Abstract
Microphysics methods for climate models typically track one, two, or
three moments of a droplet size distribution for various categories of
liquid, ice, and aerosol. Such methods rely on conversion parameters
between these categories, which introduces uncertainty into predictions.
While higher-resolution options such as bin and Lagrangian schemes
exist, they require too many degrees of freedom for climate modeling
applications and introduce numerical challenges. Here we introduce a
flexible spectral microphysics method based on collocation of basis
functions. This method generalizes to a linear bulk scheme at low
resolution and a smoothed bin scheme at high resolution. Tested in an
idealized box setting, the method improves spectral accuracy for droplet
collision-coalescence and improves precipitation predictions relative to
bulk methods; furthermore, it generalizes well to multimodal
distributions with less complexity than a bin method. The potential to
extend this collocation representation to multiple hydrometeor classes
suggests a path forward to unify liquid, ice, and aerosol microphysics
in a single, flexible, computational framework for climate modeling.