Mapping TRMM TMPA into average recurrence interval for monitoring extreme precipitation events

dc.contributor.authorZhou, Yaping
dc.contributor.authorLau, William K. M.
dc.contributor.authorHuffman, George J.
dc.date.accessioned2022-07-06T21:21:54Z
dc.date.available2022-07-06T21:21:54Z
dc.date.issued2015-05-01
dc.description.abstractprototype online extreme precipitation monitoring system is developed from the TRMM TMPA near-real-time precipitation product. The system utilizes estimated equivalent average recurrence interval (ARI) for up-to-date precipitation accumulations from the past 1, 2, 3, 5, 7, and 10 days to locate locally severe events. The mapping of precipitation accumulations into ARI is based on local statistics fitted into generalized extreme value (GEV) distribution functions. Initial evaluation shows that the system captures historic extreme precipitation events quite well. The system provides additional rarity information for ongoing precipitation events based on local climatology that could be used by the general public and decision makers for various hazard management applications. Limitations of the TRMM ARI due to short record length and data accuracy are assessed through comparison with long-term high-resolution gauge-based rainfall datasets from the NOAA Climate Prediction Center and the Asian Precipitation–Highly-Resolved Observational Data Integration Toward Evaluation of Water Resources (APHRODITE) project. TMPA-based extreme climatology captures extreme distribution patterns from gauge data, but a strong tendency to overestimate from TMPA over regimes of complex orography exists.en
dc.description.sponsorshipThis work is supported by the Precipitation Measuring Mission under Project NNX13AF73G (Headquarters Manager: Dr. R. Kakar), NASA Earth Science Division. The TMPA data are obtained from NASA Goddard Earth Sciences Data and Information Services Center (GES DISC): ftp://disc2.nascom.nasa.gov/data/TRMM/Gridded/Derived_Products/3B42RT/Daily/. We thank Dr. Siegfried Shubert’s group for providing sample code for GEV calculation and three anonymous reviewers for providing many constructive suggestions.en
dc.description.urihttps://journals.ametsoc.org/view/journals/apme/54/5/jamc-d-14-0269.1.xmlen
dc.format.extent17 pagesen
dc.genrejournal articlesen
dc.identifierdoi:10.13016/m2rosj-yudw
dc.identifier.citationZhou, Yaping, William K. M. Lau, and George J. Huffman. "Mapping TRMM TMPA into Average Recurrence Interval for Monitoring Extreme Precipitation Events", Journal of Applied Meteorology and Climatology 54, 5 (2015): 979-995, accessed Jun 22, 2022, https://doi.org/10.1175/JAMC-D-14-0269.1en
dc.identifier.urihttps://doi.org/10.1175/JAMC-D-14-0269.1
dc.identifier.urihttp://hdl.handle.net/11603/25097
dc.language.isoenen
dc.publisherAMSen
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Joint Center for Earth Systems Technology
dc.rightsPublic Domain Mark 1.0*
dc.rightsThis work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.en
dc.rights.urihttp://creativecommons.org/publicdomain/mark/1.0/*
dc.titleMapping TRMM TMPA into average recurrence interval for monitoring extreme precipitation eventsen
dc.typeTexten
dcterms.creatorhttps://orcid.org/0000-0002-7812-851Xen

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