This project investigates various aspects of the initiation of deep moist convection. Our primary goal is to improve understanding of the processes that govern convection initiation. A secondary goal is to determine the finescale structure of mesoscale boundaries and their role in promoting convection initiation. Possible emphases include either cloud-mesoscale modeling studies or field experiments. A three-dimensional cloud-mesoscale model is used with either real-data or parametric initialization approaches to identify important mesoscale processes and sensitivities influencing boundary evolution and convection initiation. Field experiments employ arrays of mobile remote and in-situ observing platforms to obtain data sets that are useful for testing various convection initiation hypotheses. Observational data may be obtained from a range of ground-based mobile and airborne platforms including microwave and millimeter-wavelength Doppler radars, DIAL lidars, mesonets, and various sounding and profiling systems. Data assimilation research investigates optimal strategies for blending the various remote in-situ observations to obtain complete and internally consistent four-dimensional analyses of wind, pressure, virtual temperature, and absolute humidity variations within the boundary layer.

 

key words

Convection initiation; Deep moist convection; Mesoscale boundary; Radar observations; Profiler observations; In-situ observations; Cloud model; Mesoscale model; Model initialization; Data assimilation;

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

Level:  Open to Postdoctoral and Senior applicants