Wednesday, 25 January 2017
4E (Washington State Convention Center )
Robust estimates of CO2 sources and sinks are necessary to support carbon management policies, as well as to improve the understanding of carbon-climate feedbacks and thus to improve the predictive ability of earth system models. With the launch of JAXA’s Greenhouse gases Observing SATellite “IBUKI” (GOSAT) in 2009 and NASA’s Orbiting Carbon Observatory-2 (OCO-2) in 2014, it is expected that the global coverage provided by satellite remote-sensing instruments will improve the scientific understanding of carbon cycle processes and budgets at regional and global scales. In this study, XCO2 observations from GOSAT-ACOS and OCO-2 and CO2 measurements from surface flask sites are assimilated using an ensemble square root filter to constrain global surface fluxes. This ensemble data assimilation system is part of NASA GMAO’s GEOS-Carb system and has been designed to: (a) handle large observational datasets available from satellites, such as the OCO-2 and the GOSAT instrument, (b) provide estimates of surface fluxes at high spatial and temporal resolutions (spatial: ~1°; temporal: daily). CO2 fluxes will be estimated over a period of eight consecutive years (June 2009 – May 2016) to highlight long-term trends and the interannual variability of carbon sources and sinks. The value of the satellite observations will be further assessed via a diagnostic metric based on information theory, which within the ensemble DA framework allows for an unbiased quantification of the observational influence on the posterior flux estimates. This will bring out not only the impact of the satellite observations relative to the surface flask network but also the complementary or competing constraints provided by the GOSAT-ACOS and OCO-2 XCO2 observations during the period when both satellites overlap, i.e., September 2014-May 2016. Finally, as part of this study, we will provide updated global and regional carbon budgets using both the satellite and the surface flask observations - a critical step towards attributing the variability and trends of the CO2 surface fluxes to the underlying drivers.
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