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On the selection of prognostic moments in parametrization schemes for drop sedimentation Cover

On the selection of prognostic moments in parametrization schemes for drop sedimentation

Open Access
|Jan 2009

Abstract

Common parametrizationmodels for cloud microphysical processes use condensate mass density and/or particle number density as prognostic properties. However, other moments of the particle size distribution can likewise be chosen for prediction. This study deals with parametrization models with one and two, respectively, prognostic moments for the sedimentation of drop ensembles. The spectral resolving model defines the reference solution.

The evolution of the vertical profiles of liquid water content, drop number density and rain rate strongly depend on the choice of the prognostic moments in the parametrizationmodels. Inmodels with a single prognostic moment, its vertical profile is copied by all other moments. The moment of most physical pertinence is recommended for prediction. In models with two prognostic moments, the vertical profiles of all moments differ. The orders of the prognostic moments should be chosen close to the order of moments of highest relevance. Otherwise large errors occur. For example, comparison of modelled versus observed radar reflectivity (6th moment with respect to diameter) does not tell much about the quality of other properties if reflectivity is diagnosed from for example, number density and mass density. Furthermore, mass conservation is fulfilled only if mass density is forecasted.

Language: English
Page range: 498 - 511
Submitted on: Oct 24, 2008
Accepted on: Apr 24, 2009
Published on: Jan 1, 2009
Published by: Stockholm University Press
In partnership with: Paradigm Publishing Services

© 2009 Ulrike Wacker, Christof Lüpkes, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.