Quantification of modelling uncertainties in a large ensemble of climate change simulations View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2004-08

AUTHORS

James M. Murphy, David M. H. Sexton, David N. Barnett, Gareth S. Jones, Mark J. Webb, Matthew Collins, David A. Stainforth

ABSTRACT

Comprehensive global climate models1 are the only tools that account for the complex set of processes which will determine future climate change at both a global and regional level. Planners are typically faced with a wide range of predicted changes from different models of unknown relative quality2,3, owing to large but unquantified uncertainties in the modelling process4. Here we report a systematic attempt to determine the range of climate changes consistent with these uncertainties, based on a 53-member ensemble of model versions constructed by varying model parameters. We estimate a probability density function for the sensitivity of climate to a doubling of atmospheric carbon dioxide levels, and obtain a 5–95 per cent probability range of 2.4–5.4 °C. Our probability density function is constrained by objective estimates of the relative reliability of different model versions, the choice of model parameters that are varied and their uncertainty ranges, specified on the basis of expert advice. Our ensemble produces a range of regional changes much wider than indicated by traditional methods based on scaling the response patterns of an individual simulation5,6. More... »

PAGES

768-772

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/nature02771

DOI

http://dx.doi.org/10.1038/nature02771

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1036499414

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/15306806


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