Monday, 7 January 2019
Hall 4 (Phoenix Convention Center - West and North Buildings)
Hurricane Harvey generated one of the most historic rainfall events in the history of the United States. Numerous gauge observations reported storm total accumulations exceeding 48 inches with some stations reporting more than 60 inches of rainfall. This resulted in catastrophic flooding and flash flooding that resulted in at least 65 direct fatalities from freshwater flooding. While these point observations provide some ground truth to the amount of rainfall produced during Hurricane Harvey, they cannot accurately depict the coverage of rainfall. Moreover, numerous rain gauge types can only handle 11-12 inches of rain before needing to be emptied, which could be difficult to do during a tropical cyclone. Radar-derived rainfall rates can provide a better spatial depiction of rainfall. This study looks at the quantitative precipitation estimations (QPEs) from the Multi-Radar Multi-Sensor (MRMS) system compared to independent CoCoRaHS gauge observations and to single radar QPEs. Featured in this analysis is an experimental MRMS dual-polarization synthetic QPE.
One of the MRMS products used in the analysis is the locally gauge-corrected radar (LGC) QPE, which utilizes quality controlled hourly automated gauge observations. The results found that the LGC QPE was statistically worse than the radar-only QPE products from MRMS. This is likely because of wind undercatch during the tropical cyclone event. A prototype wind correction algorithm was introduced to correct the hourly observations. The LGC QPE was recreated using the adjusted gauge values, and this resulted in the best statistical representation of rainfall over Texas and Louisiana. This study describes the creation of the prototype wind correction algorithm and the estimated QPEs generated with the adjusted gauge data.
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