Constraints on climate change from a multi-thousand member ensemble of simulations
The first multi thousand member "perturbed physics" ensemble simulation of present and future climate, completed by the distributed computing project climateprediction.net, is used to search for constraints on the response to increasing greenhouse gas levels among present day observable cl...
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Format: | Journal article |
Language: | English |
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2005
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author | Piani, C Frame, D Stainforth, D Allen, M |
author_facet | Piani, C Frame, D Stainforth, D Allen, M |
author_sort | Piani, C |
collection | OXFORD |
description | The first multi thousand member "perturbed physics" ensemble simulation of present and future climate, completed by the distributed computing project climateprediction.net, is used to search for constraints on the response to increasing greenhouse gas levels among present day observable climate variables. The search is conducted with a systematic statistical methodology to identify correlations between observables and the quantities we wish to predict, namely the climate sensitivity and the climate feedback parameter. A sensitivity analysis is conducted to ensure that results are minimally dependent on the parameters of the methodology. Our best estimate of climate sensitivity is 3.3 K. When an internally consistent representation of the origins of model-data discrepancy is used to calculate the probability density function of climate sensitivity, the 5th and 95th percentiles are 2.2 K and 6.8 K respectively. These results are sensitive, particularly the upper bound, to the representation of the origins of model-data discrepancy. Copyright 2005 by the American Geophysical Union. |
first_indexed | 2024-03-07T02:34:10Z |
format | Journal article |
id | oxford-uuid:a83d6227-57e3-4e3d-b230-940cc6ab5e31 |
institution | University of Oxford |
language | English |
last_indexed | 2024-03-07T02:34:10Z |
publishDate | 2005 |
record_format | dspace |
spelling | oxford-uuid:a83d6227-57e3-4e3d-b230-940cc6ab5e312022-03-27T02:59:59ZConstraints on climate change from a multi-thousand member ensemble of simulationsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:a83d6227-57e3-4e3d-b230-940cc6ab5e31EnglishSymplectic Elements at Oxford2005Piani, CFrame, DStainforth, DAllen, MThe first multi thousand member "perturbed physics" ensemble simulation of present and future climate, completed by the distributed computing project climateprediction.net, is used to search for constraints on the response to increasing greenhouse gas levels among present day observable climate variables. The search is conducted with a systematic statistical methodology to identify correlations between observables and the quantities we wish to predict, namely the climate sensitivity and the climate feedback parameter. A sensitivity analysis is conducted to ensure that results are minimally dependent on the parameters of the methodology. Our best estimate of climate sensitivity is 3.3 K. When an internally consistent representation of the origins of model-data discrepancy is used to calculate the probability density function of climate sensitivity, the 5th and 95th percentiles are 2.2 K and 6.8 K respectively. These results are sensitive, particularly the upper bound, to the representation of the origins of model-data discrepancy. Copyright 2005 by the American Geophysical Union. |
spellingShingle | Piani, C Frame, D Stainforth, D Allen, M Constraints on climate change from a multi-thousand member ensemble of simulations |
title | Constraints on climate change from a multi-thousand member ensemble of simulations |
title_full | Constraints on climate change from a multi-thousand member ensemble of simulations |
title_fullStr | Constraints on climate change from a multi-thousand member ensemble of simulations |
title_full_unstemmed | Constraints on climate change from a multi-thousand member ensemble of simulations |
title_short | Constraints on climate change from a multi-thousand member ensemble of simulations |
title_sort | constraints on climate change from a multi thousand member ensemble of simulations |
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