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Climate Dynamics

, Volume 53, Issue 3–4, pp 2061–2081 | Cite as

Improving the simulation of the climatology of the East Asian summer monsoon by coupling the Stochastic Multicloud Model to the ECHAM6.3 atmosphere model

  • Libin Ma
  • Zhiwei ZhuEmail author
  • Juan Li
  • Jian Cao
Article
  • 51 Downloads

Abstract

The East Asian summer monsoon (EASM) has significant impacts on local and global hydrological and climatic systems. However, most current atmospheric and coupled models have difficulty in capturing the climatological mean state of the EASM. The present study investigated the possible improvement of EASM simulation via coupling the Stochastic Multicloud Model (SMCM) to the state-of-the-art ECHAM6.3 atmosphere model. Evaluated by the pattern correlation coefficient and root-mean-square error, the modified ECHAM6.3, i.e., with SMCM coupling, showed better performance in simulating the EASM in terms of the precipitation pattern and intensity, the pattern of the western North Pacific subtropical high, the monsoon onset, and its seasonal evolution. Analyses also revealed that the modified ECHAM6.3 outperformed the default ECHAM6.3 in terms of large-scale circulation and vertically integrated moisture transport. Finally, it was that the intensified land–sea thermal contrast in both the meridional and zonal directions, as well as the stronger meridional temperature gradient in the upper troposphere and enhanced diabatic heating over the Tibetan Plateau, which are associated with the stochastic cloud, were the main reasons for the better performance of the modified ECHAM6.3 in simulating the EASM.

Keywords

East Asian summer monsoon Stochastic Multicloud Model Large-scale circulation Land–sea thermal contrast Meridional temperature gradient ECHAM6.3 atmospheric model 

Notes

Acknowledgements

This work was supported by the National Key R&D Program of China (Grant No. 2018YFC1505905), the National Natural Science Foundation of China (Grant No. 41605035 and Grant No. 41805048), and the Startup Foundation for Introducing Talent of NUIST (No. 2018r026; 2018r064). ZZ was supported by the Young Elite Scientists Sponsorship Program of CAST (Grant No. 2018QNRC001). This work also was supported by the Natural Science Foundation of Jiangsu Province (No. BK20161604). This is ESMC publication number 258.

Supplementary material

382_2019_4787_MOESM1_ESM.docx (345 kb)
Supplementary material 1 (DOCX 345 kb)

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Authors and Affiliations

  1. 1.Key Laboratory of Meteorological Disaster of Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD)Nanjing University of Information Science and TechnologyNanjingChina

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