Sidi Yusuf Dawa, Mou Leong Tan, N. Samat, Ranjan Roy, Fei Zhang
{"title":"Evaluation of five gridded precipitation products for estimating precipitation and drought over Yobe, Nigeria","authors":"Sidi Yusuf Dawa, Mou Leong Tan, N. Samat, Ranjan Roy, Fei Zhang","doi":"10.2166/ws.2024.113","DOIUrl":null,"url":null,"abstract":"\n Ground observations are often considered as the most reliable and precise source of precipitation data. However, long-term precipitation data from ground observations are lacking in many parts of the world. Gridded precipitation products (GPPs) therefore have emerged as crucial alternatives to ground observations, but it is essential to assess their capability to accurately replicate precipitation patterns. This study aims to evaluate the performance of five GPPs, NASA POWER, TerraClimate, Climate Hazards Group Infrared Precipitation with Climate Data (CHIRPS), GPCC, and Climate Research Unit (CRU), in capturing precipitation and drought patterns from 1981 to 2021 in Yobe, Nigeria. The results indicate that GPCC had good performance at both monthly and annual scales, with high correlation coefficients and low error values. However, it tends to underestimate precipitation amounts in certain areas. Other products also exhibit satisfactory performance with moderate correlations with ground observations. Drought analysis indicates that GPCC outperforms other products in standardised precipitation index-6 calculations, while NASA POWER demonstrates inconsistencies with ground observations, particularly during the early 1980s and mid-2000s. In conclusion, GPCC is the most preferable GPP for precipitation and drought analysis in the Yobe State in Nigeria.","PeriodicalId":509977,"journal":{"name":"Water Supply","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Water Supply","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2166/ws.2024.113","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Ground observations are often considered as the most reliable and precise source of precipitation data. However, long-term precipitation data from ground observations are lacking in many parts of the world. Gridded precipitation products (GPPs) therefore have emerged as crucial alternatives to ground observations, but it is essential to assess their capability to accurately replicate precipitation patterns. This study aims to evaluate the performance of five GPPs, NASA POWER, TerraClimate, Climate Hazards Group Infrared Precipitation with Climate Data (CHIRPS), GPCC, and Climate Research Unit (CRU), in capturing precipitation and drought patterns from 1981 to 2021 in Yobe, Nigeria. The results indicate that GPCC had good performance at both monthly and annual scales, with high correlation coefficients and low error values. However, it tends to underestimate precipitation amounts in certain areas. Other products also exhibit satisfactory performance with moderate correlations with ground observations. Drought analysis indicates that GPCC outperforms other products in standardised precipitation index-6 calculations, while NASA POWER demonstrates inconsistencies with ground observations, particularly during the early 1980s and mid-2000s. In conclusion, GPCC is the most preferable GPP for precipitation and drought analysis in the Yobe State in Nigeria.
地面观测通常被认为是最可靠、最精确的降水数据来源。然而,世界上许多地方都缺乏来自地面观测的长期降水数据。因此,网格降水产品(GPPs)成为地面观测的重要替代品,但评估其准确复制降水模式的能力至关重要。本研究旨在评估 NASA POWER、TerraClimate、Climate Hazards Group Infrared Precipitation with Climate Data (CHIRPS)、GPCC 和 Climate Research Unit (CRU) 这五种 GPP 在捕捉尼日利亚约贝 1981 年至 2021 年降水和干旱模式方面的性能。结果表明,GPCC 在月度和年度尺度上均表现良好,相关系数高,误差值低。不过,它往往会低估某些地区的降水量。其他产品的性能也令人满意,与地面观测数据的相关性适中。干旱分析表明,GPCC 在标准化降水指数-6 计算方面优于其他产品,而 NASA POWER 与地面观测数据不一致,特别是在 20 世纪 80 年代早期和 2000 年代中期。总之,在尼日利亚约贝州进行降水和干旱分析时,GPCC 是最理想的 GPP。