Climate model emulation in an integrated assessment framework: a case study for mitigation policies in the electricity sector

We present a carbon-cycle&ndash;climate modelling framework using model emulation, designed for integrated assessment modelling, which introduces a new emulator of the carbon cycle (GENIEem). We demonstrate that GENIEem successfully reproduces the CO<sub>2</sub> concentrations of the...

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Bibliographic Details
Main Authors: A. M. Foley, P. B. Holden, N. R. Edwards, J.-F. Mercure, P. Salas, H. Pollitt, U. Chewpreecha
Format: Article
Language:English
Published: Copernicus Publications 2016-02-01
Series:Earth System Dynamics
Online Access:http://www.earth-syst-dynam.net/7/119/2016/esd-7-119-2016.pdf
Description
Summary:We present a carbon-cycle&ndash;climate modelling framework using model emulation, designed for integrated assessment modelling, which introduces a new emulator of the carbon cycle (GENIEem). We demonstrate that GENIEem successfully reproduces the CO<sub>2</sub> concentrations of the Representative Concentration Pathways when forced with the corresponding CO<sub>2</sub> emissions and non-CO<sub>2</sub> forcing. To demonstrate its application as part of the integrated assessment framework, we use GENIEem along with an emulator of the climate (PLASIM-ENTSem) to evaluate global CO<sub>2</sub> concentration levels and spatial temperature and precipitation response patterns resulting from CO<sub>2</sub> emission scenarios. These scenarios are modelled using a macroeconometric model (E3MG) coupled to a model of technology substitution dynamics (FTT), and represent different emissions reduction policies applied solely in the electricity sector, without mitigation in the rest of the economy. The effect of cascading uncertainty is apparent, but despite uncertainties, it is clear that in all scenarios, global mean temperatures in excess of 2 &deg;C above pre-industrial levels are projected by the end of the century. Our approach also highlights the regional temperature and precipitation patterns associated with the global mean temperature change occurring in these scenarios, enabling more robust impacts modelling and emphasizing the necessity of focusing on spatial patterns in addition to global mean temperature change.
ISSN:2190-4979
2190-4987