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

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

Automated summary

The implementation of stochastic deep convection parameterization in the E3SM Atmosphere Model improves the simulation of precipitation by addressing the issue of too much light rain and too little heavy rain. This shift towards heavier rain in the total precipitation amount is achieved by less frequent convection and enhanced intense large-scale and convective precipitation, leading to better agreement with observations in terms of synoptic and intraseasonal variabilities.