Mapping TRMM TMPA into Average Recurrence Interval for Monitoring Extreme Precipitation Events

Yaping Zhou Goddard Earth Sciences Technology and Research, Morgan State University, Baltimore, and Earth Sciences Division, NASA Goddard Space Flight Center, Greenbelt, Maryland

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William K. M. Lau Earth Sciences Division, NASA Goddard Space Flight Center, Greenbelt, Maryland

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George J. Huffman Earth Sciences Division, NASA Goddard Space Flight Center, Greenbelt, Maryland

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Abstract

A prototype 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.

Corresponding author address: Dr. Yaping Zhou, GESTAR/Morgan State University, Climate and Radiation Laboratory, NASA/GSFC, 8800 Greenbelt Rd., Greenbelt, MD 20771. E-mail: yaping.zhou-1@nasa.gov

Abstract

A prototype 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.

Corresponding author address: Dr. Yaping Zhou, GESTAR/Morgan State University, Climate and Radiation Laboratory, NASA/GSFC, 8800 Greenbelt Rd., Greenbelt, MD 20771. E-mail: yaping.zhou-1@nasa.gov
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