Decadal climate prediction (project GCEP)

Haines, K. ORCID: https://orcid.org/0000-0003-2768-2374, Hermanson, K. L., Liu, C. L., Putt, D., Sutton, R. T. ORCID: https://orcid.org/0000-0001-8345-8583, Iwi, A. and Smith, D. (2009) Decadal climate prediction (project GCEP). Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 367 (1890). pp. 925-937. ISSN 1364-503X doi: 10.1098/rsta.2008.0178

Abstract/Summary

Decadal prediction uses climate models forced by changing greenhouse gases, as in the International Panel for Climate Change, but unlike longer range predictions they also require initialization with observations of the current climate. In particular, the upper-ocean heat content and circulation have a critical influence. Decadal prediction is still in its infancy and there is an urgent need to understand the important processes that determine predictability on these timescales. We have taken the first Hadley Centre Decadal Prediction System (DePreSys) and implemented it on several NERC institute compute clusters in order to study a wider range of initial condition impacts on decadal forecasting, eventually including the state of the land and cryosphere. The eScience methods are used to manage submission and output from the many ensemble model runs required to assess predictive skill. Early results suggest initial condition skill may extend for several years, even over land areas, but this depends sensitively on the definition used to measure skill, and alternatives are presented. The Grid for Coupled Ensemble Prediction (GCEP) system will allow the UK academic community to contribute to international experiments being planned to explore decadal climate predictability.

Additional Information	climate forecasting; decadal forecasting; coupled models; climate predictability
Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/4335
Item Type	Article
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > NCAS Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Additional Information	climate forecasting; decadal forecasting; coupled models; climate predictability
Publisher	Royal Society Publishing
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