May 30, 2019
Journal Article

Evaluation of Clouds in Version 1 of E3SM Atmosphere Model with Satellite and Simulators

Abstract

This study systematically evaluates clouds simulated by the Energy Exascale Earth System Model (E3SM) Atmosphere Model version one (EAMv1) against satellite and ground-based cloud observations. Both low (1°) and high (0.25°) resolution EAMv1 configurations generally underestimate clouds in low and midlatitutes and overestimate clouds in the Arctic although the error is smaller in the high-resolution model. The underestimate of clouds is due to the underestimate of optically thin to intermediate clouds. EAMv1 overestimates the optically intermediate to thick clouds. Other model errors include the largely under-predicted stratocumulus along the coasts and high clouds over the tropical deep convection regions. The underestimate of thin clouds results in too much LW radiation being emitted to space and too little SW radiation being reflected back to space while the overestimate of optically intermediate and thick clouds leads to too little LW radiation being emitted to space and too much SW radiation being reflected back to space. EAMv1 shows better skill in reproducing the observed distribution of clouds and their properties and has smaller radiatively relevant errors in the distribution of clouds than most of the CFMIP2 models. It produces more supercooled liquid cloud fraction than CAM5 and most CMIP5 models owing to a new ice nucleation scheme and a reduction of ice deposition growth rate. It simulates the diurnal variation of clouds during the summer season at SGP qualitatively well, with both the evolution of shallow clouds and the nocturnal peak in high clouds well captured, however, it largely overestimates the observed magnitude.

Revised: October 23, 2019 | Published: May 30, 2019

Citation

Zhang Y., S. Xie, W. Lin, S.A. Klein, M. Zelinka, P. Ma, and P.J. Rasch, et al. 2019. Evaluation of Clouds in Version 1 of E3SM Atmosphere Model with Satellite and Simulators. Journal of Advances in Modeling Earth Systems 11, no. 5:1253-1268. PNNL-SA-139643. doi:10.1029/2018MS001562