SENSITIVITY TO THE REPRESENTATION OF PRECIPITATING ICE IN CRM SIMULATIONS OF DEEP CONVECTION

A Cloud resolving model (CRM) is a useful tool for providing a proxy f or observed data, against which parameterizations of convection in glo bal and regional models can be compared. The parameterization of micro physics in CRMs has been shown to be crucial for the simulation of the evolution of heat and moisture profiles during deep convection. The a im of the study described herein is to validate the microphysics schem e in the U.K. Met. Office's Large Eddy Model as a prelude to future wo rk where simulations of deep convection will be compared to a single c olumn version of the Met. Office's Unified model. Three observed cases of convection are simulated each with different precipitation product ion mechanisms, as deduced by the multiparameter radar at Chilbolton. Four simulations are carried out of each case, using different represe ntations of precipitation. The aim is to determine whether a flexible microphysics scheme is capable of modelling the evolution of the preci pitation in each of the cases without recourse to tuning coefficients for case-specific conditions. The simulations are validated against ra dar observations by comparing spatial distribution of radar reflectivi ty and the type of precipitation at the melting layer. A number of sys tematic errors occur in simulations using a 'single-moment' microphysi cs scheme (where graupel and snow mass concentrations are each represe nted with one variable and the number concentrations are prescribed). Whereas a 'double-moment' microphysics scheme (that predicts both the mass and number concentrations of snow and graupel) produced simulatio ns consistent with radar observations for all three cases. The sensiti vity of important quantities relating to the parameterization of conve ction in GCMs to the microphysical parameterization has been examined. The total precipitation at the ground and the amount of cloud ice are compared between simulations that differ only in their representation of precipitation. The total precipitation is found to vary by up to 4 0% and the total cloud ice by up to 200% between simulations of the sa me case. (C) 1998 Elsevier Science B.V. All rights reserved.