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Evaluating Light Rain from Satellite- and Ground-Based Remote Sensing Data over the Subtropical North Atlantic

机译:从亚热带北大西洋的卫星和地面遥感数据评估小雨

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Three state-of-the-art satellite climatologies are analyzed for their ability to observe light rain from predominantly shallow, warm clouds over the subtropical North Atlantic Ocean trade winds (1998-2005). HOAPS composite (HOAPS-C), version 3.2; TMPA, version 7; and GPCP 1 Degree Daily (1DD), version 1.2, are compared with ground-based S-Pol radar data from the Rain in Cumulus over the Ocean (RICO; winter 2004/05) campaign and Micro Rain Radar data from the Barbados Cloud Observatory (2010-12). Winter rainfall amounts to one-third of annual rainfall, whereby light rain from warm clouds dominates. Daily rain occurrence and rain intensity during RICO largely differ among the satellite climatologies. TMPA best captures the frequent light rain events, only missing 7% of days on which the S-Pol radar detects rain, whereas HOAPS-C misses 33% and GPCP 1DD misses 56%. Algorithm constraints mainly cause these differences. In HOAPS-C also few available passive microwave (PMW) sensor overpasses limit its performance. TMPA outperforms HOAPS-C when only comparing nonmissing time steps, yet HOAPS-C can detect rain for S-Pol rain-covered areas down to 2%. In GPCP 1DD's algorithm, the underestimated rain occurrence derived from PMW scanners is linked to the overestimated rain intensity, being constrained by the GPCP monthly satellite-gauge combination, whereby IR sensors determine the timing. Algorithm improvements in version 1.2 increased the rain occurrence by 50% relative to version 1.1. In version 7 of TMPA, algorithm corrections in PMW sounder data largely improved the rain detection relative to version 6. TMPA best represents light rain in the North Atlantic trades, followed by HOAPS-C and GPCP 1DD.
机译:分析了三种最新的卫星气候,它们具有观测副热带北大西洋贸易风中主要来自浅暖云的小雨的能力(1998-2005年)。 HOAPS组合(HOAPS-C),版本3.2; TMPA,版本7;以及GPCP 1度日报(1DD)1.2版与来自海洋积雨中的陆基S-Pol雷达数据(RICO; 2004/05冬季)和来自巴巴多斯云天文台的微雨雷达数据进行了比较(2010-12)。冬季降雨量占年降雨量的三分之一,其中暖云的小雨占主导地位。 RICO期间的每日降雨发生和降雨强度在卫星气候之间存在很大差异。 TMPA最好地捕获了频繁的小雨事件,仅少了S-Pol雷达检测到下雨天的7%,而HOAPS-C少了33%,GPCP 1DD少了56%。算法约束主要导致这些差异。在HOAPS-C中,几乎没有可用的无源微波(PMW)传感器立交桥会限制其性能。仅比较非漏失时间步长时,TMPA的性能优于HOAPS-C,而HOAPS-C可以检测到S-Pol雨水覆盖区域低至2%的雨水。在GPCP 1DD的算法中,由PMW扫描仪得出的被低估的降雨发生与被高估的降雨强度有关,受到GPCP月度卫星仪表组合的约束,从而由IR传感器确定时间。与版本1.1相比,版本1.2中的算法改进使降雨发生率增加了50%。在TMPA的第7版中,相对于第6版,PMW测深仪数据中的算法校正大大改善了雨量检测。TMPA最能代表北大西洋贸易中的小雨,其次是HOAPS-C和GPCP 1DD。

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