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Reliability of decadal predictions
Author(s) -
Corti S.,
Weisheimer A.,
Palmer T. N.,
DoblasReyes F. J.,
Magnusson L.
Publication year - 2012
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 - 10.1029/2012gl053354
Subject(s) - predictability , climatology , anomaly (physics) , sea surface temperature , environmental science , forecast skill , reliability (semiconductor) , forcing (mathematics) , hindcast , probabilistic logic , climate model , climate change , geology , statistics , oceanography , mathematics , power (physics) , physics , quantum mechanics , condensed matter physics
The reliability of multi‐year predictions of climate is assessed using probabilistic Attributes Diagrams for near‐surface air temperature and sea surface temperature, based on 54 member ensembles of initialised decadal hindcasts using the ECMWF coupled model. It is shown that the reliability from the ensemble system is good over global land areas, Europe and Africa and for the North Atlantic, Indian Ocean and, to a lesser extent, North Pacific basins for lead times up to 6–9 years. North Atlantic SSTs are reliably predicted even when the climate trend is removed, consistent with the known predictability for this region. By contrast, reliability in the Indian Ocean, where external forcing accounts for most of the variability, deteriorates severely after detrending. More conventional measures of forecast quality, such as the anomaly correlation coefficient (ACC) of the ensemble mean, are also considered, showing that the ensemble has significant skill in predicting multi‐annual temperature averages.