A New Parameterization of the Accretion of Cloud Water by Graupel and Its Evaluation through Cloud and Precipitation Simulations

Abstract

Abstract A new parameterization of the accretion of cloud water by graupel for use in bulk microphysics schemes is derived by analytically integrating the stochastic collection equation (SCE). In this parameterization, the collection efficiency between graupel particles and cloud droplets is expressed in a functional form using the data obtained from a particle trajectory model by a previous study. The new accretion parameterization is evaluated through box model simulations in comparison with a bin-based direct SCE solver and two previously developed accretion parameterizations that employ the continuous collection equation and a simplified SCE, respectively. Changes in cloud water and graupel mass contents via the accretion process predicted by the new parameterization are closest to those predicted by the direct SCE solver. Furthermore, the new parameterization predicts a decrease in the cloud droplet number concentration that is smaller than the decreases predicted by the other accretion parameterizations, consistent with the direct SCE solver. The new and the other accretion parameterizations are implemented into a cloud-resolving model. Idealized deep convective cloud simulations show that among the accretion parameterizations, the new parameterization predicts the largest rate of accretion by graupel and the smallest rate of accretion by snow, which overall enhances rainfall through the largest rate of melting of graupel. Real-case simulations for a precipitation event over the southern Korean Peninsula show that among the examined accretion parameterizations, the new parameterization simulates precipitation closest to observations. Compared to the other accretion parameterizations, the new parameterization decreases the fractions of light and moderate precipitation amounts and increases the fraction of heavy precipitation amount.