Effects of coupling a stochastic convective parameterization with the Zhang–McFarlane scheme on precipitation simulation in the DOE E3SMv1.0 atmosphere model

Abstract. A stochastic deep convection parameterization is implemented into the US Department of Energy (DOE) Exascale Earth System Model (E3SM) Atmosphere version 1.0 (EAMv1). This study evaluates its performance in simulating precipitation. Compared to default model, probability distribution function (PDF) rainfall intensity new simulation greatly improved. The well-known problem “too much light rain and too little heavy rain” alleviated, especially over tropics. As a result, contribution from different rates total precipitation amount shifted toward heavier rain. less frequent occurrence contributes suppressed rain, while more intense large-scale convective enhanced synoptic intraseasonal variabilities are as well be closer observations. sensitivity PDF model vertical resolution examined. relationship between dilute available potential energy agrees better with that Atmospheric Radiation Measurement (ARM) observations compared standard simulation. annual mean largely unchanged use scheme except tropical western Pacific, where moderate increase represents slight improvement. responses extremes climate warming similar or without scheme.