Applied Math Seminar: Emily de Jong (Caltech)

Title: Modeling size distributions and collisions in cloud microphysics

Abstract:
Feedbacks between a warming atmosphere, emission of aerosols, and clouds and precipitation are one of the most difficult aspects for climate models to accurately capture. While these models operate at resolutions of tens or hundreds of kilometers, many of the physics that determine how and where clouds form or precipitate function at the micron droplet scale. This separation of scales means that most of these “microphysics” must be modeled with only a few approximate quantities and physical equations. These simplifications lead to large uncertainties about the future climate, such as the sensitivity of global warming to human-emitted aerosols.

This talk presents two promising techniques for mathematically representing droplet size distributions and the microphysics that govern how droplets within the distribution evolve. The first method attempts to span a gap in complexity between a simple method of moments and expensive “bin” or spectral representations by collocating smooth basis functions over the droplet size domain. With intelligently selected basis functions, this approach can represent the process of cloud droplets coalescing to form rain with bin-like accuracy, but with a degree of complexity that is attainable for global simulations. Next, we present a high-complexity high-fidelity Lagrangian approach known as the superdroplet method. This approach shows promise as a research tool to verify and train future microphysics models, but it is currently incomplete in its purview of droplet physics. We describe a probabilistic approach to representing collisional breakup, an often-overlooked process that can impact precipitation rates, cloud lifetime, and aerosol processing.