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Validating CHIRPS ability to estimate rainfall amount and detect rainfall occurrences in the Philippines

机译:验证啁啾能力来估计降雨量并检测菲律宾的降雨事件

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摘要

The lack of sufficient rainfall data has been a common problem that hampers water resources planning in many developing countries with sparse weather monitoring networks. Satellite rainfall data requires validation to be considered adequate for any purpose it may serve. This study aimed to validate the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) ability to estimate monthly rainfall amounts and detect rainfall occurrences for various water resources planning over the four types of climate in the Philippines. It was validated using data from 68 rainfall stations. The results showed that CHIRPS performed best during the dry seasons, and its performance was well correlated with climate type. It was found that the best estimate of rainfall amount is in Climate Type I. The CHIRPS showed adequate performance in reproducing rainfall amount in Climate Types II and III. Its lowest performance was seen in Climate Type IV with 50% of the stations having adequate CHIRPS estimates of monthly rainfall amount. The CHIRPS had the best results at detecting rainfall occurrences during dry seasons when random chances are accounted for, otherwise, it detected better rainfall occurrence during wet seasons. It consistently over detected rainfall occurrences across climate types and seasons. The validation showed that CHIRPS data on the monthly time scale could be applied in water resources planning especially for drought assessments. The results may serve as a useful reference to many water managers and policy- and decision-makers as the country could only currently rely on a sparse weather monitoring network for observed rainfall data which are of utmost importance in water resources planning.
机译:缺乏足够的降雨数据是一个常见的问题,即在许多发展中国家的水资源规划,具有稀疏天气监测网络。卫星降雨数据要求验证被认为是适当的,因为它可能为任何目的服务。本研究旨在验证气候危害集团红外降水与站(Chirps)估计每月降雨量的能力,并检测菲律宾四种各种气候的各种水资源规划的降雨量。使用来自68个降雨站的数据验证。结果表明,在干燥季节期间表现最佳,其性能与气候型好。结果发现,降雨量的最佳估计是气候类型I.啁啾表现出充分的性能在气候类型II和III中再现降雨量。其在气候IV型最低表现中,具有50%的站点,具有每月降雨量的充分啁啾估计。当随机机理算时,啁啾在检测干燥季节期间的降雨出现,否则在潮湿的季节期间检测到更好的降雨发生。它一直在横跨气候类型和季节的降雨出现。验证表明,每月时间规模的Chirps数据可以应用于水资源规划,特别是对干旱评估。结果可以作为许多水管理人员和政策和决策者的有用参考,因为该国目前只能依靠稀疏的天气监测网络,以便在水资源规划中最重要的降雨数据。

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  • 来源
    《Theoretical and applied climatology》 |2021年第4期|967-977|共11页
  • 作者单位

    Isabela State Univ Dept Agr & Biosyst Engn Coll Engn Echague 3309 Isabela Philippines;

    Natl Irrigat Adm Magat River Integrated Irrigat Syst Dam & Reservo Ramon 3309 Isabela Philippines;

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