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- Title
Global Intercomparison of Atmospheric Rivers Precipitation in Remote Sensing and Reanalysis Products.
- Authors
Arabzadeh, Alireza; Ehsani, Mohammad Reza; Guan, Bin; Heflin, Stella; Behrangi, Ali
- Abstract
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. Key Points: Eighteen years of global AR locations are used to regionally and seasonally assess precipitation features from various precipitation productsOver the Southern Ocean, precipitation products show the largest inconsistency in capturing ARs contribution to total and extreme precipitationThe highest inconsistencies between satellite‐based and reanalysis precipitation products are seen over the Middle East and northern Africa
- Subjects
ATMOSPHERIC rivers; REMOTE sensing; FRESH water; GLOBAL Precipitation Climatology Project; ARTIFICIAL neural networks
- Publication
Journal of Geophysical Research. Atmospheres, 2020, Vol 125, Issue 21, p1
- ISSN
2169-897X
- Publication type
Article
- DOI
10.1029/2020JD033021