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Exploitation of Gpm/Cloudsat Coincidence Dataset for Global Snowfall Retrieval

机译:利用Gpm / Cloudsat重合数据集进行全球降雪检索

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The assessment of the actual observational capabilities of snowfall by spaceborne microwave radiometers is crucial to develop and improve precipitation retrieval algorithms. Exploiting coincident spaceborne active and passive microwave sensor datasets can effectively enhance our understanding of high-frequency microwave channels sensitivity to snowfall. This study illustrates the results of the analysis of matched Global Precipitation Measurement (GPM) Microwave Imager (GMI) and CloudSat Cloud Profiling Radar (CPR) snowfall observations (mainly found at latitudes between 55° and 65°) providing insights on GMI multi-frequency signals associated with different snowfall types. These findings are used to develop a new algorithm to retrieve snow water path associated to surface snowfall from GMI multichannel measurements.
机译:利用星载微波辐射计评估降雪的实际观测能力对于开发和改进降水检索算法至关重要。利用一致的星载有源和无源微波传感器数据集可以有效地增强我们对高频微波通道对降雪敏感性的了解。这项研究说明了匹配的全球降水量测量(GPM)微波成像仪(GMI)和CloudSat云剖析雷达(CPR)降雪观测结果(主要在55°至65°之间的纬度)的分析结果,从而提供了有关GMI多频的见解与不同降雪类型相关的信号。这些发现被用于开发一种新的算法,以从GMI多通道测量中检索与地面降雪相关的雪水路径。

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