Wednesday, 31 January 2024
Hall E (The Baltimore Convention Center)
Extreme precipitation is a common phenomenon throughout the Midwestern United States that can lead to flooding, agricultural losses, and damage to infrastructure. Continued anthropogenic climate change could cause extreme precipitation to increase, thus worsening impacts in the Midwest. With warming temperatures, an increase in specific humidity is generally expected to lead to increases in extreme precipitation. However, due to the use of convective parameterization in most global models, there remains uncertainty in precipitation-temperature scaling, or the percent change in precipitation per degree of warming. In this study, we examined historically-impactful extreme precipitation events from cases representing different storm modes including training storms, mesoscale convective systems, tropical cyclone remnants, and winter storms. All of the selected cases occurred within at least a portion of the Midwest, had a duration ranging from one to seven days, and occurred between the years 2005 to 2022. Using the Weather Research and Forecasting (WRF) model, we simulated each event at convection-permitting (3 km) resolution to capture localized processes that produced higher rainfall rates. We produced five-member ensembles in both the historical hindcasts and the future climate experiments, which used the pseudo-global-warming approach, to evaluate extreme precipitation changes. We quantified future changes in storm-total precipitation, daily and sub-daily precipitation rates, and precipitation scaling. The convection-permitting resolution used in this study can generate projections of future precipitation amounts and precipitation scaling with reduced uncertainty compared to projections from global climate models that use convective parameterization, thus providing information that can help prepare for the impacts of extreme weather in the future.

