Statistical adjustment of decadal predictions in a changing climate

A method for post‐processing decadal predictions from global climate models that accounts for model deficiencies in representing climate trends is proposed and applied to decadal predictions of annual global mean temperature from the Canadian Centre for Climate Modelling and Analysis climate model....

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Bibliographic Details
Published in:Geophysical research letters 2012-10, Vol.39 (19), p.n/a
Main Authors: Kharin, V. V., Boer, G. J., Merryfield, W. J., Scinocca, J. F., Lee, W.-S.
Format: Article
Language:English
Subjects:
Atmospheric sciences
bias correction
Climate
Climate science
Computer simulation
Data processing
decadal predictions
Earth sciences
Earth, ocean, space
Exact sciences and technology
Geobiology
Geophysics
Global climate models
Mathematical models
Mathematics
skill
statistical post-processing
trend correction
Trends
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Summary:A method for post‐processing decadal predictions from global climate models that accounts for model deficiencies in representing climate trends is proposed and applied to decadal predictions of annual global mean temperature from the Canadian Centre for Climate Modelling and Analysis climate model. The method, which provides a time‐dependent trend adjustment, reduces residual drifts that remain after applying the standard time‐independent bias correction when the modelled and observed long‐term trends differ. Initialized predictions and uninitialized simulations that share common specified external forcing are analyzed. Trend adjustment substantially reduces forecast errors in both cases and initialization further enhances skill, particularly for the first forecast year. Key Points A trend‐adjusting correction of decadal predictions is proposed The method reduces residual drifts remaining after standard bias correction Initialization enhances skill in decadal predictions in the first 1‐2 years
ISSN:0094-8276
1944-8007
DOI:10.1029/2012GL052647