Sean Patrick Santos works on the Bayesian Observationally Constrained Statistical-Physical Scheme (BOSS), a new cloud microphysics scheme that will combine process-level theory with direct constraint by observations. His main research interests relate to the development and evaluation of climate models, and particularly the ways in which choice of parameterization and limited model resolution affect atmospheric modeling results.
Sean graduated with a PhD in Applied Mathematics from the University of Washington. His thesis work explored the time step sensitivity of cloud physics in the Energy Exascale Earth System Model. Before beginning his PhD program, he also spent four years at the National Center for Atmospheric Research, as a software engineer working on the Community Atmosphere Model.