PREEVENTS Track 2: Collaborative Research: Multi-scale processes impacting the predictability of severe convective weather events

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Extreme weather events (EWEs) that threaten life and property can occur across a variety of time and space regimes. On the largest scales, persistent weather patterns produce clustered convective weather events, extended drought, and excessive precipitation. On regional scales, EWEs develop when intense precipitation systems give rise to tornadoes, hail, straight-line winds, and flash flooding. This research seeks to improve short- and long-range predictions of EWEs associated with convective storms and to better understand their predictability limits. The objectives of the project are to 1) develop understanding of the multi-scale physical processes that inhibit skillful local hazard prediction, and 2) improve the usefulness of numerical model forecasts of EWEs by better representing forecast uncertainty. The project has societal value due to its focus on providing better predictions to protect the public from severe weather hazards. The PIs conduct a series of meetings to help operational forecasters and emergency managers understand their research results. The meetings also allow forecasters and emergency managers to show the PIs how they incorporate forecast guidance and uncertainty information into their decision process, thereby promoting a constructive two-way dialogue. The project also provides education and training to two graduate students and a postdoctoral research associate. The research is conducted in three phases. Phase I identifies multi-day severe weather episodes, and the chain of processes leading to the development of favorable environmental conditions for convective outbreaks across the central and eastern United States. Tools including object-based verification, time-averaged physics tendency diagnostics, and ensemble sensitivity analysis are used to conduct a process-based investigation of high-impact weather events. Phase II uses the Model for Prediction Across Scales to produce a suite of convection-permitting ensemble predictions of convective EWEs. Diagnostics developed in Phase I are then used to understand how uncertainty in physical processes leads to uncertainty in the evolution of EWE precursors and their impact on downstream pre-convective environment. Phase III investigates the sensitivity of physical process representation to model resolution and cumulus parameterization. The research looks specifically at how simplifications in physical process representation limit predictive skill for downstream severe weather.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.