Diverse, Dynamic Droplets: A Novel Numerical Method for Cloud Droplet Distributions
Emily de Jong, California Institute of Technology
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 occur at the micron droplet scale. Due to the separation of scales between these droplets and the mesoscale dynamics of the atmosphere, most of these “microphysics” are abstracted to only a few approximate quantities and physical equations. These simplifications lead to large uncertainties in the future of climate, such as drought and flooding, stratocumulus breakup, and the impact of human-emitted aerosols.
In this work, we develop an element-based numerical method using collocation of basis functions to directly track the evolution of a droplet size distribution as droplets collide and coalesce. This method can function in a flexible range of computational complexity, generalizing to existing moment-based “bulk” methods at low resolution, and to spectral “bin” methods at high resolution. Tested in an idealized setting, the collocation method can improve predictions of the droplet-size-distribution and precipitation using fewer degrees of freedom than traditional microphysics methods. The method additionally generalizes to multiple dimensions of droplet features, such as aerosol chemistry or ice crystal structure, suggesting a path toward unifying the way that atmospheric particles are represented by climate models.
Abstract Author(s): Emily de Jong