Atmospheric rivers (ARs) play an important role in the total annual precipitation regionally and globally, delivering precious freshwater to many arid/semiarid regions. On the other hand, they may cause intense precipitation and floods with huge socioeconomic effects worldwide. In this study, we investigate AR‐related precipitation using 18 years (2001–2018) of globally gridded AR locations derived from Modern‐Era Retrospective Analysis for Research and Applications, Version 2 (MERRA‐2). AR precipitation features are explored regionally and seasonally using remote sensing (Integrated Multi‐satellitE Retrievals for GPM version 6 [IMERG V6], daily Global Precipitation Climatology Project version 1.3 [GPCP V1.3], bias‐adjusted CPC Morphing Technique version 1 [CMORPH V1], and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks [PERSIANN‐CDR]) and reanalysis (MERRA‐2 and ECMWF Reanalysis 5th Generation [ERA5]) precipitation products. The results show that most of the world (except the tropics) experience more intense precipitation from AR‐related events compared to non‐AR events. Over the oceans (especially the Southern Ocean), the contribution of ARs to the total precipitation and extreme events is larger than over land. However, some coastal areas over land are highly affected by ARs (e.g., the western and eastern United States and Canada, Western Europe, North Africa, and part of the Middle East, East Asia, and eastern South America and part of Australia). Although spatial correlations for pairs of IMERG/CMORPH and GPCP/PERSIANN‐CDR are fairly high, considerable discrepancies are shown in their estimation of AR‐related events (i.e., overall IMERG and CMORPH show a higher fraction of AR‐related precipitation). It was found that the degree of consistency between reanalysis and satellite‐based products is highly regionally dependent, partly due to the uneven distribution of in situ measurements.

中文翻译：

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遥感和再分析产品中大气河流降水的全球比对

大气河流（AR）在区域和全球年度总降水量中发挥重要作用，将宝贵的淡水输送到许多干旱/半干旱地区。另一方面，它们可能引起强烈的降雨和洪水，对全世界产生巨大的社会经济影响。在本研究中，我们使用18年（2001-2018年）的全球网格化AR位置调查了与AR有关的降水，这些位置来自研究和应用的第2版现代时代回顾性分析（MERRA-2）。利用遥感技术（按GPM第6版[IMERG V6]，每日全球降水气候学项目1.3版[GPCP V1.3]，偏差调整后的CPC变形技术第1版[CMORPH]进行了综合的多卫星E检索），按区域和季节对AR降水特征进行了研究。 V1]，使用人工神经网络[PERSIANN-CDR]和再分析（MERRA-2和ECMWF第5代[ERA5]）沉淀产品从遥感信息中进行降水和降水估算。结果表明，与非AR事件相比，世界上大多数地区（热带地区除外）经历了与AR相关的事件带来的更强烈的降水。在海洋（尤其是南大洋）上，AR对总降水量和极端事件的贡献大于陆地。但是，陆地上的某些沿海地区受到AR的影响很大（例如，美国的西部和东部以及加拿大，西欧，北非以及部分中东，东亚和南美东部以及澳大利亚的一部分）。尽管IMERG / CMORPH和GPCP / PERSIANN-CDR对的空间相关性很高，在与AR有关的事件的估计中显示出相当大的差异（即，整体IMERG和CMORPH显示出与AR有关的降水的比例更高）。结果发现，再分析和基于卫星的产品之间的一致性程度在很大程度上取决于区域，部分原因是原位测量的分布不均。