Open AccessUnderstanding the CMIP3 Multimodel Ensemble
Author(s) -
J. D. Annan,
J. C. Hargreaves
Publication year - 2011
Publication title -
journal of climate
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.315
H-Index - 287
eISSN - 1520-0442
pISSN - 0894-8755
DOI - 10.1175/2011jcli3873.1
Subject(s) - ensemble average , coupled model intercomparison project , ensemble forecasting , context (archaeology) , ensemble learning , computer science , climatology , climate model , machine learning , climate change , ecology , geography , archaeology , biology , geology
The Coupled Model Intercomparison Project phase 3 (CMIP3) multimodel ensemble has been widely utilized for climate research and prediction, but the properties and behavior of the ensemble are not yet fully understood. Here, some investigations are undertaken into various aspects of the ensemble’s behavior, in particular focusing on the performance of the multimodel mean. This study presents an explanation of this phenomenon in the context of the statistically indistinguishable paradigm and also provides a quantitative analysis of the main factors that control how likely the mean is to outperform the models in the ensemble, both individually and collectively. The analyses lend further support to the usage of the paradigm of a statistically indistinguishable ensemble and indicate that the current ensemble size is too small to adequately sample the space from which the models are drawn.