Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Weight assignment in regional climate models
SMHI, Research Department, Climate research - Rossby Centre.ORCID iD: 0000-0002-6495-1038
Show others and affiliations
2010 (English)In: Climate Research (CR), ISSN 0936-577X, E-ISSN 1616-1572, Vol. 44, no 2-3, 179-194 p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
2010. Vol. 44, no 2-3, 179-194 p.
Keyword [en]
RCM, Ensemble forecast, Climate projections
National Category
Climate Research
Research subject
Climate
Identifiers
URN: urn:nbn:se:smhi:diva-591DOI: 10.3354/cr00916ISI: 000285426000006OAI: oai:DiVA.org:smhi-591DiVA: diva2:806257
Available from: 2015-04-20 Created: 2015-04-20 Last updated: 2016-01-27Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Kjellström, ErikRummukainen, Markku
By organisation
Climate research - Rossby CentreCore Services
In the same journal
Climate Research (CR)
Climate Research

Search outside of DiVA

GoogleGoogle Scholar

Altmetric score

Total: 49 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
v. 2.26.0
|