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首页> 外文会议>Asian conference on remote sensingACRS >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：喜马拉雅地区卫星衍生降水估计误差评价：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：诸如雨量站和气象雷达之类的常规工具用于监测印度许多地区的极端降雨事件。但是，这些测量的应用在印度喜马拉雅地区的情况下受到限制，因为区域内的难以进入和缺乏雨量站的均匀网络。基于卫星的降水估计是评估HIMALAYAS的任何水流气象危害的替代方案。在这项研究中，我们评估了三种基于卫星的降雨产品（即TMPA-3B42，降水（GSMAP）的全球卫星测绘，NOAA CPC传感技术（CMORPH））对雨水仪的印度气象部门（IMD）网格数据集。评估降水中的误差特别适用于2013年6月在喜马拉雅山脉举行见证的极端降雨集。此活动被广泛称为Kerdarnath灾难，这引起了广泛的闪光洪水，山体滑坡和碎片流动。该综合研究的发现表明，在TMPA-3B42和Cmorph中低估了降水量和峰值降雨强度。然而，GSMAP显示了基于仪表的IMD数据的和过度估计的双重趋势。基于统计方法对误差统计量度的确定，即MAE（均值绝对误差），NRMSE（归一化均方根误差），PBIAS（偏置百分比）和NSE（NSH-SUTCLIFFE）的各个卫星产品，与此极端降雨事件的其他两颗卫星产品相比，TMPA-3B42估计更加相关和准确。基于TMPA-3B42的沉淀偏向18％，而GSMAP呈积极偏向14％。与其他产品相比，TMPA-3B42的NSE较低（-0.93）。因此，本研究得出结论，TMPA-3B42沉淀可用于该地区的极端降雨集的任何水文研究，其中雨水仪稀疏或雨量仪网络不均匀分布。

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