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Progress in Simulation of Global Atmospheric CO2 and Comparisons to Observations

Stephan Randolph Kawa, NASA GSFC, stephan.r.kawa@nasa.gov (Presenter)
George James Collatz, NASA GSFC, jim.collatz@nasa.gov
Steven Pawson, NASA GMAO, steven.pawson@nasa.gov
Scott Denning, Colorado State University, denning@atmos.colostate.edu
Arlyn Elizabeth Andrews, NOAA ESRL, arlyn.andrews@noaa.gov
Paul Wennberg, Caltech, wennberg@gps.caltech.edu
Yuping Liu, GSFC/SSAI, yuping.liu@nasa.gov

We report on a project to synthesize an improved modeling/data analysis framework capable of incorporating satellite remote sensing and other relevant data to more precisely characterize the global atmospheric carbon budget. Recent progress in simulating atmospheric CO2 using models driven by analyzed meteorology from NASA data assimilation demonstrates considerable skill in reproducing observed variability on time scales from hourly to interannual. The most recent results reflect improvements to the GSFC version of the CASA-GFED model for uptake and emission of CO2 from vegetation metabolism and biomass burning. We show how the constraint of photosynthetic processes in CASA using observed vegetation indices is key to accurately simulating variability of CO2 in the atmosphere. Progress is also reflected in the depth and breadth of available CO2 data for model comparison including remotely sensed observations from ground and satellite as well as an increased number of in situ data sites and aircraft observations. Our goal is to utilize these comparisons to reduce uncertainty in the simulated atmospheric carbon fluxes and their dependence on changing weather and climate. We report specific progress in: 1) Evaluating and quantifying uncertainty in atmospheric transport and its impact on top-down inference of carbon source/sink distributions. 2) Integration, evaluation, and refinement of terrestrial biogeochemical process models constrained by global satellite observations. 3) Testing inverse models and pseudo-data consistent with existing and expected satellite instrument sampling to infer CO2 sources and sinks. Better understanding of these processes and their representation in numerical models is key to resolving long-standing uncertainties in the CO2 budget and confidently projecting interactions of the carbon cycle with climate change.

Presentation Type:  Poster

Session:  Coupled Processes at Land-Atmosphere-Ocean Interfaces   (Mon 4:00 PM)

Associated Project(s): 

  • Kawa, Randy: Modeling the Global Atmospheric Carbon Cycle in Preparation for OCO Data ...details

Poster Location ID: 45

 


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