التفاصيل البيبلوغرافية
| العنوان: |
The Historic Rainfalls of Hurricanes Harvey and Florence: A Perspective from the Multi-Radar Multi-Sensor System. |
| المؤلفون: |
MARTINAITIS, STEVEN M., COCKS, STEPHEN B., OSBORNE, ANDREW P., SIMPSON, MICHEAL J., LIN TANG, JIAN ZHANG, HOWARD, KENNETH W. |
| المصدر: |
Journal of Hydrometeorology; Mar2021, Vol. 22 Issue 3, p721-738, 18p |
| مصطلحات موضوعية: |
HURRICANE Florence, 2018, HURRICANE Harvey, 2017, ANEMOMETER, RAIN gauges, UNITED States history, TROPICAL cyclones |
| مصطلحات جغرافية: |
NORTH Carolina, TEXAS |
| مستخلص: |
Hurricane Harvey in 2017 generated one of the most catastrophic rainfall events in United States history. Numerous gauge observations in Texas exceeded 1200mm, and the record accumulations resulted in 65 direct fatalities from rainfall-induced flooding. This was followed by Hurricane Florence in 2018, where multiple regions in North Carolina received over 750mm of rainfall. The Multi-Radar Multi-Sensor (MRMS) system provides the unique perspective of applying fully automated seamless radarmosaics and locally gauge-corrected products for these two historical tropical cyclone rainfall events. This study investigates the performance of various MRMS quantitative precipitation estimation (QPE) products as it pertains to rare extreme tropical cyclone rainfall events. Various biases were identified in the radar-only approaches, which were mitigated in a new dual-polarimetric synthetic radar QPE approach. A local gauge correction of radar-derived QPE provided statistical improvements over the radar-only products but introduced consistent underestimation biases attributed to undercatch from tropical cyclone winds. This study then introduces a conceptual methodology to bulk correct for gauge wind undercatch across the numerous gauge networks ingested by the MRMS system. Adjusting the hourly gauge observations for wind undercatch resulted in increased storm-total accumulations for both tropical cyclones that better matched independent gauge observations, yet its application across large network collections highlighted the challenges of applying a singular wind undercatch correction scheme for significant wind events (e.g., tropical cyclones) while recognizing the need for increased metadata on gauge characteristics. [ABSTRACT FROM AUTHOR] |
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