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首页> 外文期刊>Journal of hydrometeorology >Evaluation of Precipitation Vertical Profiles Estimated by GPM-Era Satellite-Based Passive Microwave Retrievals
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Evaluation of Precipitation Vertical Profiles Estimated by GPM-Era Satellite-Based Passive Microwave Retrievals

机译:基于GPM-ERA卫星无源微波检索估算的降水垂直谱的评估

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Precipitation estimation based on passive microwave (MW) observations from low-Earth-orbiting satellites is one of the essential variables for understanding the global climate. However, almost all validation studies for such precipitation estimation have focused only on the surface precipitation rate. This study investigates the vertical precipitation profiles estimated by two passive MW-based retrieval algorithms, i.e., the emissivity principal components (EPC) algorithm and the Goddard profiling algorithm (GPROF). The passive MW-based condensed water content profiles estimated from the Global Precipitation Measurement Microwave Imager (GMI) are validated using the GMI 1 Dual-Frequency Precipitation Radar combined algorithm as the reference product. It is shown that the EPC generally underestimates the magnitude of the condensed water content profiles, described by the mean condensed water content, by about 20%-50% in the middle-to-high latitudes, while GPROF overestimates it by about 20%-50% in the middle-to-high latitudes and more than 50% in the tropics. Part of the EPC magnitude biases is associated with the representation of the precipitation type (i.e., convective and stratiform) in the retrieval algorithm. This suggests that a separate technique for precipitation type identification would aid in mitigating these biases. In contrast to the magnitude of the profile, the profile shapes are relatively well represented by these two passive MW-based retrievals. The joint analysis between the estimation performances of the vertical profiles and surface precipitation rate shows that the physically reasonable connections between the surface precipitation rate and the associated vertical profiles are achieved to some extent by the passive MW-based algorithms.
机译:基于近地轨道卫星被动微波(MW)观测的降水量估算是了解全球气候的基本变量之一。然而,几乎所有此类降水量估算的验证研究都只关注地表降水率。本研究调查了两种基于微波的被动反演算法,即发射率主成分(EPC)算法和戈达德剖面算法(GPROF)估算的垂直降水廓线。以GMI-1双频降水雷达组合算法为参考产品,验证了全球降水测量微波成像仪(GMI)估算的被动MW凝结水含量剖面。结果表明,在中高纬度地区,EPC通常低估了凝结水含量剖面(由平均凝结水含量描述)的大小约20%-50%,而GPROF在中高纬度地区高估了约20%-50%,在热带地区高估了超过50%。部分EPC震级偏差与反演算法中降水类型(即对流和层状)的表示有关。这表明,单独的降水类型识别技术将有助于缓解这些偏差。与剖面大小相反,剖面形状相对较好地由这两个基于MW的被动反演表示。垂直廓线估计性能与地面降水率之间的联合分析表明,基于被动MW的算法在一定程度上实现了地面降水率与相关垂直廓线之间的物理合理联系。

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