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Holden, P. B. and Edwards, N. R.
(2010).
DOI: https://doi.org/10.1029/2010GL045137
Abstract
Integrated Assessment Models are widely used tools for the evaluation of environmental policy. In order to include uncertainty estimates or derive optimal policies, highly efficient calculations of global change are generally required, often using pattern scaling to derive spatial distributions of change. Here we develop an alternative to pattern scaling that allows for nonlinear spatio-temporal behaviour. We use an intermediate complexity AOGCM to perform an ensemble of simulations for a range of greenhouse gas concentration profiles and model parameters. We decompose climate change fields into a series of spatial patterns and then derive the functional dependence of the dominant patterns on model input. This allows us to rapidly reconstruct a good approximation to the simulated change from an arbitrary concentration profile (without the need for further simulation). The efficiency of the approach paves the way for incorporating improved calculations of climate change into integrated assessment, including location-dependent estimates of uncertainty.
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About
- Item ORO ID
- 24659
- Item Type
- Journal Item
- ISSN
- 0094-8276
- Project Funding Details
-
Funded Project Name Project ID Funding Body Not Set Not Set UK Natural Environmental Research Council through QUEST?DESIRE [grant number NE/E007600/1] Not Set Not Set French Ministère de l�Écologie, de l�Énergie, du Développement durable et de la Mer through the Programme Gestion et Impacts du Changement Climatique [grant number G.3?0006032] - Keywords
- emulation; dimension reduction; GENIE-2; integrated assessment
- Academic Unit or School
-
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Environment, Earth and Ecosystem Sciences
Faculty of Science, Technology, Engineering and Mathematics (STEM) - Copyright Holders
- © 2010 American Geophysical Union
- Depositing User
- Philip Holden