A 10-year global monthly averaged terrestrial net ecosystem exchange dataset inferred from the ACOS GOSAT v9 XCO₂ retrievals (GCAS2021)

Abstract

Abstract. A global gridded net ecosystem exchange (NEE) of CO2 dataset is vital in global and regional carbon cycle studies. Top-down atmospheric inversion is one of the major methods to estimate the global NEE; however, the existing global NEE datasets generated through inversion from conventional CO2 observations have large uncertainties in places where observational data are sparse. Here, by assimilating the GOSAT ACOS v9 XCO2 product, we generate a 10-year (2010–2019) global monthly terrestrial NEE dataset using the Global Carbon Assimilation System, version 2 (GCASv2), which is named GCAS2021. It includes gridded (1∘×1∘), globally, latitudinally, and regionally aggregated prior and posterior NEE and ocean (OCN) fluxes and prescribed wildfire (FIRE) and fossil fuel and cement (FFC) carbon emissions. Globally, the decadal mean NEE is -3.73±0.52 PgC yr−1, with an interannual amplitude of 2.73 PgC yr−1. Combining the OCN flux and FIRE and FFC emissions, the net biosphere flux (NBE) and atmospheric growth rate (AGR) as well as their inter-annual variabilities (IAVs) agree well with the estimates of the Global Carbon Budget 2020. Regionally, our dataset shows that eastern North America, the Amazon, the Congo Basin, Europe, boreal forests, southern China, and Southeast Asia are carbon sinks, while the western United States, African grasslands, Brazilian plateaus, and parts of South Asia are carbon sources. In the TRANSCOM land regions, the NBEs of temperate N. America, northern Africa, and boreal Asia are between the estimates of CMS-Flux NBE 2020 and CT2019B, and those in temperate Asia, Europe, and Southeast Asia are consistent with CMS-Flux NBE 2020 but significantly different from CT2019B. In the RECCAP2 regions, except for Africa and South Asia, the NBEs are comparable with the latest bottom-up estimate of Ciais et al. (2021). Compared with previous studies, the IAVs and seasonal cycles of NEE of this dataset could clearly reflect the impacts of extreme climates and large-scale climate anomalies on the carbon flux. The evaluations also show that the posterior CO2 concentrations at remote sites and on a regional scale, as well as on vertical CO2 profiles in the Asia-Pacific region, are all consistent with independent CO2 measurements from surface flask and aircraft CO2 observations, indicating that this dataset captures surface carbon fluxes well. We believe that this dataset can contribute to regional- or national-scale carbon cycle and carbon neutrality assessment and carbon dynamics research. The dataset can be accessed at https://doi.org/10.5281/zenodo.5829774 (Jiang, 2022).

Flood Impacts on Net Ecosystem Exchange in the Midwestern and Southern United States in 2019

“…The current study affirms the mentioned as- The impact of flooding on NEE and atmospheric CO 2 is readily observed by satellites (Yin et al, 2020) and a variety of in situ observational approaches (this study). Like Yin et al, (2020), for the Midwestern region this study finds a decrease in net carbon uptake over June and July of 2019 of about 0.07-1.3 PgC [roughly 14-26% of an average annual carbon net uptake in North America (Jiang et al, 2022)] when compared to both 2017 and 2018 and an increase in net carbon uptake in August and September of near 0.04 PgC (roughly 8% of an average annual carbon net uptake in North America) when compared to 2018 [Note that Yin et al (2020) estimated Gross Primary Production (GPP), which does not account for RE, while this study estimated NEE]. However, the results from the current study suggest that comparing 2019 to 2018 may not be optimal as 2018 may not be representative of an average growing season carbon activity (Jiang et al, 2022).…”

“…Like Yin et al, (2020), for the Midwestern region this study finds a decrease in net carbon uptake over June and July of 2019 of about 0.07-1.3 PgC [roughly 14-26% of an average annual carbon net uptake in North America (Jiang et al, 2022)] when compared to both 2017 and 2018 and an increase in net carbon uptake in August and September of near 0.04 PgC (roughly 8% of an average annual carbon net uptake in North America) when compared to 2018 [Note that Yin et al (2020) estimated Gross Primary Production (GPP), which does not account for RE, while this study estimated NEE]. However, the results from the current study suggest that comparing 2019 to 2018 may not be optimal as 2018 may not be representative of an average growing season carbon activity (Jiang et al, 2022). For instance, assessment of 2019 NEE values with 2017 NEE values does not seem to show a "recovery" in August-September time frame as stated in Yin et al (2020) suggesting that additional inquiries are required into the detailed effects of flooding on the carbon uptake.…”

The carbon sink in China as seen from GOSAT with a regional inversion system based on CMAQ and EnSRF

“…Following previous GOSAT inversion work (Maksyutov et al, 2013;Feng et al, 2017;Wang et al, 2019;Liu et al, 2021;Jiang et al, 2022), in this study, the natural flux (i.e., biosphere-atmosphere exchange and ocean-atmosphere exchange) were assimilated, while the fossil-fuel and biomass-burning fluxes were kept unchanged. This design, in which the natural fluxes were a subset of the state vector, further allowed us to focus on investigating the uncertainty of China's carbon sink, 295 since the uncertainty in prescribed biomass-burning and fossil-fuel emissions are minor compared to that of the biosphere fluxes in the model domain (van der Werf et al, 2017;Zheng et al, 2018;Kurokawa et al, 2020).…”

Enhanced India‐Africa Carbon Uptake and Asia‐Pacific Carbon Release Associated With the 2019 Extreme Positive Indian Ocean Dipole

“…Its structure, implementation, and differences from GCASv1 have previously been described in detail (Jiang et al., 2021). GCASv2 adopted the assimilation technique of the ensemble square root filter (EnSRF) algorithm (Whitaker & Hamill, 2002) to assimilate the GOSAT ACOS XCO 2 version 9.0 Level 2 Lite product (O’Dell et al., 2012) within a 1‐week window and generated the posterior results (both land and ocean fluxes) at 1° × 1° with prescribed carbon emissions induced by fossil fuel and wildfires from 2010 to 2019 (Jiang et al., 2022). The transport model in GCASv2 is the Model for Ozone and Related chemical Tracers, version 4 (MOZART‐4) (Emmons et al., 2010).…”

“…Here, we investigated the impact of the extreme pIOD in 2019 on terrestrial net biome productivity (NBP) and its constituent fluxes over the IORC, based on the posterior fluxes optimized by the Global Carbon Assimilation System Version 2 (GCASv2) (Jiang et al, 2022(Jiang et al, , 2021, simulations from twelve state-of-the-art Terrestrial Biosphere Models (TBMs) that participated in the TRENDYv9 multimodel intercomparison (Sitch et al, 2015), two satellite-derived global GPP products, and the relevant climate data sets.…”