Improving the Prediction of the East Asian Summer Monsoon: New Approaches

Author:

Fan Ke1,Liu Ying2,Chen HuoPo3

Affiliation:

1. Nansen-Zhu International Research Centre, Institute of Atmospheric Physics, and Key Laboratory of Regional Climate-Environment for East Asia, Chinese Academy of Sciences, Beijing, China

2. Nansen-Zhu International Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, and Graduate University of the Chinese Academy of Sciences, Beijing, China

3. Nansen-Zhu International Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China

Abstract

Abstract East Asian summer monsoon (EASM) prediction is difficult because of the summer monsoon’s weak and unstable linkage with El Niño–Southern Oscillation (ENSO) interdecadal variability and its complicated association with high-latitude processes. Two statistical prediction schemes were developed to include the interannual increment approach to improve the seasonal prediction of the EASM’s strength. The schemes were applied to three models [i.e., the Centre National de Recherches Météorologiques (CNRM), the Met Office (UKMO), and the European Centre for Medium-Range Weather Forecasts (ECMWF)] and the Multimodel Ensemble (MME) from the Development of a European Multimodel Ensemble System for Seasonal-to-Interannual Prediction (DEMETER) results for 1961–2001. The inability of the three dynamical models to reproduce the weakened East Asian monsoon at the end of the 1970s leads to low prediction ability for the interannual variability of the EASM. Therefore, the interannual increment prediction approach was applied to overcome this issue. Scheme I contained the EASM in the form of year-to-year increments as a predictor that is derived from the direct outputs of the models. Scheme II contained two predictors: both the EASM and also the western North Pacific circulation in the form of year-to-year increments. Both the cross-validation test and the independent hindcast experiments showed that the two prediction schemes have a much better prediction ability for the EASM than does the original scheme. This study provides an efficient approach for predicting the EASM.

Publisher

American Meteorological Society

Subject

Atmospheric Science

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