Interannual variability of the global carbon cycle estimated with GOSAT and ground-based CO2 observations for 2009-2019
Shamil Maksyutov, National Institute for Environmental Studies, shamil@nies.go.jp (Presenter)
Tomohiro Oda, USRA, toda@usra.edu
Jiye Zeng, National Institute for Environmental Studies, zeng@nies.go.jp
Johanness W Kaiser, DWD, johannes.kaiser@dwd.de
Yukio Yoshida, National Institute for Environmental Studies, yoshida.yukio@nies.go.jp
Tsuneo Matsunaga, National Institute for Environmental Studies, matsunag@nies.go.jp
We employed a recent version of the global inverse model NTFVAR (NIES-TM-FLEXPART-variational) to estimate the regional carbon dioxide (CO2) fluxes using XCO2 retrievals from GOSAT satellite observations and ground-based observations by the Obspack dataset. To improve the accuracy of the CO2 simulation, the interhemispheric and vertical mixing rates in the transport model (Eulerian transport model NIES-TM) used ERA-5 reanalysis winds, interpolated to 42 hybrid-pressure levels with a horizontal resolution of 2.5 and 3.75 degrees, and revised 3rd order upwind advection scheme. The transport model showed an improved match with the observed interhemispheric gradient of SF6 and vertical gradient of radon. In the CO2 simulations, diurnally-resolved land biosphere fluxes were provided by the global upscaling product based on tower flux data at the spatial resolution of 0.1 degrees and temporal resolution of 10 days. Fossil emissions were provided by ODIAC, fire emissions by GFAS, and oceanic fluxes by the upscaling product based on surface ocean pCO2 observations. The FLEXPART model uses JRA-55 reanalysis data and was modified to match the Eulerian model grid and account for diurnal cycle in surface fluxes. The prior respiration and oceanic fluxes were scaled to match the global CO2 growth rate. The corrections to the prior fluxes by the inverse model were estimated on a bi-weekly time step separately for land biosphere and ocean regions. With this set of prior fluxes, the model simulation replicated the observed seasonal cycle at most global monitoring sites reasonably well. To estimate retrieval biases, the XCO2 data by GOSAT (v.02.95) were compared with forward simulations optimized with surface data inversion and showed a good agreement with model simulation, typically within 0.5 ppm for monthly average data over 10-degree latitudinal bands. The estimated biases were subtracted from GOSAT data before inversion. The estimated fluxes are aggregated to monthly mean values at a 0.1-degree resolution and summed over Transcom 22 regions. The flux estimates showed improvements over a former version of the inversion system in achieving better balance of the long-term sinks between ocean and land regions in the Southern hemisphere and improving land biosphere flux seasonality over Northern boreal and temperate regions.
Poster: Poster_Maksyutov__24_25.pdf
Presentation Type: Poster
Session: 3.5c Flux estimates and atmospheric inversions from space-based GHG measurements
Session Date: Wednesday (6/16) 12:00 PM