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首页> 外文会议>Asian conference on remote sensing;ACRS >Evaluation of Error in Satellite-Derived Precipitation Estimates over the Himalayan region: A Case study for an Extreme Event in 2013
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Evaluation of Error in Satellite-Derived Precipitation Estimates over the Himalayan region: A Case study for an Extreme Event in 2013

机译：喜马拉雅地区人造卫星降水估计误差的评估：2013年极端事件的案例研究

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Conventional tools such as rain-gauge stations and meteorological radars were used to monitor extreme rainfall events in many parts of India. But applications of these measurements to perform hydrological analysis were limited over Indian Himalayas regions because of inaccessibility of areas and lack of homogenous networks of rain-gauge stations. Satellite-based Precipitation Estimates are the alternative options for assessing any hydro-meteorological hazards over Himalayas. In this study, we evaluated three satellite based rainfall products (i.e., TMPA-3B42, Global Satellite Mapping of Precipitation (GSMaP), and NOAA CPC Morphing Technique (CMORPH)) against the rain gauge-based India Meteorological Department (IMD) gridded dataset. The errors in precipitation were assessed especially for an extreme rainfall episode that was witnessed during June 2013 in the Western Himalayas. This event was widely known as Kerdarnath disaster, which has caused widespread flash floods, landslides, and debris flow. The findings from this comprehensive study suggested that the magnitude of precipitation as well as peak rainfall intensity were underestimated in TMPA-3B42 and CMORPH. However, GSMaP showed dual trends with under- and over-estimations against gauge-based IMD data. Based on the statistical approach on the determination of error statistic metrics, namely, MAE (mean absolute error), NRMSE (normalized root mean square error), PBIAS (percent bias), and NSE (Nash-Sutcliffe efficiency) of respective satellite products, it was confirmed that TMPA-3B42 estimates were more relevant and accurate compared to other two satellite products for this extreme rainfall event. The TMPA-3B42-based precipitation was negatively biased by 18%, while GSMaP was positively biased by 14%. The NSE for TMPA-3B42 were lower (-0.93) compared to other products. Thereby, this study concludes that TMPA-3B42 precipitation can be useful for any hydrological study for extreme rainfall episode in the region, where rain-gauges are sparse or rain-gauge networks are unevenly distributed.
机译：诸如雨量计站和气象雷达之类的常规工具被用来监测印度许多地方的极端降雨事件。但是，由于该地区交通不便且缺乏雨量计站的同构网络，因此在印度喜马拉雅山地区将这些测量方法用于水文分析的应用受到了限制。基于卫星的降水估计是评估喜马拉雅山上任何水文气象灾害的替代选择。在这项研究中，我们针对基于雨量计的印度气象部门（IMD）网格数据集，评估了三种基于卫星的降雨产品（即TMPA-3B42，全球卫星降水图（GSMaP）和NOAA CPC变体技术（CMORPH））。 。尤其是针对2013年6月在西喜马拉雅山目睹的极端降雨事件，对降水误差进行了评估。该事件被广泛称为Kerdarnath灾难，已引起广泛的山洪，滑坡和泥石流。这项全面研究的结果表明，TMPA-3B42和CMORPH中的降水量和峰值降水强度被低估了。但是，GSMaP对基于量规的IMD数据显示出低估和高估的双重趋势。基于确定误差统计指标的统计方法，即相应卫星产品的MAE（平均绝对误差），NRMSE（归一化均方根误差），PBIAS（偏差百分比）和NSE（纳什-舒特克里夫效率），可以肯定的是，与本次极端降雨事件的其他两颗卫星产品相比，TMPA-3B42的估计值更加相关和准确。基于TMPA-3B42的降水偏向18％，而GSMaP偏向14％。与其他产品相比，TMPA-3B42的NSE更低（-0.93）。因此，本研究得出结论，TMPA-3B42降水量对于该雨量稀疏或雨量分布不均的地区极端降雨事件的任何水文学研究都是有用的。

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