Introducing Satellite Data Based Biosphere Model Beams to Improve Regional Transport Model Aist-Mm for Estimating Carbon Dioxide Emission from Mega-City Tokyo

Remote sensing data from GOSAT (Greenhouse gases Observing SATellite) and GOSAT-2 in the future ameliorate inversion analysis of greenhouse gas (GHG) emissions^[1],[2]. Meso-scale atmospheric transport model AIST-MM (National Institute of Advanced Industrial Science and Technology-Mesoscale Model)^[3],[4] and global-scale transport model NICAM-TM (Nonhydrostatic ICosahedral Atmospheric Model-Transport Model)^[5] have been coupled for data assimilation in order to estimate CO₂ emission from mega-city Tokyo. However, forests west and north of Tokyo Metropolis in the Kanto plain generate significant biogenic CO₂ fluxes and such atmosphere-biosphere gas exchange remains to be properly calculated during the modeling processes. In this study, we use MODIS products^[6],[7] to simulate regional gross primary production (GPP), vegetational and soil respirations based on Biosphere model integrating Eco-physiological And Mechanistic approaches using Satellite data (BEAMS) algorithms^[8],[9]. By integrating this atmosphere-terrestrial ecosystem carbon balance module to our regional inversion analysis, we aim at more precise estimation of CO₂ emission from Tokyo.