Articles | Volume 9, issue 6
Geosci. Model Dev., 9, 2031–2053, 2016
https://doi.org/10.5194/gmd-9-2031-2016
Geosci. Model Dev., 9, 2031–2053, 2016
https://doi.org/10.5194/gmd-9-2031-2016

Model description paper 03 Jun 2016

Model description paper | 03 Jun 2016

A new subgrid-scale representation of hydrometeor fields using a multivariate PDF

Brian M. Griffin and Vincent E. Larson Brian M. Griffin and Vincent E. Larson
  • University of Wisconsin – Milwaukee, Department of Mathematical Sciences, Milwaukee, WI, USA

Abstract. 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, hydrometeor fields were 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.

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 (LESs) 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.

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Short summary
A multivariate probability density function (PDF) can be used to represent the subgrid (below grid-box size) variability of atmospheric fields. The PDF was previously extended to include hydrometeor fields, such as rain water mixing ratio. Now, the PDF of hydrometeor fields is altered to account for precipitating and precipitation-less regions of the subgrid domain. Accounting for these regions allowed the hydrometeor PDF to produce an improved match to results from large-eddy simulations.