Abstract. Accurate assessment of the size and distribution of carbon dioxide (CO2) sources and sinks is important for efforts to understand the carbon cycle and support policy decisions regarding climate mitigation actions. Satellite retrievals of the column-averaged dry-air mole fractions of CO2 (XCO2) have been widely used to infer spatial and temporal variations in carbon fluxes through atmospheric inversion techniques. In this study, we present a global spatially resolved terrestrial and ocean carbon flux dataset for 2015–2022. The dataset was generated by the Global ObservatioN-based system for monitoring Greenhouse GAses (GONGGA) atmospheric inversion system through the assimilation of Orbiting Carbon Observatory-2 (OCO-2) XCO2 retrievals. We describe the carbon budget, interannual variability, and seasonal cycle for the global scale and a set of TransCom regions. The 8-year mean net biosphere exchange and ocean carbon fluxes were −2.22 ± 0.75 and −2.32 ± 0.18 Pg C yr−1, absorbing approximately 23 % and 24 % of contemporary fossil fuel CO2 emissions, respectively. The annual mean global atmospheric CO2 growth rate was 5.17 ± 0.68 Pg C yr−1, which is consistent with the National Oceanic and Atmospheric Administration (NOAA) measurement (5.24 ± 0.59 Pg C yr−1). Europe has the largest terrestrial sink among the 11 TransCom land regions, followed by Boreal Asia and Temperate Asia. The dataset was evaluated by comparing posterior CO2 simulations with Total Carbon Column Observing Network (TCCON) retrievals as well as Observation Package (ObsPack) surface flask observations and aircraft observations. Compared with CO2 simulations using the unoptimized fluxes, the bias and root mean square error (RMSE) in posterior CO2 simulations were largely reduced across the full range of locations, confirming that the GONGGA system improves the estimates of spatial and temporal variations in carbon fluxes by assimilating OCO-2 XCO2 data. This dataset will improve the broader understanding of global carbon cycle dynamics and their response to climate change. The dataset can be accessed at https://doi.org/10.5281/zenodo.8368846 (Jin et al., 2023a).

中文翻译：

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使用 GONGGA 反演系统从 OCO-2 反演推断出的全球地表 CO2 通量数据集（2015-2022）


摘要。准确评估二氧化碳 (CO2) 源和汇的规模和分布对于了解碳循环和支持有关气候缓解行动的政策决策非常重要。卫星反演柱平均干空气二氧化碳摩尔分数 (XCO2) 已被广泛用于通过大气反演技术推断碳通量的空间和时间变化。在这项研究中，我们提出了 2015-2022 年全球空间解析的陆地和海洋碳通量数据集。该数据集是由基于全球观测的温室气体监测系统 (GONGGA) 大气反演系统通过同化轨道碳观测站 2 (OCO-2) XCO2 反演生成的。我们描述了全球范围和一组 TransCom 区域的碳预算、年际变化和季节周期。 8年平均净生物圈交换和海洋碳通量分别为-2.22 ± 0.75和-2.32 ± 0.18 Pg C yr−1，分别吸收了当代化石燃料二氧化碳排放量的约23 ％和24 ％。全球大气二氧化碳年平均增长率为5.17 ± 0.68 Pg C yr−1，与美国国家海洋和大气管理局（NOAA）的测量结果（5.24 ± 0.59 Pg C yr−1）一致。在 TransCom 的 11 个陆地区域中，欧洲拥有最大的陆地汇，其次是北亚洲和温带亚洲。通过将后验二氧化碳模拟与总碳柱观测网络 (TCCON) 检索以及观测包 (ObsPack) 表面烧瓶观测和飞机观测进行比较来评估数据集。 与使用未优化通量的 CO2 模拟相比，后验 CO2 模拟中的偏差和均方根误差 (RMSE) 在整个位置范围内大大降低，证实 GONGGA 系统通过以下方式改进了碳通量时空变化的估计：同化 OCO-2 XCO2 数据。该数据集将增进对全球碳循环动态及其对气候变化的响应的更广泛理解。该数据集可通过 https://doi.org/10.5281/zenodo.8368846 访问（Jin 等人，2023a）。