利用 PERSIANN-CDR 和 TRMM 对约旦三个关键小区的卫星降雨量估算进行评估

IF 2.2 3区 工程技术 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Hydroinformatics Pub Date : 2024-02-01 DOI:10.2166/hydro.2024.154
Mohanned Al-Sheriadeh, Anas Riyad Al-Sharman
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Satellite rainfall estimates (SREs) have become increasingly popular due to their ability to provide spatial rainfall data. However, the accuracy of SREs is limited by a variety of factors including a lack of observations, inadequate evaluation techniques, and the use of short evaluation durations. To improve our understanding of SREs, this study evaluated the long-term performance of Tropical Rainfall Measuring Mission (TRMM) and PERSIANN-CDR by analyzing their spatiotemporal patterns. Daily, monthly, seasonal, and annual precipitation estimates were evaluated using statistical measures and data from 71 rain gauges across three critical cells in Jordan from 2000 to 2013. The results showed that while both SREs had low accuracy on a daily scale, TRMM 3B43 performed better than PERSIANN-CDR at the monthly level. Additionally, TRMM 3B43 exhibited superior performance during the heavy rainy season, whereas PERSIANN-CDR showed better results during other seasons. In annual studies, TRMM 3B43 was found to be more accurate than PERSIANN-CDR for the north and south cells, while PERSIANN-CDR had a higher correlation coefficient for the middle cell. These findings can contribute to the development of more reliable and accurate SREs, thereby improving water resource management studies.</p>","PeriodicalId":54801,"journal":{"name":"Journal of Hydroinformatics","volume":null,"pages":null},"PeriodicalIF":2.2000,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evaluation of satellite rainfall estimates using PERSIANN-CDR and TRMM over three critical cells in Jordan\",\"authors\":\"Mohanned Al-Sheriadeh, Anas Riyad Al-Sharman\",\"doi\":\"10.2166/hydro.2024.154\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div data- reveal-group-><div><img alt=\\\"graphic\\\" data-src=\\\"https://iwa.silverchair-cdn.com/iwa/content_public/journal/jh/26/2/10.2166_hydro.2024.154/1/m_hydro-d-23-00154gf01.png?Expires=1712246905&amp;Signature=l7k9ixdsA6TvOf4cuuVzLNAo8suokFyYQaEjqpHVCPG66-4u~GJsd5D4TZDRd0rVz70ykR0UyLf34NDPsGd8qQ6jNW0bhGPpqGTz2SME1Apw23RLHbpdLJkNXCgufLrbQJOXg-pXfq4Uo0pYjsVYH8M8OtuFjgGLXju0BKnLSjUBo1qCz~nYYD6dhv~eiGcB1R5Y5x9yeRAj02lHfhNH7RDgJPultNx1QFQd3FWSH1vp0eSFYixbu6Mirm5yi94MwYkrf9gS3MnJq-1zIS8HKGlLm6CzoUVr4t2JFbXEd4dKbkus8NiwQkzbdaF-r8o63eCFH9BBtKSgEmXkwj4Sfw__&amp;Key-Pair-Id=APKAIE5G5CRDK6RD3PGA\\\" path-from-xml=\\\"hydro-d-23-00154gf01.tif\\\" src=\\\"https://iwa.silverchair-cdn.com/iwa/content_public/journal/jh/26/2/10.2166_hydro.2024.154/1/m_hydro-d-23-00154gf01.png?Expires=1712246905&amp;Signature=l7k9ixdsA6TvOf4cuuVzLNAo8suokFyYQaEjqpHVCPG66-4u~GJsd5D4TZDRd0rVz70ykR0UyLf34NDPsGd8qQ6jNW0bhGPpqGTz2SME1Apw23RLHbpdLJkNXCgufLrbQJOXg-pXfq4Uo0pYjsVYH8M8OtuFjgGLXju0BKnLSjUBo1qCz~nYYD6dhv~eiGcB1R5Y5x9yeRAj02lHfhNH7RDgJPultNx1QFQd3FWSH1vp0eSFYixbu6Mirm5yi94MwYkrf9gS3MnJq-1zIS8HKGlLm6CzoUVr4t2JFbXEd4dKbkus8NiwQkzbdaF-r8o63eCFH9BBtKSgEmXkwj4Sfw__&amp;Key-Pair-Id=APKAIE5G5CRDK6RD3PGA\\\"/><div>View largeDownload slide</div></div></div><div content- data-reveal=\\\"data-reveal\\\"><div><img alt=\\\"graphic\\\" data-src=\\\"https://iwa.silverchair-cdn.com/iwa/content_public/journal/jh/26/2/10.2166_hydro.2024.154/1/m_hydro-d-23-00154gf01.png?Expires=1712246905&amp;Signature=l7k9ixdsA6TvOf4cuuVzLNAo8suokFyYQaEjqpHVCPG66-4u~GJsd5D4TZDRd0rVz70ykR0UyLf34NDPsGd8qQ6jNW0bhGPpqGTz2SME1Apw23RLHbpdLJkNXCgufLrbQJOXg-pXfq4Uo0pYjsVYH8M8OtuFjgGLXju0BKnLSjUBo1qCz~nYYD6dhv~eiGcB1R5Y5x9yeRAj02lHfhNH7RDgJPultNx1QFQd3FWSH1vp0eSFYixbu6Mirm5yi94MwYkrf9gS3MnJq-1zIS8HKGlLm6CzoUVr4t2JFbXEd4dKbkus8NiwQkzbdaF-r8o63eCFH9BBtKSgEmXkwj4Sfw__&amp;Key-Pair-Id=APKAIE5G5CRDK6RD3PGA\\\" path-from-xml=\\\"hydro-d-23-00154gf01.tif\\\" src=\\\"https://iwa.silverchair-cdn.com/iwa/content_public/journal/jh/26/2/10.2166_hydro.2024.154/1/m_hydro-d-23-00154gf01.png?Expires=1712246905&amp;Signature=l7k9ixdsA6TvOf4cuuVzLNAo8suokFyYQaEjqpHVCPG66-4u~GJsd5D4TZDRd0rVz70ykR0UyLf34NDPsGd8qQ6jNW0bhGPpqGTz2SME1Apw23RLHbpdLJkNXCgufLrbQJOXg-pXfq4Uo0pYjsVYH8M8OtuFjgGLXju0BKnLSjUBo1qCz~nYYD6dhv~eiGcB1R5Y5x9yeRAj02lHfhNH7RDgJPultNx1QFQd3FWSH1vp0eSFYixbu6Mirm5yi94MwYkrf9gS3MnJq-1zIS8HKGlLm6CzoUVr4t2JFbXEd4dKbkus8NiwQkzbdaF-r8o63eCFH9BBtKSgEmXkwj4Sfw__&amp;Key-Pair-Id=APKAIE5G5CRDK6RD3PGA\\\"/><div>View largeDownload slide</div></div><i> </i><span>Close modal</span></div></div><p>Effective management of water resources is heavily dependent on accurate knowledge of rainfall patterns. 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引用次数: 0

摘要

查看大尺寸下载幻灯片查看大尺寸下载幻灯片 关闭模版水资源的有效管理在很大程度上取决于对降雨模式的准确了解。卫星降雨估测(SRE)由于能够提供空间降雨数据而越来越受欢迎。然而,卫星降雨量估算的准确性受到多种因素的限制,包括缺乏观测、评估技术不足以及使用的评估持续时间较短。为了增进我们对 SRE 的了解,本研究通过分析热带降雨测量使命(TRMM)和 PERSIANN-CDR 的时空模式,评估了它们的长期性能。使用统计量和约旦三个关键小区 71 个雨量计 2000 年至 2013 年的数据,对日、月、季和年降水量估计值进行了评估。结果表明,虽然两个 SRE 的日精度都较低,但 TRMM 3B43 的月精度优于 PERSIANN-CDR。此外,TRMM 3B43 在暴雨季节表现出更优越的性能,而 PERSIANN-CDR 在其他季节则表现出更好的结果。在年度研究中,发现 TRMM 3B43 在北部和南部小区的精度高于 PERSIANN-CDR,而 PERSIANN-CDR 在中部小区的相关系数更高。这些发现有助于开发更可靠、更准确的 SRE,从而改进水资源管理研究。
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Evaluation of satellite rainfall estimates using PERSIANN-CDR and TRMM over three critical cells in Jordan
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Effective management of water resources is heavily dependent on accurate knowledge of rainfall patterns. Satellite rainfall estimates (SREs) have become increasingly popular due to their ability to provide spatial rainfall data. However, the accuracy of SREs is limited by a variety of factors including a lack of observations, inadequate evaluation techniques, and the use of short evaluation durations. To improve our understanding of SREs, this study evaluated the long-term performance of Tropical Rainfall Measuring Mission (TRMM) and PERSIANN-CDR by analyzing their spatiotemporal patterns. Daily, monthly, seasonal, and annual precipitation estimates were evaluated using statistical measures and data from 71 rain gauges across three critical cells in Jordan from 2000 to 2013. The results showed that while both SREs had low accuracy on a daily scale, TRMM 3B43 performed better than PERSIANN-CDR at the monthly level. Additionally, TRMM 3B43 exhibited superior performance during the heavy rainy season, whereas PERSIANN-CDR showed better results during other seasons. In annual studies, TRMM 3B43 was found to be more accurate than PERSIANN-CDR for the north and south cells, while PERSIANN-CDR had a higher correlation coefficient for the middle cell. These findings can contribute to the development of more reliable and accurate SREs, thereby improving water resource management studies.

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来源期刊
Journal of Hydroinformatics
Journal of Hydroinformatics 工程技术-工程:土木
CiteScore
4.80
自引率
3.70%
发文量
59
审稿时长
3 months
期刊介绍: Journal of Hydroinformatics is a peer-reviewed journal devoted to the application of information technology in the widest sense to problems of the aquatic environment. It promotes Hydroinformatics as a cross-disciplinary field of study, combining technological, human-sociological and more general environmental interests, including an ethical perspective.
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