Modeling the Global Atmospheric Carbon Cycle in Preparation for OCO
S.
Randy
Kawa, NASA GSFC, stephan.r.kawa@nasa.gov
(Presenting)
G.
James
Collatz, NASA GSFC, george.j.collatz@nasa.gov
A.
Scott
Denning, Colorado State University, denning@atmos.colostate.edu
Ravi
Lokupitaya, Colorado State University, ravi@atmos.colostate.edu
Joseph
A.
Berry, Carnegie Institution, joeberry@stanford.edu
Steven
Pawson, NASA GSFC, steven.pawson@nasa.gov
Ian
Baker, Colorado State University, baker@atmos.colostate.edu
David
J.
Erickson, Oak Ridge National Laboratory, ericksondj@ornl.gov
Elliott
Campbell, Carnegie Institutio, campbell@stanford.edu
We report progress on a project to synthesize an improved modeling/data analysis procedure capable of incorporating OCO 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 the NASA data assimilation demonstrates considerable skill in reproducing observed variability on time scales from hourly to interannual. The real-time, local observations from the Orbiting Carbon Observatory (OCO), scheduled for launch near the end of 2008, comprise a wealth of information on the distribution and sensitivity of carbon cycle processes over a wide range of time and spatial scales. 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. Our goal is to utilize OCO and other data constraints to reduce uncertainty in the atmospheric carbon budget and its dependence on changing weather and climate.
We will report specific progress in: 1) Evaluating and quantifying uncertainty in atmospheric transport and its impact on top-down inference of carbon source/sink distributions including evaluation of the transport characteristics of GEOS-5. 2) Integration, evaluation, and refinement of terrestrial biogeochemical process models constrained by global satellite observations including simulation of COS as an indicator of vegetation processes. 3) Testing inverse models and pseudo-data consistent with expected OCO instrument sampling to infer CO2 sources and sinks.
NASA Carbon Cycle & Ecosystems Active Awards Represented by this Poster: