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Markku Rummukainen. Photo.

Markku Rummukainen

Professor

Markku Rummukainen. Photo.

Weight assignment in regional climate models

Author

  • Jens Hesselbjerg Christensen
  • Erik Kjellström
  • Filippo Giorgi
  • Geert Lenderink
  • Markku Rummukainen

Summary, in English

An important new development within the European ENSEMBLES project has been to explore performance-based weighting of regional climate models (RCMs). Until now, although no weighting has been applied in multi-RCM analyses, one could claim that an assumption of ‘equal weight’ was implicitly adopted. At the same time, different RCMs generate different results, e.g. for various types of extremes, and these results need to be combined when using the full RCM ensemble. The process of constructing, assigning and combining metrics of model performance is not straightforward. Rather, there is a considerable degree of subjectivity both in the choice of metrics

and on how these may be combined into weights. We explore the applicability of combining a set of 6 specifically designed RCM performance metrics to produce one aggregated model weight with the purpose of combining climate change information from the range of RCMs used within ENSEMBLES. These metrics capture aspects of model performance in reproducing large-scale circulation patterns, meso-scale signals, daily temperature and precipitation distributions and extremes, trends and the annual cycle. We examine different aggregation procedures that generate different inter-model

spreads of weights. The use of model weights is sensitive to the aggregation procedure and shows different sensitivities to the selected metrics. Generally, however, we do not find compelling evidence of an improved description of mean climate states using performance-based weights in comparison to the use of equal weights. We suggest that model weighting adds another level of uncertainty to the generation of ensemble-based climate projections, which should be suitably explored, although our results indicate that this uncertainty remains relatively small for the weighting procedures examined.

Department/s

  • Dept of Physical Geography and Ecosystem Science
  • MERGE: ModElling the Regional and Global Earth system

Publishing year

2010

Language

English

Pages

179-194

Publication/Series

Climate Research

Volume

44

Issue

2-3

Document type

Journal article

Publisher

Inter-Research

Topic

  • Physical Geography

Keywords

  • RCM
  • regional climate model
  • Ensemble forecast
  • Climate projections
  • metrics
  • weighting

Status

Published

ISBN/ISSN/Other

  • ISSN: 1616-1572