气候变化领域集成服务门户(CCPortal): Global Intercomparison of Atmospheric Rivers Precipitation in Remote Sensing and Reanalysis Products

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DOI	10.1029/2020JD033021
	Global Intercomparison of Atmospheric Rivers Precipitation in Remote Sensing and Reanalysis Products
	Arabzadeh A.; Ehsani M.R.; Guan B.; Heflin S.; Behrangi A.
发表日期	2020
ISSN	2169897X
卷号	125 期号:21
英文摘要	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. ©2020. American Geophysical Union. All Rights Reserved.
英文关键词	atmospheric river; extreme event; IMERG V06; precipitation product; reanalysis; remote sensing
语种	英语
来源期刊	Journal of Geophysical Research: Atmospheres
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/185672
作者单位	Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, United States; Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, CA, United States; Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States; Department of Geosciences, University of Arizona, Tucson, AZ, United States
推荐引用方式 GB/T 7714	Arabzadeh A.,Ehsani M.R.,Guan B.,et al. Global Intercomparison of Atmospheric Rivers Precipitation in Remote Sensing and Reanalysis Products[J],2020,125(21).
APA	Arabzadeh A.,Ehsani M.R.,Guan B.,Heflin S.,&Behrangi A..(2020).Global Intercomparison of Atmospheric Rivers Precipitation in Remote Sensing and Reanalysis Products.Journal of Geophysical Research: Atmospheres,125(21).
MLA	Arabzadeh A.,et al."Global Intercomparison of Atmospheric Rivers Precipitation in Remote Sensing and Reanalysis Products".Journal of Geophysical Research: Atmospheres 125.21(2020).