Modeling Global Atmospheric CO2 Fluxes and Transport Using NASA MERRA Reanalysis Data
Yuping
Liu, NASA/SSAi, yuping.liu@nasa.gov
(Presenting)
Stephan
Randy
Kawa, NASA/GSFC, stephan.r.kawa@nasa.gov
George
James
Collatz, NASA/GSFC, george.j.collatz@nasa.gov
(Presenting)
Zhen
Li, NASA/SSAI, zhen.li-1@nasa.gov
We present our first results of CO2 surface biosphere fluxes and global atmospheric CO2 transport using NASA’s new MERRA reanalysis data. MERRA is the Modern Era Retrospective-Analysis For Research And Applications based on the Goddard Global Modeling and Assimilation Office GEOS-5 data assimilation system. After some application testing and analysis, we have generated biospheric CO2 fluxes at 3-hourly temporal resolution from an updated version of the CASA carbon cycle model using the 1x1.25-degree reanalysis data. The experiment covers a period of 9 years from 2000 -2008. The affects of US midwest crop (largely corn and soy) carbon uptake and removal by harvest are explicitly included in this version of CASA. Across the agricultural regions of the Midwest US, USDA crop yield data are used to scale vegetation fluxes producing a strong sink in the growing season and a comparatively weaker source from respiration after harvest. Comparisons of the new fluxes to previous ones generated using GEOS-4 data are provided. The Parameterized Chemistry/Transport Model (PCTM) is then used with the analyzed meteorology in offline CO2 transport. In the simulation of CO2 transport, we have a higher vertical resolution from MERRA (the lowest 56 of 72 levels are used in our simulation). A preliminary analysis of the CO2 simulation results is carried out, including diurnal, seasonal and latitudinal variability. We make comparisons of our simulation to continuous CO2 analyzer sites, especially those in agricultural regions. The results show that the model captures reasonably well the observed synoptic variability due to transport changes and biospheric fluxes.
Presentation Type: Poster
Poster Session: Carbon Cycle Science
NASA TE Funded Awards Represented:
Kawa, Stephan
Modeling the Global Atmospheric Carbon Cycle in Preparation for OCO Data