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

Authors :
Yan Wang
Hong-Li Ren
Fang Zhou
Joshua-Xiouhua Fu
Quan-Liang Chen
Jie Wu
Wei-Hua Jie
Pei-Qun Zhang
Source :
Atmosphere, Vol 11, Iss 5, p 515 (2020)
Publication Year :
2020
Publisher :
MDPI AG, 2020.

Abstract

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.

Details

Language :
English
ISSN :
20734433
Volume :
11
Issue :
5
Database :
Directory of Open Access Journals
Journal :
Atmosphere
Publication Type :
Academic Journal
Accession number :
edsdoj.98a8b813b2c347ca9b0bd53bdbce842b
Document Type :
article
Full Text :
https://doi.org/10.3390/atmos11050515