JpGU-AGU Joint Meeting 2020

講演情報

[E] ポスター発表

セッション記号 A (大気水圏科学) » A-CG 大気海洋・環境科学複合領域・一般

[A-CG49] Greenhouse Gas Monitoring from Space: Current Capabilities, Challenges, and Future Needs

コンビーナ:kurosu thomas p(Jet Propulsion Laboratory, California Institute of Technology)、Annmarie Eldering(Jet Propulsion Laboratory)、久世 暁彦(宇宙航空研究開発機構)、松永 恒雄(国立環境研究所地球環境研究センター/衛星観測センター)

[ACG49-P01] A high-resolution CO2 inverse modeling using observations from the global ground-based monitoring network and the GOSAT satellite

*Shamil Maksyutov1Rajesh Janardanan1Tomohiro Oda2Makoto Saito1Yukio Yoshida1Johannes W Kaiser3Vinu Valsala4Edward Dlugokencky5Tsuneo Matsunaga1 (1.National Institute for Environmental Studies, Tsukuba, Japan、2.USRA/NASA GSFC, Greenbelt, USA、3.DWD, Offenbach, Germany、4.Indian Institute for Tropical Meteorology, Pune, India、5.Global Monitoring Division, NOAA, Boulder, USA)

キーワード:inverse modeling, CO2, satellite observation, GOSAT

We present a high-resolution CO2 flux inversion system designed to estimate surface fluxes from atmospheric CO2 observational data collected by the GOSAT satellite as well as the global in-situ ground-based observation networks. Our inverse system NTFVAR is based on a coupled transport model combining the FLEXPART Lagrangian Particle Dispersion Model (LPDM) and the NIES-TM global Eulerian transport model. The system solves for flux corrections to the prior fluxes at a 0.1 x 0.1 degree spatial resolution via an iterative optimization procedure using the adjoint of the coupled transport model. We used high-resolution prior fluxes prepared from the ODIAC anthropogenic emissions data product, the GFAS global biomass burning dataset, the OTTM ocean model and the VISIT terrestrial biosphere model. The high-resolution version of VISIT biosphere flux was obtained using a separate VISIT CO2 flux simulation implemented for each vegetation type identified by a vegetation mosaic map. The prior flux uncertainty for the land and ocean regions was scaled proportionally to monthly mean MODIS-GPP and the ocean flux variability. First, we estimated bi-weekly flux corrections over the period of 2010 to 2012 solely from in-situ CO2 data by the ObsPack global observation network dataset. The application of the high-resolution atmospheric transport improved the representation of fine-scale anthropogenic CO2 plumes. A comparison to NOAA’s CarbonTracker optimized simulations shows that our high-resolution model has some advantage at coastal and island observation sites, experiencing a mix of marine and continental air inflow. We also implemented an inversion using the ground-based data and the GOSAT satellite data. The GOSAT Level 2 data (NIES L2 v02.72) were corrected by estimating the deviation of GOSAT L2 data from an optimized simulation with the ObsPack for each latitude band and month. We confirmed the reduction of misfit between the GOSAT observations and the high-resolution model simulations after the inversion.