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Weight assignment in regional climate models

Hesselbjerg Christensen, Jens; Kjellström, Erik; Giorgi, Filippo; Lenderink, Geert and Rummukainen, Markku LU (2010) In Climate Research 44(2-3). p.179-194
Abstract
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... (More)
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. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
RCM, regional climate model, Ensemble forecast, Climate projections, metrics, weighting
in
Climate Research
volume
44
issue
2-3
pages
179 - 194
publisher
Inter-Research
external identifiers
  • wos:000285426000006
  • scopus:78650412727
ISSN
1616-1572
DOI
10.3354/cr00916
project
MERGE
language
English
LU publication?
yes
id
0de9aad5-f10c-4007-a43d-75365a79a02e (old id 1749926)
alternative location
http://www.int-res.com/articles/cr_oa/c044p179.pdf
date added to LUP
2010-12-28 17:36:24
date last changed
2018-07-01 03:09:05
@article{0de9aad5-f10c-4007-a43d-75365a79a02e,
  abstract     = {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<br/><br>
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<br/><br>
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.},
  author       = {Hesselbjerg Christensen, Jens and Kjellström, Erik and Giorgi, Filippo and Lenderink, Geert and Rummukainen, Markku},
  issn         = {1616-1572},
  keyword      = {RCM,regional climate model,Ensemble forecast,Climate projections,metrics,weighting},
  language     = {eng},
  number       = {2-3},
  pages        = {179--194},
  publisher    = {Inter-Research},
  series       = {Climate Research},
  title        = {Weight assignment in regional climate models},
  url          = {http://dx.doi.org/10.3354/cr00916},
  volume       = {44},
  year         = {2010},
}