Improved Precipitation Forecasts Using Parameterized Precipitation Drag in a Hydrostatic Forecast Model

Abstract

An empirical Rayleigh drag parameterization of the nonhydrostatic mechanisms of precipitation drag and small-scale diabatically induced mixing is introduced into a hydrostatic regional forecast model to curb excessive grid-scale precipitation production. To get the needed damping, the coefficient in the Rayleigh drag is set proportional to the predicted liquid water, similar in form to the precipitation drag exhibited in nonhydrostatic calculations. The Rayleigh drag parameterization is found to be greatly superior to using the full nonhydrostatic precipitation drag term that produces a damping that is much too large in magnitude for use in a hydrostatic model. Even a rescaling of this nonhydrostatic term is found to be unsatisfactory since it lacks the sensitivity needed for hydrostatic calculations, resulting in an inability to control excessive precipitation. To incorporate nonhydrostatic vertical acceleration effects into a hydrostatic model, a modified version of the quasi-hydrostatic approximation is used. Two precipitation events are examined in detail, while statistics for several other forecasts are also presented. Without the Rayleigh drag, excessive grid-scale precipitation occurs. Two different cumulus parameterizations and three different turbulence schemes were unable to provide a satisfactory remedy for the excessive mesoscale precipitation. This study finds that the forecasted amount of precipitation depends strongly on the characteristics of the horizontal smoothing. Low-order diffusion is found to reduce the precipitation in major systems but it also hampers the development of strong gradients. This contrasts with a sixth-order tangent filter that is selective in controlling numerical noise while allowing sharper gradients and greater development and precipitation. In this study, forecasts using the new Rayleigh drag parameterization are compared with actual precipitation observations. The new drag parameterization significantly reduces the excessive precipitation production while not impairing light precipitation.