Developing PIDF Curves From Dynamically Downscaled WRF Model Fields to Examine Extreme Precipitation Events in Three Eastern U.S. Metropolitan Areas.

ABSTRACT: Extreme precipitation events influence watershed, agriculture, and urban management. The probability of extreme precipitation is estimated for storm water management using precipitation intensity-duration-frequency (PIDF) curves. This study explores developing PIDF curves from dynamically downscaled 36- and 12-km simulations using the Weather Research and Forecasting (WRF) model. Three modeled data sets are examined: 36-km WRF model forced with 2.5° (~275-km) NCEP-DOE AMIP-II Reanalysis (R2); 36-km WRF model forced with 0.75° (~80-km) ERA-Interim; and 12-km WRF model forced with ERA-Interim. The WRF outputs are verified against historical observations for three cities in the Eastern United States using a 23-year period (1988-2010). The 36-km WRF data set driven by R2 produced PIDF curves that were acceptable at the 12- to 24-hr durations, but those WRF data could not realistically simulate extremes represented by the high-intensity, short-duration precipitation events. Increasing the resolution of WRF's driving data from R2 to ERA-Interim did not improve WRF's representation of precipitation events. Using 12-km grid spacing enhances WRF's ability to reproduce PIDF curves developed from observations. Finer grid spacing dramatically improves the frequency and intensity of the 1- to 3-hr events and improves the 6- to 24-hr events. However, improvements with the 12-km WRF data did not apply equally to all study sites, suggesting further modifications to the WRF configuration and/or methodology are necessary. Although imperfect, the results here lend confidence to using modeled data to construct PIDF curves, which could be valuable for projecting changes to parameters used in urban and environmental planning.

SUBMITTER: Jalowska AM 

PROVIDER: S-EPMC7863620 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature