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首页> 外文期刊>Journal of hydrometeorology >Global Multiscale Evaluation of Satellite Passive Microwave Retrieval of Precipitation during the TRMM and GPM Eras: Effective Resolution and Regional Diagnostics for Future Algorithm Development
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Global Multiscale Evaluation of Satellite Passive Microwave Retrieval of Precipitation during the TRMM and GPM Eras: Effective Resolution and Regional Diagnostics for Future Algorithm Development

机译：TRMM和GPM时代卫星被动微波检索卫星被动微波检索的全球多尺度评估：未来算法开发的有效分辨率和区域诊断

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The constellation of spaceborne passive microwave (MW) sensors, coordinated under the framework of the Precipitation Measurement Missions international agreement, continuously produces observations of clouds and precipitation all over the globe. The Goddard profiling algorithm (GPROF) is designed to infer the instantaneous surface precipitation rate from the measured MW radiances. The last version of the algorithm (GPROF-2014)-the product of more than 20 years of algorithmic development, validation, and improvement-is currently used to estimate precipitation rates from the microwave imager GMI on board the GPM core satellite. The previous version of the algorithm (GPROF-2010) was used with the microwave imager TMI on board TRMM. In this paper, TMI-GPROF-2010 estimates and GMI-GPROF-2014 estimates are compared with coincident active measurements from the Precipitation Radar on board TRMM and the Dual-Frequency Precipitation Radar on board GPM, considered as reference products. The objective is to assess the improvement of the GPM-era microwave estimates relative to the TRMM-era estimates and diagnose regions where continuous improvement is needed. The assessment is oriented toward estimating the "effective resolution'' of the MW estimates, that is, the finest scale at which the retrieval is able to accurately reproduce the spatial variability of precipitation. A wavelet-based multiscale decomposition of the radar and passive microwave precipitation fields is used to formally define and assess the effective resolution. It is found that the GPM-era MW retrieval can resolve finer-scale spatial variability over oceans than the TRMM-era retrieval. Over land, significant challenges exist, and this analysis provides useful diagnostics and a benchmark against which future retrieval algorithm improvement can be assessed.
机译：在降水测量任务国际协议的框架内协调的星载无源微波（MW）传感器的星座不断产生对全球云和降水的观察。戈达德分析算法（GPROF）旨在推断从测量的MW辐射的瞬时表面沉淀速率。最后一个版本的算法（GPROF-2014） - 超过20年的算法开发，验证和改进的产品 - 目前用于估算GPM核心卫星的微波成像GMI的降水率。以前的算法（GPROF-2010）与船上的微波成像仪TMI一起使用。在本文中，将TMI-GPROF-2010估计和GMI-GPROF-2014估计与TRMM上的降水雷达和GPM的双频降水雷达的重合活动测量进行了比较，被认为是参考产品。目的是评估相对于TRMM-ERA估计和诊断区域的GPM-ERA微波估计的改进，诊断所需的区域。评估旨在估算MW估计的“有效分辨率”，即检索能够准确地再现降水空间变化的最佳规模。基于小波的多尺度分解的雷达和被动微波降水场用于正式定义和评估有效分辨率。发现GPM-ERA MW检索可以在海洋上解析比TRMM-ERA检索的更精细的空间变异性。在土地上，存在重大挑战，并且该分析提供了重要的挑战可以评估未来检索算法改进的有用诊断和基准。

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