Performance Assessment of Chirps, Persiann – CDR, IMERG, and TMPA Precipitation Products across Nepal

Suraj Lamichhane, Nitesh Sharma, N. Devkota
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Abstract

The observation of hydrological as well as meteorological data is very essential for any kind of hydraulic and hydrological study. In Nepal, due to the significant variation of topography and climatic characteristics as well it is necessary to establish the meteorological stations densely, here only 231 meteorological stations are available and are handled by government organizations Department of Hydrology and Meteorology (DHM).  Even though, due to many limitations, the satellite data is very useful for the water resources study. There are so many satellite products available but the performance of these products varies from place to place. In this study, the performance of four satellite products i.e., Climate Hazards Group Infrared Precipitation with Station data (CHIRPS), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN-CDR), Integrated Multi-Satellite Retrievals for GPM (IMERG), and TRMM Multi-satellite Precipitation Analysis (TMPA) all over Nepal are evaluated with different elevation bands. The performance of each product is evaluated by Probability of Detection (POD), Critical Success Index (CSI), Frequency Bias Index (FBI), False Alarm Ratio (FAR), Root Mean Square Error (RMSE), and Percentage Bias (PBIAS). After analysis of each product, the PERSIANN-CDR data set gives a reasonable performance for all elevation bands after bias correction.
尼泊尔境内Chirps、Persiann - CDR、IMERG和TMPA降水产品的性能评估
水文和气象资料的观测对于任何一种水力和水文研究都是非常必要的。在尼泊尔,由于地形和气候特征的显著变化,有必要建立密集的气象站,这里只有231个气象站,由政府组织水文和气象部(DHM)管理。尽管卫星数据有许多局限性,但对水资源研究还是非常有用的。有这么多的卫星产品,但这些产品的性能因地而异。在不同高程波段,对尼泊尔地区气候危害组红外降水(CHIRPS)、基于人工神经网络的遥感降水估算(PERSIANN-CDR)、综合多卫星反演GPM (IMERG)和TRMM多卫星降水分析(TMPA) 4个卫星产品进行了评价。每个产品的性能由检测概率(POD)、关键成功指数(CSI)、频率偏差指数(FBI)、虚警率(FAR)、均方根误差(RMSE)和百分比偏差(PBIAS)来评估。经过对每个产品的分析,经过偏差校正后,PERSIANN-CDR数据集在所有高程波段都具有合理的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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