Examining reliability of seasonal to decadal sea surface temperature forecasts: The role of ensemble dispersion. Issue 21 (11th November 2013)

• Record Type: Journal Article
• Authors: Ho, Chun Kit; Hawkins, Ed; Shaffrey, Len; Bröcker, Jochen; Hermanson, Leon; Murphy, James M.; Smith, Doug M.; Eade, Rosie
• Is Part Of: Geophysical research letters. Volume 40:Issue 21(2013:Nov.)
• Page Start: 5770
• Page End: 5775
• Publication Date: 2013-11-11
• Subjects: Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1002/2013GL057630
• Languages: English
• ISSNs: 0094-8276

Abstract

<abstract abstract-type="main" id="grl51058-abs-0001"> <title> <x xml:space="preserve">Abstract</x> </title> <p id="grl51058-para-0002">[1] Useful probabilistic climate forecasts on decadal timescales should be reliable (i.e., forecast probabilities match the observed relative frequencies) but this is seldom examined. This paper assesses a necessary condition for reliability, which the ratio of ensemble spread to forecast error being close to one, for seasonal to decadal sea surface temperature retrospective forecasts from the Met Office Decadal Prediction System. Factors which may affect reliability are diagnosed by comparing this spread‐error ratio for an initial condition ensemble and two perturbed physics ensembles for initialized and uninitialized predictions. At lead times less than 2 years, the initialized ensembles tend to be underdispersed and produce overconfident and hence unreliable forecasts. For longer lead times, all three ensembles are predominantly overdispersed. Such overdispersion is primarily related to excessive interannual variability in the climate model. These findings highlight the need to carefully evaluate simulated variability in seasonal and decadal prediction systems.</p> </abstract>