{"title":"Evaluation of Rainfall Variability Over Major River Basins of India Using Multi Temporal Satellite Data Products","authors":"Saurabh Choubey, Prashant Kumar, Shard Chander, Rina Kumari","doi":"10.1002/joc.8757","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>High resolution remotely sensed rainfall data is indispensable to accurately monitor rainfall variability at a river basin scale under climate change. The aim of the study is to assess the change in rainfall climatology and determine the performance of three GPM rainfall products (IMERG Final_Run, GSMaP_Gauge and recently developed GSMaP_ISRO) against in situ observation over major Indian River basins for the monsoon season rainfall during 2000–2020. The analysis provides valuable insights into the issues in the rainfall products and their performance under varying rainfall intensity (low, moderate and heavy) and orography. Results indicate that mean monsoon rainfall is better represented in GSMaP_ISRO than IMERG Final_Run and GSMaP_Gauge estimates. GSMaP_ISRO outperformed IMERG Final_Run and GSMaP_Gauge with smaller root-mean-square error and higher correlation coefficient. It was observed that the performance of GPM rainfall is influenced by rainfall intensity and terrain height of basins. In particular, for high rainfall occurrence, the Brahmaputra and Barak basins in northeast India exhibited large uncertainties in IMERG Final_Run and GSMaP_Gauge products. The statistical evaluation of different rainfall scores (POD, FAR and CSI) suggested that the GSMaP_ISRO rainfall has significant skill over Indian river basins. A significant improvement is observed over Brahmaputra (RMSD = 34.46, CC = 0.92, FAR = 0.26), Barak and others (RMSD = 65.75, CC = 0.95, FAR = 0.29) and Cauvery basin (RMSD = 23.1, CC = 0.8, FAR = 0.15) for GSMaP_ISRO estimates. These findings provide valuable information on the accuracy of GPM rainfall necessary for hydro-meteorological applications.</p>\n </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 5","pages":""},"PeriodicalIF":3.5000,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Climatology","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/joc.8757","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
High resolution remotely sensed rainfall data is indispensable to accurately monitor rainfall variability at a river basin scale under climate change. The aim of the study is to assess the change in rainfall climatology and determine the performance of three GPM rainfall products (IMERG Final_Run, GSMaP_Gauge and recently developed GSMaP_ISRO) against in situ observation over major Indian River basins for the monsoon season rainfall during 2000–2020. The analysis provides valuable insights into the issues in the rainfall products and their performance under varying rainfall intensity (low, moderate and heavy) and orography. Results indicate that mean monsoon rainfall is better represented in GSMaP_ISRO than IMERG Final_Run and GSMaP_Gauge estimates. GSMaP_ISRO outperformed IMERG Final_Run and GSMaP_Gauge with smaller root-mean-square error and higher correlation coefficient. It was observed that the performance of GPM rainfall is influenced by rainfall intensity and terrain height of basins. In particular, for high rainfall occurrence, the Brahmaputra and Barak basins in northeast India exhibited large uncertainties in IMERG Final_Run and GSMaP_Gauge products. The statistical evaluation of different rainfall scores (POD, FAR and CSI) suggested that the GSMaP_ISRO rainfall has significant skill over Indian river basins. A significant improvement is observed over Brahmaputra (RMSD = 34.46, CC = 0.92, FAR = 0.26), Barak and others (RMSD = 65.75, CC = 0.95, FAR = 0.29) and Cauvery basin (RMSD = 23.1, CC = 0.8, FAR = 0.15) for GSMaP_ISRO estimates. These findings provide valuable information on the accuracy of GPM rainfall necessary for hydro-meteorological applications.
在气候变化条件下，准确监测流域尺度降雨变率离不开高分辨率遥感降水数据。本研究的目的是评估降雨气候学的变化，并确定三个GPM降雨产品（IMERG Final_Run、GSMaP_Gauge和最近开发的GSMaP_ISRO）在2000-2020年期间对印度主要河流流域季风季节降雨的现场观测的表现。该分析对降雨产品及其在不同降雨强度（低、中、强）和地形下的表现提供了有价值的见解。结果表明，GSMaP_ISRO比IMERG Final_Run和GSMaP_Gauge估算值更能反映季风平均降雨量。GSMaP_ISRO的均方根误差更小，相关系数更高，优于IMERG Final_Run和GSMaP_Gauge。研究发现，GPM降雨的表现受降雨强度和流域地形高度的影响。特别是对于高降水发生，印度东北部的Brahmaputra和Barak流域在IMERG Final_Run和GSMaP_Gauge产品中表现出较大的不确定性。不同降雨评分（POD、FAR和CSI）的统计评价表明，GSMaP_ISRO的降雨在印度河流流域具有显著的技能。在雅鲁藏布江（RMSD = 34.46, CC = 0.92, FAR = 0.26）， Barak等（RMSD = 65.75, CC = 0.95, FAR = 0.29）和Cauvery盆地（RMSD = 23.1, CC = 0.8, FAR = 0.15）的GSMaP_ISRO估计上观察到显着改善。这些发现为水文气象应用所需的GPM降雨精度提供了有价值的信息。
期刊介绍：
The International Journal of Climatology aims to span the well established but rapidly growing field of climatology, through the publication of research papers, short communications, major reviews of progress and reviews of new books and reports in the area of climate science. The Journal’s main role is to stimulate and report research in climatology, from the expansive fields of the atmospheric, biophysical, engineering and social sciences. Coverage includes: Climate system science; Local to global scale climate observations and modelling; Seasonal to interannual climate prediction; Climatic variability and climate change; Synoptic, dynamic and urban climatology, hydroclimatology, human bioclimatology, ecoclimatology, dendroclimatology, palaeoclimatology, marine climatology and atmosphere-ocean interactions; Application of climatological knowledge to environmental assessment and management and economic production; Climate and society interactions
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