Publications

Li, X; Liu, YW; Wang, MH; Jiang, YQ; Dong, XY (2021). Assessment of the Coupled Model Intercomparison Project phase 6 (CMIP6) Model performance in simulating the spatial-temporal variation of aerosol optical depth over Eastern Central China. ATMOSPHERIC RESEARCH, 261, 105747.

Abstract
Atmospheric aerosols exert substantial influence on the environment and climate changes. As global climate models have become a primary tool to understand the roles of aerosols in the Earth system, it is essential to obtain a comprehensive knowledge of model capability in reproducing various aerosol properties. Here, we assess the performance of the latest Coupled Model Intercomparison Project phase 6 (CMIP6) models in simulating the annual mean AOD climatology and its seasonality in Eastern Central China (ECC) over 2000 to 2014 and explore the underlying reasons for their performance. Compared with CMIP5 models, CMIP6 models better capture the magnitude of annual mean AOD climatology over ECC with a notable enhancement of 52.98% resulting from a significant increase in the simulated magnitude of dominant sulfate AOD. However, CMIP6 models fail to capture the seasonally south-north shift of AOD maximum centers. Specifically, two centers of maximum AOD in spring over South China (SC) and in summer over North China (NC) are underestimated, which are due to the negative biases in the simulation of organic aerosol (OA) AOD and sulfate AOD separately. Specifically, two centers of maximum AOD in spring over South China (SC) and in summer over North China (NC) are underestimated, which are due to the negative biases in the simulation of organic aerosol (OA) AOD and sulfate AOD separately. Our analysis suggests that the overestimated precipitation and underestimated liquid water path (LWP) in CMIP6 models, lead to the deficiency in modelled sulfate AOD by affecting sulfate aerosol concentrations through wet deposition and aqueous-phase production. Our study calls for more attention to improving simulations of aerosol seasonality in global climate models.

DOI:
10.1016/j.atmosres.2021.105747

ISSN:
0169-8095