Satellite ocean color observations are extensively utilized in global carbon sink evaluation. However, the valid coverage of chlorophyll-a concentration (Chla, mg m−3) measurements from these observations is severely limited during autumn and winter in high latitude oceans. The high solar zenith angle (SZA) stands as one of the primary contributors to the reduced quality of Chla products in the high-latitude Southern Ocean during these seasons. This study addresses this challenge by employing a random forest-based regression ensemble (RFRE) method to enhance the quality of Moderate Resolution Imaging Spectroradiometer (MODIS) Chla products affected by high SZA conditions. The RFRE model incorporates the color index (CI), band-ratio index (R), SZA, sensor zenith angle (senz), and Rayleigh-corrected reflectance at 869 nm (Rrc(869)) as predictors. The results indicate that the RFRE model significantly increased the MODIS observed Chla coverage (1.03 to 3.24 times) in high-latitude Southern Ocean regions to the quality of standard Chla products. By applying the recovered Chla to re-evaluate the carbon sink in South Ocean, results showed that the Southern Ocean’s ability to absorb carbon dioxide (CO2) in winter has been underestimated (5.9–18.6 Tg C year−1) in previous assessments. This study underscores the significance of improving the Chla products for a more accurate estimation of winter carbon sink in the Southern Ocean.

中文翻译：

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通过在太阳天顶角高处回收 MODIS-Aqua 叶绿素-a 产品来重新评估南大洋的冬季碳汇


卫星海洋颜色观测广泛用于全球碳汇评估。然而，在高纬度海洋的秋冬季节，这些观测结果的叶绿素-a 浓度 （Chla， mg m-3） 测量的有效覆盖率受到严重限制。在这些季节，高太阳天顶角 （SZA） 是导致高纬度南大洋 Chla 产品质量下降的主要因素之一。本研究通过采用基于随机森林的回归集成 （RFRE） 方法来提高受高 SZA 条件影响的中分辨率成像光谱辐射计 （MODIS） Chla 产品的质量，从而解决了这一挑战。RFRE 模型包含颜色指数 （CI）、带比指数 （R）、SZA、传感器天顶角 （senz） 和 869 nm 处的瑞利校正反射率 （Rrc（869）） 作为预测因子。结果表明，RFRE 模型显著提高了高纬度南大洋地区 MODIS 观测的 Chla 覆盖率（1.03 至 3.24 倍），达到标准 Chla 产品的质量。通过应用回收的 Chla 重新评估南大洋的碳汇，结果表明，在之前的评估中，南大洋在冬季吸收二氧化碳 （CO2） 的能力被低估了（5.9-18.6 Tg C 年-1）。本研究强调了改进 Chla 乘积对于更准确地估计南大洋冬季碳汇的重要性。