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

Journal Article · · Geoscientific Model Development (Online)
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Abstract. 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.

Research Organization:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA); National Key Research and Development Program of China; National Natural Science Foundation of China (NSFC); USDOE Office of Science (SC), Biological and Environmental Research (BER)
Grant/Contract Number:
SC0019373; AC52-07NA27344; 2017YFA0604000; 41975126; 41605074; AC02-05CH11231
OSTI ID:
1771346
Alternate ID(s):
OSTI ID: 1785914
Report Number(s):
LLNL-JRNL-820861
Journal Information:
Geoscientific Model Development (Online), Journal Name: Geoscientific Model Development (Online) Vol. 14 Journal Issue: 3; ISSN 1991-9603
Publisher:
Copernicus GmbHCopyright Statement
Country of Publication:
Germany
Language:
English

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