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Towards a typology for constrained climate model forecasts

Lopez, A. and Suckling, E. B. and Otto, F. E. L. and Lorenz, A. and Rowlands, D. and Allen, M. R. (2015) Towards a typology for constrained climate model forecasts. Climatic Change, 132 (1). pp. 15-29. ISSN 0165-0009

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Identification Number: 10.1007/s10584-014-1292-z

Abstract

In recent years several methodologies have been developed to combine and interpret ensembles of climate models with the aim of quantifying uncertainties in climate projections. Constrained climate model forecasts have been generated by combining various choices of metrics used to weight individual ensemble members, with diverse approaches to sampling the ensemble. The forecasts obtained are often significantly different, even when based on the same model output. Therefore, a climate model forecast classification system can serve two roles: to provide a way for forecast producers to self-classify their forecasts; and to provide information on the methodological assumptions underlying the forecast generation and its uncertainty when forecasts are used for impacts studies. In this review we propose a possible classification system based on choices of metrics and sampling strategies. We illustrate the impact of some of the possible choices in the uncertainty quantification of large scale projections of temperature and precipitation changes, and briefly discuss possible connections between climate forecast uncertainty quantification and decision making approaches in the climate change context.

Item Type: Article
Official URL: http://link.springer.com/journal/10584
Additional Information: © 2014 Springer Science+Business Media Dordrecht
Divisions: Centre for Analysis of Time Series
Subjects: G Geography. Anthropology. Recreation > GF Human ecology. Anthropogeography
Q Science > QC Physics
Sets: Research centres and groups > Centre for the Analysis of Time Series (CATS)
Date Deposited: 11 Jun 2015 15:36
Last Modified: 25 Nov 2015 14:10
Projects: EQUIP project NE/H003479/1
Funders: Natural Environment Research Council, Economic and Social Research Council, Munich Re
URI: http://eprints.lse.ac.uk/id/eprint/62298

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