Abstract. Large rivers play an important role in transferring water and all of its constituents including carbon in its various forms from the land to the ocean, but the seasonal and inter-annual variations in these riverine flows remain unclear. Satellite Earth observation datasets and reanalysis products can now be used to observe synoptic-scale spatial and temporal variations in the carbonate system within large river outflows. Here we present the OceanSODA-UNEXE time series, a dataset of the full carbonate system in the surface water outflows of the Amazon (2010–2020) and Congo Rivers (2002–2016). Optimal empirical approaches were used to generate gridded Total alkalinity (TA) and dissolved inorganic carbon (DIC) fields in the outflow regions. These combinations were determined by equitably evaluating all combinations of algorithms and inputs against a matchup database of in situ observations. Gridded TA and DIC along with gridded temperature and salinity data enable the calculation of the full carbonate system in the surface ocean. The algorithm evaluation constitutes a Type A uncertainty evaluation for TA and DIC where model, input and sampling uncertainties are considered. Total combined uncertainties for TA and DIC were propagated through the carbonate system calculation allowing all variables to be provided with an associated uncertainty estimate. In the Amazon outflow, the total combined uncertainty for TA was identified as 36 μmol kg⁻¹ (weighted RMSD 35 μmol kgkg⁻¹ and weighted bias 8 μmol kg⁻¹ for n=82) and for DIC was 44 μmol kg⁻¹ (weighted RMSD 44 μmol kg⁻¹ and weighted bias −6 μmol kg⁻¹ for n=70). The spatially averaged propagated uncertainties for the partial pressure of carbon dioxide (pCO₂) and pH are 85 μatm and 0.08 respectively, where the pH uncertainty is relative to an average pH of 8.19. In the Congo outflow, the combined uncertainty for TA was identified as 29 μmol kg⁻¹ (weighted RMSD 28 μmol kg⁻¹and weighted bias 6 μmol kg⁻¹ for n=102) and for DIC was 40 μmol kg⁻¹ (weighted RMSD 37 μmol kg⁻¹and weighted bias −16 μmol kg⁻¹ for n=77). The spatially averaged propagated uncertainties for pCO₂ and pH are 74 μatm and 0.08 respectively, where the pH uncertainty is relative to an average pH of 8.21. The combined uncertainties in TA and DIC in the Amazon and Congo outflows are lower than the natural variability their respective regions allowing the time varying regional variability to be evaluated. Potential uses of these data would be for assessing the spatial and temporal flow of carbon from the Amazon and Congo rivers into the Atlantic and for assessing the riverine driven carbonate system variations experienced by tropical reefs within the outflow regions.

中文翻译：

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OceanSODA-UNEXE：一个多年网格化的亚马逊和刚果河流出地表海洋碳酸盐系统数据集

摘要。大型河流在将水及其所有成分（包括各种形式的碳）从陆地转移到海洋方面发挥着重要作用，但这些河流流量的季节和年际变化仍不清楚。卫星地球观测数据集和再分析产品现在可用于观察大型河流流出物中碳酸盐系统的天气尺度空间和时间变化。在这里，我们展示了 OceanSODA-UNEXE 时间序列，这是亚马逊河（2010-2020 年）和刚果河（2002-2016 年）地表水流出物中完整碳酸盐系统的数据集。最佳经验方法用于在流出区域生成网格总碱度 (TA) 和溶解无机碳 (DIC) 场。现场观察。网格 TA 和 DIC 以及网格温度和盐度数据能够计算表层海洋中的完整碳酸盐系统。算法评估构成了 TA 和 DIC 的 A 类不确定性评估，其中考虑了模型、输入和采样的不确定性。TA 和 DIC 的总组合不确定性通过碳酸盐系统计算传播，允许为所有变量提供相关的不确定性估计。在亚马逊流出物中，TA 的总组合不确定性被确定为 36 μmol kg ^-1（加权 RMSD 为 35 μmol kgkg ^-1，加权偏差为 8 μmol kg ^-1，n=82），DIC 为 44 μmol kg ^-1（加权 RMSD 44 μmol kg ^-1和加权偏差-6 μmol kg ^-1，n=70）。二氧化碳分压 ( p CO ₂ ) 和 pH 值的空间平均传播不确定性分别为 85 μatm 和 0.08，其中 pH 不确定性与 8.19 的平均 pH 值相关。在刚果流出物中，TA 的组合不确定性被确定为 29 μmol kg ^-1（加权 RMSD 28 μmol kg ^-1和加权偏差 6 μmol kg ^-1，n=102），DIC 为 40 μmol kg ^-1（加权RMSD 37 μmol kg ^-1和加权偏差 -16 μmol kg ^-1，n=77)。p CO ₂的空间平均传播不确定性和 pH 分别为 74 μatm 和 0.08，其中 pH 不确定性与平均 pH 8.21 相关。亚马逊和刚果流出的 TA 和 DIC 的综合不确定性低于其各自区域的自然变率，从而可以评估随时间变化的区域变率。这些数据的潜在用途将是评估从亚马逊河和刚果河流入大西洋的碳的时空流动，以及评估流出区域内热带珊瑚礁经历的河流驱动的碳酸盐系统变化。