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首页> 外文期刊>Journal of Applied Meteorology and Climatology >Satellite Estimation of Falling Snow: A Global Precipitation Measurement (GPM) Core Observatory Perspective
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Satellite Estimation of Falling Snow: A Global Precipitation Measurement (GPM) Core Observatory Perspective

机译：落雪卫星估算：全球降水测量（GPM）核心天文台视角

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摘要

Retrievals of falling snow from space-based observations represent key inputs for understanding and linking Earth's atmospheric, hydrological, and energy cycles. This work quantifies and investigates causes of differences among the first stable falling snow retrieval products from the Global Precipitation Measurement (GPM) Core Observatory satellite and CloudSat's Cloud Profiling Radar (CPR) falling snow product. An important part of this analysis details the challenges associated with comparing the various GPM and CloudSat snow estimates arising from different snow-rain classification methods, orbits, resolutions, sampling, instrument specifications, and algorithm assumptions. After equalizing snow-rain classification methodologies and limiting latitudinal extent, CPR observes nearly 10 (3) times the occurrence (accumulation) of falling snow as GPM's Dual-Frequency Precipitation Radar (DPR). The occurrence disparity is substantially reduced if CloudSat pixels are averaged to simulate DPR radar pixels and CPR observations are truncated below the 8-dBZ reflectivity threshold. However, even though the truncated CPR- and DPR-based data have similar falling snow occurrences, average snowfall rate from the truncated CPR record remains significantly higher (43%) than the DPR, indicating that retrieval assumptions (microphysics and snow scattering properties) are quite different. Diagnostic reflectivity (Z)-snow rate (S) relationships were therefore developed at Ku and W band using the same snow scattering properties and particle size distributions in a final effort to minimize algorithm differences. CPR-DPR snowfall amount differences were reduced to similar to 16% after adopting this diagnostic Z-S approach.
机译：从基于空间的观察中落下的雪的检索代表了理解和连接地球大气，水文和能源周期的关键输入。从全球降水测量（GPM）核心天文台卫星和CloudSat的云分析雷达（CPR）落下的雪产品中，这项工作量化和调查了第一稳定下降雪检索产品之间的差异的原因。该分析的重要组成部分详细介绍了与比较不同雪花分类方法，轨道，分辨率，采样，仪器规范和算法假设引起的各种GPM和CloudSat雪估计相关的挑战。在均衡雪地分类方法和限制纬度范围后，CPR观察到跌落雪的发生（累积）作为GPM的双频降水雷达（DPR）的发生近10（3）次。如果Cloudsat像素平均以模拟DPR雷达像素，则发生差异基本上减小，并且CPR观察被截断在8-DBZ反射率阈值以下。但是，即使基于CPR和DPR的数据具有相似的雪灾，截短的CPR记录的平均降雪率仍然明显高（43％），而不是DPR，表明检索假设（微专家和雪散射属性）是很不一样。因此，使用相同的雪散射特性和粒度分布在ku和w频带中开发了诊断反射率（z）-snow率的关系，以最终努力最小化算法差异。在采用这种诊断Z-S方法后，CPR-DPR降雪量差异降低至相似于16％。

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