Improving the Subgrid-Scale Representation of Hydrometeors and Microphysical Feedback Effects Using a Multivariate Pdf

Improving the Subgrid-Scale Representation of Hydrometeors and Microphysical Feedback Effects Using a Multivariate PDF by Brian M. Griffin The University of Wisconsin – Milwaukee, 2016 Under the Supervision of Professor Vincent E. Larson The subgrid-scale representation of hydrometeor fields is important for calculating microphysical process rates. In order to represent subgrid-scale variability, the Cloud Layers Unified By Binormals (CLUBB) parameterization uses a multivariate Probability Density Function (PDF). In addition to vertical velocity, temperature, and moisture fields, the PDF includes hydrometeor fields. Previously, each hydrometeor field was assumed to follow a multivariate single lognormal distribution. Now, in order to better represent the distribution of hydrometeors, two new multivariate PDFs are formulated and introduced in part one of this two-part project. The new PDFs represent hydrometeors using either a delta-lognormal or a delta-double-lognormal shape. The two new PDF distributions, plus the previous single lognormal shape, are compared to histograms of data taken from Large-Eddy Simulations (LES) of a precipitating cumulus case, a drizzling stratocumulus case, and a deep convective case. Finally, the warm microphysical process rates produced by the different hydrometeor PDFs are compared to the same process rates produced by the LES. Microphysics processes have feedback effects on moisture and heat content. Not only do these processes influence mean values, but also variability and fluxes of moisture and heat content. For example, evaporation of rain below cloud base may produce cold pools. This evaporative cooling may increase the variability in temperature in the below-cloud layer.