon Flux Inventory with Uncertainty, USA, 2006-2011. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1650

Bounding Coordinates:
West Longitude:-135.03000 East Longitude:-56.66000
North Latitude:48.99000 South Latitude:20.38000

Product Title:  Gross Primary Production Maps of Tidal Wetlands across Conterminous USA, 2000-2019
Start Date:  03/2000      End Date:  11/2019     (2000-2019)
Description:  This dataset provides mapped tidal wetland gross primary production (GPP) estimates (g C/m2/day) derived from multiple wetland types at 250-m resolution across the conterminous United States at 16-day intervals from March 5, 2000, through November 17, 2019. GPP was derived with the spatially explicit Blue Carbon (BC) model, which combined tidal wetland cover and field-based eddy covariance (EC) tower GPP data into a single Bayesian framework along with Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) datasets. Tidal wetlands are a critical component of global climate regulation. Tidal wetland-based carbon, or "blue carbon," is a valued resource that is increasingly important for restoration and conservation purposes.
Status:  Archived
CMS Science Theme(s):  Land Biomass
Keywords:  
Spatial Extent:  Tidal wetlands across the conterminous United States
Spatial Resolution:  250 m
Temporal Frequency:  16-day interval
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  6
Start Application Readiness Level:  1
Target Application Readiness Level:  9
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1792
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1792
Archived Data Citation:  Feagin, R.A., I. Forbrich, T.P. Huff, J.G. Barr, J. Ruiz-plancarte, J.D Fuentes, R.G. Najjar, R. Vargas, A. Vazquez-lule, L. Windham-Myers, K. Kroeger, E.J. Ward, G.W. Moore, M. Leclerc, K.W. Krauss, C.L. Stagg, M. Alber, S.H. Knox, K.V.R. Schafer, T.S. Bianchi, J.A. Hutchings, H.B. Nahrawi, A. Noormets, B. Mitra, A. Jaimes, A.L. Hinson, B. Bergamaschi, J. King, and G. Miao. 2020. Gross Primary Production Maps of Tidal Wetlands across Conterminous USA, 2000-2019. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1792

Bounding Coordinates:
West Longitude:-128.03000 East Longitude:-65.90000
North Latitude:47.70000 South Latitude:23.50000

Product Title:  Digital Elevation Models for the Global Change Research Wetland, Maryland, USA, 2016
Start Date:  06/2016      End Date:  08/2016     (2016)
Description:  This dataset contains four alternative digital elevation models (DEMs) at 1 m resolution and model performance statistical metrics for the Global Change Research Wetland (GCReW) site on the Rhode River, a tributary of the Chesapeake Bay in Maryland, USA, for the year 2016. Three DEMs were created by using different strategies for correcting positive biases in Light Detection and Ranging (LiDAR)-based DEMs that are common in tidal wetlands. These included (1) applying a single average offset based on a literature review, (2) using the LiDAR Elevation Correction with NDVI (LEAN)-method, and (3) applying plant community-specific offsets using a local vegetation cover map. Existing LiDAR data at 1 m resolution collected in 2011 was the basis for these DEMs. The fourth DEM was created by using Empirical Bayesian Kriging to extrapolate between measured ground points. The elevation is provided in meters relative to the North American Vertical Datum of 1988 (NAVD 88). To calibrate the four approaches, the elevation of the entire marsh complex was surveyed at 20 m x 20 m resolution to document the distribution of elevation relative to tidal datums from a single year. Two Trimble R8 real-time kinematic (RTK) GPS receivers were used to survey 525 points over the complex from July 26, 2016, to August 15, 2016. Relative plant cover was also documented. Tidal datums were calculated from the nearby Annapolis, MD tidal gauge located 13 km from GCReW.
Status:  Archived
CMS Science Theme(s):  Lake Biomass
Keywords:  
Spatial Extent:  The Rhode River wetland, a tributary of the Chesapeake Bay, Maryland, USA
Spatial Resolution:  1 meter
Temporal Frequency:  One-time measurements in the year 2016
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  
Current Application Readiness Level:  6
Start Application Readiness Level:  1
Target Application Readiness Level:  6
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1793
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1793
Archived Data Citation:  Holmquist, J.R., J. Riera, J.P. Megonigal, L. Schile-beers, K.J. Buffington, and D.E. Weller. 2021. Digital Elevation Models for the Global Change Research Wetland, Maryland, USA, 2016. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1793

Bounding Coordinates:
West Longitude:-76.55000 East Longitude:-76.54000
North Latitude:38.88000 South Latitude:38.87000

Product Title:  Aboveground Biomass High-Resolution Maps for Selected US Tidal Marshes, 2015
Start Date:  08/2015      End Date:  09/2015     (One-time estimate. in 2015)
Description:  This dataset provides maps of aboveground tidal marsh biomass (g/m2) at 30 m resolution for six estuarine regions of the conterminous United States: Cape Cod, MA; Chesapeake Bay, MD, Everglades, FL; Mississippi Delta, LA; San Francisco Bay, CA; and Puget Sound, WA. Estuarine and palustrine emergent tidal marsh areas were based on a 2010 NOAA Coastal Change Analysis Program (C-CAP) map. Aboveground biomass maps were generated from a random forest model driven by Landsat vegetation indices and a national scale dataset of field-measured aboveground biomass. The final model, driven by six Landsat vegetation indices, with the soil adjusted vegetation index as the most important, successfully predicted biomass for a range of marsh plant functional types defined by height, leaf angle, and growth form. Biomass can be converted to carbon stocks using a mean plant carbon content of 44.1%.
Status:  Archived
CMS Science Theme(s):  Land Biomass
Keywords:  
Spatial Extent:  Six estuarine study regions across the conterminous US.
Spatial Resolution:  30 m
Temporal Frequency:  One-time estimate.
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  EPA (Point of Contact: Tom Wirth)
Current Application Readiness Level:  8
Start Application Readiness Level:  1
Target Application Readiness Level:  9
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1879
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1879
Archived Data Citation:  Byrd, K.B., L. Ballanti, N. Thomas, D. Nguyen, J.R. Holmquist, M. Simard, and L. Windham-Myers. 2021. Aboveground Biomass High-Resolution Maps for Selected US Tidal Marshes, 2015. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1879

Bounding Coordinates:
West Longitude:-122.73000 East Longitude:-69.93000
North Latitude:47.12000 South Latitude:25.09000

Product Title:  Relative Tidal Marsh Elevation Maps with Uncertainty for Conterminous USA, 2010
Start Date:  01/1983      End Date:  12/2010     (1983-2010 for mapsof tidal amplitude, 2010 for elevation maps)
Description:  This dataset provides maps of the elevation of coastal wetlands relative to tidal ranges for the conterminous United States (CONUS) at 30 m resolution for 2010. It also includes maps of tidal amplitude, relative sea-level rise for the period 1983-2001, and maps for coastal lands and low marsh areas based on the probability of being below the mean higher high tide water line for spring tides (MHHWS). Uncertainty layers for elevation maps are also provided.
Status:  Archived
CMS Science Theme(s):  Land Biomass
Keywords:  
Spatial Extent:  Coastal areas of the conterminous United State
Spatial Resolution:  30 m
Temporal Frequency:  decadal
Input Data Products:  
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  
Relevant Policies/Programs:  
Potential Users:  
Stakeholders:  EPA (Point of Contact: Tom Wirth)
Current Application Readiness Level:  8
Start Application Readiness Level:  1
Target Application Readiness Level:  9
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1844
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1844
Archived Data Citation:  Holmquist, J.R., and L. Windham-Myers. 2021. Relative Tidal Marsh Elevation Maps with Uncertainty for Conterminous USA, 2010. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1844

Bounding Coordinates:
West Longitude:-134.67000 East Longitude:-56.85000
North Latitude:48.27000 South Latitude:20.57000

 
Publications: Byrd, K. B., Ballanti, L., Thomas, N., Nguyen, D., Holmquist, J. R., Simard, M., Windham-Myers, L. 2018. A remote sensing-based model of tidal marsh aboveground carbon stocks for the conterminous United States. ISPRS Journal of Photogrammetry and Remote Sensing. 139, 255-271. DOI: 10.1016/j.isprsjprs.2018.03.019

EPA, 2017. Inventory of US greenhouse gas emissions and sinks: 1990-2015. Environmental Protection Agency. https://www.epa.gov/ghgemissions/inventory-us-greenhouse-gas-emissions-and-sinks-1990-2015. Chapter 6. Land Use, Land-Use Change, and Forestry

Hinson, A. L., Feagin, R. A., Eriksson, M. 2019. Environmental Controls on the Distribution of Tidal Wetland Soil Organic Carbon in the Continental United States. Global Biogeochemical Cycles. 33(11), 1408-1422. DOI: 10.1029/2019GB006179

Hinson, A. L., Feagin, R. A., Eriksson, M., Najjar, R. G., Herrmann, M., Bianchi, T. S., Kemp, M., Hutchings, J. A., Crooks, S., Boutton, T. 2017. The spatial distribution of soil organic carbon in tidal wetland soils of the continental United States. Global Change Biology. 23(12), 5468-5480. DOI: 10.1111/gcb.13811

Holmquist, J. R., Windham-Myers, L. 2022. A Conterminous USA-Scale Map of Relative Tidal Marsh Elevation. Estuaries and Coasts. DOI: 10.1007/s12237-021-01027-9

Holmquist, J. R., Windham-Myers, L., Bernal, B., Byrd, K. B., Crooks, S., Gonneea, M. E., Herold, N., Knox, S. H., Kroeger, K. D., McCombs, J., Megonigal, J. P., Lu, M., Morris, J. T., Sutton-Grier, A. E., Troxler, T. G., Weller, D. E. 2018. Uncertainty in United States coastal wetland greenhouse gas inventorying. Environmental Research Letters. 13(11), 115005. DOI: 10.1088/1748-9326/aae157

Holmquist, J. R., Windham-Myers, L., Bliss, N., Crooks, S., Morris, J. T., Megonigal, J. P., Troxler, T., Weller, D., Callaway, J., Drexler, J., Ferner, M. C., Gonneea, M. E., Kroeger, K. D., Schile-Beers, L., Woo, I., Buffington, K., Breithaupt, J., Boyd, B. M., Brown, L. N., Dix, N., Hice, L., Horton, B. P., MacDonald, G. M., Moyer, R. P., Reay, W., Shaw, T., Smith, E., Smoak, J. M., Sommerfield, C., Thorne, K., Velinsky, D., Watson, E., Grimes, K. W., Woodrey, M. 2018. Accuracy and Precision of Tidal Wetland Soil Carbon Mapping in the Conterminous United States. Scientific Reports. 8(1). DOI: 10.1038/s41598-018-26948-7

Rogers, K., Kelleway, J. J., Saintilan, N., Megonigal, J. P., Adams, J. B., Holmquist, J. R., Lu, M., Schile-Beers, L., Zawadzki, A., Mazumder, D., Woodroffe, C. D. 2019. Wetland carbon storage controlled by millennial-scale variation in relative sea-level rise. Nature. 567(7746), 91-95. DOI: 10.1038/s41586-019-0951-7

Thomas, N., Simard, M., Castaneda-Moya, E., Byrd, K., Windham-Myers, L., Bevington, A., Twilley, R. R. 2019. High-resolution mapping of biomass and distribution of marsh and forested wetlands in southeastern coastal Louisiana. International Journal of Applied Earth Observation and Geoinformation. 80, 257-267. DOI: 10.1016/j.jag.2019.03.013

Windham-Myers, L., T. Troxler, and S. Crooks (eds) (2018) A Blue Carbon Primer: The State of Coastal Wetland Carbon Science, Practice and Policy. 352pp. CRC Press, Taylor and Francis Group: Boca Raton, FL ISBN-13: 978-1498769099

Morris, J. T., Barber, D. C., Callaway, J. C., Chambers, R., Hagen, S. C., Hopkinson, C. S., Johnson, B. J., Megonigal, P., Neubauer, S. C., Troxler, T., Wigand, C. 2016. Contributions of organic and inorganic matter to sediment volume and accretion in tidal wetlands at steady state. Earth's Future. 4(4), 110-121. DOI: 10.1002/2015EF000334

Archived Data Citations: Hinson, A.L., R.A. Feagin, and M. Eriksson. 2019. Tidal Wetlands Soil Organic Carbon and Estuarine Characteristics, USA, 1972-2015. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1742

James R Holmquist, Windham-Myers, Lisamarie, Bliss, Norman, Crooks, Stephen, Morris, James T, Megonigal, J Patrick, Troxler, Tiffany, Weller, Donald, Callaway, John, Drexler, Judith, Ferner, Matthew C, Gonneea, Meagan E, Kroeger, Kevin D, Schile-Beers, Lisa, Woo, Isa, Buffington, Kevin, Boyd, Brandon M, Breithaupt, Joshua, Brown, Lauren N, Dix, Nicole, Hice, Lyndie, Horton, Benjamin P, MacDonald, Glen M, Moyer, Ryan P, Reay, William, Shaw, Timothy, Smith, Erik, Smoak, Joseph M, Sommerfield, Christopher, Thorne, Karen, Velinsky, David, Watson, Elizabeth, Wilson Grimes, Kristen, Woodrey, Mark. (2018). [Dataset:] Accuracy and Precision of Tidal Wetland Soil Carbon Mapping in the Conterminous United States: Public Soil Carbon Data Release Version 1. Smithsonian Institution. DOI: 10.25572/ccrcn/10088/35684. [Date Accessed].

Ballanti, L., and K.B. Byrd. 2018. Green Vegetation Fraction High-Resolution Maps for Selected US Tidal Marshes, 2015. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1608

Ballanti, L., and K.B. Byrd. 2018. Vegetation and Open Water High-Resolution Maps for Selected US Tidal Marshes, 2015. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1609

Holmquist, J.R., L. Windham-Myers, N. Bliss, S. Crooks, J.T. Morris, P.J. Megonigal, T. Troxler, D. Weller, J. Callaway, J. Drexler, M.C. Ferner, M.E. Gonneea, K. Kroeger, L. Schile-beers, I. Woo, K. Buffington, B.M. Boyd, J. Breithaupt, L.N. Brown, N. Dix, L. Hice, B.P. Horton, G.M. Macdonald, R.P. Moyer, W. Reay, T. Shaw, E. Smith, J.M. Smoak, C. Sommerfield, K. Thorne, D. Velinsky, E. Watson, K. Grimes, and M. Woodrey. 2019. Tidal Wetland Soil Carbon Stocks for the Conterminous United States, 2006-2010. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1612

Holmquist, J.R., L. Windham-Myers, B. Bernal, K.B. Byrd, S. Crooks, M.E. Gonneea, N. Herold, S.H. Knox, K. Kroeger, J. Mccombs, P.J. Megonigal, L. Meng, J.T. Morris, A.E. Sutton-grier, T. Troxler, and D. Weller. 2019. Coastal Wetland Elevation and Carbon Flux Inventory with Uncertainty, USA, 2006-2011. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1650

Holmquist, J.R., J. Riera, J.P. Megonigal, L. Schile-beers, K.J. Buffington, and D.E. Weller. 2021. Digital Elevation Models for the Global Change Research Wetland, Maryland, USA, 2016. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1793

Feagin, R.A., I. Forbrich, T.P. Huff, J.G. Barr, J. Ruiz-plancarte, J.D Fuentes, R.G. Najjar, R. Vargas, A. Vazquez-lule, L. Windham-Myers, K. Kroeger, E.J. Ward, G.W. Moore, M. Leclerc, K.W. Krauss, C.L. Stagg, M. Alber, S.H. Knox, K.V.R. Schafer, T.S. Bianchi, J.A. Hutchings, H.B. Nahrawi, A. Noormets, B. Mitra, A. Jaimes, A.L. Hinson, B. Bergamaschi, J. King, and G. Miao. 2020. Gross Primary Production Maps of Tidal Wetlands across Conterminous USA, 2000-2019. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1792

Byrd, K.B., L. Ballanti, N. Thomas, D. Nguyen, J.R. Holmquist, M. Simard, and L. Windham-Myers. 2021. Aboveground Biomass High-Resolution Maps for Selected US Tidal Marshes, 2015. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1879

Holmquist, J.R., and L. Windham-Myers. 2021. Relative Tidal Marsh Elevation Maps with Uncertainty for Conterminous USA, 2010. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1844

2015 NASA Carbon Cycle & Ecosystems Joint Science Workshop Poster(s)
  • Developing Policy-Relevant 'Blue Carbon' Protocols for Monitoring and Verification - Linking soil and satellite data to reduce uncertainty in coastal wetland carbon storage fluxes for national GHG inventories and market incentives   --   (Lisamarie Windham-Myers, Brian Bergamaschi, Judith Drexler, Kristin Byrd, Matthew Ferner, Patrick J. Megonigal, Lisa Schile, Donald Weller, Kevin Kroeger, Stephen Crooks, James Morris, Ariana Sutton-Grier, John Callaway, Marc Simard, Isa Woo, John Takekawa, Rusty A Feagin, Tiffany Troxler)   [abstract]   [poster]
  • Spatial quantification of blue carbon at landscape and continental scales   --   (Rusty A Feagin, R Wasantha Kulawardhana, Audra L Hinson, Sorin C Popescu, Thomas S Bianchi, Kevin M Yeager, Raymond G Najjar, Kevin D Kroeger, Lisa Windham-Myers)   [abstract]   [poster]
5th NACP All-Investigators Meeting Posters (2015):
  • Spatial quantification of blue carbon at landscape and continental scales -- (Rusty A Feagin, R Wasantha Kulawardhana, Audra L Hinson, Sorin C Popescu, Thomas S Bianchi, Kevin M Yeager, Raymond G Najjar, Kevin D Kroeger, Lisamarie Windham-Myers) [abstract]   [poster]