Impacts of observation-based cloud droplet size distributions on the simulation of warm stratiform precipitation using a double-moment microphysics scheme

Abstract

A double-moment cloud microphysics scheme requires an assumption for cloud droplet size distributions (DSDs). However, since observations of cloud DSDs are limited, default values for shape parameters and cloud condensation nuclei activation parameters are often used in numerical simulations. In this study, the effects of cloud DSDs on numerical simulations of warm stratiform precipitation around Tokyo are investigated using the Japan Meteorological Agency's non-hydrostatic model, which incorporates a double-moment cloud microphysics scheme. Simulations using the default cloud DSD showed higher cloud droplet number concentrations and lower radar reflectivity than observed data, suggesting that the default cloud DSD is too narrow. Simulations with a cloud DSD based on in situ cloud observations corrected these errors. In addition, observation-based cloud DSDs affected rainfall amounts through the autoconversion rate of cloud water and improved the threat scores. These results suggest that realistic cloud DSDs should be provided for double-moment cloud microphysics schemes in scientific studies.