This research focuses on the understanding of severe convective weather utilizing both state-of-the-art observing systems and numerical model simulations of thunderstorms in order to improve the prediction of hazardous weather. Topics include the full spectrum of severe convective weather, including supercells, tornadoes, long-lived damaging convective windstorms (derechos), large hail, and heavy precipitation. The research can be performed through diagnostic studies using routine operational data and/or data obtained from experimental observing platforms (e.g. NSSL CLAMPS) or those from well-focused field projects. One approach is to assimilate radar data (from WSR-88Ds, fixed and mobile research platforms), along with surface, rawinsonde, and profiler observations into numerical model simulations of thunderstorms and convective systems using an ensemble Kalman filter. Another approach is to composite gridded mesoscale analyses or other observations to refine our knowledge of precursor conditions of severe weather phenomena in the pre-convective and near-storm environments.  Emphasis is placed on understanding the dynamics and interaction of severe convective weather events with the environment, including storm-environment feedbacks.

 

key words

Severe weather; VORTEX2; Supercells; Tornadoes; Derecho; Model verification; Severe storm environments; Thunderstorms; Forecasting; MPEX; PECAN; Field programs; Doppler Lidar; AERI; Data Assimilation; mini-MPEX

Citizenship:  Open to U.S. citizens, permanent residents and non-U.S. citizens

Level:  Open to Postdoctoral and Senior applicants