Adapting Passive Microwave-Based Precipitation Algorithms to Variable Microwave Land Surface Emissivity to Improve Precipitation Estimation from the GPM Constellation

A fully global satellite-based precipitation estimate that can transition across changing Earth surface and complex land/water conditions is an important capability for many hydrological applications, and for independent evaluation of the precipitation derived from weather and climate models. This capability is inherently challenging owing to the complexity of the surface geophysical properties upon which the satellite-based instruments view. To date, these satellite observations originate primarily from a variety of wide-swath passive microwave (MW) imagers and sounders. In contrast to open ocean and large water bodies, the surface emissivity contribution to passive MW measurements is much more variable for land surfaces, with varying sensitivities to near-surface precipitation. The NASA/JAXA Global Precipitation Measurement (GPM) spacecraft (2014-current) is equipped with a dual-frequency precipitation radar and a multichannel passive MW imaging radiometer specifically designed for precipitation measurement, covering substantially more land area than its predecessor Tropical Rainfall Measuring Mission (TRMM). The synergy between GPM’s instruments has guided a number of new frameworks for passive MW precipitation retrieval algorithms, whereby the information carried by the single narrow-swath precipitation radar is exploited to recover precipitation from a disparate constellation of passive MW imagers and sounders. With over six years of increased land surface coverage provided by GPM, new insight has been gained into the nature of the microwave surface emissivity over land and ice/snow covered surfaces, leading to improvements in a number of physical and semi-physical based precipitation retrieval techniques that adapt to variable Earth surface conditions. In this manuscript, the workings and capabilities of several of these approaches are highlighted.

一种能够在不断变化的地球表面以及复杂的陆地/水域条件之间转换的完全基于全球卫星的降水估算，对于许多水文应用以及对天气和气候模型得出的降水进行独立评估来说是一项重要能力。由于卫星仪器所观测的地表地球物理特性的复杂性，这种能力本身具有挑战性。到目前为止，这些卫星观测主要来自各种宽幅被动微波成像仪和探测仪。与开阔海洋和大型水体相比，陆地表面的发射率对被动微波测量的影响变化更大，对近地表降水的敏感度也各不相同。美国国家航空航天局/日本宇宙航空研究开发机构的全球降水测量（GPM）航天器（2014年至今）配备了双频降水雷达和一个专门用于降水测量的多通道被动微波成像辐射计，其覆盖的陆地面积比其前身热带降雨测量任务（TRMM）大得多。GPM仪器之间的协同作用为被动微波降水反演算法带来了一些新的框架，通过这些框架，利用单条窄幅降水雷达所携带的信息从不同的被动微波成像仪和探测仪星座中获取降水信息。随着GPM提供的陆地表面覆盖范围增加了六年多，人们对陆地以及冰雪覆盖表面的微波表面发射率的性质有了新的认识，从而改进了许多基于物理和半物理的、适应不同地球表面条件的降水反演技术。在本文中，将重点介绍其中几种方法的工作原理和能力。