基于gpm时代卫星无源微波反演降水垂直廓线的评价。

IF 3.1 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES
Journal of Hydrometeorology Pub Date : 2020-12-23 Epub Date: 2021-01-01 DOI:10.1175/jhm-d-20-0160.1
Nobuyuki Utsumi, F Joseph Turk, Ziad S Haddad, Pierre-Emmanuel Kirstetter, Hyungjun Kim
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引用次数: 11

摘要

基于低轨道卫星无源微波(MW)观测的降水估算是了解全球气候的重要变量之一。然而,几乎所有对这种降水估计的验证研究都只关注地表降水率。研究了发射率主成分(EPC)算法和Goddard剖面算法(GPROF)两种基于毫瓦的被动反演算法估算的垂直降水剖面。采用全球降水测量微波成像仪(GMI) +双频降水雷达组合算法作为参考产品,对GMI估算的基于被动毫瓦的凝结水含量剖面进行验证。结果表明,EPC在中高纬度地区普遍低估了由平均凝析水含量描述的凝析水含量剖面的大小,低估幅度约为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50%以上。部分EPC震级偏差与检索算法中降水类型(即对流和层状)的表示有关。这表明,一种单独的降水类型识别技术将有助于减轻这些偏差。与剖面的大小相反,这两种被动的基于mw的检索相对较好地代表了剖面形状。通过对垂直剖面与地表降水率估算性能的联合分析表明,被动毫瓦算法在一定程度上实现了地表降水率与相关垂直剖面之间的物理合理联系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluation of Precipitation Vertical Profiles Estimated by GPM-Era Satellite-Based Passive Microwave Retrievals.

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 + 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.

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来源期刊
Journal of Hydrometeorology
Journal of Hydrometeorology 地学-气象与大气科学
CiteScore
7.40
自引率
5.30%
发文量
116
审稿时长
4-8 weeks
期刊介绍: The Journal of Hydrometeorology (JHM) (ISSN: 1525-755X; eISSN: 1525-7541) publishes research on modeling, observing, and forecasting processes related to fluxes and storage of water and energy, including interactions with the boundary layer and lower atmosphere, and processes related to precipitation, radiation, and other meteorological inputs.
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