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• W2328871316 abstract "CR Climate Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials CR 51:35-58 (2012) - DOI: https://doi.org/10.3354/cr01046 CMIP3 ensemble climate projections over the ­western tropical Pacific based on model skill Sarah E. Perkins1,2,3,*, Damien B. Irving1,2, Josephine R. Brown2,3, Scott B. Power2,3, Aurel F. Moise2,3, Robert A. Colman2,3, Ian Smith2,3 1Centre for Australian Weather and Climate Research, CSIRO Marine and Atmospheric Research, Aspendale, Victoria 3195, Australia 2Centre for Australian Weather and Climate Research, Bureau of Meteorology, GPO Box 1289, Melbourne, Victoria 3001, Australia 3Present address: ARC Centre of Excellence for Climate System Science, The University of New South Wales, Sydney, NSW 2052 Australia *Email: sarah.perkins@unsw.edu.au ABSTRACT: Climate projections provide important information for risk assessment and adaptation planning. The CMIP3 archive of global climate model (GCM) simulations has been used extensively for such projections over land-based regions, but limited attention has been paid to the western tropical Pacific, where vulnerability is likely to be high. Adaptation policies within the western Pacific currently are based on the heavily summarised information within the IPCC fourth assessment report. This study builds upon the IPCC projections by analysing and presenting projections of change from the CMIP3 GCMs and demonstrating spatial differences in projections across the west Pacific domain. Atmospheric fields considered in this paper include surface air temperature, precipitation, and wind speed and direction for the SRES A2 emission scenario for 2080−2099, where the projected change is relative to 1980−1999. Results for all fields are based on 3 types of multi-model ensembles: the all-model (ALL) ensemble (19 models), the BEST ensemble (15 models) and the WORST ensemble (4 models). The BEST and WORST ensembles are based on model skill in simulating relevant climatic features, drivers and variables, which govern the interannual and annual climate of the study region. The WORST ensemble was found to generally exhibit a statistically significant bias in projections for precipitation, wind speed and wind direction in reference to the ALL ensemble. This bias is always statistically significantly different for surface air temperature. Some biases are still present in the BEST ensemble for all variables in comparison to the ALL ensemble, and uncertainty is not always reduced when the WORST models are eliminated from the ensemble. Overall, we advocate the use of the BEST ensemble when considering domain-wide projections due to the ability of the model members to simulate the current climate across the region. KEY WORDS: CMIP3 climate models · Ensembles · Pacific region · Climate projections Full text in pdf format PreviousNextCite this article as: Perkins SE, Irving DB, Brown JR, Power SB, Moise AF, Colman RA, Smith I (2012) CMIP3 ensemble climate projections over the ­western tropical Pacific based on model skill. Clim Res 51:35-58. https://doi.org/10.3354/cr01046 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in CR Vol. 51, No. 1. Online publication date: January 24, 2012 Print ISSN: 0936-577X; Online ISSN: 1616-1572 Copyright © 2012 Inter-Research." @default.
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• W2328871316 date "2012-01-24" @default.
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• W2328871316 title "CMIP3 ensemble climate projections over the ­western tropical Pacific based on model skill" @default.
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