CMS Phase 2 (2012 Selection) Projects


 

Andrews (CMS 2011) (2012)
Project Title:North American Regional-Scale Flux Estimation and Observing System Design for the NASA Carbon Monitoring System

Science Team
Members:

Arlyn Andrews, NOAA Earth System Research Laboratory (Project Lead)

Solicitation:NASA: Carbon Monitoring System (2011)
Successor Projects: Andrews (CMS 2014)  
Abstract: We propose to apply a high-resolution regional inverse modeling framework to quantify CO2 fluxes that are optimally consistent with surface, aircraft, and satellite data, both current and planned. We will develop objective metrics for weighting the data and use a Lagrangian atmospheric transport model to compute a library of footprints corresponding to the various sources of CO2 observations. We will investigate consistency among the available datasets, taking into account uncertainties caused by satellite retrieval errors and model inadequacies, such as errors in simulated atmospheric transport and structural and numerical limitations of current inversion approaches (particularly when applied to the large volume of satellite data). This work fosters collaboration between Federal agencies, academia, and private industry engaged in greenhouse gas research and monitoring and leverages multiple NASA- and USGCRP-funded efforts to obtain measurements of atmospheric CO2 and develop regional-scale inverse modeling tools for quantifying carbon dioxide fluxes and their uncertainties. The proposed work will inform the development of the NASA Carbon Monitoring System (CMS) Flux Product, in particular regarding strategies for incorporating diverse CO2 observations and quantifying fluxes at policy-relevant scales. The proposed data products will be directly useful for evaluating the current CMS Flux Product.
Project Associations:
  • CMS
CMS Primary Theme:
  • Land-Atmosphere Flux
CMS Science Theme(s):
  • Atmospheric Transport
  • Land-Atmosphere Flux

Participants:

Arlyn Andrews, NOAA Earth System Research Laboratory
Seungbum (Sab) Kim, JPL
Anna Michalak, Carnegie Institution for Science
Christopher (Chris) O'Dell, Colorado State University

Project URL(s): None provided.
 
Data
Products:
Product Title:  Estimated CO2 profiles corresponding to GOSAT XCO2 observations.
Time Period:  July 2009 – December 2010
Description:  - Use in situ observations and remote sensing data (ACOS GOSAT + TCCON) together in a regional inverse modeling framework for North America.; - Compare with CMS Flux Pilot Project (FPP) results.
Status:  Planned
CMS Science Theme(s):  Atmospheric Transport; Land-Atmosphere Flux
Keywords:  Flux/Movement (; terrestrial; ; atmospheric)
Spatial Extent:  North America
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  ACOS/GOSAT, TCCON, NOAA surface and aircraft observations, Environment Canada surface CO2, Earth Networks CO2, Penn State / Ameriflux CO2, NCAR RACCOON CO2, TCCON CO2
Algorithm/Models Used:  STILT-WRF, Geostatistical Inverse Modeling (GIM), Bayesian Inverse Modeling, NOAA CarbonTracker
Evaluation:  Multiple transport models, GOSAT, surface and aircraft network
Intercomparison Efforts/Gaps:  Comparison of best estimate CQ2 profiles with ACOS GOSAT data
Uncertainty Estimates:  -flux uncertainty will be projected onto simulated XCO2 retrievals; no atmospheric transport uncertainty estimate
Uncertainty Categories:  All: ensemble, deterministic, model-data comparison, model-model comparison, data-data comparison
Application Areas:  - 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:  1
Start Application Readiness Level:  1
Target Application Readiness Level:  9
Future Developments:  - Collaborate with OCO-2 retrieval tesm
Limitations:  - Ground-based data used for optimization is sparse.; - Limited information on the fidelity of the atmospheric transport model.
Date When Product Available:  Projected Sept 2015
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.
Time Period:  July 2009 – December 2010
Description:  - Use in situ observations and remote sensing data (ACOS GOSAT + TCCON) together in a regional inverse modeling framework for North America.; - Compare with CMS Flux Pilot Project (FPP) results.
Status:  Public
CMS Science Theme(s):  Atmospheric Transport; Land-Atmosphere Flux
Keywords:  Flux/Movement (; terrestrial; ; atmospheric)
Spatial Extent:  North America
Spatial Resolution:  1° x 1°
Temporal Frequency:  3-hourly
Input Data Products:  ACOS/GOSAT, TCCON, NOAA surface and aircraft observations, Environment Canada surface CO2, Earth Networks CO2, Penn State / Ameriflux CO2, NCAR RACCOON CO2, TCCON CO2
Algorithm/Models Used:  STILT-WRF, Geostatistical Inverse Modeling (GIM), Bayesian Inverse Modeling, NOAA CarbonTracker
Evaluation:  Multiple transport models, GOSAT, surface and aircraft network
Intercomparison Efforts/Gaps:  - Evaluation of posterior fluxes using surface and aircraft data.; - Comparison of best estimate fluxes with CMS-FPP and NOAA CarbonTracker fluxes.
Uncertainty Estimates:  - Case study with two separate transport models (STILT-WRF vs HYSPLIT-NAMS).; - Bayesian versus geostatistical inverse modeling.; - Tests of alternative data-weighting and inclusion/exclusion of certain datasets.
Uncertainty Categories:  All: ensemble, deterministic, model-data comparison, model-model comparison, data-data comparison
Application Areas:  - 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:  1
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:  Projected Sept 2015
Assigned Data Center:  Goddard
Metadata URL(s):
Data Server URL(s):

https://www.esrl.noaa.gov/gmd/ccgg/arc/?id=131
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Measurement sampling footprints
Time Period:  2007-2010; 1 July - 20 August 2012
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 (; pool: anthropogenic;; pool: terrestrial; ; pool: atmospheric)
Spatial Extent:  North America
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:  ACOS/GOSAT, TCCON, NOAA surface and aircraft observations, Environment Canada surface CO2, Earth Networks CO2, Penn State / Ameriflux CO2, NCAR RACCOON CO2, TCCON CO2
Algorithm/Models Used:  STILT-WRF, 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:  1
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:  Available now
Assigned Data Center:  Goddard
Metadata URL(s):
Data Server URL(s):

ftp://aftp.cmdl.noaa.gov/products/carbontracker/lagrange/footprints/ctl-na-v1.1
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

Shiga, Y. P., Tadic, J. M., Qiu, X., Yadav, V., Andrews, A. E., Berry, J. A., Michalak, A. M. 2018. Atmospheric CO 2 Observations Reveal Strong Correlation Between Regional Net Biospheric Carbon Uptake and Solar-Induced Chlorophyll Fluorescence. Geophysical Research Letters. 45(2), 1122-1132. DOI: 10.1002/2017GL076630

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]


 

Bowman (CMS 2011) (2012)
Project Title:Continuation of the Carbon Monitoring System Flux Pilot Project

Science Team
Members:

Kevin Bowman, JPL (Project Lead)
Holger Brix, UCLA
Scott Denning, Colorado State University
Christian Frankenberg, Caltech
Kevin Gurney, Northern Arizona University
Daven Henze, University of Colorado
Christopher (Chris) Hill, MIT
Meemong Lee, JPL
Junjie Liu, JPL
Eric Marland, Appalachian State University
Dimitris Menemenlis, Jet Propulsion Laboratory

Solicitation:NASA: Carbon Monitoring System (2011)
Precursor Projects: Gunson-Pawson-Potter (2009)  
Abstract: We propose to evolve the Carbon Monitoring System Flux Pilot Project funded under Phase 1 into a framework that integrates observational constraints on all major components of the carbon-cycle-anthropogenic system anthropogenic, terrestrial, oceanic, atmospheric in a top-down CO2 attribution system constrained by atmospheric satellite observations. This expanded framework will enable a deeper understanding of the global carbon cycle and a means of quantifying the effectiveness of climate mitigation policies. This CMS-FPP is motivated by the increase in tropospheric CO2 from anthropogenic emissions, which is the single largest driver of observed and predicted climate change [Forster et al, 2007]. However, roughly half of the CO2 produced from these emissions has been removed by terrestrial and ocean sinks. Consequently, The future trajectory of climate forcing will depend on future emissions and on the capacity of the carbon-cycle to absorb more CO2 [Friedlingstein, 2008]. Recent years have seen an acceleration of fossil fuel emissions and signs of an onset of carbon-cycle feedbacks [Canadell et al, 2007]. Since 2005, fossil fuel emissions have been regionally redistributed towards developing countries, which now make up more than half of CO2 emissions (>4 PgC/yr) [Peters et al, 2012]. While the global carbon budget and its partitioning between anthropogenic, terrestrial, and oceanic fluxes are reasonably understood, the contribution of regional drivers to that budget are not [Canadell et al, 2010]. Consequently, uncertainty in the attribution of CO2 accumulation rate on a year-to-year basis to those drivers limits our capacity to quantify the effectiveness of climate mitigation policies [Le Quere et al, 2009]. In order to reduce uncertainty in CO2 attribution, we will simultaneously improve and augment all major aspects of the current CMS-FPP: new satellites observations, an additional terrestrial eco-system model, a new fossil fuel assimilation system, updated ocean assimilation algorithms, and improved atmospheric inversion algorithms. The CMS-FPP Phase 2 will generate a suite of new and updated products covering 7/2009- 2011 including new global spatially resolved CO2 sources and sinks, new high resolution global fossil fuel emissions, better estimates of oceanic CO2 air-sea exchange, new estimates of global above-ground biomass, and refinements in top-down attribution and uncertainty algorithms. Products generated from bottom-up and top-down estimates will be made publically available through carbon.nasa.gov and linked to cmsflux.jpl.nasa.gov. Through these updates, the CMS-FPP will play a crucial and on-going role in assessing the current capability of space-borne observing systems to improve our knowledge of the integrated carbon-cycle-anthropogenic system and its impact on climate forcing
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:

Christopher Badurek, College of New Jersey
Nicolas Bousserez, University of Colorado
Kevin Bowman, JPL
Holger Brix, UCLA
Scott Denning, Colorado State University
Christian Frankenberg, Caltech
Kevin Gurney, Northern Arizona University
Daven Henze, University of Colorado
Christopher (Chris) Hill, MIT
Maya Hutchins, Arizona State University
Meemong Lee, JPL
Junjie Liu, JPL
Gregg Marland, Appalachian State University
Eric Marland, Appalachian State University
Rohit Mathur, U.S. EPA
Dimitris Menemenlis, Jet Propulsion Laboratory
John Worden, JPL

Project URL(s): http://cmsflux.jpl.nasa.gov
http://ecco2.org
 
Data
Products:
Product Title:  Spatially gridded, temporally resolved estimates of terrestrial biospheric CO2 fluxes.
Time Period:  2010-2015
Description:  - Provide estimates of terrestrial biospheric carbon dioxide fluxes.

This product builds on products from the CMS Pilot Flux project which are available:
Collatz, G.J. and S.R. Kawa. 2014. CMS-Flux Pilot Project Land Biosphere Fluxes 2003-2013 from the CASA GFED3 Model. Data set. Available online at the North American Carbon Program Website: http://nacp-files.nacarbon.org/nacp-kawa-01/
Status:  Preliminary
CMS Science Theme(s):  Land-Atmosphere Flux
Keywords:  Flux/Movement (; terrestrial;; atmospheric)
Spatial Extent:  Global
Spatial Resolution:  0.5°
Temporal Frequency:  Monthly
Input Data Products:  MERRA meteorology, GIMMS NDVI, MODIS Vegetation Cover Fractions, MODIS Burned Area
Algorithm/Models Used:  CASA-GFED
Evaluation:  surface and column atmospheric CO2, fluxes from atmospheric inversions, eddy covariance fluxes
Intercomparison Efforts/Gaps:  Comparison of fuel loads estimates for the U.S. and those of Nancy French (French-04).
Uncertainty Estimates:  Influence of parameter uncertainty using Monte Carlo ensemble. Uncertainties estimated from model-data comparisons (surface and column CO2, eddy covariance fluxes, inversions, independent biomass estimates).
Uncertainty Categories:  Stochastic, model-data
Application Areas:  ; - Forest inventory; - Land management;
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:  - Continue improving the model using Evaluation and validation efforts.
Limitations:  - Have not yet identified regional to global carbon sink mechanisms.; - Coarse spatial resolution.; - Capturing interannual variability in the fluxes is difficult – perhaps need more work on estimates of fire emissions, NPP, and respiration; on the other
Date When Product Available:  2013 on rolling basis
Assigned Data Center:  Goddard
Metadata URL(s):
Data Server URL(s):

http://cmsflux.jpl.nasa.gov/
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Spatially gridded, temporally resolved estimates of vertically resolved CO2 concentrations.
Time Period:  2010-2015
Description:  - Provide posterior CO2 concentration data for Evaluation and boundary condition to regional models
Status:  Preliminary
CMS Science Theme(s):  Global Surface-Atmosphere Flux
Keywords:  Flux/Movement (; anthropogenic; terrestrial; ; oceanic; ; atmospheric); ; Carbon Stocks (atmospheric)
Spatial Extent:  Global
Spatial Resolution:  4° x 5°
Temporal Frequency:  3-hourly
Input Data Products:  Not provided
Algorithm/Models Used:  Not provided
Evaluation:  surface and aircraft sampling network, TCCON
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  - GHG emissions inventory; - Forest inventory; - Land management; - Watershed protection plans; - Global carbon budget calculations; - Ocean acidification mitigation
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:  
Limitations:  Not provided
Date When Product Available:  2013 on rolling basis
Assigned Data Center:  Goddard
Metadata URL(s):
Data Server URL(s):

http://cmsflux.jpl.nasa.gov/
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

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:  SiB4 Modeled Global 0.5-Degree Daily Carbon Fluxes and Pools, 2000-2018
Start Date:  01/2000      End Date:  12/2018
Description:  This dataset provides global daily output predicted by the Simple Biosphere Model, Version 4.2 (SiB4), at a 0.5-degree spatial resolution covering the time period 2000 through 2018. SiB4 is a mechanistic land surface model that integrates heterogeneous land cover, environmentally responsive phenology, dynamic carbon allocation, and cascading carbon pools from live biomass to surface litter to soil organic matter. Daily output includes carbon, carbonyl sulfide, and energy fluxes; solar-induced fluorescence; carbon pools; soil moisture and temperatures in the top three layers; total column soil water and plant available water; and environmental potentials used to scale photosynthesis. The SiB4 output is per plant functional type (PFT) within each 0.5-degree grid cell. SiB4 partitions variable output to 15 PFTs in each grid cell that are indexed by the "npft" dimension (01-15) in each data file. The PFT three-character abbreviations ("pft_names" variable) are listed in the same order as the "npft" dimension. To combine the PFT-specific output into grid cell totals, users must compute the area-weighted mean across the vector of PFT-specific values for each cell. Fractional areal coverages are given in the "pft_area" variable for each cell.
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:  
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/1849
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1849
Archived Data Citation:  Haynes, K.D., I.T. Baker, and A.S. Denning. 2021. SiB4 Modeled Global 0.5-Degree Daily Carbon Fluxes and Pools, 2000-2018. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1849

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

Product Title:  SiB4 Modeled Global 0.5-Degree Hourly Carbon Fluxes and Productivity, 2000-2018
Start Date:  01/2000      End Date:  12/2018
Description:  This dataset provides global hourly output predicted from the Simple Biosphere Model, Version 4.2 (SiB4), at a 0.5-degree spatial resolution covering the time period 2000 through 2018. SiB4 is a mechanistic land surface model that integrates heterogeneous land cover, environmentally responsive phenology, dynamic carbon allocation, and cascading carbon pools from live biomass to surface litter to soil organic matter. Hourly output includes carbon fluxes, carbonyl sulfide (COS) fluxes, gross primary production, ecosystem respiration, solar-induced fluorescence (SIF), top-layer soil temperature and moisture, vegetation stress, photosynthetically active radiation (PAR), leaf and canopy-level carbon-dioxide partial pressures, and canopy conductance. The SiB4 output is per plant functional type (PFT) within each 0.5-degree grid cell. SiB4 partitions variable output to 15 PFTs in each grid cell that are indexed by the "npft" dimension (01-15) in each data file. The PFT three-character abbreviations ("pft_names" variable) are listed in the same order as the "npft" dimension. To combine the PFT-specific output into grid cell totals, users must compute the area-weighted mean across the vector of PFT-specific values for each cell. Fractional areal coverages are given in the "pft_area" variable for each cell.
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:  
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/1847
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1847
Archived Data Citation:  Haynes, K.D., I.T. Baker, and A.S. Denning. 2021. SiB4 Modeled Global 0.5-Degree Hourly Carbon Fluxes and Productivity, 2000-2018. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1847

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

Product Title:  SiB4 Modeled Global 0.5-Degree Monthly Carbon Fluxes and Pools, 2000-2018
Start Date:  01/2000      End Date:  12/2018
Description:  This dataset provides global monthly output predicted by the Simple Biosphere Model, Version 4.2 (SiB4), at a 0.5-degree spatial resolution covering the time period 2000 through 2018. SiB4 is a mechanistic land surface model that integrates heterogeneous land cover, environmentally responsive phenology, dynamic carbon allocation, and cascading carbon pools from live biomass to surface litter to soil organic matter. Monthly output includes carbon, carbonyl sulfide (COS), and energy fluxes; solar-induced fluorescence (SIF); carbon pools; soil moisture and temperatures in the top three layers; total column soil water and plant available water; and environmental potentials used to scale photosynthesis. The SiB4 output is per plant functional type (PFT) within each 0.5-degree grid cell. SiB4 partitions variable output to 15 PFTs in each grid cell that are indexed by the "npft" dimension (01-15) in each data file. The PFT three-character abbreviations ("pft_names" variable) are listed in the same order as the "npft" dimension. To combine the PFT-specific output into grid cell totals, users must compute the area-weighted mean across the vector of PFT-specific values for each cell. Fractional areal coverages are given in the "pft_area" variable for each cell.
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:  
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/1848
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1848
Archived Data Citation:  Haynes, K.D., I.T. Baker, and A.S. Denning. 2021. SiB4 Modeled Global 0.5-Degree Monthly Carbon Fluxes and Pools, 2000-2018. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1848

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

 
Publications: Haynes, K. D., Baker, I. T., Denning, A. S., Stockli, R., Schaefer, K., Lokupitiya, E. Y., Haynes, J. M. 2019. Representing Grasslands Using Dynamic Prognostic Phenology Based on Biological Growth Stages: 1. Implementation in the Simple Biosphere Model (SiB4). Journal of Advances in Modeling Earth Systems. 11(12), 4423-4439. DOI: 10.1029/2018MS001540

Haynes, K. D., Baker, I. T., Denning, A. S., Wolf, S., Wohlfahrt, G., Kiely, G., Minaya, R. C., Haynes, J. M. 2019. Representing Grasslands Using Dynamic Prognostic Phenology Based on Biological Growth Stages: Part 2. Carbon Cycling. Journal of Advances in Modeling Earth Systems. 11(12), 4440-4465. DOI: 10.1029/2018MS001541

Haynes, K., I. Baker, and S. Denning. 2020. Simple Biosphere Model version 4.2 (SiB4) technical description. Mountain Scholar, Colorado State University, Fort Collins, CO, USA. https://hdl.handle.net/10217/200691

Hogue, S., Marland, E., Andres, R. J., Marland, G., Woodard, D. 2016. Uncertainty in gridded CO 2 emissions estimates. Earth's Future. 4(5), 225-239. DOI: 10.1002/2015EF000343

Brix, H., Menemenlis, D., Hill, C., Dutkiewicz, S., Jahn, O., Wang, D., Bowman, K., Zhang, H. 2015. Using Green's Functions to initialize and adjust a global, eddying ocean biogeochemistry general circulation model. Ocean Modelling. 95, 1-14. DOI: 10.1016/j.ocemod.2015.07.008

Bousserez, N., Henze, D. K., Perkins, A., Bowman, K. W., Lee, M., Liu, J., Deng, F., Jones, D. B. A. 2015. Improved analysis-error covariance matrix for high-dimensional variational inversions: application to source estimation using a 3D atmospheric transport model. Quarterly Journal of the Royal Meteorological Society. 141(690), 1906-1921. DOI: 10.1002/qj.2495

Liu, J., Bowman, K. W., Lee, M., Henze, D. K., Bousserez, N., Brix, H., James Collatz, G., Menemenlis, D., Ott, L., Pawson, S., Jones, D., Nassar, R. 2014. Carbon monitoring system flux estimation and attribution: impact of ACOS-GOSAT XCO2 sampling on the inference of terrestrial biospheric sources and sinks. Tellus B: Chemical and Physical Meteorology. 66(1), 22486. DOI: 10.3402/tellusb.v66.22486

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 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 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 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

Haynes, K.D., I.T. Baker, and A.S. Denning. 2021. SiB4 Modeled Global 0.5-Degree Daily Carbon Fluxes and Pools, 2000-2018. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1849

Haynes, K.D., I.T. Baker, and A.S. Denning. 2021. SiB4 Modeled Global 0.5-Degree Hourly Carbon Fluxes and Productivity, 2000-2018. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1847

Haynes, K.D., I.T. Baker, and A.S. Denning. 2021. SiB4 Modeled Global 0.5-Degree Monthly Carbon Fluxes and Pools, 2000-2018. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1848

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]
4th NACP All-Investigators Meeting Posters (2013):
  • Source quantification and geolocation of global power plant emissions using a novel crowd-sourcing system: transfer of knowledge from one decisionmaker group to another -- (Kevin Robert Gurney, Fionn Darragh O'Keeffe) [abstract]
  • Complementary Constrains on Seasonal Carbon Balance in Amazonia from GOSAT Measurements of XCO2 and Chlorophyll Fluorescence -- (Nick Parazoo, Kevin W Bowman, Christian Frankenberg, Jung-Eun Lee, Joshua B. Fisher, John R. Worden, Dylan Jones, Joseph A Berry, George James Collatz, Ian Baker, Martin Jung, Junjie Liu, Gregory Osterman, Christopher O'Dell, Athena Sparks, Andre Butz, Sandrine Guerlet, Yoshida Yukio, Huilin Chen, Christoph Gerbig) [abstract]
  • Analysis of interpolation technique and resolution effects on the aggregation of power plant carbon dioxide emissions at state and county scales -- (Maya G. Hutchins, Christopher A. Badurek, Gregg Marland, Eric Marland) [abstract]


 

Cook (CMS 2011) (2012)
Project Title:Improving Forest Biomass Mapping Accuracy with Optical-LiDAR Data and Hierarchical Bayesian Spatial Models

Science Team
Members:

Bruce Cook, NASA GSFC (Project Lead)
Andrew (Andy) Finley, Michigan State University

Solicitation:NASA: Carbon Monitoring System (2011)
Abstract: We propose to implement a novel approach for mapping forest biomass and associated errors using the fusion of airborne LiDAR, passive optical and thermal data and a Bayesian hierarchical model that accounts for spatial variances between ground observations and remotely sensed data. This method will be compared with the more traditional approach of using a variety of plot-scale LiDAR metrics in a generalized, multiple linear regression model for relatively large region of interest (e.g., county- or state- scale). Also, we will use fine-resolution LiDAR and passive optical data (<1 m) to delineate individual trees, identify species class, and derive additional tree-level attributes (e.g., crown dimensions, crown area weighted heights, stem density) to improve upon biomass estimates made with aggregated point cloud metrics and inventory data at the plot-level (the traditional approach). These three methods will be evaluated and compared at four study sites in the midAtlantic and New England regions of the eastern US: Howland Forest and Holt Research Forest, ME; Harvard Forest, MA; and the Smithsonian Environmental Research Center near Edgewater, MD. This study will leverage coincident and co-registered LiDAR, passive optical, and thermal data that were collected at these sites for NASA s local-scale biomass pilot project between 2011 and 2012. Remotely sensed data was collected with Goddard s LiDAR, Hyperspectral, and Thermal (G-LiHT) airborne imager, which PI Cook developed at NASA-GSFC for studying the complex relationship between terrestrial ecosystem form and function. Large-area stem maps (3 to 35 ha per site, in which all stems greater than 1 cm have been measured) exist at each of these study sites, and these data will be used to verify crown delineations and enable the creation of a fineresolution spectral library. Subsets of the stem map areas will be used to simulate inventory plots, which will then be used as inputs for the Bayesian spatial latent factor model. Each of the stem map areas contain a variety of over/understory tree species, variable topography and range of drainage conditions, which will allow us to validate each of the methods over a wide range of forest types between and within each of the four study sites. Benefits of the proposed Bayesian spatial latent factor prediction model are 1) variables are selected using an efficient, dimension reduction technique; 2) spatial dependencies are incorporated into the model to and improve inference; 3) data compression is used to reduce the computational burden; and 4) sources of uncertainty are acknowledged and propagated through to prediction. Benefits of using data fusion for biomass mapping is that LiDAR and passive optical data provide unique information on the 3- dimensional structure and species composition of the forest, respectively. This synergy has been the focus of recent research, and has spawned the development of multi-instrument airborne systems such at the Carnegie Airborne Observatory (CAO), NASA s G-LiHT, and National Ecological Observatory Network (NEON) system that will begin systematic data collections in 2012. New algorithms and model variables for mapping forest biomass, such as the Bayesian latent spatial factor model and individual tree attributes we propose in this study, are needed to take full advantage of the synergy offered by these new, complementary datasets.
Measurement Approaches:
  • Remote Sensing
  • Airborne Sampling
  • In Situ Measurements
Project Associations:
  • CMS
CMS Primary Theme:
  • Land Biomass
CMS Science Theme(s):
  • Land Biomass
Other Keywords:  LiDAR

Participants:

Hans Andersen, U.S. Forest Service Pacific Northwest Research Station
Chad Babcock, University of Minnesota
Bruce Cook, NASA GSFC
Andrew (Andy) Finley, Michigan State University
Hank Margolis, NASA Headquarters
Jamon Van Den Hoek, Oregon State University

Project URL(s): http://gliht.gsfc.nasa.gov/
 
Data
Products:
Product Title:  Forest biomass estimation using individual tree crown information
Time Period:  2008-2012
Description:  - Quantify carbon stocks on local-scale at high spatial resolution for inventory and land management purposes.
Status:  Preliminary
CMS Science Theme(s):  Land Biomass
Keywords:  Carbon Stocks (; terrestrial)
Spatial Extent:  Smithsonian Environmental Research Center of Maryland and Sierra Nevada Mountains (Teakettle) of California
Spatial Resolution:  Greater than or equal to 1 m (tree-scale)
Temporal Frequency:  Single point time observation
Input Data Products:  Small footprint airborne scanning Lidar (G-LiHT, commercial ALS): Area of Lidar data acquisition is 40 to 1,300 ha
Algorithm/Models Used:  Single time delineation and physical attributes using CHM and Lidar point clouds
Evaluation:  Comparison to stem-map data and field plots
Intercomparison Efforts/Gaps:  Compared with traditional models using plot-scale Lidar metrics
Uncertainty Estimates:  RMSE
Uncertainty Categories:  deterministic
Application Areas:  - Forest inventory; - Land management
Relevant Policies/Programs:  USFS Forest Inventory and Analysis (FIA), SilvaCarbon, USDA Forest Service Experimental Forests & Ranges system
Potential Users:  USFS, private timber firms that are interested in productivity and biomass estimates, forest ecologists, and carbon cycle scientists who are interested in using Lidar to quantify biomass and structure.
Stakeholders:  
Current Application Readiness Level:  5
Start Application Readiness Level:  1
Target Application Readiness Level:  5
Future Developments:  - Transfer the lessons learned with researchers on Nelson-03 and Dubayah-04 to improve methodology.
Limitations:  - Small (but dense) sampling areas.; - Focus on evaluating methodology instead of producing maps.
Date When Product Available:  Dec-13
Assigned Data Center:  ORNL DAAC
Metadata URL(s):
Data Server URL(s):

http://gliht.gsfc.nasa.gov
Archived Data Citation:  

Product Title:  CMS: Aboveground Biomass from Penobscot Experimental Forest, Maine, 2012
Start Date:  01/2012      End Date:  12/2012     (2009-2012)
Description:  This data set includes estimates of aboveground biomass (AGB) in 2012 from the Penobscot Experimental Forest (PEF) in Bradley, Maine. The AGB was modeled using LiDAR data gathered with the LiDAR Hyperspectral and Thermal Imager (G-LiHT) operated by Goddard Space Flight Center and field inventory data from 604 permanent Forest Inventory and Analysis (FIA) plots within the PEF. The estimates were produced through a novel modeling approach that accommodates temporal misalignment between field measurements and remotely sensed data by including multiple time-indexed measurements at plot locations to estimate changes in AGB.
Status:  Archived
CMS Science Theme(s):  Land Biomass
Keywords:  Carbon Stocks (; terrestrial); ; Uncertainties & Standard Errors
Spatial Extent:  Penobscot Experimental Forest of Maine
Spatial Resolution:  10 – 20 m (plot-scale)
Temporal Frequency:  Every 5 years for Maine and sampling snapshots for other sites
Input Data Products:  Large and small footprint scanning Lidar (G-LiHT, LVIS): Area of Lidar data acquisition is 40 to 1,600 ha
Algorithm/Models Used:  Hierarchical Bayesian spatial models
Evaluation:  Hierarchical Bayesian spatial models
Intercomparison Efforts/Gaps:  Could be compared with other biomass maps prepared from LVIS, UAVSAR, and ETC
Uncertainty Estimates:  Hierarchical Bayesian spatial models
Uncertainty Categories:  ensemble (Bayesian)
Application Areas:  - Forest inventory; - Land management
Relevant Policies/Programs:  USFS Forest Inventory and Analysis (FIA), SilvaCarbon, USDA Forest Service Experimental Forests & Ranges system
Potential Users:  USFS, private timber firms that are interested in productivity and biomass estimates, forest ecologists, and carbon cycle scientists who are interested in using Lidar to quantify biomass and structure.
Stakeholders:  
Current Application Readiness Level:  5
Start Application Readiness Level:  1
Target Application Readiness Level:  5
Future Developments:  - Transfer the lessons learned with researchers on Nelson-03 to improve methodology.
Limitations:  - Small (but dense) sampling areas.; - Focus on evaluating methodology instead of producing maps.
Date When Product Available:  May 2016
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1318
Data Server URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1318

http://gliht.gsfc.nasa.gov
Archived Data Citation:  Babcock, C., A.O. Finley, B.D. Cook, A. Weiskittel, and C.W. Woodall. 2016. CMS: Aboveground Biomass from Penobscot Experimental Forest, Maine, 2012. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1318

Bounding Coordinates:
West Longitude:-68.64000 East Longitude:-68.59000
North Latitude:44.87000 South Latitude:44.83000

 
Publications: 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

Duncanson, L. I., Dubayah, R. O., Cook, B. D., Rosette, J., Parker, G. 2015. The importance of spatial detail: Assessing the utility of individual crown information and scaling approaches for lidar-based biomass density estimation. Remote Sensing of Environment. 168, 102-112. DOI: 10.1016/j.rse.2015.06.021

Rosette, J., Cook, B., Nelson, R., Huang, C., Masek, J., Tucker, C., Sun, G., Huang, W., Montesano, P., Rubio-Gil, J., Ranson, J. 2015. Sensor Compatibility for Biomass Change Estimation Using Remote Sensing Data Sets: Part of NASA's Carbon Monitoring System Initiative. IEEE Geoscience and Remote Sensing Letters. 12(7), 1511-1515. DOI: 10.1109/LGRS.2015.2411262

Goetz, S. J., Hansen, M., Houghton, R. A., Walker, W., Laporte, N., Busch, J. 2015. Measurement and monitoring needs, capabilities and potential for addressing reduced emissions from deforestation and forest degradation under REDD+. Environmental Research Letters. 10(12), 123001. DOI: 10.1088/1748-9326/10/12/123001

Finley, A. O., Banerjee, S., Cook, B. D. 2014. Bayesian hierarchical models for spatially misaligned data in R. Methods in Ecology and Evolution. 5(6), 514-523. DOI: 10.1111/2041-210X.12189

White, J. C., Wulder, M. A., Varhola, A., Vastaranta, M., Coops, N. C., Cook, B. D., Pitt, D., Woods, M. 2013. A best practices guide for generating forest inventory attributes from airborne laser scanning data using an area-based approach. The Forestry Chronicle. 89(06), 722-723. DOI: 10.5558/tfc2013-132

White, J.C., M. A. Wulder, A. Varhola, M. Vastaranta, N. C. Coops, B. D. Cook, D. Pitt, and M. Woods. 2013. A best practices guide for generating forest inventory attributes from airborne laser scanning data using the area-based approach. Information Report FI-X-10. Natural Resources Canada, Canadian Forest Service, Canadian Wood Fibre Centre, Pacific Forestry Centre, Victoria, BC. 50 p. http://cfs.nrcan.gc.ca/pubwarehouse/pdfs/34887.pdf

Duncanson, L. I., Cook, B. D., Hurtt, G. C., Dubayah, R. O. 2014. An efficient, multi-layered crown delineation algorithm for mapping individual tree structure across multiple ecosystems. Remote Sensing of Environment. 154, 378-386. DOI: 10.1016/j.rse.2013.07.044

Cook, B., Corp, L., Nelson, R., Middleton, E., Morton, D., McCorkel, J., Masek, J., Ranson, K., Ly, V., Montesano, P. 2013. NASA Goddard's LiDAR, Hyperspectral and Thermal (G-LiHT) Airborne Imager. Remote Sensing. 5(8), 4045-4066. DOI: 10.3390/rs5084045

Huang, W., Sun, G., Dubayah, R., Cook, B., Montesano, P., Ni, W., Zhang, Z. 2013. Mapping biomass change after forest disturbance: Applying LiDAR footprint-derived models at key map scales. Remote Sensing of Environment. 134, 319-332. DOI: 10.1016/j.rse.2013.03.017

Babcock, C., Matney, J., Finley, A. O., Weiskittel, A., Cook, B. D. 2013. Multivariate Spatial Regression Models for Predicting Individual Tree Structure Variables Using LiDAR Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 6(1), 6-14. DOI: 10.1109/JSTARS.2012.2215582

Finley, A. O., Banerjee, S., Cook, B. D., Bradford, J. B. 2013. Hierarchical Bayesian spatial models for predicting multiple forest variables using waveform LiDAR, hyperspectral imagery, and large inventory datasets. International Journal of Applied Earth Observation and Geoinformation. 22, 147-160. DOI: 10.1016/j.jag.2012.04.007

Montesano, P. M., Cook, B. D., Sun, G., Simard, M., Nelson, R. F., Ranson, K. J., Zhang, Z., Luthcke, S. 2013. Achieving accuracy requirements for forest biomass mapping: A spaceborne data fusion method for estimating forest biomass and LiDAR sampling error. Remote Sensing of Environment. 130, 153-170. DOI: 10.1016/j.rse.2012.11.016

Archived Data Citations: Babcock, C., A.O. Finley, B.D. Cook, A. Weiskittel, and C.W. Woodall. 2016. CMS: Aboveground Biomass from Penobscot Experimental Forest, Maine, 2012. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1318

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]
5th NACP All-Investigators Meeting Posters (2015):
  • Application of Airborne Remote Sensing to Define Terrestrial Ecosystem Form & Function -- (Lawrence A Corp, Bruce Cook, Elizabeth M. Middleton, Petya Krasteva Entcheva Campbell, Karl Fred Huemmrich) [abstract]
4th NACP All-Investigators Meeting Posters (2013):
  • Examining the Carbon Sequestration Potential of Recently Disturbed Trees in a Managed Northern Wisconsin Forest -- (Jamon Van Den Hoek, Bruce Cook, Jeffrey Masek, Robert E Kennedy, Compton Tucker) [abstract]   [poster]
2013 NASA Terrestrial Ecology Science Team Meeting Poster(s)
  • Lidar derived canopy height models of Harvard Forest   --   (Ian Paynter, Edward Saenz, Xiaoyuan Yang, Yan Liu, Zhuosen Wang, Crystal Schaaf, Zhan Li, Alan Strahler, Bruce Cook, Keith Krause, Nathan Leisso, Courtney Meier, Darius Culvenor, Glenn Newnham, David Jupp, Jenny Lovell, Ewan Douglas, Jason Martel, Supriya Chakrabarti, Timothy Cook, Glenn Howe, Kuravi Hewawasam, Jeffrey Thomas, Jihyun Kim, Shabnam Rouhani, Yun Yang, Nima Pahlevan, Qingsong Sun, Francesco Peri, Angela Erb)   [abstract]
  • G-LiHT: Goddard’s LiDAR, Hyperspectral and Thermal Airborne Imager   --   (Bruce Cook, Lawrence Corp, Ross Nelson, Douglas Morton, Kenneth J Ranson, Jeffery Masek, Elizabeth Middleton)   [abstract]


 

Dubayah (CMS 2011) (2012)
Project Title:High Resolution Carbon Monitoring and Modeling: A CMS Phase 2 Study

Science Team
Members:

Ralph Dubayah, University of Maryland (Project Lead)
George Hurtt, University of Maryland

Solicitation:NASA: Carbon Monitoring System (2011)
Abstract: The overall goal of our proposed research is the continuing prototype development of a framework for estimating local-scale carbon stocks and future carbon sequestration potential for the State of Maryland using remote sensing and ecosystem modeling. Specifically, we will address the following objectives: (1) Improve our existing methodology for carbon stock estimation and uncertainty and assess its efficacy across an expanded range of environmental and forest conditions; (2) Provide local-scale estimates of carbon stocks and their uncertainties for the entire state of Maryland representing Eastern U.S. forest types; (3) Initialize and run a prognostic ecosystem model to estimate carbon stocks and their changes, and to estimate carbon sequestration potential; (4) Provide detailed validation of national biomass maps using FIA data and localscale biomass maps.(5) Demonstrate new data acquisition technology (single photon counting) for lowcost, rapid carbon assessments. Our proposed work will greatly expand our coverage from 2 to 24 Maryland counties and extends from the tidewater forests of the Chesapeake Bay through the coastal plains and uplands, to the mountainous forests of Western Maryland and the Appalachians. This gradient in land use, topographic, edaphic, and climatic conditions enables an appropriate expansion of methods, models, data, and assessments consistent with the goals of the second phase of CMS. Our objectives build from our Phase 1 work and lead to a clear set of tasks for the proposed effort. These are divided into seven categories of activities traceable to this framework: (1) Remote sensing data acquisition and processing; (2) Field data collection and analysis; (3) Algorithm development and image processing; (4) Statistical and machine learning model development; (5) County biomass and uncertainty map generation, and end-to-end error analysis; (6) Prognostic ecosystem modeling, and; (7) national biomass map validations. An additional element of our proposed work is a coordinated outreach effort to county and state agencies to inform and promote their activities in CMS and includes a transfer of technology to the State of Vermont. To promote this outreach we will also implement a new, web-based data visualization, query and delivery system, Grid^Intel Online (GIO) that allows any user to call up lidar data, associated imagery, biomass and error estimates for arbitrary map areas. Deliverables for this project expand upon those from Phase 1. In addition to the developed framework the project will produce the following CMS products: (1) tiled and mosaicked canopy height and forest/non-forest maps at 2 m and 30 m resolution for Maryland; (2) AGBM maps at 30 m resolution with associated uncertainty maps; (3) EDmodel based carbon and carbon-flux maps at 90 m resolution; (4) ED-model maps of carbon sequestration potential; (5) web-based data visualization and query system; (6) map of canopy structure and biomass derived from wall-to-wall single photon lidar for Alleghany county; (7) assessment of main sources of error and proposed strategies for reducing errors in future deployment of an operational CMS.
Project Associations:
  • CMS
CMS Primary Theme:
  • Land Biomass
CMS Science Theme(s):
  • Land Biomass
  • Decision Support

Participants:

Phillip Abbott, Purdue University
Richard (Rich) Birdsey, Woodwell Climate Research Center
Michelle Canick, The Nature Conservancy
Philip (Phil) DeCola, University of Maryland
Ralph Dubayah, University of Maryland
George Hurtt, University of Maryland
Anuradha (Anu) Swatantran, University of Maryland
Maosheng Zhao, University of Maryland

Project URL(s): None provided.
 
Data
Products:
Product Title:  Prognostic ecosystem model (ED) based maps of carbon stocks and flux.
Time Period:  Updates forthcoming
Description:  - Develop a framework for estimating local-scale, high-resolution carbon stocks and future carbon sequestration potential using remote sensing and ecosystem modeling.
Status:  Planned
CMS Science Theme(s):  Land Biomass
Keywords:  Carbon Stocks (; terrestrial); ; Flux/Movement (; anthropogenic;; terrestrial;; atmospheric)
Spatial Extent:  Maryland (all 24 counties)
Spatial Resolution:  90 m
Temporal Frequency:  
Input Data Products:  Updates forthcoming
Algorithm/Models Used:  Ecosystem Demography Model
Evaluation:  Updates forthcoming
Intercomparison Efforts/Gaps:  Comparisons between Lidar and FIA biomass maps and ED modeled biomass at local scale. Use of local scale maps to validate national scale maps (e.g. Kellndorfer, CMS Phase 1 National Map, Blackard (FIA map) )
Uncertainty Estimates:  Updates forthcoming
Uncertainty Categories:  model-data comparison, model-model comparison
Application Areas:  - 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
Potential Users:  Maryland Department of Natural Resources (DNR) Forest Service, DOE, EPA, private landowners, county GIS departments, national and global entities that want to validate top down products
Stakeholders:  
Current Application Readiness Level:  8,9
Start Application Readiness Level:  5
Target Application Readiness Level:  8,9
Future Developments:  Updates forthcoming
Limitations:  Updates forthcoming
Date When Product Available:  By 2017
Assigned Data Center:  ORNL DAAC
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:  Single photon Lidar canopy height and derived biomass maps.
Time Period:  Updates forthcoming
Description:  - Develop a framework for estimating local-scale, high-resolution carbon stocks and future carbon sequestration potential using remote sensing and ecosystem modeling.
Status:  Planned
CMS Science Theme(s):  Land Biomass
Keywords:  Ecosystem Composition & Structure (canopy height); Carbon Stocks (; terrestrial)
Spatial Extent:  Only Garrett County of Maryland
Spatial Resolution:  Canopy height at 1m and biomass at 30 m
Temporal Frequency:  
Input Data Products:  Single Photon Lidar (Sigma Space Corporation instrument called High Resolution Quantum Lidar System (HRQLS)): Area of Lidar data acquisition is 170,000 ha in a 12-hour-coverage.
Algorithm/Models Used:  Updates forthcoming
Evaluation:  Updates forthcoming
Intercomparison Efforts/Gaps:  Updates forthcoming
Uncertainty Estimates:  Updates forthcoming
Uncertainty Categories:  model-data comparison, model-model comparison
Application Areas:  - 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
Potential Users:  Maryland Department of Natural Resources (DNR) Forest Service, DOE, EPA, private landowners, county GIS departments, national and global entities that want to validate top down products
Stakeholders:  
Current Application Readiness Level:  8,9
Start Application Readiness Level:  5
Target Application Readiness Level:  8,9
Future Developments:  Updates forthcoming
Limitations:  Updates forthcoming
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
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:  Web-based data visualization and query system.
Description:  - Provide an easy-to-access platform for obtaining data products.
Status:  Planned
CMS Science Theme(s):  Decision Support; Land Biomass
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:  - 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
Potential Users:  Maryland Department of Natural Resources (DNR) Forest Service, DOE, EPA, private landowners, county GIS departments, national and global entities that want to validate top down products
Stakeholders:  
Current Application Readiness Level:  8,9
Start Application Readiness Level:  5
Target Application Readiness Level:  8,9
Future Developments:  Updates forthcoming
Limitations:  Updates forthcoming
Date When Product Available:  
Assigned Data Center:  ORNL DAAC
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:  CMS: LiDAR-derived Aboveground Biomass, Canopy Height and Cover for Maryland, 2011
Start Date:  01/2011      End Date:  12/2011     (Variable based on Lidar acquisition dates (2004-2012))
Description:  This data set provides 30-meter gridded estimates of aboveground biomass (AGB), canopy height, and canopy coverage for the state of Maryland in 2011. Leaf-off LiDAR data were combined with high-resolution leaf-on agricultural imagery to select 848 field sampling sites for biomass measurements. The field-based estimates were related to LiDAR height and volume metrics through random forests regression models across three physiographic regions of Maryland.
Status:  Archived
CMS Science Theme(s):  Land Biomass
Keywords:  Carbon Stocks (; terrestrial); ; Uncertainties & Standard Errors
Spatial Extent:  Maryland (all 24 counties) and Addison County of Vermont
Spatial Resolution:  30 m
Temporal Frequency:  
Input Data Products:  Updates forthcoming
Algorithm/Models Used:  Updates forthcoming
Evaluation:  Biomass from field measurements and allometry. Comparisons between empirical and modeled biomass
Intercomparison Efforts/Gaps:  Comparisons between Lidar and FIA biomass maps and ED modeled biomass at local scale. Use of local scale maps to validate national scale maps (e.g. Kellndorfer, CMS Phase 1 National Map, Blackard (FIA map) )
Uncertainty Estimates:  - Pixel-level uncertainty estimates for local scale biomass map. ; - Improved methodology for estimating FIA biomass estimates in 'non-forest' lands and plot-pixel level comparisons with Lidar biomass maps.
Uncertainty Categories:  model-data comparison, model-model comparison
Application Areas:  - 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
Potential Users:  Maryland Department of Natural Resources (DNR) Forest Service, DOE, EPA, private landowners, county GIS departments, national and global entities that want to validate top down products
Stakeholders:  
Current Application Readiness Level:  8,9
Start Application Readiness Level:  5
Target Application Readiness Level:  8,9
Future Developments:  Updates forthcoming
Limitations:  Updates forthcoming
Date When Product Available:  July 2016
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1320

http://carbonmonitoring.umd.edu/index.html
Data Server URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1320

http://carbonmonitoring.umd.edu/index.html
Archived Data Citation:  Dubayah, R.O., A. Swatantran, W. Huang, L. Duncanson, K. Johnson, H. Tang, J.O. Dunne, and G.C. Hurtt. 2016. CMS: LiDAR-derived Aboveground Biomass, Canopy Height and Cover for Maryland, 2011. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1320

Bounding Coordinates:
West Longitude:-79.71000 East Longitude:-74.82000
North Latitude:39.95000 South Latitude:37.69000

Product Title:  LiDAR Derived Biomass, Canopy Height and Cover for Tri-State (MD, PA, DE) Region, V2
Start Date:  01/2004      End Date:  12/2014
Description:  This dataset provides 30-meter gridded estimates of aboveground biomass (AGB), forest canopy height, and canopy coverage for Maryland, Pennsylvania, and Delaware in 2011. Leaf-off LiDAR data were combined with high-resolution leaf-on agricultural imagery in a model-based stratification that was used to select 848 sampling sites for AGB estimation. Field-based estimates were then related to LiDAR height and volume metrics through random forest regression models across three physiographic regions. Spatial errors were estimated at the pixel level using standard prediction intervals to assess the accuracy of the modeling approach. Estimates of biomass were further validated against the permanent network of FIA plots and compared with existing coarse resolution national biomass maps.
Status:  Archived
CMS Science Theme(s):  Land Biomass
Keywords:  
Spatial Extent:  Maryland, Pennsylvania, Delaware
Spatial Resolution:  30 and 90 m resolution
Temporal Frequency:  Each county had a one time lidar sampling done between 2004 and 2014
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:  9
Start Application Readiness Level:  5
Target Application Readiness Level:  9
Future Developments:  
Limitations:  
Date When Product Available:  November 2018
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

https://doi.org/10.3334/ORNLDAAC/1538
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1538
Archived Data Citation:  Dubayah, R.O., A. Swatantran, W. Huang, L. Duncanson, K. Johnson, H. Tang, J.O. Dunne, and G.C. Hurtt. 2018. LiDAR Derived Biomass, Canopy Height and Cover for Tri-State (MD, PA, DE) Region, V2. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1538

Bounding Coordinates:
West Longitude:-81.23000 East Longitude:-74.02000
North Latitude:42.71000 South Latitude:37.80000

Product Title:  Forest Aboveground Biomass and Carbon Sequestration Potential for Maryland, USA
Start Date:  01/2011      End Date:  12/2011     (Variable based on Lidar acquisition dates (2004-2012))
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:  Sink (; terrestrial)
Spatial Extent:  Maryland (all 24 counties)
Spatial Resolution:  90 m
Temporal Frequency:  nominal year 2011
Input Data Products:  Updates forthcoming
Algorithm/Models Used:  Ecosystem Demography Model
Evaluation:  Updates forthcoming
Intercomparison Efforts/Gaps:  Updates forthcoming
Uncertainty Estimates:  Updates forthcoming
Uncertainty Categories:  model-data comparison, model-model comparison
Application Areas:  - 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
Potential Users:  Maryland Department of Natural Resources (DNR) Forest Service, DOE, EPA, private landowners, county GIS departments, national and global entities that want to validate top down products
Stakeholders:  
Current Application Readiness Level:  8,9
Start Application Readiness Level:  5
Target Application Readiness Level:  8,9
Future Developments:  Updates forthcoming
Limitations:  Updates forthcoming
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

Product Title:  CMS: Tree Canopy Cover at 0.5-meter resolution, Vermont, 2016
Start Date:  07/2016      End Date:  09/2016     (2016-07-27 to 2016-09-13)
Description:  This dataset contains estimates of tree canopy cover presence at high resolution (0.5m) across the state of Vermont for 2016 in Cloud-Optimized GeoTIFF (.tif) format. Tree canopy was derived from 2016 high-resolution remotely sensed data as part of the Vermont High-Resolution Land Cover mapping project. Object-based image analysis techniques (OBIA) were employed to extract potential tree canopy and trees using the best available remotely sensed and vector GIS datasets. OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to ensure that the end product is both accurate and cartographically pleasing. Following the automated OBIA mapping a detailed manual review of the dataset was carried out at a scale of 1:3000 and all observable errors were corrected. Tree canopy assessments have been conducted for numerous communities throughout the U.S. where the results have been instrumental in helping to establish tree canopy goals.
Status:  Archived
CMS Science Theme(s):  Land Biomass
Keywords:  vegetation, canopy characteristics, forests, terrestrial ecosystems
Spatial Extent:  Vermont, USA
Spatial Resolution:  0.5m
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:  
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/2072
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/2072
Archived Data Citation:  O'Neil-Dunne, J., E. Buford, S. Macfaden, and A. Royar. 2022. CMS: Tree Canopy Cover at 0.5-meter resolution, Vermont, 2016. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/2072

Bounding Coordinates:
West Longitude:-73.49000 East Longitude:-71.46000
North Latitude:45.02000 South Latitude:42.70000

 
Publications: 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

O'Neil-Dunne J, MacFaden S, Royar A, Reis M., Dubayah R. and Swatantran A. (2014) An Object-Based Approach to Statewide Land Cover Mapping. Proceedings of the 2014 ASPRS Annual Conference. Louisville, KY http://www.asprs.org/a/publications/proceedings/Louisville2014/ONeilDunne.pdf

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

Tang, H., Swatantran, A., Barrett, T., DeCola, P., Dubayah, R. 2016. Voxel-Based Spatial Filtering Method for Canopy Height Retrieval from Airborne Single-Photon Lidar. Remote Sensing. 8(9), 771. DOI: 10.3390/rs8090771

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

Swatantran, A., Tang, H., Barrett, T., DeCola, P., Dubayah, R. 2016. Rapid, High-Resolution Forest Structure and Terrain Mapping over Large Areas using Single Photon Lidar. Scientific Reports. 6(1). DOI: 10.1038/srep28277

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

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

Archived Data Citations: 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

Dubayah, R.O., A. Swatantran, W. Huang, L. Duncanson, K. Johnson, H. Tang, J.O. Dunne, and G.C. Hurtt. 2016. CMS: LiDAR-derived Aboveground Biomass, Canopy Height and Cover for Maryland, 2011. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1320

Dubayah, R.O., A. Swatantran, W. Huang, L. Duncanson, K. Johnson, H. Tang, J.O. Dunne, and G.C. Hurtt. 2018. LiDAR Derived Biomass, Canopy Height and Cover for Tri-State (MD, PA, DE) Region, V2. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1538

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

O'Neil-Dunne, J., E. Buford, S. Macfaden, and A. Royar. 2022. CMS: Tree Canopy Cover at 0.5-meter resolution, Vermont, 2016. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/2072

2015 NASA Carbon Cycle & Ecosystems Joint Science Workshop Poster(s)
  • Fusing Next-generation Active Remote Sensing Data for Improved Forest Height and Structure Mapping   --   (Wenlu Qi, Ralph Dubayah)   [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]
  • Integrating LIDAR and Forest Inventories to Fill the Trees Outside Forests Data Gap   --   (Kristofer Johnson, Richard Birdsey, Jason Cole, Anuradha Swatantran, Jarlath O'Neil-Dunne, Ralph Dubayah, Andrew J. Lister)   [abstract]
4th NACP All-Investigators Meeting Posters (2013):
  • A High-Resolution Carbon Monitoring System by Combining Ecosystem Demography Model with Remotely Sensed Land Cover and Canopy Height -- (Maosheng Zhao, George Hurtt, Ralph Dubayah, Justin Fisk, Amanda Armstrong, Anuradha Swatantran, Naiara Pinto) [abstract]
  • A High-Resolution Carbon Monitoring System by Combining Ecosystem Demography Model with Remotely Sensed Land Cover and Canopy Height -- (Maosheng Zhao, George Hurtt, Ralph Dubayah, Justin Fisk, Amanda Armstrong, Anuradha Swatantran, Naiara Pinto, Oliver Rourke, Larry Flanagan) [abstract]
  • A High-Resolution Carbon Monitoring System by Combining Ecosystem Demography Model with Remotely Sensed Land Cover and Canopy Height -- (Maosheng Zhao, George Hurtt, Ralph Dubayah, Justin Fisk, Amanda Armstrong, Anuradha Swatantran, Naiara Pinto, Oliver Rourke, Steve Flanagan) [abstract]
2013 NASA Terrestrial Ecology Science Team Meeting Poster(s)
  • High-Resolution Ecosystem Modeling as part of Robust Carbon Monitoring System   --   (Maosheng Zhao, George Hurtt, Ralph Dubayah, Justin Fisk, Amanda Armstrong, Anuradha Swatantran, Naira Pinto, Oliver Rourke, Steve Flanagan, Chengquan Huang)   [abstract]
  • Forest Structure and Biomass Mapping Using Time Series Landsat Observations, Small Footprint Lidar, and Field Inventory Data in North Carolina   --   (Chengquan Huang)   [abstract]


 

French (CMS 2011) (2012)
Project Title:Development of Regional Fire Emissions Products for NASA's Carbon Monitoring System using the Wildland Fire Emissions Information System

Science Team
Members:

Nancy French, Michigan Tech Research Institute (MTRI) (Project Lead)
Michael Billmire, Michigan Tech Research Institute (MTRI)

Solicitation:NASA: Carbon Monitoring System (2011)
Abstract: Current work under the NASA-CMS Flux Pilot project includes measures of biomass burning emissions for the quantification of carbon flux from land to the atmosphere. Fire is recognized as an important mechanism for this exchange. Measures of biomass burning emissions are included in this pilot project, but the estimates would greatly benefit from further refinement, and some idea of the uncertainty in biomass burning emissions is needed. There is a growing community of international, federal, and state-level parties that desire and in some cases require refinements in methods to quantify emissions from wildland and prescribed fire (biomass burning). To meet these requirements, these parties are developing a suite of methods to address their needs. We propose to use tools developed from collaborations with the US Forest Service and US Environmental Protection Agency, as well as recent research carried out for NASA, to refine the fire emissions module of the CASA-GFED model currently used by CMS. For the proposed project, to be conducted in Phase II of the CMS, we are proposing to assist the NASA-Goddard CASA-GFED team in improving the GFED approach currently used in the CMS Phase I Flux Pilot project. We will use the Wildland Fire Emissions Information System (WFEIS), an approach developed under NASA s Carbon Cycle Science program in collaboration with others in the fire emissions community, to adjust GFED estimates over North America. WFEIS operates at a 1-km spatial grid scale, while GFED operates at a 0.5 deg grid scale. The two approaches use the same general construct, however they use different data sources for the model parameters and make different assumptions when applying the general model. WFEIS uses a ground-based method to map biomass (fuel loading) and a more direct method to estimate combustion completeness (fuel consumption) than GFED. WFEIS was developed as a regional to landscape-scale method, making it an appropriate tool to refine the GFED estimates of emissions for areas where the two methods can be implemented. The proposed activity includes: 1) improvements in quantifying mapped fuels (biomass) for the US and combustion in deep organic soils of Alaska; 2) development of an uncertainty measurement methodology for emissions estimation; 3) production of 1-kmscale fire emissions estimates for the US; 4) a comparison of these products to CASAGFED emissions estimates; and 5) refinements of GFED parameters based on the results found with WFEIS. Specific outputs from this activity will provide important information for improving our understanding of carbon emissions from wildland fire.
Measurement Approaches:
  • Remote Sensing
  • Modeling
Project Associations:
  • CMS
CMS Primary Theme:
  • Land Biomass
CMS Science Theme(s):
  • Land Biomass
  • Land-Atmosphere Flux
  • Decision Support
Other Keywords:  fire fuels, biomass

Participants:

Michael Billmire, Michigan Tech Research Institute (MTRI)
Nancy French, Michigan Tech Research Institute (MTRI)

Project URL(s): http://wfeis.mtri.org
 
Data
Products:
Product Title:  Annual wildland fire emissions (WFEIS v0.5) for Conterminous US and Alaska, 2001-2013
Start Date:  01/2001      End Date:  12/2013     (2001-2013)
Description:  This data set contains annual modeled estimates of wildland fire emissions at 0.01 degree (~1-km) spatial resolution from the Wildland Fire Emissions Information System (WFEIS v0.5) for the conterminous U.S. (CONUS) and Alaska for 2001 through 2013. WFEIS is a web-based tool that provides resources to quantify emissions from past fires and output results as spatial data files (French et al., 2014). The data set includes emissions estimates of carbon (C), carbon monoxide (CO), carbon dioxide (CO2), methane (CH4), other non-methane hydrocarbons (NMHC), and particulate matter (PM) as well as estimates of above-ground biomass, total fuel availability, and consumption estimates.
Status:  Archived
CMS Science Theme(s):  Land Biomass; Land-Atmosphere Flux
Keywords:  Source (; anthropogenic; terrestrial)
Spatial Extent:  CONUS and Alaska
Spatial Resolution:  1 km
Temporal Frequency:  Monthly
Input Data Products:  Wildland Fire Emissions Information System (WFEIS), Landsat, MODIS
Algorithm/Models Used:  WFEIS
Evaluation:  Compare with GFED v.3 & 4
Intercomparison Efforts/Gaps:  Site (landscape-scale) comparisons with other fire emissions methods including GFED (French et al 2011)
Uncertainty Estimates:  Developing a full uncertainty estimation plan under this grant with some aspects completed. Some part of the model will be difficult to assess, so strategies to complete a full error analysis will be developed for implementation in future versions of the model.
Uncertainty Categories:  model-data and model-model comparisons
Application Areas:  - Fire management; - Forest inventory; - Land management; - Air quality protection
Relevant Policies/Programs:  Wildland Fire Emissions Information System (WFEIS), Global Fire Data (GFED), BlueSky, CAA, NGHGI, FLPMA
Potential Users:  EPA, USFS, BLM, carbon accounting researchers, state agencies that prescribe burning and/or monitor air quality
Stakeholders:  
Current Application Readiness Level:  5
Start Application Readiness Level:  4
Target Application Readiness Level:  7
Future Developments:  - Meet with smoke managers in every national park by the end of 2014.; - Follow up on last year's engagement with USFS Geospatial Service and Technology Center and EPA's air quality modeling group.
Limitations:  - No uncertainty analysis.; - No data on small and short-lived fires.
Date When Product Available:  Now
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1306

http://wfeis.mtri.org/examples
Data Server URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1306

http://wfeis.mtri.org/examples

http://wfeis.mtri.org/media/model_outputs/
Archived Data Citation:  French, N.H.F., D. McKenzie, T. Erickson, B. Koziol, M. Billmire, K.A. Endsley, N.K.Y. Scheinerman, L. Jenkins, M.E. Miller, R. Ottmar, and S. Prichard. 2016. Annual wildland fire emissions (WFEIS v0.5) for Conterminous US and Alaska, 2001-2013. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1306

Bounding Coordinates:
West Longitude:-178.22000 East Longitude:-65.00000
North Latitude:71.41000 South Latitude:24.20000

 
Publications: French, N. H. F., McKenzie, D., Erickson, T., Koziol, B., Billmire, M., Endsley, K. A., Yager Scheinerman, N. K., Jenkins, L., Miller, M. E., Ottmar, R., Prichard, S. 2014. Modeling Regional-Scale Wildland Fire Emissions with the Wildland Fire Emissions Information System. Earth Interactions. 18(16), 1-26. DOI: 10.1175/EI-D-14-0002.1

van Leeuwen, T. T., van der Werf, G. R., Hoffmann, A. A., Detmers, R. G., Rucker, G., French, N. H. F., Archibald, S., Carvalho Jr., J. A., Cook, G. D., de Groot, W. J., Hely, C., Kasischke, E. S., Kloster, S., McCarty, J. L., Pettinari, M. L., Savadogo, P., Alvarado, E. C., Boschetti, L., Manuri, S., Meyer, C. P., Siegert, F., Trollope, L. A., Trollope, W. S. W. 2014. Biomass burning fuel consumption rates: a field measurement database. Biogeosciences. 11(24), 7305-7329. DOI: 10.5194/bg-11-7305-2014

McKenzie, D., French, N. H. F., Ottmar, R. D. 2012. National database for calculating fuel available to wildfires. Eos, Transactions American Geophysical Union. 93(6), 57-58. DOI: 10.1029/2012EO060002

Archived Data Citations: French, N.H.F., D. McKenzie, T. Erickson, B. Koziol, M. Billmire, K.A. Endsley, N.K.Y. Scheinerman, L. Jenkins, M.E. Miller, R. Ottmar, and S. Prichard. 2016. Annual wildland fire emissions (WFEIS v0.5) for Conterminous US and Alaska, 2001-2013. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1306

4th NACP All-Investigators Meeting Posters (2013):
  • Large emissions of carbon dioxide, carbon monoxide, and methane from Alaska boreal fires during the 2000s -- (Eric S. Kasischke, Elizabeth E Hoy, Merritt R. Turetsky, Evan Kane, William J deGroot, Nancy HF French) [abstract]


 

Healey (CMS 2011) (2012)
Project Title:A Global Forest Biomass Inventory Based upon GLAS Lidar Data

Science Team
Members:

Sean Healey, USDA Forest Service (Project Lead)

Solicitation:NASA: Carbon Monitoring System (2011)
Abstract: The United Nations Food and Agriculture Organization (FAO) compiles and monitors national-level biomass estimates across the world s forests through the Global Forest Resources Assessment (FRA). FRA reports represent the current state of knowledge regarding key forest parameters as expressed by national forest agencies and ministries worldwide. Data collected in the FRA is important to UN initiatives such as REDD (Reducing Emissions from Deforestation and Degradation), which depend upon accurate, precise, and consistent national-level reporting of forest carbon storage. The proposed work would establish a satellite-based NASA CMS global inventory of aboveground tree biomass (a primary component of overall biomass) as an official component of FAO s FRA 2015. Methods for this inventory were developed during the CMS pilot phase though a partnership between members of the CMS national biomass pilot team and representatives of the national forest inventory (FIA: US Forest Service s Forest Inventory and Analysis unit) on the CMS Science Definition Team. Discrete full waveform lidar footprints from the GLAS (Geoscience Laser Altimeter System aboard ICESat) are strongly correlated with aboveground tree biomass, and are here used in a survey/sample context as the basis for the CMS/FAO global biomass inventory. Based upon CMS pilot results, this approach is likely to provide an improvement in the precision of biomass estimates for countries without established national forest inventories, and its global consistency should enhance inter-comparability of biomass stocks across all nations. This inventory would be based upon model-based estimation, an approach which provides clear estimates of biomass and related uncertainty, accounting for both the variance of the sample and variance introduced by modeling biomass at each GLAS shot. FAO will coordinate global compilation of the ground data needed from national forestry agencies for calibration of models to be used in this inventory. A series of approximately 10 regional workshops will be held for national forest inventory representatives from around the world in 2013. At each workshop, time will be dedicated to engage participating countries in the needed data sharing. Almost all costs associated with this effort (including travel and lodging for many participants) will be borne by FAO. In addition to providing country- and global-level forest biomass estimates, this project will publish relationships between GLAS heights and field-measured biomass, which may be of use to other CMS efforts using GLAS data to calibrate wall-to-wall maps. Lastly, there is a forward-looking element which involves forecasting the precision of this inventory approach using lidar data from the ICESat-2 satellite (launch: 2016). Collection of ground data by this project will be coordinated with the ICESat-2 Science Team, which is programming overflights of GLAS shots by MABEL (an ICESat-2 simulation platform) and airborne lidar. Taken together, the components of the proposed project will: 1) develop a global CMS aboveground forest biomass product; 2) establish it as a critical monitoring asset within the FAO FRA monitoring process; and 3) assess its sustainability in view of upcoming NASA missions. The proposed work includes a good deal of in-kind salary contribution from the Forest Service, and there is a 55/45 balance of funding to non-federal/federal entities. Sean Healey, FIA s remote sensing representative to FAO and a member of the CMS Science Definition Team, is nominated for membership on the CMS Science Team.
Project Associations:
  • CMS
CMS Primary Theme:
  • Land Biomass
CMS Science Theme(s):
  • Land Biomass
  • MRV

Participants:

Sean Healey, USDA Forest Service
Sylvia Wilson, USGS / SilvaCarbon

Project URL(s): None provided.
 
Data
Products:
Product Title:  CMS: GLAS LiDAR-derived Global Estimates of Forest Canopy Height, 2004-2008
Start Date:  10/2004      End Date:  11/2004     (2004-2008)
Description:  This data set provides estimates of forest canopy height derived from the Geoscience Laser Altimeter System (GLAS) LiDAR instrument that was aboard the NASA Ice, Cloud, and land Elevation (ICESat) satellite. A global GLAS waveform data set (n=12,336,553) from collection periods between October 2004 and March 2008 was processed to obtain canopy height estimates.Estimates of GLAS maximum canopy height and crown-area-weighted Lorey's height are provided for 18,578 statistically-selected globally distributed forested sites in a point shapefile. Country is included as a site attribute.Also provided is the average canopy height for the forested area of each country, plus the number of GLAS data footprints (shots), number of selected sample sites, and estimates of the variance for each country.
Status:  Archived
CMS Science Theme(s):  Land Biomass
Keywords:  Uncertainties & Standard Errors
Spatial Extent:  Global
Spatial Resolution:  
Temporal Frequency:  
Input Data Products:  ICESat GLAS, inventory information volunteered by contributing countries
Algorithm/Models Used:  Model-based estimation
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  We have a straightforward variance estimator, based on sample theory, that will provide credible confidence intervals for our country- and global-level estimates.
Uncertainty Categories:  deterministic
Application Areas:  - MRV, REDD+; - Forest inventory; - Land management
Relevant Policies/Programs:  2015 Global Forest Resources Assessment, Reduced Emissions from Deforestation and Forest Degradation (REDD+), FIA, ICESat-2 Science Mission
Potential Users:  UN Food and Agriculture Organization (FAO), USFS, SilvaCarbon, and any country that needs the baseline data in order to improve its forest inventory system
Stakeholders:  
Current Application Readiness Level:  7
Start Application Readiness Level:  3
Target Application Readiness Level:  9
Future Developments:  - Engage with the ICESat-2 science team to ensure the endurance of the data products in the future. ; - Promote the data products at the SilvaCarbon event in Central Africa in April 2014.; - Attend multi-lateral meetings to solicit ground data for calibra
Limitations:  - No spatial maps.; - No temporal variability, just one biomass density estimate centered around 2005.; - Data that is at least 8 years old.
Date When Product Available:  2016-05-16
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1271
Data Server URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1271
Archived Data Citation:  Healey, S.P., M.W. Hernandez, D.P. Edwards, M.A. Lefsky, E. Freeman, P.L. Patterson, E.J. Lindquist, and A.J. Lister. 2015. CMS: GLAS LiDAR-derived Global Estimates of Forest Canopy Height, 2004-2008. ORNL DAAC, Oak Ridge, Tennessee, USA DOI: 10.3334/ORNLDAAC/1271

Bounding Coordinates:
West Longitude:-161.41000 East Longitude:179.89000
North Latitude:69.29000 South Latitude:-55.45000

Product Title:  CMS: GLAS LiDAR-derived Global Estimates of Forest Canopy Height, 2004-2008
Start Date:  10/2004      End Date:  11/2004     (2004-2008)
Description:  This data set provides estimates of forest canopy height derived from the Geoscience Laser Altimeter System (GLAS) LiDAR instrument that was aboard the NASA Ice, Cloud, and land Elevation (ICESat) satellite. A global GLAS waveform data set (n=12,336,553) from collection periods between October 2004 and March 2008 was processed to obtain canopy height estimates.Estimates of GLAS maximum canopy height and crown-area-weighted Lorey's height are provided for 18,578 statistically-selected globally distributed forested sites in a point shapefile. Country is included as a site attribute.Also provided is the average canopy height for the forested area of each country, plus the number of GLAS data footprints (shots), number of selected sample sites, and estimates of the variance for each country.
Status:  Archived
CMS Science Theme(s):  Land Biomass
Keywords:  Carbon Stocks (; terrestrial); ; Ecosystem Composition & Structure (canopy height)
Spatial Extent:  Global
Spatial Resolution:  230 x 230-meters
Temporal Frequency:  One time estimates
Input Data Products:  ICESat GLAS, inventory information volunteered by contributing countries
Algorithm/Models Used:  Model-based estimation
Evaluation:  Estimates can be compared with field-based estimates in countries with an established national forest inventory
Intercomparison Efforts/Gaps:  Authors of the UN Forest Resources Assessment, together with country correspondents, will determine whether to include our estimate, an estimate from a dedicated national forest inventory, or an international default.
Uncertainty Estimates:  We have a straightforward variance estimator, based on sample theory, that will provide credible confidence intervals for our country- and global-level estimates.
Uncertainty Categories:  deterministic
Application Areas:  - MRV, REDD+; - Forest inventory; - Land management
Relevant Policies/Programs:  2015 Global Forest Resources Assessment, Reduced Emissions from Deforestation and Forest Degradation (REDD+), FIA, ICESat-2 Science Mission
Potential Users:  UN Food and Agriculture Organization (FAO), USFS, SilvaCarbon, and any country that needs the baseline data in order to improve its forest inventory system
Stakeholders:  
Current Application Readiness Level:  7
Start Application Readiness Level:  3
Target Application Readiness Level:  9
Future Developments:  - Engage with the ICESat-2 science team to ensure the endurance of the data products in the future. ; - Promote the data products at the SilvaCarbon event in Central Africa in April 2014.; - Attend multi-lateral meetings to solicit ground data for calibration
Limitations:  - No spatial maps.; - No temporal variability, just one biomass density estimate centered around 2005.; - Data that is at least 8 years old.
Date When Product Available:  2016-05-16
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1271
Data Server URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1271
Archived Data Citation:  Healey, S.P., M.W. Hernandez, D.P. Edwards, M.A. Lefsky, E. Freeman, P.L. Patterson, E.J. Lindquist, and A.J. Lister. 2015. CMS: GLAS LiDAR-derived Global Estimates of Forest Canopy Height, 2004-2008. ORNL DAAC, Oak Ridge, Tennessee, USA DOI: 10.3334/ORNLDAAC/1271

Bounding Coordinates:
West Longitude:-161.41000 East Longitude:179.89000
North Latitude:69.29000 South Latitude:-55.45000

 
Publications: Birdsey, Richard A.; Dugan, Alexa J.; Healey, Sean P.; Dante-Wood, Karen; Zhang, Fangmin; Mo, Gang; Chen, Jing M.; Hernandez, Alexander J.; Raymond, Crystal L.; McCarter, James. 2019. Assessment of the influence of disturbance, management activities, and environmental factors on carbon stocks of U.S. national forests. Gen. Tech. Rep. RMRS-GTR-402. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 116 pages plus appendices.

Healey, S. P., Patterson, P. L., Saatchi, S., Lefsky, M. A., Lister, A. J., Freeman, E. A. 2012. A sample design for globally consistent biomass estimation using lidar data from the Geoscience Laser Altimeter System (GLAS). Carbon Balance and Management. 7(1). DOI: 10.1186/1750-0680-7-10

Archived Data Citations: Healey, S.P., M.W. Hernandez, D.P. Edwards, M.A. Lefsky, E. Freeman, P.L. Patterson, E.J. Lindquist, and A.J. Lister. 2015. CMS: GLAS LiDAR-derived Global Estimates of Forest Canopy Height, 2004-2008. ORNL DAAC, Oak Ridge, Tennessee, USA DOI: 10.3334/ORNLDAAC/1271

2015 NASA Carbon Cycle & Ecosystems Joint Science Workshop Poster(s)
  • The New Forest Carbon Accounting Framework of the US and NASA Carbon Cycle Science: Identifying Concomitant Knowledge Gaps and Research Opportunities   --   (Sean P Healey, Christopher W. Woodall, Grant M Domke, John Coulston, Brian F Walters, James A Smith, Andy Gray)   [abstract]
2013 NASA Terrestrial Ecology Science Team Meeting Poster(s)
  • The Global Forest Biomass Inventory   --   (Sean P Healey, Erik Lindquist, Paul Patterson, Sassan Saatchi, Michael Lefsky, Michael Hernandez, Alicia Peduzzi)   [abstract]


 

Houghton (CMS 2011) (2012)
Project Title:Spatially Explicit Sources and Sinks of Carbon from Deforestation, Reforestation, Growth and Degradation in the Tropics: Development of a Method and a 10 Year Data Set 2000-2010

Science Team
Members:

Richard (Skee) Houghton, Woodwell Climate Research Center (Project Lead)

Solicitation:NASA: Carbon Monitoring System (2011)
Abstract: Neither of the pilot studies in NASA s Phase 1 of the CMS has explicitly considered changes in terrestrial carbon storage that result from land use and land-cover change (LULCC). The biomass pilot study could be extended to estimate changes in aboveground carbon density, but modeling and ancillary data will be needed to account for changes in soils, downed wood, and wood products. The flux pilot study has, so far, concentrated on short-term fluxes of carbon (i.e., photosynthesis, respiration, etc.) and has paid less attention to the longer-term, structural changes that result from disturbance and recovery. Yet it is these changes in biomass and soil carbon that define the net contribution of LULCC to the global carbon budget. We propose (1) to develop and demonstrate a method for monitoring changes in carbon density in forests and (2) to produce a map of gross and net fluxes of carbon associated with deforestation, reforestation, growth and degradation for the entire tropics. We will focus on the changes in carbon density that result from disturbance and recovery. We propose to use multi-scale changes in forest cover (gains and losses) combined with lidar-based estimates of aboveground carbon density to inform a carbon-tracking model that will calculate losses and gains of carbon at a spatial resolution of 250m across the tropics and at a resolution of 30m for two regions within southeast Asia and the Congo Basin. As a part of this research, we will determine the propagation of error for each method (change in land cover, change in carbon density), including allometry error and modeling error. The analysis of error will help define how small a disturbance (in area and in carbon density) can be observed. And, using a carbon tracking model, we will investigate the effect of this minimum detection on carbon emissions. The work proposed here will complement the current pilot studies and will track changes in terrestrial carbon density, in particular the changes that result from disturbance and recovery of forests. The model will use a combination of MODIS, Landsat, and GLAS data to determine annual changes in carbon density in aboveground living and dead biomass, belowground biomass, litter, coarse woody debris, and wood products. The work will focus on identifying, characterizing, and measuring disturbances (and recovery) and on calculating the resulting fluxes of carbon. The products of this work will be (1) a methodological approach incorporating satellite data, a carbon-tracking model, and error analyses, and (2) multi-scale gridded data sets showing the distribution of carbon sources and sinks attributable to forest disturbance and recovery. The method will not be limited to the data inputs used here. Rather the model will be flexible enough to accommodate other data sets as they evolve. The products will include the data sets used to calculate carbon sources and sinks (rates and intensities of disturbance and aboveground carbon densities), the errors in each data set and the propagation of error through the calculation of net carbon flux. The work is relevant to societal needs in two ways: first, carbon emissions from LULCC are an important but poorly constrained component in the global carbon balance; this work will demonstrate the capacity of satellite-based measurements to reduce the error of that flux. Second, project-level and national-level emissions are the basis for evaluating emission reduction strategies, arguably the most effective mechanism for reducing emissions of carbon from developing countries.
Measurement Approaches:
  • Modeling
Project Associations:
  • CMS
CMS Primary Theme:
  • Land Biomass
CMS Science Theme(s):
  • Land Biomass
  • Land-Atmosphere Flux
  • MRV

Participants:

Alessandro (Ale) Baccini, Boston University
Nancy Harris, World Resources Institute
Richard (Skee) Houghton, Woodwell Climate Research Center

Project URL(s): None provided.
 
Data
Products:
Product Title:  CMS: Estimated Deforested Area Biomass, Tropical America, Africa, and Asia, 2000
Start Date:  01/2000      End Date:  12/2012     (2000-2012)
Description:  This data set provides estimates of pre-deforestation aboveground live woody biomass (AGLB) at 30-m resolution for deforested areas of tropical America, tropical Africa, and tropical Asia for the year 2000. The biomass estimates are only for areas where deforestation occurred during the period 2000 through 2012. These estimates represent biomass loss over this time period and can be used to derive average annual carbon emissions from tropical deforestation.
Status:  Archived
CMS Science Theme(s):  Land Biomass; Land-Atmosphere Flux
Keywords:  Flux/Movement (; anthropogenic; atmospheric)
Spatial Extent:  Tropical regions of America, Africa, and Asia
Spatial Resolution:  30 m
Temporal Frequency:  One-time estimate for the year 2000
Input Data Products:  Ground-based data, Landsat 7, deforestation data sets, GLAS LiDAR, Normalized Difference Vegetation Index (NDVI), and the Normalized Difference Infrared Index (NDII), and biophysical predictor variables (Zarin et al., 2016)
Algorithm/Models Used:  RandomForest models
Evaluation:  Previous estimates of tropical emissions from land use and land-cover change
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  Errors associated with changes in forest area and aboveground carbon density will be analyzed.
Uncertainty Categories:  model-data comparison
Application Areas:  - MRV, REDD+; - Forest inventory; - Land management; - Forest inventory; - Global carbon budget calculations
Relevant Policies/Programs:  REDD+, UNFCCC-National Forest Monitoring System (NFMS), US-Indonesia Partnership on Climate Change and Clean Energy (US-Indonesia Partnership)
Potential Users:  World Resources Institute (Global Forest Watch), Developing countries who are seeking to reduce emissions in the tropics (Brazil, Indonesia), Brazilian National Institute for Space Research (INPE), Indonesia National Aerospace Institute (LAPAN), FAO, USAID, GCP
Stakeholders:  
Current Application Readiness Level:  7
Start Application Readiness Level:  3
Target Application Readiness Level:  7
Future Developments:  - Hold routine meetings with the GCP for updates.; - Publish results in 3 articles by the end of 2014 to raise awareness of the data products in the scientific community.
Limitations:  - Coarse spatial resolution; - Too fine of temporal resolution – more noise associated with annual maps.; - Higher uncertainty associated with ancillary data for carbon pools that are not aboveground biomass.
Date When Product Available:  October 2016
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1337
Data Server URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1337
Archived Data Citation:  Baccini, M., W. Walker, M. Farina, and R.A. Houghton. 2016. CMS: Estimated Deforested Area Biomass, Tropical America, Africa, and Asia, 2000. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1337

Bounding Coordinates:
West Longitude:-119.00000 East Longitude:180.00000
North Latitude:30.00000 South Latitude:-30.00000

 
Publications: Anderegg, W. R. L., Ballantyne, A. P., Smith, W. K., Majkut, J., Rabin, S., Beaulieu, C., Birdsey, R., Dunne, J. P., Houghton, R. A., Myneni, R. B., Pan, Y., Sarmiento, J. L., Serota, N., Shevliakova, E., Tans, P., Pacala, S. W. 2015. Tropical nighttime warming as a dominant driver of variability in the terrestrial carbon sink. Proceedings of the National Academy of Sciences. 112(51), 15591-15596. DOI: 10.1073/pnas.1521479112

Ballantyne, A. P., Andres, R., Houghton, R., Stocker, B. D., Wanninkhof, R., Anderegg, W., Cooper, L. A., DeGrandpre, M., Tans, P. P., Miller, J. B., Alden, C., White, J. W. C. 2015. Audit of the global carbon budget: estimate errors and their impact on uptake uncertainty. Biogeosciences. 12(8), 2565-2584. DOI: 10.5194/bg-12-2565-2015

Goetz, S. J., Hansen, M., Houghton, R. A., Walker, W., Laporte, N., Busch, J. 2015. Measurement and monitoring needs, capabilities and potential for addressing reduced emissions from deforestation and forest degradation under REDD+. Environmental Research Letters. 10(12), 123001. DOI: 10.1088/1748-9326/10/12/123001

Olofsson, P., Kuemmerle, T., Griffiths, P., Knorn, J., Baccini, A., Gancz, V., Blujdea, V., Houghton, R. A., Abrudan, I. V., Woodcock, C. E. 2011. Carbon implications of forest restitution in post-socialist Romania. Environmental Research Letters. 6(4), 045202. DOI: 10.1088/1748-9326/6/4/045202

Pan, Y., Birdsey, R. A., Fang, J., Houghton, R., Kauppi, P. E., Kurz, W. A., Phillips, O. L., Shvidenko, A., Lewis, S. L., Canadell, J. G., Ciais, P., Jackson, R. B., Pacala, S. W., McGuire, A. D., Piao, S., Rautiainen, A., Sitch, S., Hayes, D. 2011. A Large and Persistent Carbon Sink in the World's Forests. Science. 333(6045), 988-993. DOI: 10.1126/science.1201609

Baccini, A., Goetz, S. J., Walker, W. S., Laporte, N. T., Sun, M., Sulla-Menashe, D., Hackler, J., Beck, P. S. A., Dubayah, R., Friedl, M. A., Samanta, S., Houghton, R. A. 2012. Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps. Nature Climate Change. 2(3), 182-185. DOI: 10.1038/nclimate1354

Gloor, M., Gatti, L., Brienen, R., Feldpausch, T. R., Phillips, O. L., Miller, J., Ometto, J. P., Rocha, H., Baker, T., de Jong, B., Houghton, R. A., Malhi, Y., Aragao, L. E. O. C., Guyot, J., Zhao, K., Jackson, R., Peylin, P., Sitch, S., Poulter, B., Lomas, M., Zaehle, S., Huntingford, C., Levy, P., Lloyd, J. 2012. The carbon balance of South America: a review of the status, decadal trends and main determinants. Biogeosciences. 9(12), 5407-5430. DOI: 10.5194/bg-9-5407-2012

Goetz, S. J., Bond-Lamberty, B., Law, B. E., Hicke, J. A., Huang, C., Houghton, R. A., McNulty, S., O'Halloran, T., Harmon, M., Meddens, A. J. H., Pfeifer, E. M., Mildrexler, D., Kasischke, E. S. 2012. Observations and assessment of forest carbon dynamics following disturbance in North America. Journal of Geophysical Research: Biogeosciences. 117(G2). DOI: 10.1029/2011JG001733

Houghton, R. A. 2012. Carbon emissions and the drivers of deforestation and forest degradation in the tropics. Current Opinion in Environmental Sustainability. 4(6), 597-603. DOI: 10.1016/j.cosust.2012.06.006

Houghton, R. A. 2012. Historic Changes in Terrestrial Carbon Storage in: Recarbonization of the Biosphere. Springer Netherlands, 59-82. DOI: 10.1007/978-94-007-4159-1_4

Houghton, R. A., House, J. I., Pongratz, J., van der Werf, G. R., DeFries, R. S., Hansen, M. C., Le Quere, C., Ramankutty, N. 2012. Carbon emissions from land use and land-cover change. Biogeosciences. 9(12), 5125-5142. DOI: 10.5194/bg-9-5125-2012

Erb, K., Kastner, T., Luyssaert, S., Houghton, R. A., Kuemmerle, T., Olofsson, P., Haberl, H. 2013. Bias in the attribution of forest carbon sinks. Nature Climate Change. 3(10), 854-856. DOI: 10.1038/nclimate2004

Houghton, R. A. 2014. The emissions of carbon from deforestation and degradation in the tropics: past trends and future potential. Carbon Management. 4(5), 539-546. DOI: 10.4155/cmt.13.41

Houghton, R.A. 2013. Role of forests and impact of deforestation in the global carbon cycle. Pages 15-38 in: F. Achard & M.C. Hansen (editors). Global Forest Monitoring from Earth Observation. CRC Press, Boca Raton. ISBN 9781466552012 - CAT# K15197

Patra, P. K., Canadell, J. G., Houghton, R. A., Piao, S. L., Oh, N., Ciais, P., Manjunath, K. R., Chhabra, A., Wang, T., Bhattacharya, T., Bousquet, P., Hartman, J., Ito, A., Mayorga, E., Niwa, Y., Raymond, P. A., Sarma, V. V. S. S., Lasco, R. 2013. The carbon budget of South Asia. Biogeosciences. 10(1), 513-527. DOI: 10.5194/bg-10-513-2013

Tyukavina, A., Stehman, S. V., Potapov, P. V., Turubanova, S. A., Baccini, A., Goetz, S. J., Laporte, N. T., Houghton, R. A., Hansen, M. C. 2013. National-scale estimation of gross forest aboveground carbon loss: a case study of the Democratic Republic of the Congo. Environmental Research Letters. 8(4), 044039. DOI: 10.1088/1748-9326/8/4/044039

Valentini, R., Arneth, A., Bombelli, A., Castaldi, S., Cazzolla Gatti, R., Chevallier, F., Ciais, P., Grieco, E., Hartmann, J., Henry, M., Houghton, R. A., Jung, M., Kutsch, W. L., Malhi, Y., Mayorga, E., Merbold, L., Murray-Tortarolo, G., Papale, D., Peylin, P., Poulter, B., Raymond, P. A., Santini, M., Sitch, S., Vaglio Laurin, G., van der Werf, G. R., Williams, C. A., Scholes, R. J. 2014. A full greenhouse gases budget of Africa: synthesis, uncertainties, and vulnerabilities. Biogeosciences. 11(2), 381-407. DOI: 10.5194/bg-11-381-2014

Archived Data Citations: Baccini, M., W. Walker, M. Farina, and R.A. Houghton. 2016. CMS: Estimated Deforested Area Biomass, Tropical America, Africa, and Asia, 2000. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1337


 

Huntzinger (CMS 2011) (2012)
Project Title:Reduction in Bottom-Up Land Surface CO2 Flux Uncertainty in NASA's Carbon Monitoring System Flux Project through Systematic Multi-Model Evaluation and Infrastructure Development

Science Team
Members:

Deborah (Debbie) Huntzinger, Northern Arizona University (Project Lead)
Joshua Fisher, Chapman University
Christopher Schwalm, Woodwell Climate Research Center

Solicitation:NASA: Carbon Monitoring System (2011)
Abstract: This study will generate improved global estimates of land-atmosphere carbon exchange by combining and enhancing the technical infrastructure and observational constraints within the NASA Carbon Monitoring System (CMS) Flux Project with new “bottom-up” a priori surface flux estimates. These new surface flux products will be derived from a community of models that represent our best process-based understanding of how carbon is exchanged between the land and the atmosphere. We will leverage and build off of an existing NASA funded grant: The Multi-Scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP). MsTMIP is a coordinated, large-scale intercomparison effort that combines common forcing data and a detailed simulation protocol in order to improve the diagnosis and attribution of carbon sources and sinks across both global and regional scales. What MsTMIP does that other intercomparisons have failed to do, is create a framework that isolates, interprets, and helps inform understanding of how differences in process parameterizations among current “bottom-up” models impact their flux estimations. As a result, the MsTMIP framework allows for the isolation and quantification of the intermodel variance in estimates of land-atmosphere carbon exchange due to model structure, or variations in the types of processes consider in the model and how these process are represented. This inter-model variance provides a robust assessment of uncertainty in land surface priors due to varying model physics, a component currently missing from the CMS-Flux system. CMS-Flux has the ability to produce ensembles of atmospheric CO2 distributions using perturbations to transport and surface fluxes. These ensembles can help build understanding of the relationship between surface flux and atmospheric CO2 concentrations, particularly if the consistency (or inconsistency) between surface flux representations and atmospheric CO2 measurements can be linked back to representation of processes within the models. However, to do so effectively CMS-Flux needs to include a priori flux estimates that are more representative of our current understanding of landatmosphere sources and sinks than what is currently in the system. In other words, the a priori flux estimates need to be informed by the range of models used by the scientific community given that there is no consensus on the “best” model overall. CMS-Flux is currently limited with respect to the land surface bottom-up priors because: 1) it uses only two closely related land surface models, and as a result has a restricted representation of the “true” uncertainty in the land surface bottom-up fluxes; 2) the uncertainty in the bottom-up fluxes themselves is not quantified in the system; and, 3) the atmospheric inversion system is disconnected from the TBMs in that one unified system cannot currently be run. This proposed effort improves the current CMS-Flux product with four key advances. First, we propose to leverage the existing NASA funded MsTMIP activity to generate new a priori “bottom-up” land-surface flux products for the CMS-Flux system. Second, we will quantify uncertainties in a priori flux estimates. Third, we will develop the technical infrastructure of CMS-Flux to handle multiple land-surface models as priors. Four, we will combine the new a priori input products with the enhanced CMS infrastructure to test the influence of prior flux estimates (and their associated uncertainty) on posterior flux estimations from the inversion. Finally, the new infrastructure will also be used to compare existing terrestrial biospheric model estimates to the atmospheric CO2 constraints within CMS-Flux, providing another means of evaluating understanding of the processes controlling land-atmosphere carbon exchange. Combined, this proposed activity will expand the operational-use of CMS-Flux and allow for more robust posterior flux estimates and their associated uncertainties.
Project Associations:
  • CMS
CMS Primary Theme:
  • Land-Atmosphere Flux
CMS Science Theme(s):
  • Land-Atmosphere Flux

Participants:

Dominique Bachelet, Oregon State University
Joshua Fisher, Chapman University
Deborah (Debbie) Huntzinger, Northern Arizona University
Christopher Schwalm, Woodwell Climate Research Center

Project URL(s): None provided.
 
Data
Products:
Product Title:  CMS: Modeled Net Ecosystem Exchange at 3-hourly Time Steps, 2004-2010
Start Date:  01/2004      End Date:  12/2010     (2004-2010)
Description:  This data set provides global, gridded, model-derived net ecosystem exchange (NEE) of CO2 flux between the land and atmosphere at 3-hourly time steps over seven years (2004-2010) at three different spatial resolutions: 0.5 x 0.5 degree, 2.0 x 2.5 degrees, and 4.0 x 5.0 degrees (latitude/longitude). The 3-hourly data were derived from monthly NEE outputs of 15 global land surface models and four ensemble products in the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP).
Status:  Archived
CMS Science Theme(s):  Land-Atmosphere Flux
Keywords:  Flux/Movement (; terrestrial; ; atmospheric); ; Uncertainties & Standard Errors
Spatial Extent:  Global
Spatial Resolution:  0.5 x 0.5 degree; 2.0 x 2.5 degree; and 4.0 x 5.0 degree
Temporal Frequency:  3-hourly time steps
Input Data Products:  Simulation out from the Mulit-scale synthesis and model intercomparison project (MsTMIP) Version 1.0 (http://nacp.ornl.gov/mstmipdata/)
Algorithm/Models Used:  Multiple terrestrial biosphere models through MsTMIP
Evaluation:  Multiple benchmark datasets
Intercomparison Efforts/Gaps:  This project is based on an intercomparison.
Uncertainty Estimates:  Structural uncertainty from the multi-model ensemble for the GEOS-Chem atmospheric inversion model.
Uncertainty Categories:  model-model comparison
Application Areas:  - GHG emissions inventory; - Global carbon budget calculations; - Land management
Relevant Policies/Programs:  CMS FPP, Multi-Scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), Doha/Kyoto, NFMS
Potential Users:  Process-based and inversion modeling communities participating in MsTMIP, NASA CMS, and elsewhere, IPCC Task Force on National Greenhouse Gas Inventories (IPCC TFI), GEO, USFS
Stakeholders:  
Current Application Readiness Level:  5
Start Application Readiness Level:  1
Target Application Readiness Level:  6
Future Developments:  - PIntegrate findings into MsTMIP efforts.; - Publish findings in summer 2015.
Limitations:  - A community of models informs the uncertainty of the new land flux priors. Thus it captures the uncertainty associated with model choice (model structure). However, it likely does not capture the full extent of uncertainty in terrestrial net CO2 fluxes
Date When Product Available:  May 2016
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1315
Data Server URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1315

ftp://nacp.ornl.gov/synthesis/2009/reutlingen/CMS/updated_data_2014_OCT/
Archived Data Citation:  Fisher, J.B., M. Sikka, D.N. Huntzinger, C.R. Schwalm, J. Liu, Y. Wei, R.B. Cook, A.M. Michalak, K. Schaefer, A.R. Jacobson, M.A. Arain, P. Ciais, B. El-masri, D.J. Hayes, M. Huang, S. Huang, A. Ito, A.K. Jain, H. Lei, C. Lu, F. Maignan, J. Mao, N.C. Parazoo, C. Peng, S. Peng, B. Poulter, D.M. Ricciuto, H. Tian, X. Shi, W. Wang, N. Zeng, F. Zhao, and Q. Zhu. 2016. CMS: Modeled Net Ecosystem Exchange at 3-hourly Time Steps, 2004-2010. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1315

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

Product Title:  Atmospheric CO2 signals generated from 15 terrestrial biospheric models.
Time Period:  2009-2010
Description:  - Evaluate the consistency of MsTMIP model estimates with atmospheric CO2 observations, providing an additional benchmark of land-atmosphere model performance.
Status:  Public
CMS Science Theme(s):  Land-Atmosphere Flux
Keywords:  Flux/Movement (; terrestrial; ; atmospheric)
Spatial Extent:  Global
Spatial Resolution:  2° x 2.5°
Temporal Frequency:  Sub-daily
Input Data Products:  Simulation out from the Mulit-scale synthesis and model intercomparison project (MsTMIP) Version 1.0 (http://nacp.ornl.gov/mstmipdata/)
Algorithm/Models Used:  Multiple terrestrial biosphere models through MsTMIP
Evaluation:  Comparison with GOSAT
Intercomparison Efforts/Gaps:  This project is based on an intercomparison.
Uncertainty Estimates:  Structural uncertainty from the multi-model ensemble for the GEOS-Chem atmospheric inversion model.
Uncertainty Categories:  model-model comparison
Application Areas:  - GHG emissions inventory; - Global carbon budget calculations; - Land management
Relevant Policies/Programs:  CMS FPP, Multi-Scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), Doha/Kyoto, NFMS
Potential Users:  Process-based and inversion modeling communities participating in MsTMIP, NASA CMS, and elsewhere, IPCC Task Force on National Greenhouse Gas Inventories (IPCC TFI), GEO, USFS
Stakeholders:  
Current Application Readiness Level:  5
Start Application Readiness Level:  1
Target Application Readiness Level:  6
Future Developments:  Comparison with OCO-2
Limitations:  Based only on the MsTMIP models (surface fluxes) and on the atmospheric transport model (GEOS-CHEM).
Date When Product Available:  March 2018
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

ftp://ecco.jpl.nasa.gov/ECCO2/CMS/MsTMIP/forward
Data Server URL(s):

ftp://ecco.jpl.nasa.gov/ECCO2/CMS/MsTMIP/forward
Archived Data Citation:  

Product Title:  Updated estimates of terrestrial net CO2 fluxes inferred from the CMS inversion and informed by these new land flux priors.
Time Period:  2009-2010
Description:  - Develop the technical infrastructure of a carbon monitoring system to handle an integrated multiple land surface models system for operational use.
Status:  Public
CMS Science Theme(s):  Land-Atmosphere Flux
Keywords:  Flux/Movement (; terrestrial; ; atmospheric)
Spatial Extent:  Global
Spatial Resolution:  2° x 2.5°
Temporal Frequency:  Sub-daily
Input Data Products:  Simulation out from the Mulit-scale synthesis and model intercomparison project (MsTMIP) Version 1.0 (http://nacp.ornl.gov/mstmipdata/)
Algorithm/Models Used:  Multiple terrestrial biosphere models through MsTMIP
Evaluation:  
Intercomparison Efforts/Gaps:  This project is based on an intercomparison.
Uncertainty Estimates:  Structural uncertainty from the multi-model ensemble for the GEOS-Chem atmospheric inversion model.
Uncertainty Categories:  model-model comparison
Application Areas:  - GHG emissions inventory; - Global carbon budget calculations; - Land management
Relevant Policies/Programs:  CMS FPP, Multi-Scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), Doha/Kyoto, NFMS
Potential Users:  Process-based and inversion modeling communities participating in MsTMIP, NASA CMS, and elsewhere, IPCC Task Force on National Greenhouse Gas Inventories (IPCC TFI), GEO, USFS
Stakeholders:  
Current Application Readiness Level:  5
Start Application Readiness Level:  1
Target Application Readiness Level:  6
Future Developments:  Use in inverse modeling studies
Limitations:  - A community of models informs the uncertainty of the new land flux priors. Thus it captures the uncertainty associated with model choice (model structure). However, it likely does not capture the full extent of uncertainty in terrestrial net CO2 fluxes
Date When Product Available:  March 2018
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

ftp://ecco.jpl.nasa.gov/ECCO2/CMS/MsTMIP/Inversion
Data Server URL(s):

ftp://ecco.jpl.nasa.gov/ECCO2/CMS/MsTMIP/Inversion
Archived Data Citation:  

 
Publications: Jung, M., Reichstein, M., Schwalm, C. R., Huntingford, C., Sitch, S., Ahlstrom, A., Arneth, A., Camps-Valls, G., Ciais, P., Friedlingstein, P., Gans, F., Ichii, K., Jain, A. K., Kato, E., Papale, D., Poulter, B., Raduly, B., Rodenbeck, C., Tramontana, G., Viovy, N., Wang, Y., Weber, U., Zaehle, S., Zeng, N. 2017. Compensatory water effects link yearly global land CO2 sink changes to temperature. Nature. 541(7638), 516-520. DOI: 10.1038/nature20780

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

Archived Data Citations: Fisher, J.B., M. Sikka, D.N. Huntzinger, C.R. Schwalm, J. Liu, Y. Wei, R.B. Cook, A.M. Michalak, K. Schaefer, A.R. Jacobson, M.A. Arain, P. Ciais, B. El-masri, D.J. Hayes, M. Huang, S. Huang, A. Ito, A.K. Jain, H. Lei, C. Lu, F. Maignan, J. Mao, N.C. Parazoo, C. Peng, S. Peng, B. Poulter, D.M. Ricciuto, H. Tian, X. Shi, W. Wang, N. Zeng, F. Zhao, and Q. Zhu. 2016. CMS: Modeled Net Ecosystem Exchange at 3-hourly Time Steps, 2004-2010. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1315

5th NACP All-Investigators Meeting Posters (2015):
  • Current and future sensitivity of ecosystem productivity to precipitation in the humid United States -- (Jia Yang, Hanqin Tian, Wei Ren, Chaoqun Lu, Sebastian Wolf, Ankur Desai, Shufen Pan, Bo Tao, Bowen Zhang, Christopher Gough, Peter Blanken, Steven Lohrenz, Margaret Torn) [abstract]
2013 NASA Terrestrial Ecology Science Team Meeting Poster(s)
  • Multi-Scale Synthesis and Terrestrial Model Intercomparison Project – A Systematic Approach for Evaluating Land-Atmosphere Flux Estimates   --   (Deborah Nicole Huntzinger, Christopher R Schwalm, Anna M Michalak, Mac Post, Kevin M Schaefer, Andy Jacobson, Yaxing Wei, Robert B. Cook)   [abstract]


 

Jacob (CMS 2011) (2012)
Project Title:Use of GOSAT, TES, and Suborbital Observations to Constrain North American Methane Emissions in the Carbon Monitoring System

Science Team
Members:

Daniel Jacob, Harvard University (Project Lead)
Steven (Steve) Wofsy, Harvard University

Solicitation:NASA: Carbon Monitoring System (2011)
Abstract: We propose to contribute to the NASA Carbon Monitoring System (CMS) with a fourdimensional variational (4D-var) inverse modeling capability for methane emissions in North America integrating satellite (GOSAT, TES), aircraft (CalNex, HIPPO, NOAA/CCGG), and surface-based (TCCON, NOAA/CCGG) observations. Our work will build on the existing CMS capability at JPL for carbon flux inversions using the adjoint of the global GEOS-Chem chemical transport model (CTM). Here we will apply the adjoint of the nested version of GEOS-Chem with 1/2o × 2/3o (~50 × 50 km2) horizontal resolution over North America and adjacent oceans. The nested model will enable fine-scale constraints on methane sources through the 4D-var inversion. We will focus on 2009 2011 when data from both GOSAT and TES are available together with aircraft campaign data over the US from CalNex (May July 2010) and HIPPO (June September 2011). Combined use of GOSAT and TES data will enable us to separate boundary layer and free tropospheric contributions to the methane column through the inversion. The satellite data will be ingested in the 4D-var inverse model while the suborbital data will be used for independent analysis of the optimized methane fluxes. We will conduct a targeted analysis of the CalNex period to constrain methane sources in California by applying both Lagrangian (STILT) and Eulerian (GEOS-Chem) inverse modeling approaches to the aircraft and satellite data, testing the effect of different meteorological data sets and of different a priori constraints. This analysis will provide a unique opportunity to assess inverse modeling uncertainties related to resolution, data type (satellite or aircraft), meteorological model, and inversion procedure. We will use results from our continental-scale inversion of methane fluxes to better understand and quantify the major sources contributing to methane emissions in North America, and to provide guidance to the US EPA for improving its national emission inventories. The inverse modeling capability for methane will be implemented into the existing CMS Flux Pilot Project at JPL for consistent inversion of CO2 and methane fluxes over North America using the same 4D-var system. This will provide a powerful facility to monitor the fluxes of the two most important anthropogenic greenhouse gases. Our work will be directly responsive to major climate policy initiatives in the US targeting methane emissions including the Global Climate Change and Clean Air Initiative of the US State Department and the Global Methane Initiative of the U.S. EPA. P.I. Daniel Jacob and CoI Steve Wofsy will join the CMS Science Team as part of this project.
Project Associations:
  • CMS
CMS Primary Theme:
  • Land-Atmosphere Flux
CMS Science Theme(s):
  • Atmospheric Transport
  • Land-Atmosphere Flux
  • Decision Support

Participants:

Ramon Alvarez, Environmental Defense Fund
Jonathan Franklin, Harvard University
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)
Vivienne Payne, Jet Propulsion Laboratory / Caltech
Ben Ratner, Environmental Defense Fund
Alexander Turner, University of California
Kevin Wecht, Oxford Street Consultants
Melissa Weitz, U.S. EPA Climate Change Division
Steven (Steve) Wofsy, Harvard University

Project URL(s): None provided.
 
Data
Products:
Product Title:  CMS (Carbon Monitoring System) Methane (CH4) Flux for North America 0.5 degree x 0.667 degree V1 (CMS_CH4_FLX_NA) at GES DISC
Start Date:  01/2010      End Date:  01/2012     (2010-2012)
Description:  An error was found in this product; therefore, it has been deleted. Please use the CMS Methane (CH4) Flux for North America Daily product (CMS_CH4_FLX_NAD) in its place.

The CMS Methane (CH4) Flux for North America data set contains estimates of methane emission in North America based on an inversion of the GEOS-Chem chemical transport model constrained by Greenhouse Gases Observing SATellite (GOSAT) observations . The nested approach of the inversion enables large point sources to be resolved while aggregating regions with weak emissions and minimizing aggregation errors. The emission sources are separated into 9 different sectors as follows: Total, Wetlands, Livestock, Oil/Gas, Waste (Landfills wastewater), Coal, Rice, Open Fires, and Other. More details about the algorithm and error characterization can be found in (Turner, Jacob, Wecht, et al. 2015).

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
Keywords:  Source (; anthropogenic;; terrestrial)
Spatial Extent:  North America
Spatial Resolution:  1/2° x 2/3°; (~50km x 50km)
Temporal Frequency:  Monthly
Input Data Products:  GOSAT, TES, CalNex, HIPPO, NOAA/CCGG, TCCON
Algorithm/Models Used:  GEOS-Chem
Evaluation:  surface and aircraft sampling networks, TCCON
Intercomparison Efforts/Gaps:  SCIAMACHY
Uncertainty Estimates:  Formal uncertainty analysis from ensemble 4-D Var approach, evaluating with suborbital data sets
Uncertainty Categories:  ensemble
Application Areas:  - Fire management; - Air quality protection; - GHG emissions inventory; - Land management
Relevant Policies/Programs:  Global Climate Change and Clean Air Initiative of the US State Department, Global Methane Initiative of the US EPA, CAA, NGHGI, President Obama's Climate Action Plan (CAP), NALS
Potential Users:  Air quality agencies at both state and national levels (e.g. EPA, Iowa Department of Natural Resources), industry groups (e.g. American Petroleum Institute), US State Department
Stakeholders:  
Current Application Readiness Level:  5
Start Application Readiness Level:  1
Target Application Readiness Level:  9
Future Developments:  - Hold routine meetings with the NASA Air Quality Applied Sciences team: next meeting in June at Harvard University.; - Hold routine webinars with air quality agencies: most recent one with American Petroleum Institute, next one .; - Plan for next project
Limitations:  Not provided
Date When Product Available:  October 2016
Assigned Data Center:  GES DISC
Metadata URL(s):
DOI:10.5067/RF3R3G9I3UVX
Data Server URL(s):
DOI:10.5067/RF3R3G9I3UVX
Archived Data Citation:  Daniel Jacob (2016), Carbon Monitoring System (CMS) Methane (CH4) Flux for North America 0.5 degree x 0.667 degree V1, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed [Data Access Date] DOI: 10.5067/RF3R3G9I3UVX

Bounding Coordinates:
West Longitude:-140.00000 East Longitude:-40.00000
North Latitude:70.00000 South Latitude:10.00000

Product Title:  Methane (CH4) Flux for North America L4 Daily V1 (CMS_CH4_FLX_NAD) at GES DISC
Start Date:  01/2010      End Date:  12/2011     (2010-2011)
Description:  The CMS Methane (CH4) Flux for North America data set contains estimates of methane emission in North America based on an inversion of the GEOS-Chem chemical transport model constrained by Greenhouse Gases Observing SATellite (GOSAT) observations. The nested approach of the inversion enables large point sources to be resolved while aggregating regions with weak emissions and minimizing aggregation errors. The emission sources are separated into 12 different sectors as follows: Total, Oil/Gas, Coal, Cows, Waste (Landfills+ Wastewater), Biofuel, Rice, Other Anthropogenic, Biomass Burning, Wetlands, Soil Absorption, Other Natural. More details about the algorithm and error characterization can be found in Turner, Jacob, Wecht, et al. 2015.

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:  methane
Spatial Extent:  CONUS
Spatial Resolution:  0.5 x 0.667 degrees
Temporal Frequency:  daily
Input Data Products:  GOSAT, TES, CalNex, HIPPO, NOAA/CCGG, TCCON
Algorithm/Models Used:  GEOS-Chem
Evaluation:  surface and aircraft sampling networks, TCCON
Intercomparison Efforts/Gaps:  SCIAMACHY
Uncertainty Estimates:  Formal uncertainty analysis from ensemble 4-D Var approach, evaluating with suborbital data sets
Uncertainty Categories:  ensemble
Application Areas:  - Fire management; - Air quality protection; - GHG emissions inventory; - Land management
Relevant Policies/Programs:  Global Climate Change and Clean Air Initiative of the US State Department, Global Methane Initiative of the US EPA, CAA, NGHGI, President Obama's Climate Action Plan (CAP), NALS
Potential Users:  Air quality agencies at both state and national levels (e.g. EPA, Iowa Department of Natural Resources), industry groups (e.g. American Petroleum Institute), US State Department
Stakeholders:  
Current Application Readiness Level:  5
Start Application Readiness Level:  1
Target Application Readiness Level:  9
Future Developments:  
Limitations:  
Date When Product Available:  March 2018
Assigned Data Center:  GES DISC
Metadata URL(s):

https://disc.gsfc.nasa.gov/datasets/CMS_CH4_FLX_NAD_1/summary
Data Server URL(s):

https://disc.gsfc.nasa.gov/datasets/CMS_CH4_FLX_NAD_1/summary
Archived Data Citation:  Alex Turner & Daniel Jacob(2018), Methane (CH4) Flux for North America L4 Daily V1, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed [Data Access Date] 10.5067/GLUV19BRB081

Bounding Coordinates:
West Longitude:-140.00000 East Longitude:-40.00000
North Latitude:70.00000 South Latitude:10.00000

 
Publications: Barrera, Y. D., Nehrkorn, T., Hegarty, J., Sargent, M., Benmergui, J., Gottlieb, E., Wofsy, S. C., DeCola, P., Hutyra, L., Jones, T. 2019. Using Lidar Technology To Assess Urban Air Pollution and Improve Estimates of Greenhouse Gas Emissions in Boston. Environmental Science & Technology. 53(15), 8957-8966. DOI: 10.1021/acs.est.9b00650

Wecht, K. J., Jacob, D. J., Sulprizio, M. P., Santoni, G. W., Wofsy, S. C., Parker, R., Bosch, H., Worden, J. 2014. Spatially resolving methane emissions in California: constraints from the CalNex aircraft campaign and from present (GOSAT, TES) and future (TROPOMI, geostationary) satellite observations. Atmospheric Chemistry and Physics. 14(15), 8173-8184. DOI: 10.5194/acp-14-8173-2014

Wecht, K. J., Jacob, D. J., Frankenberg, C., Jiang, Z., Blake, D. R. 2014. Mapping of North American methane emissions with high spatial resolution by inversion of SCIAMACHY satellite data. Journal of Geophysical Research: Atmospheres. 119(12), 7741-7756. DOI: 10.1002/2014JD021551

Archived Data Citations: Daniel Jacob (2016), Carbon Monitoring System (CMS) Methane (CH4) Flux for North America 0.5 degree x 0.667 degree V1, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed [Data Access Date] DOI: 10.5067/RF3R3G9I3UVX

Alex Turner & Daniel Jacob(2018), Methane (CH4) Flux for North America L4 Daily V1, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed [Data Access Date] 10.5067/GLUV19BRB081


 

Kennedy (CMS 2011) (2012)
Project Title:Integrating and Expanding a Regional Carbon Monitoring System into the NASA CMS

Science Team
Members:

Robert Kennedy, Oregon State University (Project Lead)
Van Kane, University of Washington
Scott Powell, Montana State University

Solicitation:NASA: Carbon Monitoring System (2011)
Abstract: A key challenge in a carbon monitoring system is scaling thematically rich but highly localized information to the broad spatial scales needed for carbon accounting and management. This is particularly true for wooded ecosystems, where carbon storage potential is high, but actual carbon status is highly determined by local-scale environmental and forest management conditions. Through a USDA-NIFA funded project entitled Integrated, observation-based carbon monitoring for wooded lands of Washington, Oregon and California , our team is developing a system to integrate Landsat satellite imagery, maps of environmental characteristics, Forest Inventory and Analysis (FIA) plot data, small-footprint lidar data, and aerial photos to characterize key carbon dynamics in forested ecosystems across all ownerships in the states of Washington, Oregon, and California from 1985 to 2010. Key characteristics of our system include: ' Operational scaling of local-scale dynamics to all forests in Washington, Oregon, and California ' Yearly mapping of forest biomass and change in biomass from 1990 to 2010 ' Explicit characterization of cause of change ' Integration of USDA Forest Service Forest Inventory and Analysis (FIA) plot data ' Linkage of small-footprint lidar data with regional scale biomass maps ' Explicit quantification of methodological uncertainties for all estimates Because our approach addresses key challenges faced by the current NASA Carbon Monitoring System (CMS), we believe it has the potential to complement and aid NASA s mandate for operational carbon monitoring. To help reach that potential, we propose three activities. -- 1. We will utilize the products from our own carbon monitoring program in forests of Washington, Oregon, and California to evaluate, understand, and improve performance of the NASA CMS products, and compare a variety of national-scale products both to each other and to FIA plot estimates. -- 2. We will work with collaborators within the USDA FIA to extend our approaches to a different forest system, linking explicitly with the local-scale NASA CMS efforts in eastern forests. -- 3. Finally, we will bring our data, methods, and lessons-learned to NASA CMS Science Definition Team, and work closely with other SDT members to link our approaches into those analytical and modeling frameworks to further the overarching goals of the CMS. The following characteristics of our project are relevant to NASA s need to evaluate and improve its CMS: - Evaluating the utility and characterizing uncertainties in CMS products - Understanding scaling issues needed to link local to national scale products - Developing and demonstrating feasibility of alternative approaches to monitoring - Illustrating capabilities of satellite-based monitoring for science and management
Project Associations:
  • CMS
CMS Primary Theme:
  • Land Biomass
CMS Science Theme(s):
  • Land Biomass
  • Decision Support

Participants:

Van Kane, University of Washington
Robert Kennedy, Oregon State University
Scott Powell, Montana State University

Project URL(s): None provided.
 
Data
Products:
Product Title:  Forest biomass maps.
Time Period:  1990-2010
Description:  - Create a forest carbon monitoring system using Landsat, airborne Lidar, and field plot data for evaluation of other CMS biomass products.; - Test the carbon monitoring system (originally developed in western forests) in eastern U.S. forests.
Status:  Planned
CMS Science Theme(s):  Land Biomass
Keywords:  Carbon Stocks (; terrestrial)
Spatial Extent:  Washington, Oregon, and California
Spatial Resolution:  30 m
Temporal Frequency:  Annually
Input Data Products:  Landsat time series; Forest Inventory and Analysis plot data (all occasions); small-footprint, airborne discrete return Lidar data and associated field data.; ; Airborne Lidar data collection sites (2001 to 2010, depending on site, variable instruments): Cedar River, WA; Colville, WA; Coos Bay, OR; Deschutes National Forest, OR; Ellsworth, WA; Savanna River, GA/SC; Wind River, WA; Yosemite, CA; ; Area of Lidar data collection: Variable depending on the site, 2349 ha (Ellsworth) to 48,000 ha (Coos Bay)
Algorithm/Models Used:  Landsat analysis: LandTrendr time series algorithms; Lidar: various regression-based approaches; Imputation: canonical correspondence analysis, k-neighbor imputation
Evaluation:  Cross-validation of imputation models with observations using leave-one-out approaches; Comparison of Landsat-scale with lidar-scale biomass estimates at selected locations
Intercomparison Efforts/Gaps:  - Comparison to national scale maps (NBCD, FIA, CMS P1); ; - Comparison at select sites to lidar-based estimates
Uncertainty Estimates:  To characterize uncertainty in our core imputation steps, we will use the cross-validation results. That measure of uncertainty is aspatial, however. For spatially-explicit estimates of uncertainty, we will produce multiple runs of the entire prediction system for all pixels, and use the variability as an estimate of uncertainty. The multiple runs will vary in three categories: 1. different strategies for time-series analysis of Landsat imagery; 2. different approaches to drawing plot data in imputation space; 3. different allometric equations to convert plot-level tree data to plot-wide biomass estimates.
Uncertainty Categories:  model-model comparison
Application Areas:  - Fire management; - Forest inventory; - Land management ; - Invasive species; - Air quality protection
Relevant Policies/Programs:  USDA-NIFA project called Integrated, observation-based carbon monitoring for wooded lands of Washington, Oregon, and California, FIA, FLPMA
Potential Users:  USFS, Oregon Department of Forestry, Oregon Department of Fish and Wildlife, Washington State Department of Natural Resources, California Department of Forestry and Fire Protection, California Clean Air Resources Board
Stakeholders:  
Current Application Readiness Level:  3,4
Start Application Readiness Level:  1
Target Application Readiness Level:  6
Future Developments:  Most products now complete (March 2015), with validation and change agent mapping the last steps to complete
Limitations:  - Only focused on forests, incomparable to agricultural and urban areas.; - Empirical as opposed to mechanistic, constricted by FIA data.; - Biomass estimates are not likely to capture high biomass situations since they are fundamentally based in optical
Date When Product Available:  Anticipated posting on FTP sites by July 2015
Assigned Data Center:  ORNL DAAC
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  

Product Title:  Maps of forest disturbance by agent, severity, and timing.
Time Period:  1990-2010
Description:  - Test the carbon monitoring system (originally developed in western forests) in eastern U.S. forests.
Status:  Planned
CMS Science Theme(s):  Land Biomass
Keywords:  Disturbance (agent; severity; timing)
Spatial Extent:  Harvard Forest and environs (Massachusetts), Savanna River Forest and environs (South Carolina & Georgia)
Spatial Resolution:  30 m
Temporal Frequency:  Annually
Input Data Products:  Landsat time series
Algorithm/Models Used:  Landsat analysis: LandTrendr time series algorithms; Lidar: various regression-based approaches
Evaluation:  Point-based validation of disturbance
Intercomparison Efforts/Gaps:  None
Uncertainty Estimates:  Overall estimates of error from point-based disturbance methods
Uncertainty Categories:  model-data comparison
Application Areas:  - Fire management; - Forest inventory; - Land management ; - Invasive species; - Air quality protection
Relevant Policies/Programs:  USDA-NIFA project called Integrated, observation-based carbon monitoring for wooded lands of Washington, Oregon, and California, FIA, FLPMA
Potential Users:  USFS, Oregon Department of Forestry, Oregon Department of Fish and Wildlife, Washington State Department of Natural Resources, California Department of Forestry and Fire Protection, California Clean Air Resources Board
Stakeholders:  
Current Application Readiness Level:  1,2
Start Application Readiness Level:  1
Target Application Readiness Level:  6
Future Developments:  Basic mapping to be completed later this summer
Limitations:  Only maps of disturbance in forest
Date When Product Available:  Anticipated posting by September 2015
Assigned Data Center:  ORNL DAAC
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  

 
Publications: Bell, D. M., Gregory, M. J., Kane, V., Kane, J., Kennedy, R. E., Roberts, H. M., Yang, Z. 2018. Multiscale divergence between Landsat- and lidar-based biomass mapping is related to regional variation in canopy cover and composition. Carbon Balance and Management. 13(1). DOI: 10.1186/s13021-018-0104-6

Kennedy, R. E., Ohmann, J., Gregory, M., Roberts, H., Yang, Z., Bell, D. M., Kane, V., Hughes, M. J., Cohen, W. B., Powell, S., Neeti, N., Larrue, T., Hooper, S., Kane, J., Miller, D. L., Perkins, J., Braaten, J., Seidl, R. 2018. An empirical, integrated forest biomass monitoring system. Environmental Research Letters. 13(2), 025004. DOI: 10.1088/1748-9326/aa9d9e

Neeti, N., Kennedy, R. 2016. Comparison of national level biomass maps for conterminous US: understanding pattern and causes of differences. Carbon Balance and Management. 11(1). DOI: 10.1186/s13021-016-0060-y

2015 NASA Carbon Cycle & Ecosystems Joint Science Workshop Poster(s)
  • An integrated, observation-based system to monitor aboveground forest carbon dynamics in Washington, Oregon, and California   --   (Robert E Kennedy, Matthew Gregory, Janet L. Ohmann, Heather Roberts, Neeti Neeti, David Miller, Zhiqiang Yang, Warren B. Cohen, Van Kane, Jonathan Kane, Scott L. Powell)   [abstract]


 

Loboda (CMS 2011) (2012)
Project Title:The Forest Disturbance Carbon Tracking System -- A CMS Pilot Project

Science Team
Members:

Tatiana Loboda, University of Maryland (Project Lead)

Solicitation:NASA: Carbon Monitoring System (2011)
Abstract: Forest disturbances are a key process that drives significant variations in the terrestrial carbon budget for North America. While many NASA funded projects for the North American Carbon Program, as well as others funded by U.S. land management agencies, were focused on developing approaches to map forest disturbances, and assess the impacts of these disturbances on carbon cycling. However, efforts have not progressed enough to integrate the results from these efforts in order to provide a forest disturbance product that is useful for assessing the impacts of disturbances. The goal for this proposed Carbon Monitoring System (CMS) pilot project is to (1) develop a new regional carbon monitoring product that utilizes satellite remote sensing data to map forest disturbed area on an annual basis at medium resolution; and (2) to use this product as a basis for assessing the impacts of disturbance on forest carbon stocks for specific ecoregions of the United States. The development of the Forest Disturbance Carbon Tracking System (FDCTS) will provide an approach based on using a number of information products derived from remotely sensed data to address the following objectives: (a) Integrate a number of forest disturbance products in systematic fashion to create a map of the spatial and temporal extent of different forest disturbance events and episodes; and (b) Assess the impacts of these disturbances on key forest characteristics that control changes to carbon cycling (tree mortality, damage to branches and foliage, loss of live biomass, harvest removals, and combustion) for specific forest types in two North American forest ecoregions in order to produce a data product that depicts changes to forest carbon stocks on an annual basis for the ecoregions being studied. This CMS pilot project would focus on forest disturbances in two Level II U.S. ecoregions where disturbances have been dominant drivers of the terrestrial carbon cycle over the past decade: (a) the Western Cordillera ecoregion which has experienced major outbreaks of pine bark beetles as well as wildfire; and (b) the Alaska Boreal Interior ecoregion where burning of deep organic layers during fires represents the major impact on forest carbon cycles. As part of this pilot project, for each ecoregion, we would develop disturbance maps and forest impact products for the 2000s on an annual basis. The outputs from thithis CMS pilot project would be medium resolution (30 m) maps of all forest disturbances in the study ecoregions, which also contains data layers on pre-disturbance forest and carbon pool characteristics, the impacts of forest disturbances on carbon pools, and the amount of carbon remaining after the disturbances for specific pools. Within the climate change area, reliable and up-to-date information is needed on the terrestrial sources and sinks for a number of carbon-based greenhouse gases. The results from this pilot project will demonstrate a new approach for integrating multiple data sources to generate a product that quantifies the impacts of forest disturbance on the primary forest carbon pools. This new data product would not only provide the basis for providing inputs into models that quantify the impacts of disturbances on carbon cycling, but also to validate such models. The pilot project not only represents the first step towards creating national and continental-scale forest disturbance products, but also would provide the foundation for developing a system that would be able to quantify the impacts of forest disturbances on an annual basis going back thirty years to the mid-1980s (based on exploiting the Landsat TM/ETM+ data archive). Such an analysis would not only provide scientists, managers, and policy makers with clearer information on the integrated impacts of past disturbances, but the approach could be used to provide improved information on the impacts of forest disturbance on an annual basis.
Measurement Approaches:
  • Remote Sensing
  • Modeling
Project Associations:
  • CMS
CMS Primary Theme:
  • Land Biomass
CMS Science Theme(s):
  • Land Biomass
  • Land-Atmosphere Flux
  • Decision Support
Other Keywords:  Fire, carbon emissions, carbon pools

Participants:

Kirsten Barrett, University of Leicester
Nancy French, Michigan Tech Research Institute (MTRI)
Helene Genet, Institute of Arctic Biology
Elizabeth (Liz) Hoy, NASA GSFC / Global Science and Technology, Inc.
Chengquan (Cheng) Huang, University of Maryland
Tatiana Loboda, University of Maryland
Jeffrey (Jeff) Masek, NASA GSFC
A. (Dave) McGuire, USGS

Project URL(s): None provided.
 
Data
Products:
Product Title:  CMS: Fire Weather Indices for Interior Alaska, 2001-2010
Start Date:  01/2001      End Date:  09/2010     (2001-2010)
Description:  This dataset provides daily fire weather indices for interior Alaska during the active fire seasons from 2001 to 2010. Data are gridded at 60-m resolution. The active fire season is defined as May 24-September 18 (days of the year 144-261) in this dataset. Fire weather is the use of meteorological parameters such as relative humidity, wind speed and direction, cloud cover, mixing heights, and soil moisture to determine whether conditions are favorable for fire growth and smoke dispersion. The six indices provided in this dataset are defined and produced following the methodology of the Canadian Forest Fire Weather Index System: Fine Fuel Moisture Code, Duff Moisture Code, Drought Code, Initial Spread Index, Buildup Index, Fire Weather Index. The dataset was developed following point source data interpolation from weather station observations.
Status:  Archived
CMS Science Theme(s):  Decision Support; Land Biomass; Land-Atmosphere Flux
Keywords:  Disturbance (; severity)
Spatial Extent:  Interior Alaska
Spatial Resolution:  60 m
Temporal Frequency:  Daily, end of May through beginning of September for the years of 2001 through 2010
Input Data Products:  Remote Automated Weather Stations database
Algorithm/Models Used:  Canadian Forest Fire Danger Rating System protocol
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  - Fire management; - Forest inventory; - Land management
Relevant Policies/Programs:  FLPMA, SilvaCarbon, USCCSP, NACP
Potential Users:  Federal land management agencies in Alaska (i.e. USFS, BLM, Fish and Wildlife Service, Department of Defense, National Park Service, and EPA)
Stakeholders:  
Current Application Readiness Level:  1
Start Application Readiness Level:  1
Target Application Readiness Level:  1
Future Developments:  - Publish results by the end of 2015.
Limitations:  - uncertainty is associated with sparse network of point-source observations and spatial interpolation methods
Date When Product Available:  January 2018
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

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

https://doi.org/10.3334/ORNLDAAC/1509
Archived Data Citation:  Loboda, T.V., and E.E. Hoy. 2017. CMS: Fire Weather Indices for Interior Alaska, 2001-2010. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1509

Bounding Coordinates:
West Longitude:-171.59000 East Longitude:-131.80000
North Latitude:73.66000 South Latitude:56.62000

 
Publications: None provided.
Archived Data Citations: Loboda, T.V., and E.E. Hoy. 2017. CMS: Fire Weather Indices for Interior Alaska, 2001-2010. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1509

5th NACP All-Investigators Meeting Posters (2015):
  • The Alaska Forest Disturbance Carbon Tracking System -- (Tatiana Loboda, Eric S. Kasischke, A. David McGuire, Helene Genet, Elizabeth E Hoy) [abstract]
4th NACP All-Investigators Meeting Posters (2013):
  • Large emissions of carbon dioxide, carbon monoxide, and methane from Alaska boreal fires during the 2000s -- (Eric S. Kasischke, Elizabeth E Hoy, Merritt R. Turetsky, Evan Kane, William J deGroot, Nancy HF French) [abstract]


 

Lohrenz (CMS 2011) (2012)
Project Title:Development of Observational Products and Coupled Models of Land-Ocean-Atmospheric Fluxes in the Mississippi River Watershed and Gulf of Mexico in Support of Carbon Monitoring

Science Team
Members:

Steven (Steve) Lohrenz, University of Massachusetts (Project Lead)

Solicitation:NASA: Carbon Monitoring System (2011)
Abstract: Information about carbon fluxes in continental margins and linkages to terrestrial carbon cycles is key focus of NASA s Earth Science Research Program and a central aspect of NASA s Carbon Monitoring System. The uncertainties in coastal carbon fluxes are such that the net uptake of carbon in the coastal margins remains a poorly constrained term in global budgets. In particular, our ability to estimate current air-sea CO2 fluxes in continental margins is limited, and there is even less capability for predicting changes in the CO2 uptake capacity in coastal waters. The need to improve the understanding of coastal carbon dynamics and precision of estimates of coastal carbon fluxes has implications for attribution of land sources and sinks because atmospheric inversions are sensitive to uncertainties in coastal boundaries. Moreover, characterization of trends in carbon inventories reveal an increasing fraction of fossil fuel carbon is remaining in the atmosphere due to reductions in the efficiencies of ocean sinks and other sink processes not considered in current models. The proposed research will employ 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. Such information is critically needed to better constrain the contribution of coastal margins to carbon sources and sinks and improve capabilities to attribute sources and sinks to different regions as well as reducing uncertainties in estimates. The proposed effort will use a combination of observations and coupled terrestrial and ocean models to examine carbon processes and fluxes from the watershed to the continental margin. A major aspect of this proposed project will be to establish and populate geospatial portals for sharing and analysis of carbon datasets and products. The primary region of study will be the Mississippi River watershed and northern Gulf of Mexico. However, the model domain will also include the continental margins of Florida and the South Atlantic Bight. The region of study provides an excellent setting to carry out this work as there are a large number of supporting datasets and on-going programs that will complement this work. The proposed work is closely aligned with objectives of the NASA Carbon Monitoring System scoping effort and of the North American Carbon Program and will support National Climate Assessment activities. The effort will also contribute to NASA Coastal Carbon Synthesis effort and international efforts to develop a North American carbon budget (CarboNA). The unique nature of our approach, coupling models of terrestrial and ocean ecosystem dynamics and associated carbon processes, will allow for assessment of how societal and human-related LCLUC, as well as climate change, affects terrestrial carbon sources and sinks, export of materials to coastal margins, and associated carbon processes in the continental margins. Results would also benefit efforts to describe and predict how land cover and land use changes impact coastal water quality, including possible effects of coastal eutrophication, hypoxia, and ocean acidification.
Measurement Approaches:
  • Remote Sensing
  • In Situ Measurements
  • Modeling
Project Associations:
  • CMS
CMS Primary Theme:
  • Land-Ocean Flux
CMS Science Theme(s):
  • Ocean-Atmosphere Flux
  • Land-Ocean Flux
  • Decision Support

Participants:

Wei-Jun Cai, University of Delaware
Ruoying He, North Carolina State University & Fathom Science
Stephan Howden, University of Southern Mississippi
Steven (Steve) Lohrenz, University of Massachusetts
Chaoqun (Crystal) Lu, Iowa State University
Benjamin Pfeil, Surface Ocean Carbon Atlas (SOCAT)
Wei Ren, University of Kentucky
Hanqin Tian, Schiller Institute for Integrated Science and Society, Boston College

Project URL(s): None provided.
 
Data
Products:
Product Title:  Continental shelf-ocean exchanges of carbon and nitrogen
Time Period:  1904-1910, ; 2004-2010
Description:  1) MRB-C-Historical:
The variables include river discharge, dissolved inorganic carbon (DIC), dissolved organic carbon (DOC), particulate organic carbon (POC), and total organic carbon (TOC).

2) MRB-C-Future:
The variables include river discharge, and dissolved inorganic carbon (DIC).

3) MRB-N-Historical:
The variables include river discharge, dissolved inorganic nitrogen (i.e., NH4+ and NO3-), and total organic nitrogen (TON).
.
Status:  Preliminary
CMS Science Theme(s):  Land-Ocean Flux
Keywords:  Flux/Movement (; anthropogenic;; terrestrial; ; oceanic)
Spatial Extent:  Mississippi River Watershed and Gulf of Mexico, including continental margins of Florida and the South Atlantic Bight
Spatial Resolution:  5 km
Temporal Frequency:  Monthly
Input Data Products:  Various
Algorithm/Models Used:  DLEM, SABGOM, ROMS, other
Evaluation:  USGS monitoring data, 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:  - Land management; - Global carbon budget calculations; - Watershed protection plans; - Ocean acidification mitigation
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:  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:  4
Start Application Readiness Level:  1
Target Application Readiness Level:  4
Future Developments:  - Populate the geospatial portal with modeled and observational data products and uncertainties.Z4N
Limitations:  - Model validation is limited to locations and times when observational data were available. More model-data validation is needed to further refine the models and begin to evaluate future scenarios (e.g. climatic extremes).; - Since there is no available
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1699
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Land and ocean carbon inventories in continental US and South Atlantic Bight and Gulf of Mexico
Time Period:  1904-1910, ; 2004-2010
Description:  Spatial patterns in carbon and other products
Status:  Public
CMS Science Theme(s):  Land-Ocean Flux
Keywords:  Flux/Movement (; anthropogenic; terrestrial; ; oceanic)
Spatial Extent:  Mississippi River Watershed and Gulf of Mexico, including continental margins of Florida and the South Atlantic Bight
Spatial Resolution:  5 arc-minutes
Temporal Frequency:  Monthly
Input Data Products:  Various
Algorithm/Models Used:  DLEM, SABGOM, ROMS, other
Evaluation:  USGS monitoring data, 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:  - Land management; - Global carbon budget calculations; - Watershed protection plans; - Ocean acidification mitigation
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:  EPA (Mississippi River/Gulf of Mexico Watershed Nutrient Task Force), NOAA, USGS, US Global Change Research Program, CMS terrestrial flux teams
Stakeholders:  National Climate Assessment (Point of Contact: Fred Lipschultz, US Global Change Research Program, flipschultz@usgcrp.gov); USDA Environmental Markets Division (Point of Contact: Chris Hartley, chartley@oce.usda.gov)
Current Application Readiness Level:  4
Start Application Readiness Level:  1
Target Application Readiness Level:  4
Future Developments:  - Populate the geospatial portal with modeled and observational data products and uncertainties.
Limitations:  - Model validation is limited to locations and times when observational data were available. More model-data validation is needed to further refine the models and begin to evaluate future scenarios (e.g. climatic extremes).; - Since there is no available
Date When Product Available:  8/20/2014
Metadata URL(s):

http://webmap.ornl.gov/wcsdown/dataset.jsp?ds_id=20015
Data Server URL(s):

http://omgsrv1.meas.ncsu.edu:8080/ocean-circulation/carbon.jsp

http://webmap.ornl.gov/wcsdown/dataset.jsp?ds_id=20015
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

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     (1904-1910, ; 2004-2010)
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):  Ocean-Atmosphere Flux
Keywords:  Flux/Movement (; anthropogenic; oceanic; ; atmospheric)
Spatial Extent:  Mississippi River Watershed and Gulf of Mexico, including continental margins of Florida and the South Atlantic Bight
Spatial Resolution:  5 km
Temporal Frequency:  Monthly
Input Data Products:  Various
Algorithm/Models Used:  DLEM, SABGOM, ROMS, other
Evaluation:  USGS monitoring data, 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:  - Land management; - Global carbon budget calculations; - Watershed protection plans; - Ocean acidification mitigation
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:  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); Surface Ocean Carbon Atlas (SOCAT) (Point of Contact: Benjamin Pfeil, benjamin.pfeil@gfi.uib.no)
Current Application Readiness Level:  4
Start Application Readiness Level:  1
Target Application Readiness Level:  4
Future Developments:  - Populate the geospatial portal with modeled and observational data products and uncertainties.
Limitations:  - Model validation is limited to locations and times when observational data were available. More model-data validation is needed to further refine the models and begin to evaluate future scenarios (e.g. climatic extremes).; - Since there is no available
Date When Product Available:  10/1/2012
Assigned Data Center:  CDIAC
Metadata URL(s):

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

http://cdiac.ess-dive.lbl.gov/ftp/oceans/UG_GoM_UW_Data/2007.data/

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

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

http://cdiac.ess-dive.lbl.gov/ftp/oceans/UG_GoM_UW_Data/2007.data/

http://cdiac.ess-dive.lbl.gov/ftp/oceans/Cape_Hatteras_GM/
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.ess-dive.lbl.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

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.ess-dive.lbl.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

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:-93.43010 East Longitude:-87.33980
North Latitude:30.23490 South Latitude:28.17990

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:  Environmental managers, researchers, federal agencies including USGS, EPA, and NOAA
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

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

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

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

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

Cai, W., Arthur Chen, C. T., Borges, A. 2013. Carbon dioxide dynamics and fluxes in coastal waters influenced by river plumes in: Biogeochemical Dynamics at Major River-Coastal Interfaces. Cambridge University Press, 155-173. DOI: 10.1017/CBO9781139136853.010

Lohrenz, S. E., Cai, W., Chakraborty, S., Gundersen, K., Murrell, M. C. 2013. Nutrient and carbon dynamics in a large river-dominated coastal ecosystem: the Mississippi-Atchafalaya River system in: Biogeochemical Dynamics at Major River-Coastal Interfaces. Cambridge University Press, 448-472. DOI: 10.1017/CBO9781139136853.023

Huang, W., Cai, W., Castelao, R. M., Wang, Y., Lohrenz, S. E. 2013. Effects of a wind-driven cross-shelf large river plume on biological production and CO2 uptake on the Gulf of Mexico during spring. Limnology and Oceanography. 58(5), 1727-1735. DOI: 10.4319/lo.2013.58.5.1727

Xue, Z., He, R., Fennel, K., Cai, W., Lohrenz, S., Hopkinson, C. 2013. Modeling ocean circulation and biogeochemical variability in the Gulf of Mexico. Biogeosciences. 10(11), 7219-7234. DOI: 10.5194/bg-10-7219-2013

Liu, M., Tian, H., Yang, Q., Yang, J., Song, X., Lohrenz, S. E., Cai, W. 2013. Long-term trends in evapotranspiration and runoff over the drainage basins of the Gulf of Mexico during 1901-2008. Water Resources Research. 49(4), 1988-2012. DOI: 10.1002/wrcr.20180

Chen, G., Tian, H., Zhang, C., Liu, M., Ren, W., Zhu, W., Chappelka, A. H., Prior, S. A., Lockaby, G. B. 2012. Drought in the Southern United States over the 20th century: variability and its impacts on terrestrial ecosystem productivity and carbon storage. Climatic Change. 114(2), 379-397. DOI: 10.1007/s10584-012-0410-z

Guo, X., Cai, W., Huang, W., Wang, Y., Chen, F., Murrell, M. C., Lohrenz, S. E., Jiang, L., Dai, M., Hartmann, J., Lin, Q., Culp, R. 2011. Carbon dynamics and community production in the Mississippi River plume. Limnology and Oceanography. 57(1), 1-17. DOI: 10.4319/lo.2012.57.1.0001

Hopkinson, C. S., Cai, W., Hu, X. 2012. Carbon sequestration in wetland dominated coastal systems--a global sink of rapidly diminishing magnitude. Current Opinion in Environmental Sustainability. 4(2), 186-194. DOI: 10.1016/j.cosust.2012.03.005

Huang, W., Wang, Y., Cai, W. 2012. Assessment of sample storage techniques for total alkalinity and dissolved inorganic carbon in seawater. Limnology and Oceanography: Methods. 10(9), 711-717. DOI: 10.4319/lom.2012.10.711

Tian, H., Lu, C., Chen, G., Tao, B., Pan, S., Grosso, S. J. D., Xu, X., Bruhwiler, L., Wofsy, S. C., Kort, E. A., Prior, S. A. 2012. Contemporary and projected biogenic fluxes of methane and nitrous oxide in North American terrestrial ecosystems. Frontiers in Ecology and the Environment. 10(10), 528-536. DOI: 10.1890/120057

Tian, H., Chen, G., Zhang, C., Liu, M., Sun, G., Chappelka, A., Ren, W., Xu, X., Lu, C., Pan, S., Chen, H., Hui, D., McNulty, S., Lockaby, G., Vance, E. 2012. Century-Scale Responses of Ecosystem Carbon Storage and Flux to Multiple Environmental Changes in the Southern United States. Ecosystems. 15(4), 674-694. DOI: 10.1007/s10021-012-9539-x

Xu, X. F., Tian, H. Q., Chen, G. S., Liu, M. L., Ren, W., Lu, C. Q., Zhang, C. 2012. Multifactor controls on terrestrial N&lt;sub&gt;2&lt;/sub&gt;O flux over North America from 1979 through 2010. Biogeosciences. 9(4), 1351-1366. DOI: 10.5194/bg-9-1351-2012

Zhang, C., Tian, H., Chen, G., Chappelka, A., Xu, X., Ren, W., Hui, D., Liu, M., Lu, C., Pan, S., Lockaby, G. 2012. Impacts of urbanization on carbon balance in terrestrial ecosystems of the Southern United States. Environmental Pollution. 164, 89-101. DOI: 10.1016/j.envpol.2012.01.020

Tian, H., Chen, G., Lu, C., Xu, X., Hayes, D. J., Ren, W., Pan, S., Huntzinger, D. N., Wofsy, S. C. 2014. North American terrestrial CO2 uptake largely offset by CH4 and N2O emissions: toward a full accounting of the greenhouse gas budget. Climatic Change. 129(3-4), 413-426. DOI: 10.1007/s10584-014-1072-9

Tao, B., Tian, H., Ren, W., Yang, J., Yang, Q., He, R., Cai, W., Lohrenz, S. 2014. Increasing Mississippi river discharge throughout the 21st century influenced by changes in climate, land use, and atmospheric CO2. Geophysical Research Letters. 41(14), 4978-4986. DOI: 10.1002/2014GL060361

Chen, G., Tian, H., Huang, C., Prior, S. A., Pan, S. 2013. Integrating a process-based ecosystem model with Landsat imagery to assess impacts of forest disturbance on terrestrial carbon dynamics: Case studies in Alabama and Mississippi. Journal of Geophysical Research: Biogeosciences. 118(3), 1208-1224. DOI: 10.1002/jgrg.20098

Wang, Z. A., Wanninkhof, R., Cai, W., Byrne, R. H., Hu, X., Peng, T., Huang, W. 2013. The marine inorganic carbon system along the Gulf of Mexico and Atlantic coasts of the United States: Insights from a transregional coastal carbon study. Limnology and Oceanography. 58(1), 325-342. DOI: 10.4319/lo.2013.58.1.0325

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

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.ess-dive.lbl.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 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.ess-dive.lbl.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 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

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]
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]
4th NACP All-Investigators Meeting Posters (2013):
  • Impacts of terrestrial exports on carbon dynamics of the northern Gulf of Mexico -- (Wei-jun Cai) [abstract]
  • Impacts of Population Growth, Urbanization and Agricultural Expansion on Riverine Fluxes and Coastal Ecosystems in the Southeastern U.S. as assessed by the Coupled Land-Ocean Modeling System, Part 1: Riverine Flux Variations -- (Hanqin Tian, Ruoying He, Wei Ren, Bo Tao, Jia Yang, Chaoqun Lu, Qichun Yang, Bowen Zhang, Zuo Xue, Joseph Zambon, Wei-jun Cai, Steven Lohrenz) [abstract]
  • Impacts of Population Growth, Urbanization and Agricultural Expansion on Riverine Fluxes and Coastal Ecosystems in the Southeastern U.S. as assessed by the Coupled Land-Ocean Modeling System, Part 2: Marine Ecosystem Responses -- (Ruoying He, Hanqin Tian, Zuo Xue, Joseph Zambon, Zhigang Yao, Wei Ren, Chaoqun Lu, Bo Tao, Wei-jun Cai, Steven Lohrenz) [abstract]


 

Miller (CMS 2011) (2012)
Project Title:In Situ CO2-Based Evaluation of the Carbon Monitoring System Flux Product

Science Team
Members:

John Miller, NOAA Global Monitoring Laboratory (Project Lead)
Sourish Basu, NASA GSFC GMAO / University of Maryland

Solicitation:NASA: Carbon Monitoring System (2011)
Abstract: The fundamental objective of the NASA Carbon Monitoring System (CMS) flux product is to derive surface CO2 fluxes using satellite-based column CO2 mole fractions. Although the CMS flux product has an existing evaluation strategy, it is limited in scope and has acknowledged shortcomings, especially with regard to tropical carbon fluxes. Here, we propose to use the large number of high-accuracy, high-precision, globally distributed in situ tropospheric CO2 observations (including a unique set of tropical observations) to assess the realism of the optimized CMS fluxes and their stated uncertainties. First, CO2 observations will be compared directly with a posteriori CMS-modeled CO2 mole fractions. To first-order, near surface CO2 surpluses in the modeled CO2 mole fractions can be interpreted as excess positive surface flux, and vice versa. Second, CMS fluxes will be compared to fluxes derived from independent flux optimization systems (using in situ CO2 data). This more direct flux evaluation will be conducted globally using the CarbonTracker data assimilation system. Moreover, CarbonTracker will be run using multiple transport models to help assess the role of transport errors in the mismatch between simulation and observation. Additionally, in tropical South America we will use a state of the art regional flux inversion system to create a second set of fluxes, taking advantage of a two-year data set of fortnightly measurements in Brazil at four vertical profile sites and two additional surface sites. Tropical South America is of particular interest in global satellite-based inversions because of its disproportionate importance for the global carbon cycle combined with the anticipated seasonal biases in tropical satellite-based column CO2 arising from frequent cloud cover and high aerosol loadings. Working with the CMS flux product team, we will use the in situ CO2-based flux evaluations to diagnose shortcomings in the existing CMS flux optimization approach, transport parameterization and input GOSAT/ACOS CO2 columns. Finally, while we do expect OCO-2 to ultimately have better coverage than GOSAT over tropical South America, we still anticipate significant seasonal biases in sensitivity to Amazonian surface fluxes. To address this issue, and guard against biases in eventual CO2 flux optimization, we will produce an in situ CO2-optimized flux map for use as a prior in future CMS flux products. For any top-down CO2 flux estimation system, evaluation and uncertainty characterization is as important as the flux calculation itself, and the research proposed here will leverage the highest precision measurements in the global carbon cycle to assess the quality of the CMS flux product.
Project Associations:
  • CMS
CMS Primary Theme:
  • Land-Atmosphere Flux
CMS Science Theme(s):
  • Atmospheric Transport
  • Land-Atmosphere Flux

Participants:

Sourish Basu, NASA GSFC GMAO / University of Maryland
John Miller, NOAA Global Monitoring Laboratory

Project URL(s): None provided.
 
Data
Products:
Product Title:  A comparative evaluation of observed CO2 fluxes and a posteriori modeled CO2 fluxes from a CMS Bowman-01 flux product.
Time Period:  2009-2011
Description:  - Evaluate the CMS Bowman-01 flux product by using NOAA's in situ CO2 data.
Status:  Planned
CMS Science Theme(s):  Atmospheric Transport; Land-Atmosphere Flux
Keywords:  Flux/Movement (; anthropogenic; terrestrial; ; oceanic; ; atmospheric)
Spatial Extent:  Global
Spatial Resolution:  Variable
Temporal Frequency:  Weekly to Monthly
Input Data Products:  NOAA in situ CO2; IPEN (Brazil) in situ CO2
Algorithm/Models Used:  GEOS-Chem output (from Bowman-01 project)
Evaluation:  Evaluate the CMS Bowman-01 flux product by using NOAA's in situ CO2 data.
Intercomparison Efforts/Gaps:  Evaluate the CMS Bowman-01 flux product by using NOAA's in situ CO2 data.
Uncertainty Estimates:  distributions and summary stats of differences between observed and modeled CO2
Uncertainty Categories:  model-data comparison
Application Areas:  - MRV, REDD+; - GHG emissions inventory; - Land management
Relevant Policies/Programs:  NACP, USCCSP, IPCC
Potential Users:  CMS Bowman-01 Flux Product team
Stakeholders:  
Current Application Readiness Level:  1
Start Application Readiness Level:  1
Target Application Readiness Level:  1
Future Developments:  - Compare analysis with Bowman-01 team's results.
Limitations:  - Limited number of times and places for validating CMS Bowman-01 flux product.
Date When Product Available:  
Metadata URL(s):
Data Server URL(s):
Archived Data Citation:  

 
Publications: Alden, C. B., Miller, J. B., Gatti, L. V., Gloor, M. M., Guan, K., Michalak, A. M., Laan-Luijkx, I. T., Touma, D., Andrews, A., Basso, L. S., Correia, C. S. C., Domingues, L. G., Joiner, J., Krol, M. C., Lyapustin, A. I., Peters, W., Shiga, Y. P., Thoning, K., Velde, I. R., Leeuwen, T. T., Yadav, V., Diffenbaugh, N. S. 2016. Regional atmospheric CO 2 inversion reveals seasonal and geographic differences in Amazon net biome exchange. Global Change Biology. 22(10), 3427-3443. DOI: 10.1111/gcb.13305


 

Pawson (CMS 2011) (2012)
Project Title:GEOS-CARB: A Framework for Monitoring Carbon Concentrations and Fluxes

Science Team
Members:

Steven Pawson, NASA GSFC GMAO (Project Lead)
David Baker, CIRA/Colorado State University
Stephan (Randy) Kawa, NASA GSFC
Tomohiro (Tom) Oda, USRA

Solicitation:NASA: Carbon Monitoring System (2011)
Precursor Projects: Gunson-Pawson-Potter (2009)  
Abstract: This proposal is for a continuation of NASA GSFC s activities related to the Carbon Monitoring System, Flux Pilot Study (CMS FPP). The work will enhance and develop the capabilities of NASA s Goddard Earth Observing System (GEOS) set of models and assimilation components to further develop a core capability for CMS-related carbon cycle science and monitoring. The work consists of three components: (i) continuation of past work to compute atmosphere-ocean and atmosphere-land biosphere fluxes, as well as their evaluation using forward modeling in GEOS-5; (ii) enhancements of GEOS-5 for carbon monitoring, including a model study of the intermingling of uncertainties in anthropogenic and land-biospheric carbon emissions, and development of an enhanced assimilation capability to include multiple space-borne CO2 estimates (from AIRS and ACOS-GOSAT); (iii) a focused activity that examines aspects related to top-down (inverse) estimates of carbon fluxes. The latter effort will include a controlled comparison of three inverse estimates, including the one from CMS FPP, that use the same input data but use different methods. It also includes the implementation and application of a Lagrangian particle dispersion model to compute global footprints of GOSAT observations. Further, substantial new developments will be implemented into an existing variation inversion system. The work proposed in GEOS-CARB will implement and adapt various modeling and analysis tools, linking them closely with GEOS-5 systems available in the Global Modeling and Assimilation Office, in order to better exploit NASA s carbon-relevant observations for monitoring and understanding the global carbon cycle. The development work will leave NASA with enhanced modeling and analysis tools for carbon-cycle monitoring using space-based observations. These tools will be used to address some of the research questions that have arisen in the course of CMS FPP, with a strong emphasis on characterizing uncertainty in CO2 flux computations.
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:

David Baker, CIRA/Colorado State University
Watson Gregg, NASA GSFC
Stephan (Randy) Kawa, NASA GSFC
Christopher (Chris) O'Dell, Colorado State University
Tomohiro (Tom) Oda, USRA
Steven Pawson, NASA GSFC GMAO
Cecile Rousseaux, NASA GSFC
Andrew Schuh, Colorado State University
Brad Weir, NASA GSFC GMAO / GESTAR USRA

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:  

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:  

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:  

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:  

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:  

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:  

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:  

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:  

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:  

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:  

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:  

 
Publications: 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

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

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.

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

5th NACP All-Investigators Meeting Posters (2015):
  • The Effects of Chlorophyll Assimilation on Carbon Fluxes in a Global Biogeochemical Model -- (Cecile S. Rousseaux, Watson W. Gregg) [abstract]


 

Saatchi (CMS 2011) (2012)
Project Title:Prototyping MRV Systems Based on Systematic and Spatial Estimates of Carbon Stock and Stock Changes of Forestlands

Science Team
Members:

Sassan Saatchi, Jet Propulsion Laboratory / Caltech (Project Lead)
Sangram Ganguly, Rhombus Power Inc.
Nancy Harris, World Resources Institute
Ramakrishna (Rama) Nemani, NASA ARC

Solicitation:NASA: Carbon Monitoring System (2011)
Precursor Projects: Masek-Nemani-Saatchi-Tucker (2009)  
Successor Projects: Saatchi (CMS 2015)  
Abstract: Under phase I of the Carbon Monitoring System (CMS) Biomass Pilot Project, we developed a map of aboveground carbon stocks at 100-m spatial resolution using a combination of remote sensing products combined with ground inventory data. In phase II, we propose to build upon phase I by developing similar spatial products for carbon stocks in all pools (belowground biomass, dead wood, forest floor, soil organic carbon) for three points in time so that net annual carbon stock changes (fluxes) over time may be estimated spatially over US forestlands. Additionally, we propose to test a methodology for separating net flux into its component parts of gross emissions and gross removals to enable a better understanding of how forests should be managed to decrease emissions and increase removals. We will use remote sensing products to quantify areas of forest disturbance and change and develop a fully spatial framework for estimating GHG dynamics (i.e., gross emissions and removals). Our proposed methodology will follow the IPCC Good Practice Guidelines for national GHG accounting from the forest/land-use sector. The expected spatial framework will enable future integration of the proposed activities and products with the CMS Flux Pilot Project. It will also demonstrate a method by which spatial data and models can be integrated with ground data to prototype IPCC recommended Monitoring, Reporting and Verification (MRV) systems for reducing emissions from deforestation and forest degradation and increasing removals from enhancement of forest carbon stocks.
Measurement Approaches:
  • Remote Sensing
  • In Situ Measurements
  • Modeling
Project Associations:
  • CMS
CMS Primary Theme:
  • Land Biomass
CMS Science Theme(s):
  • Land Biomass
  • Land-Atmosphere Flux
  • MRV
Other Keywords:  Forest Biomass, Biomass Change, Carbon Pools, GHG, MRV

Participants:

Richard (Rich) Birdsey, Woodwell Climate Research Center
Andrew (Andy) Finley, Michigan State University
Alexander Fore, JPL
Sangram Ganguly, Rhombus Power Inc.
Stephen (Steve) Hagen, Applied Geosolutions
Nancy Harris, World Resources Institute
Kristofer (Kris) Johnson, USDA Forest Service
Ramakrishna (Rama) Nemani, NASA ARC
Sassan Saatchi, Jet Propulsion Laboratory / Caltech
Christopher (Chris) Woodall, USDA Forest Service
Yifan Yu, UCLA

Project URL(s): http://carbon.jpl.nasa.gov/
http://carbon.nasa.gov/
 
Data
Products:
Product Title:  Disturbance layers (time since disturbance, recovery rate, disturbance severity)
Time Period:  Updates forthcoming
Description:  Updates forthcoming
Status:  Planned
CMS Science Theme(s):  Land Biomass
Keywords:  Disturbance (timing; severity; recovery rate)
Spatial Extent:  CONUS and Alaska
Spatial Resolution:  Updates forthcoming
Temporal Frequency:  Updates forthcoming
Input Data Products:  Updates forthcoming
Algorithm/Models Used:  Updates forthcoming
Evaluation:  Updates forthcoming
Intercomparison Efforts/Gaps:  Updates forthcoming
Uncertainty Estimates:  Updates forthcoming
Uncertainty Categories:  Updates forthcoming
Application Areas:  - MRV; - Forest inventory; - Land management
Relevant Policies/Programs:  NGHGI, CAP, IPCC Good Practice Guidance for Land, Use, Land-Use Change, and Forestry (IPCC GPG), FIA, NFMS
Potential Users:  USGS, USFS, EPA, President's Interagency Climate Change Adaptation Task Force
Stakeholders:  
Current Application Readiness Level:  6,7
Start Application Readiness Level:  3
Target Application Readiness Level:  8,9
Future Developments:  Updates forthcoming
Limitations:  Updates forthcoming
Date When Product Available:  Updates forthcoming
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:  CMS: Forest Carbon Stocks, Emissions, and Net Flux for the Conterminous US: 2005-2010
Start Date:  01/2005      End Date:  12/2010     (2005-2010)
Description:  This data set provides maps of estimated carbon in forests of the 48 continental states of the US for the years 2005-2010. Carbon (termed committed carbon) stocks were estimated for forest aboveground biomass, belowground biomass, standing dead stems, and litter for the year 2005. Carbon emissions were estimated from land use conversion to agriculture, insect damage, logging, wind, and weather events in the forests for the years 2006 - 2010. Committed net carbon flux was estimated as the sum of carbon emissions and sequestration. The maps are provided at 100-m spatial resolution in GeoTIFF format. Average annual carbon estimates, by US county, for (1) emissions for the multiple disturbance sources, (2) sequestration, and (3) the committed net carbon flux are provided in an ESRI shapefile.
Status:  Archived
CMS Science Theme(s):  Land Biomass
Keywords:  Carbon Stocks (; terrestrial)
Spatial Extent:  CONUS (all carbon pools) and Alaska (only AGB and BGB)
Spatial Resolution:  100-m resolution and county level
Temporal Frequency:  Annual
Input Data Products:  GLAS, FIA, Dubayah-03 product (wall-to-wall airborne Lidar map of the state of Maryland), Landsat 5 & 7 Derived LAI, Landsat 8 (NLCD 2014), Landsat 7 (NLCD 2006), MODIS VI/ Reflectance, ALOS PALSAR, SRTM, USFS Carbon Pool
Algorithm/Models Used:  Maxent, Leaf Area Index Radiative Transfer Model, Radar Backscatter Model
Evaluation:  Updates forthcoming
Intercomparison Efforts/Gaps:  Updates forthcoming
Uncertainty Estimates:  Produce error propagation and uncertainty analysis for all carbon stock and stock change calculations. The bootstrapping approach to uncertainty assessment will be used. Estimate statistical uncertainty bounds associated with the final forest carbon stock and change estimates using a randomized, Monte Carlo-style sampling technique. The bootstrapping will be performed on each individual model component used in generating the gridded forest carbon estimates. The major individual model components for which we will conduct this procedure include: (a) the allometry models relating forest structure to biomass (USFS-FIA); (b) the model relating FIA estimated above-ground biomass to the remotely sensed observations; (c) the relationship between above and below-ground biomass (USFS-FIA); (d) the spatial modeling for extrapolating litter, CWD, and SOC; and (e) the model for estimating forest loss/recovery from remote sensing observations.
Uncertainty Categories:  ensemble
Application Areas:  - MRV; - Forest inventory; - Land management
Relevant Policies/Programs:  NGHGI, CAP, IPCC Good Practice Guidance for Land, Use, Land-Use Change, and Forestry (IPCC GPG), FIA, NFMS
Potential Users:  USGS, USFS, EPA, President's Interagency Climate Change Adaptation Task Force
Stakeholders:  
Current Application Readiness Level:  6,7
Start Application Readiness Level:  3
Target Application Readiness Level:  8,9
Future Developments:  - By the end of February 2014, provide USFS with new Alaska maps.; - Collaborate on the CMS Carbon Calculator project (Riley-01).
Limitations:  - The spatial resolution of soil carbon data is variable – may not be 100 m everywhere.
Date When Product Available:  June 2016
Metadata URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1313
Data Server URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1313
Archived Data Citation:  Hagen, S., N. Harris, S.S. Saatchi, T. Pearson, C.W. Woodall, S. Ganguly, G.M. Domke, B.H. Braswell, B.F. Walters, J.C. Jenkins, S. Brown, W.A. Salas, A. Fore, Y. Yu, R.R. Nemani, C. Ipsan, and K.R. Brown. 2016. CMS: Forest Carbon Stocks, Emissions, and Net Flux for the Conterminous US: 2005-2010. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1313

Bounding Coordinates:
West Longitude:-136.15000 East Longitude:-55.85000
North Latitude:50.00000 South Latitude:19.29000

Product Title:  CMS: Forest Carbon Stocks, Emissions, and Net Flux for the Conterminous US: 2005-2010
Start Date:  01/2005      End Date:  12/2010     (2000-2010)
Description:  This data set provides maps of estimated carbon in forests of the 48 continental states of the US for the years 2005-2010. Carbon (termed committed carbon) stocks were estimated for forest aboveground biomass, belowground biomass, standing dead stems, and litter for the year 2005. Carbon emissions were estimated from land use conversion to agriculture, insect damage, logging, wind, and weather events in the forests for the years 2006 - 2010. Committed net carbon flux was estimated as the sum of carbon emissions and sequestration. The maps are provided at 100-m spatial resolution in GeoTIFF format. Average annual carbon estimates, by US county, for (1) emissions for the multiple disturbance sources, (2) sequestration, and (3) the committed net carbon flux are provided in an ESRI shapefile.
Status:  Archived
CMS Science Theme(s):  Land-Atmosphere Flux
Keywords:  Flux/Movement (; anthropogenic; terrestrial; ; atmospheric)
Spatial Extent:  CONUS and Alaska
Spatial Resolution:  100 m
Temporal Frequency:  2000-2005, 2005-2010
Input Data Products:  GLAS, FIA, Dubayah-03 product (wall-to-wall airborne Lidar map of the state of Maryland), Landsat 5 & 7 Derived LAI, Landsat 8 (NLCD 2014), Landsat 7 (NLCD 2006), MODIS VI/ Reflectance, ALOS PALSAR, SRTM, USFS Carbon Pool
Algorithm/Models Used:  Maxent, Leaf Area Index Radiative Transfer Model, Radar Backscatter Model
Evaluation:  Updates forthcoming
Intercomparison Efforts/Gaps:  Updates forthcoming
Uncertainty Estimates:  Produce error propagation and uncertainty analysis for all carbon stock and stock change calculations. The bootstrapping approach to uncertainty assessment will be used. Estimate statistical uncertainty bounds associated with the final forest carbon stock and change estimates using a randomized, Monte Carlo-style sampling technique. The bootstrapping will be performed on each individual model component used in generating the gridded forest carbon estimates. The major individual model components for which we will conduct this procedure include: (a) the allometry models relating forest structure to biomass (USFS-FIA); (b) the model relating FIA estimated above-ground biomass to the remotely sensed observations; (c) the relationship between above and below-ground biomass (USFS-FIA); (d) the spatial modeling for extrapolating litter, CWD, and SOC; and (e) the model for estimating forest loss/recovery from remote sensing observations.
Uncertainty Categories:  ensemble
Application Areas:  - MRV; - Forest inventory; - Land management
Relevant Policies/Programs:  NGHGI, CAP, IPCC Good Practice Guidance for Land, Use, Land-Use Change, and Forestry (IPCC GPG), FIA, NFMS
Potential Users:  USGS, USFS, EPA, President's Interagency Climate Change Adaptation Task Force
Stakeholders:  
Current Application Readiness Level:  6,7
Start Application Readiness Level:  3
Target Application Readiness Level:  8,9
Future Developments:  Updates forthcoming
Limitations:  Updates forthcoming
Date When Product Available:  June 2016
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1313
Data Server URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1313
Archived Data Citation:  Hagen, S., N. Harris, S.S. Saatchi, T. Pearson, C.W. Woodall, S. Ganguly, G.M. Domke, B.H. Braswell, B.F. Walters, J.C. Jenkins, S. Brown, W.A. Salas, A. Fore, Y. Yu, R.R. Nemani, C. Ipsan, and K.R. Brown. 2016. CMS: Forest Carbon Stocks, Emissions, and Net Flux for the Conterminous US: 2005-2010. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1313

Bounding Coordinates:
West Longitude:-136.15000 East Longitude:-55.85000
North Latitude:50.00000 South Latitude:19.29000

Product Title:  CMS: Terrestrial Carbon Stocks, Emissions, and Fluxes for Conterminous US, 2001-2016
Start Date:  01/2001      End Date:  12/2016     (2001-2016)
Description:  This dataset provides estimates of carbon pools, fluxes, and associated uncertainties across the contiguous USA (CONUS) at 0.5-degree resolution for all terrestrial land cover types. Carbon pools include labile carbon, foliar carbon, fine root, woody carbon, litter carbon, and soil organic carbon. Carbon fluxes include gross primary production (GPP), net primary production (NPP), net biome exchange, autotrophic respiration, and heterotrophic respiration. The modeled estimates are provided as monthly averages over the 16-year period, 2001 through 2016. The data were derived from the CARbon DAta MOdel fraMework (CARDAMOM) that included climate data, and above and below ground biomass maps of CONUS for the years 2005, 2010, 2015 and 2016 as input data sources to this model-data fusion framework. The input data were integrated into the CARDAMOM model to constrain on the terrestrial carbon and to specifically attribute changes of forest carbon stocks and spatial distributions of carbon emissions and removals across forested lands. United States Forest Service's Forest Inventory and Analysis (FIA) plot data were used to train models for the prediction of forest above-ground biomass (AGB).
Status:  Archived
CMS Science Theme(s):  Land Biomass; Land-Atmosphere Flux
Keywords:  Carbon Stocks (; terrestrial) Flux/Movement (; anthropogenic; terrestrial; ; atmospheric)
Spatial Extent:  Conterminous U.S.
Spatial Resolution:  monthly
Temporal Frequency:  Half-degree
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:  3
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/1837
Data Server URL(s):

https://doi.org/10.3334/ORNLDAAC/1837
Archived Data Citation:  Yang, Y., and S.S. Saatchi. 2020. CMS: Terrestrial Carbon Stocks, Emissions, and Fluxes for Conterminous US, 2001-2016. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1837

Bounding Coordinates:
West Longitude:-130.00000 East Longitude:-60.00000
North Latitude:50.00000 South Latitude:25.00000

 
Publications: 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

Junttila, V., Finley, A. O., Bradford, J. B., Kauranne, T. 2013. Strategies for minimizing sample size for use in airborne LiDAR-based forest inventory. Forest Ecology and Management. 292, 75-85. DOI: 10.1016/j.foreco.2012.12.019

Babcock, C., Matney, J., Finley, A. O., Weiskittel, A., Cook, B. D. 2013. Multivariate Spatial Regression Models for Predicting Individual Tree Structure Variables Using LiDAR Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 6(1), 6-14. DOI: 10.1109/JSTARS.2012.2215582

Finley, A. O., Banerjee, S., Cook, B. D., Bradford, J. B. 2013. Hierarchical Bayesian spatial models for predicting multiple forest variables using waveform LiDAR, hyperspectral imagery, and large inventory datasets. International Journal of Applied Earth Observation and Geoinformation. 22, 147-160. DOI: 10.1016/j.jag.2012.04.007

Guhaniyogi, R., Finley, A. O., Banerjee, S., Kobe, R. K. 2013. Modeling Complex Spatial Dependencies: Low-Rank Spatially Varying Cross-Covariances With Application to Soil Nutrient Data. Journal of Agricultural, Biological, and Environmental Statistics. 18(3), 274-298. DOI: 10.1007/s13253-013-0140-3

Archived Data Citations: Hagen, S., N. Harris, S.S. Saatchi, T. Pearson, C.W. Woodall, S. Ganguly, G.M. Domke, B.H. Braswell, B.F. Walters, J.C. Jenkins, S. Brown, W.A. Salas, A. Fore, Y. Yu, R.R. Nemani, C. Ipsan, and K.R. Brown. 2016. CMS: Forest Carbon Stocks, Emissions, and Net Flux for the Conterminous US: 2005-2010. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1313

Yang, Y., and S.S. Saatchi. 2020. CMS: Terrestrial Carbon Stocks, Emissions, and Fluxes for Conterminous US, 2001-2016. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1837

2015 NASA Carbon Cycle & Ecosystems Joint Science Workshop Poster(s)
  • The New Forest Carbon Accounting Framework of the US and NASA Carbon Cycle Science: Identifying Concomitant Knowledge Gaps and Research Opportunities   --   (Sean P Healey, Christopher W. Woodall, Grant M Domke, John Coulston, Brian F Walters, James A Smith, Andy Gray)   [abstract]
4th NACP All-Investigators Meeting Posters (2013):
  • Estimation of Aboveground Biomass at a High Spatial Resolution Using an Extensive Data Record of Satellite Derived Metrics: A Case Study with California -- (Sangram Ganguly, Gong Zhang, Ramakrishna R. Nemani, Sassan Saatchi, Cristina Milesi, Michael White, Yifan Yu, Alexander Fore, Weile Wang, Petr Votava, Ranga B. Myneni) [abstract]
  • Decision Support and Robust Estimation of Uncertainty in Carbon Stocks and Fluxes -- (Stephen Hagen, Nancy Harris, Sassan Saatchi, William A. Salas, Sangram Ganguly, Christopher W. Woodall) [abstract]   [poster]


 

Shuchman (CMS 2011) (2012)
Project Title:Development of New Regional Carbon Monitoring Products for the Great Lakes Using Satellite Remote Sensing Data

Science Team
Members:

Robert (Bob) Shuchman, Michigan Technological University (Project Lead)
Gary Fahnenstiel, Michigan Technological University

Solicitation:NASA: Carbon Monitoring System (2011)
Successor Projects: Sayers (CMS 2016)  
Abstract: The Great Lakes represent approximately 20% of Earth's surface freshwater and are the largest surface area of freshwater on the planet. Understanding the magnitude of the contribution that the Great Lakes make to Earth's carbon budget is important to regional, national, and international carbon monitoring efforts. Quantifying the annual carbon fixation for each of the five Great Lakes as well as determining which of the Lakes are carbon sinks versus sources will be a significant contribution to the overall understanding of the Earth's carbon budget. Despite the large number of in situ based productivity measurements made at selected locations and limited times during the year in the Great Lakes, a strong case can be made that accurate annual lake-wide estimates of primary production do not exist for any of the Great Lakes. Thus, a new approach using satellite data is needed to provide truly lake-wide primary production in these important large ecosystems. This proposed satellite based program will result in new regional carbon monitoring products that will characterize each Laurentian Great Lake's annual carbon fixation and additionally address whether each Great Lake is a net source or sink of carbon. This will be accomplished through characterization of phytoplankton primary production (PP) using a new Great Lakes Primary Productivity Model (GLPPM). The GLPPM utilizes NASA OceanColor satellite imagery (MODIS, VIIRS). Additionally, aggregating annual PP for all five lakes will give insight into whether the Great Lakes are as a whole is a source or sink of carbon and to determine the significance of the Great Lakes to Earth's total carbon budget. Individual Great Lakes annual carbon production information will also be invaluable input into high resolution regional carbon models. A key element to the success of this program includes additional field measurements in Lakes Superior, Michigan, Huron and Great Lakes embayments. These in situ observations will be used to better quantify carbon fixation rates that are key to producing accurate carbon estimation products. Additionally the field data will aid in the product accuracy assessment. In summary, monthly and annual carbon production products for each of the five Great Lakes generated under this program will be provided to stakeholders via an active data sharing program within NOAA/Great Lakes Environmental Research Lab (GLERL) and the Great Lakes Observing System (GLOS). A key to providing this valuable data for decision makers, scientists, the public, and other stakeholders will be rigorous error quantification and accuracy assessment.
Project Associations:
  • CMS
CMS Primary Theme:
  • Ocean-Atmosphere Flux
CMS Science Theme(s):
  • Lake Biomass
  • Ocean Biomass
  • Ocean-Atmosphere Flux

Participants:

Gary Fahnenstiel, Michigan Technological University
Robert (Bob) Shuchman, Michigan Technological University

Project URL(s): None provided.
 
Data
Products:
Product Title:  Lake-wide primary production estimates for all five Great Lakes in the U.S.
Time Period:  2002-2014
Description:  - Develop new satellite-derived primary production estimate for Great Lakes. ; - Conduct historical analysis of primary production and key input parameters (i.e., chlorophyll, KdPAR, and PAR).

cite these data as
Shuchman, R.A., Fahnenstiel, G.L., Sayers, M. 2015. Great Lakes Primary Production Estimates 2002-2014 From New Great Lakes Primary Production model (GLPPM). Data Set. Program Website: http://mtri.org/glppm.html
Status:  Preliminary
CMS Science Theme(s):  Lake Biomass; Ocean Biomass; Ocean-Atmosphere Flux
Keywords:  Carbon Stocks (; inland & coastal water)
Spatial Extent:  Laurentian Great Lakes
Spatial Resolution:  1 km
Temporal Frequency:  Annually – time series for Lakes Michigan, Superior, and Huron: 2002-2014; ; Monthly – seasonal analysis for upper three Lakes: only 2011
Input Data Products:  Ocean color satellite data, carbon fixation rate data
Algorithm/Models Used:  Great Lakes Primary Production Model (GLPPM)
Evaluation:  NOAA GLERL in situ monitoring data
Intercomparison Efforts/Gaps:  Comparisons to Lakes Michigan, Huron and Superior measurements and other Great Lakes observations.
Uncertainty Estimates:  Preliminary evaluation of errors will be made with comparisons to observations. Pixel level uncertainty and production model uncertainty will be evaluated with Monte Carlo simulation and modeling.
Uncertainty Categories:  model-data comparison
Application Areas:  - Watershed protection plans; - Global carbon budget calculations; - Coastal land management
Relevant Policies/Programs:  EPA's State of the Lakes Ecosystem (SOLEC), EPA's Great Lakes Restoration Initiative, Great Lakes Binational Toxics Strategy, NGHGI, CAP, CAA, CWA, NALS, Doha/Kyoto
Potential Users:  Michigan Department of Environmental Quality; Great Lakes Observing System (GLOS); US National Park Service; USGS; NOAA; US Coast Guard; EPA Regions 2, 3, & 5; Illinois, Indiana, Michigan, Pennsylvania, New York, Wisconsin, Minnesota, & Ohio Departments of Natural Resources or equivalent agencies; Environment Canada; Great Lakes Fishery Commission
Stakeholders:  
Current Application Readiness Level:  5
Start Application Readiness Level:  2
Target Application Readiness Level:  5
Future Developments:  - Hold meetings with NOAA Great Lakes Environmental Lab, EPA, USGS, Michigan Departments of Natural Resources and Environmental Quality, and US National Park Service.; - Post data on GLOS by the end of 2014.; - Publish results in 2014.
Limitations:  - limited Ground-based data to validate satellite and model derived measurements, both spatially and temporally.
Date When Product Available:  2002-2014 Monthly Average PP maps for Lakes Michigan, Superior, and Huron available April 2015
Assigned Data Center:  Goddard
Metadata URL(s):
Data Server URL(s):

http://www.greatlakesremotesensing.org/
Archived Data Citation:  
Bounding Coordinates:
West Longitude:0.00000 East Longitude:0.00000
North Latitude:0.00000 South Latitude:0.00000

Product Title:  Carbon Monitoring System Lake Huron Primary Production Monthly V1 (CMSLakeHuronPPM) at GES DISC
Start Date:  01/2010      End Date:  12/2013     (2010-2013)
Description:  Monthly Average primary production/carbon fixation data for Lake Huron. The primary production data is derived using MODIS imagery with model data.

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):  Lake Biomass; Ocean Biomass; Ocean-Atmosphere Flux
Keywords:  Carbon Stocks (; inland & coastal water)
Spatial Extent:  Lake Huron
Spatial Resolution:  0.01 degree x 0.01 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:  5
Start Application Readiness Level:  2
Target Application Readiness Level:  5
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  GES DISC
Metadata URL(s):
10.5067/CZ39JIR4ZAT4
Data Server URL(s):
10.5067/CZ39JIR4ZAT4
Archived Data Citation:  Gary L. Fahnenstiel, Michael J. Sayers, Robert A. Shuchman, Foad Yousef, & Steven A. Pothoven (2019), Carbon Monitoring System Lake Huron Primary Production Monthly, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/CZ39JIR4ZAT4

Bounding Coordinates:
West Longitude:-84.76200 East Longitude:-79.65200
North Latitude:46.59100 South Latitude:43.00100

Product Title:  Carbon Monitoring System Lake Huron Primary Production Yearly V1 (CMSLakeHuronPPY) at GES DISC
Start Date:  01/2010      End Date:  12/2013     (2010-2013)
Description:  Yearly Average primary production/carbon fixation data for Lake Huron. The primary production data is derived using MODIS imagery with model data.

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):  Lake Biomass; Ocean Biomass; Ocean-Atmosphere Flux
Keywords:  Carbon Stocks (; inland & coastal water)
Spatial Extent:  Lake Huron
Spatial Resolution:  0.01 degree x 0.01 degree
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:  5
Start Application Readiness Level:  2
Target Application Readiness Level:  5
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  GES DISC
Metadata URL(s):
10.5067/11TMFK7VSHDY
Data Server URL(s):
10.5067/11TMFK7VSHDY
Archived Data Citation:  Gary L. Fahnenstiel, Michael J. Sayers, Robert A. Shuchman, Foad Yousef, & Steven A. Pothoven (2019), Carbon Monitoring System Lake Huron Primary Production Yearly, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/11TMFK7VSHDY

Bounding Coordinates:
West Longitude:-84.76200 East Longitude:-79.65200
North Latitude:46.59100 South Latitude:43.00100

Product Title:  Carbon Monitoring System Lake Michigan Primary Production Monthly V1 (CMSLakeMichiganPPM) at GES DISC
Start Date:  01/2010      End Date:  12/2013     (2010-2013)
Description:  Monthly Average primary production/carbon fixation data for Lake Michigan. The primary production data is derived using MODIS imagery with model data.

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):  Lake Biomass; Ocean Biomass
Keywords:  Carbon Stocks (; inland & coastal water)
Spatial Extent:  Lake Michigan
Spatial Resolution:  0.01 degree x 0.01 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:  5
Start Application Readiness Level:  2
Target Application Readiness Level:  5
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  GES DISC
Metadata URL(s):
10.5067/5AZRS4SRGS1R
Data Server URL(s):
10.5067/5AZRS4SRGS1R
Archived Data Citation:  Gary L. Fahnenstiel, Michael J. Sayers, Robert A. Shuchman, Foad Yousef, & Steven A. Pothoven (2019), Carbon Monitoring System Lake Michigan Primary Production Monthly, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/5AZRS4SRGS1R

Bounding Coordinates:
West Longitude:-84.76200 East Longitude:-79.65200
North Latitude:46.59100 South Latitude:43.00100

Product Title:  Carbon Monitoring System Lake Michigan Primary Production Yearly V1 (CMSLakeMichiganPPY) at GES DISC
Start Date:  01/2010      End Date:  12/2013     (2010-2013)
Description:  Yearly Average primary production/carbon fixation data for Lake Michigan. The primary production data is derived using MODIS imagery with model data.

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):  Lake Biomass; Ocean Biomass; Ocean-Atmosphere Flux
Keywords:  Carbon Stocks (; inland & coastal water)
Spatial Extent:  Lake Michigan
Spatial Resolution:  0.01 degree x 0.01 degree
Temporal Frequency:  yearly
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:  2
Target Application Readiness Level:  5
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  GES DISC
Metadata URL(s):
10.5067/NCJELM4CS8H8
Data Server URL(s):
10.5067/NCJELM4CS8H8
Archived Data Citation:  Gary L. Fahnenstiel, Michael J. Sayers, Robert A. Shuchman, Foad Yousef, & Steven A. Pothoven (2019), Carbon Monitoring System Lake Michigan Primary Production Yearly, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/NCJELM4CS8H8

Bounding Coordinates:
West Longitude:-84.76200 East Longitude:-79.65200
North Latitude:46.59100 South Latitude:43.00100

Product Title:  Carbon Monitoring System Lake Superior Primary Production Monthly V1 (CMSLakeSuperiorPPM) at GES DISC
Start Date:  01/2010      End Date:  12/2013     (2010-2013)
Description:  Monthly Average primary production/carbon fixation data for Lake Superior. The primary production data is derived using MODIS imagery with model data.

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):  Lake Biomass; Ocean Biomass; Ocean-Atmosphere Flux
Keywords:  Carbon Stocks (; inland & coastal water)
Spatial Extent:  Lake Superior
Spatial Resolution:  0.01 degree x 0.01 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:  5
Start Application Readiness Level:  2
Target Application Readiness Level:  5
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  GES DISC
Metadata URL(s):
10.5067/FZRE98046VM7
Data Server URL(s):
10.5067/FZRE98046VM7
Archived Data Citation:  Gary L. Fahnenstiel, Michael J. Sayers, Robert A. Shuchman, Foad Yousef, & Steven A. Pothoven (2019), Carbon Monitoring System Lake Superior Primary Production Monthly, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/FZRE98046VM7

Bounding Coordinates:
West Longitude:-84.76200 East Longitude:-79.65200
North Latitude:46.59100 South Latitude:43.00100

Product Title:  Carbon Monitoring System Lake Superior Primary Production Yearly V1 (CMSLakeSuperiorPPY) at GES DISC
Start Date:  01/2010      End Date:  12/2013     (2010-2013)
Description:  Yearly Average primary production/carbon fixation data for Lake Superior. The primary production data is derived using MODIS imagery with model data.

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):  Lake Biomass; Ocean Biomass; Ocean-Atmosphere Flux
Keywords:  Carbon Stocks (; inland & coastal water)
Spatial Extent:  Lake Superior
Spatial Resolution:  0.01 degree x 0.01 degree
Temporal Frequency:  yearly
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:  2
Target Application Readiness Level:  5
Future Developments:  
Limitations:  
Date When Product Available:  
Assigned Data Center:  GES DISC
Metadata URL(s):
10.5067/SQ2R9DWW6WDV
Data Server URL(s):
10.5067/SQ2R9DWW6WDV
Archived Data Citation:  Gary L. Fahnenstiel, Michael J. Sayers, Robert A. Shuchman, Foad Yousef, & Steven A. Pothoven (2019), Carbon Monitoring System Lake Superior Primary Production Yearly, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/SQ2R9DWW6WDV

Bounding Coordinates:
West Longitude:-84.76200 East Longitude:-79.65200
North Latitude:46.59100 South Latitude:43.00100

 
Publications: Fahnenstiel, G. L., Sayers, M. J., Shuchman, R. A., Yousef, F., Pothoven, S. A. 2016. Lake-wide phytoplankton production and abundance in the Upper Great Lakes: 2010-2013. Journal of Great Lakes Research. 42(3), 619-629. DOI: 10.1016/j.jglr.2016.02.004

Yousef, F., Charles Kerfoot, W., Shuchman, R., Fahnenstiel, G. 2014. Bio-optical properties and primary production of Lake Michigan: Insights from 13-years of SeaWiFS imagery. Journal of Great Lakes Research. 40(2), 317-324. DOI: 10.1016/j.jglr.2014.02.018

Archived Data Citations: Gary L. Fahnenstiel, Michael J. Sayers, Robert A. Shuchman, Foad Yousef, & Steven A. Pothoven (2019), Carbon Monitoring System Lake Huron Primary Production Yearly, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/11TMFK7VSHDY

Gary L. Fahnenstiel, Michael J. Sayers, Robert A. Shuchman, Foad Yousef, & Steven A. Pothoven (2019), Carbon Monitoring System Lake Superior Primary Production Monthly, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/FZRE98046VM7

Gary L. Fahnenstiel, Michael J. Sayers, Robert A. Shuchman, Foad Yousef, & Steven A. Pothoven (2019), Carbon Monitoring System Lake Michigan Primary Production Monthly, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/5AZRS4SRGS1R

Gary L. Fahnenstiel, Michael J. Sayers, Robert A. Shuchman, Foad Yousef, & Steven A. Pothoven (2019), Carbon Monitoring System Lake Huron Primary Production Monthly, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/CZ39JIR4ZAT4

Gary L. Fahnenstiel, Michael J. Sayers, Robert A. Shuchman, Foad Yousef, & Steven A. Pothoven (2019), Carbon Monitoring System Lake Michigan Primary Production Yearly, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/NCJELM4CS8H8

Gary L. Fahnenstiel, Michael J. Sayers, Robert A. Shuchman, Foad Yousef, & Steven A. Pothoven (2019), Carbon Monitoring System Lake Superior Primary Production Yearly, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/SQ2R9DWW6WDV


 

Verdy (CMS 2011) (2012)
Project Title:Towards a 4D-Var Approach for Estimation of Air-Sea Carbon Dioxide Fluxes

Science Team
Members:

Ariane Verdy, Scripps Institution of Oceanography (Project Lead)
Robert (Bob) Key, Princeton University

Solicitation:NASA: Carbon Monitoring System (2011)
Abstract: The challenge- Any Carbon Monitoring System (CMS) must account for fluxes of carbon between the atmosphere and the oceans, the world s largest reservoir of carbon dioxide (CO2). Currently, air-sea CO2 flux estimates are produced by sophisticated physical-biogeochemical models. However, these models still fail to represent significant patterns in the observed fluxes, and these discrepancies are thought to be largely due to errors in the simulation of biogeochemical processes. Our goal- This proposal capitalizes on two recent developments in oceanography to lay the groundwork for a global ocean CMS with improved biogeochemistry. Satellite measurements of the surface ocean and sensor-based measurements of the interior ocean are rapidly increasing the temporal and spatial coverage of biogeochemical data. Simultaneously, the development of four-dimensional variational assimilation (4D-Var) modeling has combined the forward modeling and traditional static inversion approaches to overcome the primary limitations of both: forward models estimate what could have happened in the ocean rather than what actually happened, and inversions cannot yield predictions. The 4D-Var approach automates the process of adjusting initial conditions and model parameters to produce an optimal fit of the model to physical constraints and all available observations. Our vision is of a state-of-the-art global physical-biogeochemical ocean model that incorporates data from the growing global network of satellites, sensors, and shipboard measurements to improve its estimates of air-sea CO2 fluxes. Our contribution- We will provide the missing components for 4D-Var physical-biogeochemical assimilation. As we build toward our goal of a global model-observation synthesis, each step of the proposed research will generate independently valuable scientific products: 1. We will test the efficacy of extending the 4D-Var approach to biogeochemistry by using it to optimize both the idealized biogeochemical and physical state of an eddy-resolving model of the California Current Ecosystem (CCE) for 2007-2011. The model will be optimized by adjusting the initial conditions, boundary conditions, external forcing, and parameter values to reduce the misfit between the model and the dense and diverse observations (including in situ measurements of carbon, oxygen, phosphate, pH, and alkalinity) available of the CCE during this time period. 2. We will further develop the biogeochemical component of the model to allow assimilation of satellite-based chlorophyll estimates and to improve the representation of other constraints, and optimize this new implementation of the physical-biogeochemical model to improve our estimate of air-sea CO2 fluxes in the CCE. 3. We will extend the data-processing of hydrographic observations to produce a self-consistent dataset of the quality, richness of properties, and temporal extent that will be required to constrain a global 4D-Var biogeochemical model. GLODAPv2 (GLobal Ocean Data Analysis Project version 2) will be a calibrated unification of existing biogeochemical data products and new data over the period 1972-2011. As more observations become available, state estimation is undoubtedly the way forward for addressing the objectives of NASA's CMS by bringing together observations and modeling tools to generate accurate high-resolution and time-varying maps of air-sea CO2 fluxes. Together, the development of 4D-Var methods and the observational dataset will enable global model-observation syntheses of the ocean carbon cycle over climate-relevant time scales.
Project Associations:
  • CMS
CMS Primary Theme:
  • Ocean-Atmosphere Flux
CMS Science Theme(s):
  • Ocean-Atmosphere Flux

Participants:

Brendan Carter, NOAA
Robert (Bob) Key, Princeton University
Matthew Mazloff, Scripps Institution of Oceanography
Jorge Sarmiento, Princeton University
Ariane Verdy, Scripps Institution of Oceanography

Project URL(s): http://iod.ucsd.edu/~averdy/becco.html
http://cdiac.ornl.gov/oceans/glodap/
 
Data
Products:
Product Title:  Global Ocean Data Analysis Project version 2 (GLODAPv2), a comprehensive data product of ocean carbon and biogeochemistry observations.
Time Period:  1973-2013
Description:  - Compile a calibrated dataset of in-situ ocean observations needed to constrain a global 4D-Var biogeochemical model.
Status:  Archived
CMS Science Theme(s):  Ocean-Atmosphere Flux
Keywords:  Flux/Movement (; oceanic; ; atmospheric)
Spatial Extent:  Global
Spatial Resolution:  1°
Temporal Frequency:  (climatology)
Input Data Products:  Available high quality shipboard data from 1973-present provided by the global research community
Algorithm/Models Used:  
Evaluation:  All parameters are subject to 2 rounds of quality control including basin scale inversion as well as crossover type data comparisons.
Intercomparison Efforts/Gaps:  GLODAPv1, CARINA, PACIFICA
Uncertainty Estimates:  Measurement accuracy is generally determined by simultaneous analysis of primary or secondary standards of known concentration.
Uncertainty Categories:  data-data comparison
Application Areas:  - Global carbon budget calculations; - Watershed protection plans; - Ocean acidification mitigation
Relevant Policies/Programs:  FOARAM, President's Executive Order on Oceans (EO 13547), NOAA Ocean Acidification Program, IOCCP, GO-SHIP, CWA, Doha/Kyoto, USCCSP, IPCC
Potential Users:  NOAA, EPA, White House Council on Environmental Quality, any oceanographer or modeler who needs to know the global ocean 3-D distribution of carbon system parameters and tracers that are not commonly cataloged by National Oceanographic Data Center
Stakeholders:  
Current Application Readiness Level:  7
Start Application Readiness Level:  3
Target Application Readiness Level:  7
Future Developments:  - Coordinate to release the data through the carbon dioxide information analysis Center (CDIAC) website.
Limitations:  - Summer bias in GLODAPv2 shipboard data collection.; - Insufficient or no data in GLODAPv2 for Southern Ocean, Indonesian throughflow region, Gulf of Mexico, Caribbean Sea, and less marginal seas.; - Insufficient data to produce global-scale, seasonal oc
Date When Product Available:  2016-08-16
Assigned Data Center:  NODC
Metadata URL(s):

https://cdiac.ess-dive.lbl.gov/ftp/oceans/GLODAPv2/Data_Products/

https://www.nodc.noaa.gov/ocads/oceans/GLODAPv2/

http://cchdo.ucsd.edu/
Data Server URL(s):

https://cdiac.ess-dive.lbl.gov/ftp/oceans/GLODAPv2/Data_Products/

https://www.nodc.noaa.gov/ocads/oceans/GLODAPv2/

http://cchdo.ucsd.edu/
Archived Data Citation:  Key, R.M., A. Olsen, S. van Heuven, S. K. Lauvset, A. Velo, X. Lin, C. Schirnick, A. Kozyr, T. Tanhua, M. Hoppema, S. Jutterström, R. Steinfeldt, E. Jeansson, M. Ishi, F. F. Perez, and T. Suzuki. 2015. Global Ocean Data Analysis Project, Version 2 (GLODAPv2), ORNL/CDIAC-162, NDP-P093. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, US Department of Energy, Oak Ridge, Tennessee.

DOI: 10.3334/CDIAC/OTG.NDP093_GLODAPv2

Product Title:  Ocean Biogeochemistry in the California Current System 2007-2010 L4 Monthly
Start Date:  01/2007      End Date:  12/2010     (2007-2010)
Description:  A coupled physical-biogeochemical ocean model (the MITgcm with BLING biogeochemistry) is a least squares fit to all available ocean observations in the region of the California Current System. This is accomplished iteratively through the adjoint method, using the methodology developed by the Consortium for Estimating the Circulation and Climate of the Ocean (ECCO). The result is a physically realistic estimate of the ocean state. The model domain extends from 28N to 40N and from 130W to 114W. It has a 1/16-degree horizontal resolution (~7km) and 72 vertical levels.

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):  Ocean-Atmosphere Flux
Keywords:  Flux/Movement (oceanic; atmospheric)
Spatial Extent:  California coastal ocean
Spatial Resolution:  7 km
Temporal Frequency:  Monthly and hourly
Input Data Products:  Satellite: Altimeter SSH (Jason1-2, TOPEX), Microwave SST, Ocean Color (MODIS), In Situ temperature, salinity, biogeochemistry
Algorithm/Models Used:  BLING (Biogeochemistry with Light, Iron, Nutrient and Gases) coupled to the MITgcm (ocean general circulation model)
Evaluation:  Adjoint model evaluation of the cost function (misfit between observations and model)
Intercomparison Efforts/Gaps:  ECCO2-Darwin, ECCOv4
Uncertainty Estimates:  We will quantify the consistency of the model with available observations
Uncertainty Categories:  model-data comparison
Application Areas:  - Global carbon budget calculations; - Watershed protection plans; - Ocean acidification mitigation
Relevant Policies/Programs:  FOARAM, President's Executive Order on Oceans (EO 13547), NOAA Ocean Acidification Program, IOCCP, GO-SHIP, CWA, Doha/Kyoto, USCCSP, IPCC
Potential Users:  NOAA, EPA, White House Council on Environmental Quality, any oceanographer or modeler who needs to know the global ocean 3-D distribution of carbon system parameters and tracers that are not commonly cataloged by National Oceanographic Data Center
Stakeholders:  
Current Application Readiness Level:  5
Start Application Readiness Level:  3
Target Application Readiness Level:  5
Future Developments:  Post new data on the Biogeochemistry Estimation in the California Coastal Ocean (BECCO) website.
Limitations:  - Limited ground-based data to validate satellite and model derived measurements. ; - Model-based errors due to simplification of a complex system.
Date When Product Available:  January 2018
Assigned Data Center:  GES DISC
Metadata URL(s):

https://acdisc.gsfc.nasa.gov/data/CMS/CMS_OCE_BGC_CCS.1/doc/README.CMS_OCE_BGC_CCS_V1.pdf

http://sose.ucsd.edu/CASE/case_stateestimation_data.html
Data Server URL(s):

https://acdisc.gsfc.nasa.gov/data/CMS/CMS_OCE_BGC_CCS.1/

http://sose.ucsd.edu/CASE/
Archived Data Citation:  Ariane Verdy(2017), Ocean Biogeochemistry in the California Current System 2007-2010 L4 Monthly, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), DOI: 10.5067/G854SWM56S7H

Bounding Coordinates:
West Longitude:-129.00000 East Longitude:-114.00000
North Latitude:39.95000 South Latitude:27.20000

 
Publications: Verdy, A., Mazloff, M. R., Cornuelle, B. D., Kim, S. Y. 2014. Wind-Driven Sea Level Variability on the California Coast: An Adjoint Sensitivity Analysis. Journal of Physical Oceanography. 44(1), 297-318. DOI: 10.1175/JPO-D-13-018.1

Archived Data Citations: Key, R.M., A. Olsen, S. van Heuven, S. K. Lauvset, A. Velo, X. Lin, C. Schirnick, A. Kozyr, T. Tanhua, M. Hoppema, S. Jutterström, R. Steinfeldt, E. Jeansson, M. Ishi, F. F. Perez, and T. Suzuki. 2015. Global Ocean Data Analysis Project, Version 2 (GLODAPv2), ORNL/CDIAC-162, NDP-P093. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, US Department of Energy, Oak Ridge, Tennessee. DOI: 10.3334/CDIAC/OTG.NDP093_GLODAPv2

Ariane Verdy(2017), Ocean Biogeochemistry in the California Current System 2007-2010 L4 Monthly, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), DOI: 10.5067/G854SWM56S7H


 

West (CMS 2011) (2012)
Project Title:Estimating Global Inventory-Based Net Carbon Exchange from Agricultural Lands for Use in the NASA Flux Pilot Study

Science Team
Members:

Tristram (Tris) West, DOE (Project Lead)

Solicitation:NASA: Carbon Monitoring System (2011)
Abstract: Inventory-based estimates of C flux have been developed for US agriculture (West et al. 2011), US forests (Zheng et al. 2011 and McKinley et al. 2011), and for North American agriculture and forest lands (Hayes et al. 2012). These estimates combine C uptake, harvest and removal, and C release to generate regional C flux estimates. These estimates differ from carbon biomass or stock estimates which often only represent the net C uptake component of the flux. The inventory-based C flux method of estimation has evolved over the past 5 years, as noted by the recent aforementioned citations, and has been used successfully as input to biogeochemical models, atmospheric transport models, and economic models. Estimates have also been used as independent data sets for comparison with other methods (King et al. 2012). The usefulness of this new method is evident. What is needed now is an expansion of the method for global use. The purpose of this proposed research is to develop a global C budget for agricultural carbon uptake and release, as was done for the US by West et al. (2011). A global US C budget, together with satellite remote sensing of land cover, will provide a gridded global C flux for agricultural lands. This product can be used as input to the NASA Flux Pilot Study and by models currently engaged in the Study. The proposed method combines aforementioned methods of spatially explicit C uptake and release with a NASA-generated global data set on human consumption of agricultural commodities (Imhoff et al. 2004, 2006) for use in the CASA model (Potter et al. 1993, Williams et al. 2012) and other Pilot Study models. Datasets generated will also be commensurate with those used in the DOE Integrated Assessment (IA) program, which allows for future economic projections of land use and human population to be linked with carbon fluxes generated with NASA models.
Measurement Approaches:
  • Remote Sensing
  • Modeling
  • Synthesis
Project Associations:
  • CMS
CMS Primary Theme:
  • Land-Atmosphere Flux
CMS Science Theme(s):
  • Land Biomass
  • Land-Atmosphere Flux
  • Decision Support
Other Keywords:  emperical, inventory-based estimates of net carbon exchange from global agricultural systems

Participants:

Varaprasad (Prasad) Bandaru, USDA ARS
George (Jim) Collatz, NASA GSFC - retired
Marc Imhoff, Joint Global Change Research Institute
Tristram (Tris) West, DOE
Julie Wolf, Joint Global Change Research Institute

Project URL(s): None provided.
 
Data
Products:
Product Title:  Carbon release by human.
Time Period:  2005-2010
Description:  - Develop a global gridded dataset for cropland carbon fluxes using global- and country-level inventory data on crop yields.
Status:  Planned
CMS Science Theme(s):  Land-Atmosphere Flux
Keywords:  Source (; anthropogenic)
Spatial Extent:  Global
Spatial Resolution:  0.05°
Temporal Frequency:  Annually
Input Data Products:  MODIS PFT v5.1 land cover (cropland, grassland, and shrubland areas)
Algorithm/Models Used:  Combination of IPCC, EPA, FAO, and empirical carbon dynamics developed under the NACP MCI program. Downscaling algorithms documented in 2014 paper (see below).
Evaluation:  Evaluation with other existing datasets on cropland, livestock, and human spatial distributions and emissions. Additional evaluations are expected in the future with atmospheric inversion estimates.
Intercomparison Efforts/Gaps:  Inherent intercomparison with inventory (FAO) and NASA SEDAC data
Uncertainty Estimates:  Standard deviation was generated using PDF functions around all major input variables. SD is provided at province and grid cell level.
Uncertainty Categories:  Deterministic
Application Areas:  - GHG emissions inventory; - Land management
Relevant Policies/Programs:  IPCC GPG, NASA FPP, NASA Carnegie Ames Stanford Approach (CASA) model, DOE Integrated Assessment program, US Farm Bill, CAP
Potential Users:  EPA, USDA Farm Service Agency, CMS flux teams, United Nations Environment Programme – Global Environmental Facility, UNFCCC, FAO, NGOs: World Wildlife Fund, The Nature Conservancy, & Natural Resource Defense Council
Stakeholders:  
Current Application Readiness Level:  5
Start Application Readiness Level:  3
Target Application Readiness Level:  6
Future Developments:  - Publish results in 2015.; - Collaborate with Bowman-01 and Collatz-02 teams to improve CMS flux projects.
Limitations:  - Food intake data is not available for all geopolitical areas, whereas Food supply is available. supply has been scaled to intake where necessary.
Date When Product Available:  Available when published
Assigned Data Center:  ORNL DAAC
Metadata URL(s):
Data Server URL(s):

http://daac.ornl.gov/
Archived Data Citation:  

Product Title:  CMS: Carbon Fluxes from Global Agricultural Production and Consumption, 2005-2011
Start Date:  01/2005      End Date:  12/2011     (2005-2011)
Description:  This data set provides global estimates of carbon fluxes associate with annual crop net primary production (NPP) and harvested biomass, annual uptake and release by humans and livestock, and the total annual estimate of net carbon exchange (NCE) derived from these carbon fluxes. NCE estimates are for the combined crop plant harvest and consumption/expiration of fodder by livestock and of food by humans. Estimation of carbon uptake and release from global agricultural production and consumption required compilation and analysis of inventory data from various sources for the years 2005-2011. The flux estimates were spatially distributed to a global 0.05-degree resolution grid using MODIS land cover data. The quantities of carbon flux in each gridcell are represented in two ways: (1) where the quantities of carbon distributed to each gridcell were divided by the total gridcell area, resulting in average carbon fluxes per unit of total area (g C/m2/yr), and (2), where annual carbon fluxes associated with a source were summed over all types for the gridcell (Mg C/yr). The total surface area of the grid cells is provided.There are eight data files in netCDF format (.nc4) with this data set -- two files (per area and per gridcell) for each of the four flux source types. Data for all years are in each .nc4 file.
Status:  Archived
CMS Science Theme(s):  Land-Atmosphere Flux
Keywords:  Flux/Movement (; terrestrial; ; atmospheric)
Spatial Extent:  Global
Spatial Resolution:  0.05°
Temporal Frequency:  Annually
Input Data Products:  The basis of these calculations was annual harvested biomass (Y) of 92 crops for years 1961-2011, which was compiled from FAOSTAT (FAO, 2013) for all reporting nations.
Algorithm/Models Used:  
Evaluation:  
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  
Uncertainty Categories:  
Application Areas:  The spatial distribution of these fluxes may be used for global carbon monitoring, estimation of regional uncertainty, and for use as input to Earth system models.
Relevant Policies/Programs:  IPCC GPG, NASA FPP, NASA Carnegie Ames Stanford Approach (CASA) model, DOE Integrated Assessment program, US Farm Bill, CAP
Potential Users:   Global or regional models with needs to improve agriculture biomass estimates, the amount of biomass removed from the field vs remaining as residue, and the approximate location of cropland carbon release.
Stakeholders:  
Current Application Readiness Level:  6
Start Application Readiness Level:  
Target Application Readiness Level:  
Future Developments:  
Limitations:  There is no incorporation of soil carbon in the global agricultural carbon budget.
Date When Product Available:  Dec 2015
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1279
Data Server URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1279
Archived Data Citation:  Wolf, J., T.O. West, Y. Le Page, G. Kyle, X. Zhang, G.J. Collatz, and M.L. Imhoff. 2015. CMS: Carbon Fluxes from Global Agricultural Production and Consumption, 2005-2011. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1279

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:83.64000 South Latitude:-59.46000

Product Title:  CMS: Land Cover Projections (5.6-km) from GCAM v3.1 for Conterminous USA, 2005-2095
Start Date:  01/2005      End Date:  12/2095     (2005-2095)
Description:  The data provided are annual land cover projections for years 2005 through 2095 generated by the Global Change Assessment Model (GCAM) Version 3.1. For the conterminous USA, the GCAM global gridded results were downscaled to ~5.6 km (0.05 degree) resolution. For each 5.6 x 5.6 km area, the annual land cover percentage comprised by each of the nineteen different land cover classes/plant functional types (PFTs) of the Community Land Model (CLM) (Table 1) are provided.Results are reported for GCAM runs of three scenarios of future human efforts towards climate mitigation as related to global carbon emissions, radiative forcing, and land cover change. Specific scenario conditions were 1) a reference scenario with no explicit climate mitigation efforts that reaches a radiative forcing level of over 7 W/m2 in 2100, 2) the 2.6 mitigation pathway (MP) scenario which is a very low emission scenario with a mid-century peak in radiative forcing at ~3 W/m2, declining to 2.6 W/m2 in 2100, and 3) the 4.5 MP scenario which stabilizes radiative forcing at 4.5 W/m2 (~ 650 ppm CO2-equivalent) before 2100.These downscaled land cover projections can be used to derive spatially explicit estimates of potential shifts in croplands, grasslands, shrub lands, and forest lands in each future climate scenario.Data are presented as three NetCDF v4 files (.nc4), one for each future climate scenario -- 2.6 MP, 4.5 MP, and GCAM reference).
Status:  Archived
CMS Science Theme(s):  Land-Atmosphere Flux
Keywords:  Disturbance (; land cover change)
Spatial Extent:  CONUS
Spatial Resolution:  0.05° (~5.6 km)
Temporal Frequency:  Annually
Input Data Products:  MODIS PFT v5.1 land cover (cropland, grassland, and shrubland areas)
Algorithm/Models Used:  Based on algorithms consistent with current state-of-the-art land cover change models (community land model).
Evaluation:  Evaluation with historic land cover change in the Midwestern US.
Intercomparison Efforts/Gaps:  
Uncertainty Estimates:  Uncertainty in the model downscaling procedure was evaluated by comparing model projections for years 2005 - 2010 against historical land cover change in the US using MODIS PFT data and national inventory statistics. An evaluation of the downscaling method indicates that it is able to reproduce recent changes in cropland and grassland distributions (West et al. 2014). No formal statistical uncertainty is associated with the data set.
Uncertainty Categories:  
Application Areas:  - GHG emissions inventory; - Land management These downscaled data can be applied to analyses of environmental impacts at sub-regional and landscape scales and may provide relevant insights into the potential impacts of socio-economic and environmental drivers on future changes in land cover.
Relevant Policies/Programs:  IPCC GPG, NASA FPP, NASA Carnegie Ames Stanford Approach (CASA) model, DOE Integrated Assessment program, US Farm Bill, CAP
Potential Users:  carbon cycle scientists, those interested in climate change and land cover change
Stakeholders:  
Current Application Readiness Level:  6
Start Application Readiness Level:  3
Target Application Readiness Level:  6
Future Developments:  - Publish results in 2014.; - This is completed and documents the spatial distribution methods used in our global flux estimates.
Limitations:  The limitation here is that we can not know exactly where lands will change. However, we can estimate the regions where land cover change is expected and we can approximate the spatial distribution of land-cover change. We have compared this against historic land-cover change estimates from inventory data and from MODIS.
Date When Product Available:  2014
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1216
Data Server URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1216
Archived Data Citation:  West, T.O. and Le Page, Y. 2014. CMS: Land Cover Projections (5.6-km) from GCAM v3.1 for Conterminous USA, 2005-2095. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1216

Bounding Coordinates:
West Longitude:-124.69000 East Longitude:-67.09000
North Latitude:49.35000 South Latitude:25.25000

Product Title:  CMS: Carbon Fluxes from Global Agricultural Production and Consumption, 2005-2011
Start Date:  01/2005      End Date:  12/2011     (2005-2010)
Description:  This data set provides global estimates of carbon fluxes associate with annual crop net primary production (NPP) and harvested biomass, annual uptake and release by humans and livestock, and the total annual estimate of net carbon exchange (NCE) derived from these carbon fluxes. NCE estimates are for the combined crop plant harvest and consumption/expiration of fodder by livestock and of food by humans. Estimation of carbon uptake and release from global agricultural production and consumption required compilation and analysis of inventory data from various sources for the years 2005-2011. The flux estimates were spatially distributed to a global 0.05-degree resolution grid using MODIS land cover data. The quantities of carbon flux in each gridcell are represented in two ways: (1) where the quantities of carbon distributed to each gridcell were divided by the total gridcell area, resulting in average carbon fluxes per unit of total area (g C/m2/yr), and (2), where annual carbon fluxes associated with a source were summed over all types for the gridcell (Mg C/yr). The total surface area of the grid cells is provided.There are eight data files in netCDF format (.nc4) with this data set -- two files (per area and per gridcell) for each of the four flux source types. Data for all years are in each .nc4 file.
Status:  Archived
CMS Science Theme(s):  Land-Atmosphere Flux
Keywords:  Source (; terrestrial)
Spatial Extent:  Global
Spatial Resolution:  0.05°
Temporal Frequency:  Annually
Input Data Products:  MODIS PFT v5.1 land cover (cropland, grassland, and shrubland areas)
Algorithm/Models Used:  Combination of IPCC, EPA, FAO, and empirical carbon dynamics developed under the NACP MCI program. Downscaling algorithms documented in 2014 paper (see below).
Evaluation:  Evaluation with other existing datasets on cropland, livestock, and human spatial distributions and emissions. Additional evaluations are expected in the future with atmospheric inversion estimates.
Intercomparison Efforts/Gaps:  Inherent intercomparison with inventory (FAO livestock) and MODIS data
Uncertainty Estimates:  Standard deviation was generated using PDF functions around all major input variables. SD is provided at province and grid cell level.
Uncertainty Categories:  Deterministic
Application Areas:  - GHG emissions inventory; - Land management
Relevant Policies/Programs:  IPCC GPG, NASA FPP, NASA Carnegie Ames Stanford Approach (CASA) model, DOE Integrated Assessment program, US Farm Bill, CAP
Potential Users:  EPA, USDA Farm Service Agency, CMS flux teams, United Nations Environment Programme – Global Environmental Facility, UNFCCC, FAO, NGOs: World Wildlife Fund, The Nature Conservancy, & Natural Resource Defense Council
Stakeholders:  
Current Application Readiness Level:  5
Start Application Readiness Level:  3
Target Application Readiness Level:  6
Future Developments:  - Publish results in 2015.; - Collaborate with Bowman-01 and Collatz-02 teams to improve CMS flux projects.
Limitations:  - methane carbon coefficients changing. We are already planning for a future update.
Date When Product Available:  Dec 2015
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1279
Data Server URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1279
Archived Data Citation:  Wolf, J., T.O. West, Y. Le Page, G. Kyle, X. Zhang, G.J. Collatz, and M.L. Imhoff. 2015. CMS: Carbon Fluxes from Global Agricultural Production and Consumption, 2005-2011. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1279

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:83.64000 South Latitude:-59.46000

Product Title:  CMS: Carbon Fluxes from Global Agricultural Production and Consumption, 2005-2011
Start Date:  01/2005      End Date:  12/2011     (2005-2010)
Description:  This data set provides global estimates of carbon fluxes associate with annual crop net primary production (NPP) and harvested biomass, annual uptake and release by humans and livestock, and the total annual estimate of net carbon exchange (NCE) derived from these carbon fluxes. NCE estimates are for the combined crop plant harvest and consumption/expiration of fodder by livestock and of food by humans. Estimation of carbon uptake and release from global agricultural production and consumption required compilation and analysis of inventory data from various sources for the years 2005-2011. The flux estimates were spatially distributed to a global 0.05-degree resolution grid using MODIS land cover data. The quantities of carbon flux in each gridcell are represented in two ways: (1) where the quantities of carbon distributed to each gridcell were divided by the total gridcell area, resulting in average carbon fluxes per unit of total area (g C/m2/yr), and (2), where annual carbon fluxes associated with a source were summed over all types for the gridcell (Mg C/yr). The total surface area of the grid cells is provided.There are eight data files in netCDF format (.nc4) with this data set -- two files (per area and per gridcell) for each of the four flux source types. Data for all years are in each .nc4 file.
Status:  Archived
CMS Science Theme(s):  Land-Atmosphere Flux
Keywords:  Flux/Movement (; anthropogenic; terrestrial; ; atmospheric)
Spatial Extent:  Global
Spatial Resolution:  0.05°
Temporal Frequency:  Annually
Input Data Products:  MODIS PFT v5.1 land cover (cropland, grassland, and shrubland areas)
Algorithm/Models Used:  Combination of IPCC, EPA, FAO, and empirical carbon dynamics developed under the NACP MCI program. Downscaling algorithms documented in 2014 paper (see below).
Evaluation:  Evaluation with other existing datasets on cropland, livestock, and human spatial distributions and emissions. Additional evaluations are expected in the future with atmospheric inversion estimates.
Intercomparison Efforts/Gaps:  Intercomparison with existing global agricultural flux estimates and with individual flux components.
Uncertainty Estimates:  Standard deviation was generated using PDF functions around all major input variables. SD is provided at province and grid cell level.
Uncertainty Categories:  Deterministic
Application Areas:  - GHG emissions inventory; - Land management
Relevant Policies/Programs:  IPCC GPG, NASA FPP, NASA Carnegie Ames Stanford Approach (CASA) model, DOE Integrated Assessment program, US Farm Bill, CAP
Potential Users:  EPA, USDA Farm Service Agency, CMS flux teams, United Nations Environment Programme – Global Environmental Facility, UNFCCC, FAO, NGOs: World Wildlife Fund, The Nature Conservancy, & Natural Resource Defense Council
Stakeholders:  
Current Application Readiness Level:  5
Start Application Readiness Level:  3
Target Application Readiness Level:  6
Future Developments:  - Publish results in 2015.; - Collaborate with Bowman-01 and Collatz-02 teams to improve CMS flux projects.
Limitations:  - Emission data is constantly improving, and the data products will need to be periodically updated to reflect these changes.; - Coarse spatial resolution, using MODIS rather than Landsat.; - No incorporation of soil carbon data.; - Methane carbon coeffic
Date When Product Available:  Dec 2015
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1279
Data Server URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1279
Archived Data Citation:  Wolf, J., T.O. West, Y. Le Page, G. Kyle, X. Zhang, G.J. Collatz, and M.L. Imhoff. 2015. CMS: Carbon Fluxes from Global Agricultural Production and Consumption, 2005-2011. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1279

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:83.64000 South Latitude:-59.46000

Product Title:  CMS: Carbon Fluxes from Global Agricultural Production and Consumption, 2005-2011
Start Date:  01/2005      End Date:  12/2011     (2005-2010)
Description:  This data set provides global estimates of carbon fluxes associate with annual crop net primary production (NPP) and harvested biomass, annual uptake and release by humans and livestock, and the total annual estimate of net carbon exchange (NCE) derived from these carbon fluxes. NCE estimates are for the combined crop plant harvest and consumption/expiration of fodder by livestock and of food by humans. Estimation of carbon uptake and release from global agricultural production and consumption required compilation and analysis of inventory data from various sources for the years 2005-2011. The flux estimates were spatially distributed to a global 0.05-degree resolution grid using MODIS land cover data. The quantities of carbon flux in each gridcell are represented in two ways: (1) where the quantities of carbon distributed to each gridcell were divided by the total gridcell area, resulting in average carbon fluxes per unit of total area (g C/m2/yr), and (2), where annual carbon fluxes associated with a source were summed over all types for the gridcell (Mg C/yr). The total surface area of the grid cells is provided.There are eight data files in netCDF format (.nc4) with this data set -- two files (per area and per gridcell) for each of the four flux source types. Data for all years are in each .nc4 file.
Status:  Archived
CMS Science Theme(s):  Land Biomass; Land-Atmosphere Flux
Keywords:  Sink (; terrestrial)
Spatial Extent:  Global
Spatial Resolution:  0.05°
Temporal Frequency:  Annually
Input Data Products:  MODIS PFT v5.1 land cover (cropland area)
Algorithm/Models Used:  Combination of IPCC, EPA, FAO, and empirical carbon dynamics developed under the NACP MCI program. Downscaling algorithms documented in 2014 paper (see below).
Evaluation:  Evaluation with other existing datasets on cropland, livestock, and human spatial distributions and emissions. Additional evaluations are expected in the future with atmospheric inversion estimates.
Intercomparison Efforts/Gaps:  Inherent intercomparison with inventory (FAO and USDA NASS) and MODIS data
Uncertainty Estimates:  A range of values have been collected in a meta-analysis for each parameter used in estimating crop growth and associated carbon content. These values will be used to generate PDFs which will constitute the Monte Carlo analysis.
Uncertainty Categories:  Deterministic
Application Areas:  - GHG emissions inventory; - Land management
Relevant Policies/Programs:  IPCC GPG, NASA FPP, NASA Carnegie Ames Stanford Approach (CASA) model, DOE Integrated Assessment program, US Farm Bill, CAP
Potential Users:  EPA, USDA Farm Service Agency, CMS flux teams, United Nations Environment Programme – Global Environmental Facility, UNFCCC, FAO, NGOs: World Wildlife Fund, The Nature Conservancy, & Natural Resource Defense Council
Stakeholders:  
Current Application Readiness Level:  5
Start Application Readiness Level:  3
Target Application Readiness Level:  6
Future Developments:  - Publish results in 2015.; - Collaborate with Bowman-01 and Collatz-02 teams to improve CMS flux projects.
Limitations:  - Emission data is constantly improving, and the data products will need to be periodically updated to reflect these changes.; - Coarse spatial resolution, using MODIS rather than Landsat.; - No incorporation of soil carbon data.
Date When Product Available:  Dec 2015
Assigned Data Center:  ORNL DAAC
Metadata URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1279
Data Server URL(s):

http://dx.doi.org/10.3334/ORNLDAAC/1279
Archived Data Citation:  Wolf, J., T.O. West, Y. Le Page, G. Kyle, X. Zhang, G.J. Collatz, and M.L. Imhoff. 2015. CMS: Carbon Fluxes from Global Agricultural Production and Consumption, 2005-2011. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1279

Bounding Coordinates:
West Longitude:-180.00000 East Longitude:180.00000
North Latitude:83.64000 South Latitude:-59.46000

 
Publications: Wolf, J., West, T. O., Le Page, Y., Kyle, G. P., Zhang, X., Collatz, G. J., Imhoff, M. L. 2015. Biogenic carbon fluxes from global agricultural production and consumption. Global Biogeochemical Cycles. 29(10), 1617-1639. DOI: 10.1002/2015GB005119

West, T. O., Le Page, Y., Huang, M., Wolf, J., Thomson, A. M. 2014. Downscaling global land cover projections from an integrated assessment model for use in regional analyses: results and evaluation for the US from 2005 to 2095. Environmental Research Letters. 9(6), 064004. DOI: 10.1088/1748-9326/9/6/064004

King, A. W., Hayes, D. J., Huntzinger, D. N., West, T. O., Post, W. M. 2012. North American carbon dioxide sources and sinks: magnitude, attribution, and uncertainty. Frontiers in Ecology and the Environment. 10(10), 512-519. DOI: 10.1890/120066

Li, Z., Liu, S., Tan, Z., Bliss, N. B., Young, C. J., West, T. O., Ogle, S. M. 2014. Comparing cropland net primary production estimates from inventory, a satellite-based model, and a process-based model in the Midwest of the United States. Ecological Modelling. 277, 1-12. DOI: 10.1016/j.ecolmodel.2014.01.012

Ogle, S. M., Davis, K., Lauvaux, T., Schuh, A., Cooley, D., West, T. O., Heath, L. S., Miles, N. L., Richardson, S., Breidt, F. J., Smith, J. E., McCarty, J. L., Gurney, K. R., Tans, P., Denning, A. S. 2015. An approach for verifying biogenic greenhouse gas emissions inventories with atmospheric CO 2 concentration data. Environmental Research Letters. 10(3), 034012. DOI: 10.1088/1748-9326/10/3/034012

Post, W. M., Izaurralde, R. C., West, T. O., Liebig, M. A., King, A. W. 2012. Management opportunities for enhancing terrestrial carbon dioxide sinks. Frontiers in Ecology and the Environment. 10(10), 554-561. DOI: 10.1890/120065

Schuh, A. E., Lauvaux, T., West, T. O., Denning, A. S., Davis, K. J., Miles, N., Richardson, S., Uliasz, M., Lokupitiya, E., Cooley, D., Andrews, A., Ogle, S. 2013. Evaluating atmospheric CO2inversions at multiple scales over a highly inventoried agricultural landscape. Global Change Biology. 19(5), 1424-1439. DOI: 10.1111/gcb.12141

West, T. O., Brown, M. E., Duren, R. M., Ogle, S. M., Moss, R. H. 2014. Definition, capabilities and components of a terrestrial carbon monitoring system. Carbon Management. 4(4), 413-422. DOI: 10.4155/CMT.13.36

Zeng, N., Zhao, F., Collatz, G. J., Kalnay, E., Salawitch, R. J., West, T. O., Guanter, L. 2014. Agricultural Green Revolution as a driver of increasing atmospheric CO2 seasonal amplitude. Nature. 515(7527), 394-397. DOI: 10.1038/nature13893

Zhang, X., Sahajpal, R., Manowitz, D. H., Zhao, K., LeDuc, S. D., Xu, M., Xiong, W., Zhang, A., Izaurralde, R. C., Thomson, A. M., West, T. O., Post, W. M. 2014. Multi-scale geospatial agroecosystem modeling: A case study on the influence of soil data resolution on carbon budget estimates. Science of The Total Environment. 479-480, 138-150. DOI: 10.1016/j.scitotenv.2014.01.099

Archived Data Citations: Wolf, J., T.O. West, Y. Le Page, G. Kyle, X. Zhang, G.J. Collatz, and M.L. Imhoff. 2015. CMS: Carbon Fluxes from Global Agricultural Production and Consumption, 2005-2011. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1279

West, T.O. and Le Page, Y. 2014. CMS: Land Cover Projections (5.6-km) from GCAM v3.1 for Conterminous USA, 2005-2095. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/1216