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Changes in Extreme Precipitation Events Over Eastern U.S. Urban Areas Reflected in Observed and WRF-model Hourly Precipitation Data
Citation:
Jalowska, A. AND T. Spero. Changes in Extreme Precipitation Events Over Eastern U.S. Urban Areas Reflected in Observed and WRF-model Hourly Precipitation Data. 2018 AGU Fall Meeting, Washington, DC, December 10 - 14, 2018.
Impact/Purpose:
Presented at the 2018 AGU Fall Meeting
Description:
Extreme precipitation events influence watershed, agriculture and urban management decisions. Based on 30-year flood loss averages, flooding associated with extreme precipitation causes 82 casualties and about 8 billion dollars in damages across the United States each year. Intensity-Duration-Frequency (IDF) curves are a common tool used to project extreme precipitation events in urban and environmental planning. The IDF curves estimate a frequency of occurrence of extreme rain events based on analyses of the available historical observational data. Long-term observations of precipitation data are not available for many locations, motivating a need to develop models that can reasonably estimate hourly precipitation for historical and future periods. This study examines changes in extreme precipitation in three Eastern U.S. cities, during 1950-2010 in observational hourly precipitation data, and during 1988-2010 in hourly data from 12-km dynamically downscaled Weather Research and Forecasting (WRF) model simulation forced with ERA‐Interim data. The IDF curves and frequency analysis applied to 60 years of observed hourly precipitation data show overall increases in the intensity of extreme precipitation, and decrease in their frequency, with decadal and multidecadal fluctuations. The study shows a shift in seasonal precipitation patterns, with the magnitude of observed changes varying by longitude Analysis of WRF-model hourly precipitation demonstrates the model’s ability to reproduce the observed increase in extreme precipitation intensities, shift in seasonal precipitation patterns, and longitudinal pattern in the magnitude of change, but the magnitude of change is over- or under- estimated depending on the city location. The WRF model performance in reproducing hourly historical data provides confidence for future-climate modeling to project changes in extreme precipitation events under different climate and land use scenarios.gu 2018
