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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
earth and planetary sciences
Performance of recalibration systems for GCM forecasts for southern Africa
International Journal of Climatology, Volume 26, No. 12, Year 2006
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Description
Two regression-based methods that recalibrate the ECHAM4.5 general circulation model (GCM) output during austral summer have been developed for southern Africa, and their performance assessed over a 12-year retroactive period 1989/90-2000/01. A linear statistical model linking near-global sea-surface temperatures (SSTs) to regional rainfall has also been developed. The recalibration technique is model output statistics (MOS) using principal components regression (PCR) and canonical correlation analysis (CCA) to statistically link archived records of the GCM to regional rainfall over much of Africa, south of the equator. The predictability of anomalously dry and wet conditions over each rainfall region during December-February (DJF) using the linear statistical model and MOS models has been quantitatively evaluated. The MOS technique outperforms the raw-GCM ensembles and the linear statistical model. Neither the PCR-MOS nor the CCA-MOS models show clear superiority over the other, probably because the two methods are closely related. The need to recalibrate GCM predictions at regional scales to improve their skill at smaller spatial scales is further demonstrated in this paper. Copyright © 2006 Royal Meteorological Society.
Authors & Co-Authors
Shongwe, Mxolisi Excellent
Swaziland, Mbabane
Swaziland Meteorological Service
South Africa, Pretoria
University of Pretoria
Netherlands, De Bilt
Royal Netherlands Meteorological Institute
Landman, Willem Adolf
South Africa, Pretoria
University of Pretoria
South Africa, Pretoria
South African Weather Service
Mason, Simon J.
United States, Palisades
International Research Institute for Climate and Society
Statistics
Citations: 55
Authors: 3
Affiliations: 5
Identifiers
Doi:
10.1002/joc.1319
ISSN:
08998418
e-ISSN:
10970088
Study Approach
Quantitative