Improved leading modes of interannual variability of the Asian-Australian monsoon in an AGCM via incorporating a stochastic multicloud model

  • Libin MaEmail author
  • Zijun Jiang


In the present study, we investigated improvements in simulating the two major modes of the Asian-Australian monsoon (AAM) interannual variability by incorporating the stochastic multicloud model (SMCM) into the state-of-the-art ECHAM6.3 atmospheric model. Model results showed that the modified ECHAM6.3, i.e., with the SMCM, improves the simulation of seasonal evolution of anomalous rainfall and low-level circulation. Analysis revealed that the improvement in the simulation of precipitation anomalies of the first mode is associated with the improvement in both enhanced and suppressed convection. In addition, the enhanced easterly vertical shear over the Maritime Continent in the modified ECHAM6.3 contributes to the improvement in an equatorial asymmetry of precipitation anomalies of the first mode. Moreover, the moisture budget analysis demonstrated that the modified ECHAM6.3 improves the seasonal anomalous rainfall of the first mode by ameliorating the vertical mass integral of the moist flux divergence. In addition, the second mode of the AAM interannual variability produced by the modified ECHAM6.3 potentially exerts stronger influence on the ENSO variability compared to the default ECHAM6.3.


The Asian-Australian monsoon Stochastic multicloud model Leading modes Interannual variability Precipitation 



The authors appreciate Dr. Karsten Peters for his help on coupling the SMCM to ECHAM6.3. This study is sponsored by the Basic Research Fund of CAMS (2018Z007) and the Startup Foundation for Introducing Talent of NUIST (No. 2018r064). This is ESMC publication number 282.

Supplementary material

382_2019_5025_MOESM1_ESM.docx (1.8 mb)
Supplementary material 1 (DOCX 1890 kb)


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© Springer-Verlag GmbH Germany, part of Springer Nature 2019

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), School of Atmospheric SciencesNanjing University of Information Science and TechnologyNanjingChina
  2. 2.School of Mathematics and Computational ScienceHunan First Normal UniversityChangshaChina
  3. 3.State Key Laboratory of Severe WeatherChinese Academy of Meteorological SciencesBeijingChina

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