Evaluating the Representations of Atmospheric Rivers and Their Associated Precipitation in Reanalyses With Satellite Observations
Evaluating the Representations of Atmospheric Rivers and Their Associated Precipitation in Reanalyses With Satellite Observations
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卫星观测再分析中评估大气河流及其相关降水的表征
DOI：
10.1029/2023jd038937
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Yanez, Emilio
中科院分区：
文献类型：
--
作者：
Ma, Weiming;Chen, Gang;Guan, Bin;Shields, Christine A.;Tian, Baijun;Yanez, Emilio
大气河流（AR）是大气中增强的水平水分输送的细丝。由于其在经向水汽输送和区域极端天气中的突出作用，ARs 近年来得到了广泛的研究。然而，全球范围内 AR 及其相关降水的表现仍然很大程度上未知。在这项研究中，我们开发了一种专门用于卫星观测的 AR 检测算法，使用水分和地转风，这些风是从 NASA Aqua 卫星上的大气红外探测器和高级微波探测装置联合检索得到的 3D 位势高度场得出的。该算法使我们能够开发第一个仅基于卫星观测的全球 AR 目录。然后将基于卫星的 AR 目录与基于卫星的降水（GPM 集成多卫星检索）相结合，以评估再分析产品中 AR 和 AR 引起的降水的表示。我们的结果表明，AR 频率和 AR 长度分布在数据集中的分布通常较小，而 AR 宽度的分布相对较大。研究发现，再分析产品始终低估与 AR 相关的平均降水量和极端降水量。然而，在 AR 条件下，所有重新分析往往会过于频繁地沉淀，尤其是在低纬度地区。这一发现与困扰几代气候模型的“毛毛雨”偏差是一致的。总体而言，这项研究的结果有助于改善再分析和气候模型中 AR 和相关降水的表征。
Atmospheric rivers (ARs) are filaments of enhanced horizontal moisture transport in the atmosphere. Due to their prominent role in the meridional moisture transport and regional weather extremes, ARs have been studied extensively in recent years. Yet, the representations of ARs and their associated precipitation on a global scale remains largely unknown. In this study, we developed an AR detection algorithm specifically for satellite observations using moisture and the geostrophic winds derived from 3D geopotential height field from the combined retrievals of the Atmospheric Infrared Sounder and the Advanced Microwave Sounding Unit on NASA Aqua satellite. This algorithm enables us to develop the first global AR catalog based solely on satellite observations. The satellite‐based AR catalog is then combined with the satellite‐based precipitation (Integrated Muti‐SatellitE Retrievals for GPM) to evaluate the representations of ARs and AR‐induced precipitation in reanalysis products. Our results show that the spreads in AR frequency and AR length distribution are generally small across data sets, while the spread in AR width is relatively larger. Reanalysis products are found to consistently underestimate both mean and extreme AR‐related precipitation. However, all reanalyses tend to precipitate too often under AR conditions, especially over low latitude regions. This finding is consistent with the “drizzling” bias which has plagued generations of climate models. Overall, the findings of this study can help to improve the representations of ARs and associated precipitation in reanalyses and climate models.
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影响因子：
5.2
作者：
Lavers, David A.;Villarini, Gabriele
通讯作者：
Villarini, Gabriele
理想化综合气候模型中大气河流对全球变暖的稳健响应
影响因子：
4.9
作者：
Zhang, Pengfei;Chen, Gang;Ma, Weiming;Ming, Yi;Wu, Zheng
通讯作者：
Wu, Zheng
大气红外探测器和先进微波扫描辐射计的总可降水水汽气候学偏差
影响因子：
--
作者：
E. Fetzer;B. Lambrigtsen;A. Eldering;H. Aumann;M. Chahine
通讯作者：
M. Chahine
影响因子：
7.9
作者：
J. Wille;V. Favier;N. Jourdain;C. Kittel;J. Turton;Cécile Agosta;I. Gorodetskaya;G. Picard;Francis Codron;Christophe Leroy-Dos Santos;C. Amory;X. Fettweis;J. Blanchet;V. Jomelli;A. Berchet
通讯作者：
J. Wille;V. Favier;N. Jourdain;C. Kittel;J. Turton;Cécile Agosta;I. Gorodetskaya;G. Picard;Francis Codron;Christophe Leroy-Dos Santos;C. Amory;X. Fettweis;J. Blanchet;V. Jomelli;A. Berchet
DOI：
10.1029/2019jd030936
发表时间：
2019-12
期刊：
Journal of Geophysical Research: Atmospheres
影响因子：
--
作者：
J. Rutz;C. Shields;J. Lora;A. Payne;B. Guan;P. Ullrich;T. O’Brien;L. Leung;F. Ralph;M. Wehner;S. Brands;A. Collow;N. Goldenson;I. Gorodetskaya;Helen V. Griffith;K. Kashinath;B. Kawzenuk;Harinarayan Krishnan;V. Kurlin;D. Lavers;G. Magnusdottir;K. Mahoney;E. McClenny;G. Muszynski;P. Nguyen;M. Prabhat;Y. Qian;A. Ramos;C. Sarangi;S. Sellars;T. Shulgina;R. Tomé;D. Waliser;D. Walton;G. Wick;Anna M. Wilson;M. Viale
通讯作者：
J. Rutz;C. Shields;J. Lora;A. Payne;B. Guan;P. Ullrich;T. O’Brien;L. Leung;F. Ralph;M. Wehner;S. Brands;A. Collow;N. Goldenson;I. Gorodetskaya;Helen V. Griffith;K. Kashinath;B. Kawzenuk;Harinarayan Krishnan;V. Kurlin;D. Lavers;G. Magnusdottir;K. Mahoney;E. McClenny;G. Muszynski;P. Nguyen;M. Prabhat;Y. Qian;A. Ramos;C. Sarangi;S. Sellars;T. Shulgina;R. Tomé;D. Waliser;D. Walton;G. Wick;Anna M. Wilson;M. Viale