Abstract
Abstract. Satellite retrievals of the column-averaged dry air mole fractions of CO2 (XCO2) could help to improve carbon flux estimation due to their good spatial coverage. In this study, in order to assimilate the GOSAT (Greenhouse Gases Observing Satellite) XCO2 retrievals, the Global Carbon Assimilation System (GCAS) is upgraded with new assimilation algorithms, procedures, a localization scheme, and a higher assimilation parameter resolution. This upgraded system is referred to as GCASv2. Based on this new system, the global terrestrial ecosystem (BIO) and ocean (OCN) carbon fluxes from 1 May 2009 to 31 December 2015 are constrained using the GOSAT ACOS (Atmospheric CO2 Observations from Space) XCO2 retrievals (Version 7.3). The posterior carbon fluxes from 2010 to 2015 are independently evaluated using CO2 observations from 52 surface flask sites. The results show that the posterior carbon fluxes could significantly improve the modeling of atmospheric CO2 concentrations, with global mean bias decreases from a prior value of 1.6 ± 1.8 ppm to −0.5 ± 1.8 ppm. The uncertainty reduction (UR) of the global BIO flux is 17 %, and the highest monthly regional UR could reach 51 %. Globally, the mean annual BIO and OCN carbon sinks and their interannual variations inferred in this study are very close to the estimates of CarbonTracker 2017 (CT2017) during the study period, and the inferred mean atmospheric CO2 growth rate and its interannual changes are also very close to the observations. Regionally, over the northern lands, the strongest carbon sinks are seen in temperate North America, followed by Europe, boreal Asia, and temperate Asia; in the tropics, there are strong sinks in tropical South America and tropical Asia, but a very weak sink in Africa. This pattern is significantly different from the estimates of CT2017, but the estimated carbon sinks for each continent and some key regions like boreal Asia and the Amazon are comparable or within the range of previous bottom-up estimates. The inversion also changes the interannual variations in carbon fluxes in most TransCom land regions, which have a better relationship with the changes in severe drought area (SDA) or leaf area index (LAI), or are more consistent with previous estimates for the impact of drought. These results suggest that the GCASv2 system works well with the GOSAT XCO2 retrievals and shows good performance with respect to estimating the surface carbon fluxes; meanwhile, our results also indicate that the GOSAT XCO2 retrievals could help to better understand the interannual variations in regional carbon fluxes.
Highlights
Atmospheric carbon dioxide (CO2) is one of the most important greenhouse gases, and fossil fuel burning and land use change are mostly responsible for its increase from the preindustrial concentration
When the length of the data assimilation (DA) window was increased from 1 week to 4 weeks, the respective mean super-observation number increased from four to nine and the respective inverted global burning (FIRE) Terrestrial ecosystem (BIO) flux increased from −4.16 to −4.49 Pg yr−1, resulting in a larger deviation of the simulated and observed atmospheric CO2 growth rate (AGR) and larger simulation error against the surface observations
The leaf area index (LAI) was inverted from surface reflectance data sets of Moderate Resolution Imaging Spectroradiometer (MODIS) (Liu et al, 2012), and the clumping index was derived from the MODIS Bidirectional Reflectance Distribution Function (BRDF) products, which provided the finest pseudo-multiangular data for the land surface, according to the normalized difference between hotspot and darkspot (NDHD) index (Chen et al, 2005; He et al, 2012)
Summary
Atmospheric carbon dioxide (CO2) is one of the most important greenhouse gases, and fossil fuel burning and land use change are mostly responsible for its increase from the preindustrial concentration. Atmospheric inversion is an effective method for estimating the surface CO2 fluxes using globally distributed atmospheric CO2 concentration observations (Enting and Newsam, 1990; Gurney et al, 2002). Most studies have focused on the impact of GOSAT XCO2 retrievals on the inversion of surface carbon fluxes; in many regions, there are still large divergences for carbon sinks between different inversions with the same GOSAT data or between inversions with GOSAT and in situ observations (e.g., Chevallier et al, 2014; Feng et al, 2016; Wang et al, 2018a). We present a 6-year inversion from 2010 to 2015 for the global and regional carbon fluxes using only the GOSAT XCO2 retrievals.
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