On the selection of prognostic moments in parametrization schemes for drop sedimentation
Common parametrization models 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 parametrization models. In models 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. © 2009 The Authors Journal compilation © 2009 Blackwell Munksgaard.
Helmholtz Research Programs > PACES I (2009-2013) > TOPIC 1: The Changing Arctic and Antarctic > WP 1.3: A Bi-Polar Perspective of Sea Ice - Atmosphere - Ocean - Ecosystem Interactions