Abstract

A comprehensive evaluation was recently completed that benchmarks the skill of the Weather Prediction Center’s (WPC) Quantitative Precipitation Forecasts (QPF) in capturing extreme precipitation events. Extreme precipitation is defined using three thresholds: the 99th and 99.9th percentile precipitation values of all wet-site days from 2012 to 2023 for each NOAA River Forecast Center (RFC) region, and the 2-year average recurrence interval from the NOAA Atlas-14. Stage IV quantitative precipitation estimates are used both to evaluate WPC’s QPF and to calculate the 99th and 99.9th percentile precipitation thresholds.

Results show a general improvement in WPC extreme QPF skill at Days 1-3 lead times across the contiguous US (CONUS). However, substantial regional and seasonal variability was observed. Forecast skill is highest along US coastal regions, especially in the cool and transition seasons (i.e., winter, fall, and spring), and has steadily improved over time. In contrast, skill is lowest across the central US and inland regions, especially during the warm season where WPC often underforecasts extreme precipitation. Trends in these inland regions show stagnation or even deterioration in forecast skill over time. Given the prevalence of warm-season precipitation contributing to flash-floods in the central US, this presentation will focus on the spatial and temporal variations of WPC’s warm-season extreme QPF in these regions.

This seminar is part of the NOAA Hydrometeorology Testbed (HMT) 2025 Flash Flood and Intense Rainfall Experiment (FFaIR) Seminar Series.

Bio: Diana Stovern (she/her) is a Research Physical Scientist in PSL's Hydrology Applications Division. She is currently part of the team tasked with modernizing estimates of Probable Maximum Precipitation. Her expertise is in model evaluation, statistical post-processing, and advancing the understanding of processes that drive extreme precipitation. Before joining PSL in 2021, Diana worked at the Weather Prediction Center, where she developed tools to enhance forecasting of high-impact precipitation events. She received her Ph. D. in Atmospheric Science at the University of Arizona, where her research identified key processes that cause size and structure changes in tropical cyclones.