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Correction of atmospheric dynamical seasonal forecasts using the leading ocean‐forced spatial patterns
Author(s) -
Lin Hai,
Derome Jacques,
Brunet Gilbert
Publication year - 2005
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2005gl023060
Subject(s) - geopotential height , climatology , forecast skill , general circulation model , gcm transcription factors , geopotential , ensemble average , north atlantic oscillation , singular value decomposition , environmental science , meteorology , ensemble forecasting , econometrics , mathematics , geography , climate change , geology , precipitation , oceanography , algorithm
A statistical approach to correct ensemble seasonal forecasts is formulated based on the regression of the forecast model's leading forced singular value decomposition (SVD) patterns and the observed 500 hPa geopotential height. This technique is applied to the winter forecasts from two general circulation models (GCMs). The performance of the corrected forecasts is assessed by comparing their cross‐validated skill with that of the original GCM ensemble mean forecasts. We are particularly interested in the forecast skill of the Pacific/North American (PNA) and the North Atlantic Oscillation (NAO). In the case of the PNA, the technique significantly improves the skill of the less skillful of the two models, and does not modify significantly that of the other model, which produces very good PNA forecasts even before the correction. For the NAO, the correction significantly improves the forecast skill of both models.