4.5 Article

Super-ensemble of three RCMs for climate projection over East Asia and Taiwan

Journal

THEORETICAL AND APPLIED CLIMATOLOGY
Volume 103, Issue 1-2, Pages 265-278

Publisher

SPRINGER WIEN
DOI: 10.1007/s00704-010-0275-x

Keywords

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Funding

  1. National Science Council of Republic of China [NSC95-2621-Z-002-004, NSC96-2621-Z-002-004, NSC97-2621-M-002-002, NSC98-2621-M-002-001]

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Runs of three regional climate models (RCMs) dynamically downscaling the outputs of atmosphere-ocean coupling general circulation models (AOGCMs) are studied. These RCMs are NCAR-MM5, NCEP-RSM (Regional Spectral Model), and Purdue-PRM (Purdue Regional Model). A useful approach is developed to compare the variability, error, and spatial distribution of model-simulated results with respect to the Climatic Research Unit (CRU) datasets over East Asia and seven sub-regions during the 1990s. The results show that NCEP-RSM outperforms the other two in meeting criteria selected on evaluating the model performance. Furthermore, three super-ensemble approaches are tested on merging RCMs' outputs. The inverse of the square error summation (ISES) method is selected as a suitable method with a generally good performance during the verification period. The projected future climate changes by ISES indicate larger temperature increases over high-latitude continent and smaller over low-latitude maritime areas. Rainfall will increase in summer over the central simulation domain, i.e. the eastern China, but decrease in winter, which are clearly linked to the variation in the synoptic airflows. Also, a more frequent occurrence of extreme rainfall events than what happened in the 1990s is projected. The projection over Taiwan suggests strong warming in summer, followed by autumn, winter, and spring. The interaction between the synoptic flow and the local terrain affects significantly the changes in precipitation. In general, larger change of the variability of rainfall will be over areas with lesser rainfall in the future, while lesser change will be over areas with more projected rainfall.

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