Abstract
Abstract. We present the application of a global carbon cycle modeling system to the estimation of monthly regional CO2 fluxes from the column-averaged mole fractions of CO2 (XCO2) retrieved from spectral observations made by the Greenhouse gases Observing SATellite (GOSAT). The regional flux estimates are to be publicly disseminated as the GOSAT Level 4 data product. The forward modeling components of the system include an atmospheric tracer transport model, an anthropogenic emissions inventory, a terrestrial biosphere exchange model, and an oceanic flux model. The atmospheric tracer transport was simulated using isentropic coordinates in the stratosphere and was tuned to reproduce the age of air. We used a fossil fuel emission inventory based on large point source data and observations of nighttime lights. The terrestrial biospheric model was optimized by fitting model parameters to observed atmospheric CO2 seasonal cycle, net primary production data, and a biomass distribution map. The oceanic surface pCO2 distribution was estimated with a 4-D variational data assimilation system based on reanalyzed ocean currents. Monthly CO2 fluxes of 64 sub-continental regions, between June 2009 and May 2010, were estimated from GOSAT FTS SWIR Level 2 XCO2 retrievals (ver. 02.00) gridded to 5° × 5° cells and averaged on a monthly basis and monthly-mean GLOBALVIEW-CO2 data. Our result indicated that adding the GOSAT XCO2 retrievals to the GLOBALVIEW data in the flux estimation brings changes to fluxes of tropics and other remote regions where the surface-based data are sparse. The uncertainties of these remote fluxes were reduced by as much as 60% through such addition. Optimized fluxes estimated for many of these regions, were brought closer to the prior fluxes by the addition of the GOSAT retrievals. In most of the regions and seasons considered here, the estimated fluxes fell within the range of natural flux variabilities estimated with the component models.
Highlights
Hydrology andTtiahlelyreacbenatteidncbreyascearinboantmEuopsatpahrkteehribcySCoOyc2secatonenmacnendtrlaatniodn, is parwhich indicates disequilibrium in CO2Secxciehanngcees sbetween the atmosphere and oceans and between the atmosphere and the terrestrial biosphere (Keeling et al, 1995)
The a priori flux dataset used in this study is comprised of four components: daily net ecosystem exchange (NEE) predicted by the terrestrial biosphere process model VISIT (Vegetation Integrative SImulator for Trace gases) (Ito, 2010; Saito, M. et al, 2011); monthly ocean-atmosphere CO2 fluxes generated by an ocean pressure of surface ocean CO2 (pCO2) data assimilation system (Valsala and Maksyutov, 2010); monthly CO2 emissions due to biomass burning stored in the Global Fire Emissions Database (GFED) version 3.1; and monthly fossil fuel CO2 emissions obtained via combining the high-resolution Open source Data Inventory of Anthropogenic CO2 emission (ODIAC) dataset (Oda and Maksyutov, 2011) and the Carbon Dioxide Information Analysis Center’s (CDIAC) monthly 1◦ × 1◦ resolution dataset (Andres et al, 1996, 2011)
We took account of errors associated with the retrieval of XCO2 values and the forward atmospheric transport simulation by setting the minimum of the observation error for gases Observing SATellite (GOSAT) XCO2 retrievals at 3 ppm, which consists of an uncertainty associated with the retrieval of GOSAT XCO2 (2 ppm) and that of forward XCO2 modeling (1 ppm) The GV sites were selected by comparing GV data against concentrations predicted by National Institute for Environmental Studies (NIES)-TM over the analysis period
Summary
TtiahlelyreacbenatteidncbreyascearinboantmEuopsatpahrkteehribcySCoOyc2secatonenmacnendtrlaatniodn, is parwhich indicates disequilibrium in CO2Secxciehanngcees sbetween the atmosphere and oceans and between the atmosphere and the terrestrial biosphere (Keeling et al, 1995). A more detailed analysis with atmospheric transport and inversion models allocated a large sink to the US (Fan et al, 1998), a result supported by a bottom-up estimate (Pacala et al, 2001). This paper provides an overview of a carbon cycle modeling system that consists of components for modeling atmospheric transport, anthropogenic CO2 emissions, and terrestrial and oceanic CO2 exchanges. It further describes the application of the system to the estimation of surface CO2 fluxes from GOSAT retrievals. We assessed the utility of the GOSAT XCO2 retrievals in inverse modeling of surface sources and sinks.
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