My research aims to understand the role of clouds in the Earth’s climate system using high-resolution numerical modeling. I focus on cloud microphysics, turbulent mixing and entrainment, boundary-layer cloud life cycles, drizzle formation, and the dynamics of shallow and deep convection. I am particularly interested in interactions between clouds, radiation, and aerosols, and how these interactions control large-scale organization of convection.

My research has focused on the development and application of the global cloud-resolving model gSAM. This model enables kilometer- and sub-kilometer-scale simulations over regional to global domains, bridging the gap between weather and climate modeling. Using gSAM, I study the multiscale organization of convection, including mesoscale convective systems and the MJO, and investigate how cloud microphysics and surface fluxes influence these processes.

A new thrust of my work is high-resolution dynamic downscaling of extreme weather events, including hurricanes, winter storms, and severe convection, using grid spacings down to O(100 m). These simulations provide physically consistent estimates of extreme winds, precipitation, and cloud structure that are not accessible with conventional models. I use these simulations both for scientific understanding and as a testbed for improving physical parameterizations.

I am also developing mechanism-denial numerical experiments to isolate the processes that control convective organization and its response to environmental forcing, such as sea surface temperature structure and radiative feedbacks. In parallel, I am exploring the use of machine learning to emulate key physical processes, including surface fluxes and cloud microphysics, trained on high-resolution simulations and observational datasets.

Research Topics