Skofronick-Jackson Gail, Kulie Mark, Milani Lisa, Munchak Stephen J, Wood Norman B, Levizzani Vincenzo
NASA Goddard Space Flight Center, Greenbelt, Maryland.
NOAA/NESDIS/STAR/Advanced Satellite Products Branch, Madison, Wisconsin.
J Appl Meteorol Climatol. 2019 Jul;58(7):1429-1448. doi: 10.1175/JAMC-D-18-0124.1. Epub 2019 Jun 24.
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) satellite and Cloud Profiling Radar (CPR) falling snow product. An important part of this analysis details the challenges associated with comparing the various GPM and 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 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 ()-snow rate () 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 ~16% after adopting this diagnostic - approach.
从天基观测中反演降雪是理解和关联地球大气、水文和能量循环的关键输入。这项工作量化并研究了全球降水测量（GPM）卫星的首批稳定降雪反演产品与云廓线雷达（CPR）降雪产品之间差异的成因。该分析的一个重要部分详细阐述了因不同的雨雪分类方法、轨道、分辨率、采样、仪器规格和算法假设而在比较各种GPM和降雪估计值时所面临的挑战。在统一雨雪分类方法并限制纬度范围后，CPR观测到的降雪发生率（累积量）几乎是GPM的双频降水雷达（DPR）的10（3）倍。如果对像素进行平均以模拟DPR雷达像素，并将CPR观测值截断在8 dBZ反射率阈值以下，发生率差异将大幅减小。然而，即使基于截断后的CPR和DPR的数据具有相似的降雪发生率，截断后的CPR记录的平均降雪率仍比DPR显著高（43%），这表明反演假设（微物理和雪的散射特性）有很大不同。因此，最后利用相同的雪散射特性和粒径分布，在Ku波段和W波段建立了诊断反射率（）-降雪率（）关系，以尽量减少算法差异。采用这种诊断-方法后，CPR-DPR降雪量差异减小到约16%。
