PLASIM-ENTSem v1.0: a spatio-temporal emulator of future climate change for impacts assessment

Many applications in the evaluation of climate impacts and environmental policy require detailed spatio-temporal projections of future climate. To capture feedbacks from impacted natural or socio-economic systems requires interactive two-way coupling, but this is generally computationally infeasible...

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Bibliographic Details
Main Authors: P. B. Holden, N. R. Edwards, P. H. Garthwaite, K. Fraedrich, F. Lunkeit, E. Kirk, M. Labriet, A. Kanudia, F. Babonneau
Format: Article
Language:English
Published: Copernicus Publications 2014-02-01
Series:Geoscientific Model Development
Online Access:http://www.geosci-model-dev.net/7/433/2014/gmd-7-433-2014.pdf
Description
Summary:Many applications in the evaluation of climate impacts and environmental policy require detailed spatio-temporal projections of future climate. To capture feedbacks from impacted natural or socio-economic systems requires interactive two-way coupling, but this is generally computationally infeasible with even moderately complex general circulation models (GCMs). Dimension reduction using emulation is one solution to this problem, demonstrated here with the GCM PLASIM-ENTS (Planet Simulator coupled with the efficient numerical terrestrial scheme). Our approach generates temporally evolving spatial patterns of climate variables, considering multiple modes of variability in order to capture non-linear feedbacks. The emulator provides a 188-member ensemble of decadally and spatially resolved (~ 5° resolution) seasonal climate data in response to an arbitrary future CO<sub>2</sub> concentration and non-CO<sub>2</sub> radiative forcing scenario. We present the PLASIM-ENTS coupled model, the construction of its emulator from an ensemble of transient future simulations, an application of the emulator methodology to produce heating and cooling degree-day projections, the validation of the simulator (with respect to empirical data) and the validation of the emulator (with respect to high-complexity models). We also demonstrate the application to estimates of sea-level rise and associated uncertainty.
ISSN:1991-959X
1991-9603