Atmosphere (May 2020)

Multi-Model Ensemble Sub-Seasonal Forecasting of Precipitation over the Maritime Continent in Boreal Summer

  • Yan Wang,
  • Hong-Li Ren,
  • Fang Zhou,
  • Joshua-Xiouhua Fu,
  • Quan-Liang Chen,
  • Jie Wu,
  • Wei-Hua Jie,
  • Pei-Qun Zhang

DOI
https://doi.org/10.3390/atmos11050515
Journal volume & issue
Vol. 11, no. 5
p. 515

Abstract

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The Maritime Continent (MC) is a critical region with unique geographical conditions and significant monsoon activities that plays a vital role in global climate variation. In this study, the weekly prediction of precipitation over the MC during boreal summer (from May to September) was analyzed using the 12-year reforecasts data from five Sub-seasonal to Seasonal (S2S) models, including the China Meteorological Administration (CMA), the European Centre for Medium-Range Weather Forecasts (ECMWF), Environment and Climate Change Canada (ECCC), the National Centers for Environmental Prediction (NCEP), and the Met Office (UKMO). The result shows that, compared with the individual models, our newly derived median multi-model ensemble (MME) can significantly improve the prediction skill of sub-seasonal precipitation in the MC. Both the Temporal Correlation Coefficient (TCC) skill and the Pattern Correlation Coefficient (PCC) skill reached 0.6 in lead week 1, dropped the following week, did not exceed 0.2 in lead week 3, and then lost their significance. The results show higher prediction skill near the Equator than in the north at 10° N. It is difficult to make effective predictions with the models beyond three weeks. The prediction ability of the median MME improves significantly as the total number of model members increases. The prediction performance of the median MME depends not only on the diversity of models but also on the number of model members. Moreover, the prediction skill is particularly sensitive to the intensity and phase of Boreal Summer Intraseasonal Oscillation 1 (BSISO1) with the highest skills appearing at initial phases 1 and 5.

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