Cloud and precipitation processes are important for weather and climate. I am interested in understanding these processes, how these processes are manifested in remote sensing observations, and how to best represent these processes in numerical models.
One approach to studying microphysics is the use of simplified physical models called process models, in which certain microphysical processes are explored in isolation from other complicating factors. Microphysical processes that I have investigated include those governing the evolution of raindrop spectra in warm clouds (e.g., size sorting, evaporation, coalescence, breakup), particle phase transitions (e.g., melting of hailstones, freezing of raindrops), and particle growth (e.g., vapor deposition of ice crystals).
Another approach is to use more complex models that account for all physical processes as well as the evolving storms themselves. These models more realistically depict an entire storm system and the interactions among storm dynamics, microphysics, and thermodynamics.
Such models can be coupled to observation operators to simulate what a radar would “see” in various circumstances. This allows us to understand how the processes are observed with remote sensing platforms, but also provides a pathway to critically examine and evaluate model microphysics parameterizations.
My publications involving microphysical modeling and/or observations are listed on the Publications page.