Comment on essd-2022-15

Abstract

<strong class="journal-contentHeaderColor">Abstract.</strong> A global gridded net ecosystem exchange (NEE) of CO<span class="inline-formula">₂</span> 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 CO<span class="inline-formula">₂</span> observations have large uncertainties in places where observational data are sparse. Here, by assimilating the GOSAT ACOS v9 XCO<span class="inline-formula">₂</span> 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 (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M5" display="inline" overflow="scroll" dspmath="mathml"><mrow><mn mathvariant="normal">1</mn><msup><mi/><mo>∘</mo></msup><mo>×</mo><mn mathvariant="normal">1</mn><msup><mi/><mo>∘</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="34pt" height="11pt" class="svg-formula" dspmath="mathimg" md5hash="d308210e38ed1a4940972a050836d54c"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="essd-14-3013-2022-ie00001.svg" width="34pt" height="11pt" src="essd-14-3013-2022-ie00001.png"/></svg:svg></span></span>), 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 <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M6" display="inline" overflow="scroll" dspmath="mathml"><mrow><mo>-</mo><mn mathvariant="normal">3.73</mn><mo>±</mo><mn mathvariant="normal">0.52</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="64pt" height="10pt" class="svg-formula" dspmath="mathimg" md5hash="683dca71b946e19ce51300e412e17067"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="essd-14-3013-2022-ie00002.svg" width="64pt" height="10pt" src="essd-14-3013-2022-ie00002.png"/></svg:svg></span></span> PgC yr<span class="inline-formula">^−1</span>, with an interannual amplitude of 2.73 PgC yr<span class="inline-formula">^−1</span>. 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 CO<span class="inline-formula">₂</span> concentrations at remote sites and on a regional scale, as well as on vertical CO<span class="inline-formula">₂</span> profiles in the Asia-Pacific region, are all consistent with independent CO<span class="inline-formula">₂</span> measurements from surface flask and aircraft CO<span class="inline-formula">₂</span> 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 <a href="https://doi.org/10.5281/zenodo.5829774">https://doi.org/10.5281/zenodo.5829774</a> (Jiang, 2022).