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How Accurately Can Satellite Products (TMPA and IMERG) Detect Precipitation Patterns, Extremities, and Drought Across the Nepalese Himalaya?

机译:卫星产品(TMPA和IMERG)如何检测降水模式,四肢和尼泊尔喜马拉雅亚的干旱?

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This study aims to assess the accuracy of two satellite‐based precipitation products (SBPPs), that is, Tropical Rainfall Measurement Mission (TRMM)‐based Multi‐satellite Precipitation Analysis (TMPA) and its upgraded version Integrated Multi‐Satellite Retrievals for Global Precipitation Measurement (IMERG), in capturing spatial and temporal variation of precipitation and their application for extreme events (high‐intensity precipitation and drought). They were evaluated against 142‐gauge stations from Nepal during 2001–2018. The results show that, in general, both SBPPs show the overall characteristics of precipitation patterns, although underestimated the mean annual precipitation during the study period. It was also noted that IMERG product yields better performance to detect precipitation events (probability of detection) and no‐precipitation events (false alarm ratio) than TMPA. Based on four different extreme precipitation indices: heavy precipitation events (R10mm), extreme precipitation events (R25mm), five consecutive dry days (CDD), and five consecutive wet days (CWD), it was observed that the SBPPs underestimated the frequency of R25mm and CDD spells while overestimated R10mm and CWD spells. Additionally, both SBPPs exhibited considerable capabilities in capturing the drought events during the study period. Overall, the drought event, bias, and frequency show that the IMERG product has slightly better capabilities to capture drought than the TMPA product. In general, IMERG was found to be superior at a daily timescale, while TMPA shows consistent performance on a monthly scale during the study period. Furthermore, there is still space for further improvement of IMERG rainfall retrieval algorithms.
机译:本研究旨在评估两颗卫星沉淀产品(SBPPS)的准确性,即热带降雨量测量任务(TRMM) - 基于多卫星降水分析(TMPA)及其升级版的全球降水量的综合多卫星检索测量(IMERG),捕获降水的空间和时间变化及其对极端事件的应用(高强度降水和干旱)。在2001-2018期间,对来自尼泊尔的142尺度站进行评估。结果表明,一般而言,SBPPS都显示出降水模式的总体特征,尽管在研究期间低估了平均年降水量。还有人注意到,Imerc产物产生更好的性能来检测比TMPA的降水事件(检测概率)和无沉淀事件(误报例)。基于四种不同的极端降水指数:重度降水事件(R10mm),极端降水事件(R25mm),连续五天(CDD)和五个连续潮湿的天(CWD),观察到SBPP低估了R25MM的频率和CDD咒语,而高估R10MM和CWD法术。此外,SBPPS都表现出在研究期间捕获干旱事件时具有相当大的能力。总体而言,干旱事件,偏见和频率表明,Imerc产品具有略微更好的能力来捕获干旱而不是TMPA产品。通常,Imerc被发现在每日时间尺度上优越,而TMPA在学习期间每月表现出一致的性能。此外,仍然存在进一步改善IMERG降雨检索算法的空间。

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