A Simple Cloud Parameterization Derived from Cloud Resolving Model Data: Diagnostic and Prognostic Applications
- 1 August 2002
- journal article
- Published by American Meteorological Society in Journal of the Atmospheric Sciences
- Vol. 59 (15) , 2362-2372
Abstract
A simple statistical parameterization of cloud water–related variables that has been originally developed for nonprecipitating boundary layer clouds is extended for all cloud types including deep precipitating convection. Based on three-dimensional cloud resolving model (CRM) simulations of observed tropical maritime and continental midlatitude convective periods, expressions for the partial cloudiness and the cloud water content are derived, which are a function of the normalized saturation deficit Q1. It turns out that these relations are equivalent to boundary layer cloud relations described earlier, therefore allowing for a general description of subgrid-scale clouds. The usefulness of the cloud relations is assessed by applying them diagnostically and prognostically in a mesoscale model for a midlatitude cyclone case and a subtropical case, and comparing the simulated cloud fields to satellite observations and to reference simulations with an explicit microphysical scheme. The comparison use... Abstract A simple statistical parameterization of cloud water–related variables that has been originally developed for nonprecipitating boundary layer clouds is extended for all cloud types including deep precipitating convection. Based on three-dimensional cloud resolving model (CRM) simulations of observed tropical maritime and continental midlatitude convective periods, expressions for the partial cloudiness and the cloud water content are derived, which are a function of the normalized saturation deficit Q1. It turns out that these relations are equivalent to boundary layer cloud relations described earlier, therefore allowing for a general description of subgrid-scale clouds. The usefulness of the cloud relations is assessed by applying them diagnostically and prognostically in a mesoscale model for a midlatitude cyclone case and a subtropical case, and comparing the simulated cloud fields to satellite observations and to reference simulations with an explicit microphysical scheme. The comparison use...Keywords
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