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Volume 11, issue 2 | Copyright
Geosci. Model Dev., 11, 541-560, 2018
https://doi.org/10.5194/gmd-11-541-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.

Development and technical paper 06 Feb 2018

Development and technical paper | 06 Feb 2018

Climate pattern-scaling set for an ensemble of 22 GCMs – adding uncertainty to the IMOGEN version 2.0 impact system

Przemyslaw Zelazowski1,2, Chris Huntingford3, Lina M. Mercado3,4, and Nathalie Schaller1,5 Przemyslaw Zelazowski et al.
  • 1Oxford University Centre for the Environment, University of Oxford, Oxford, OX1 3QY, UK
  • 2Centre of New Technologies, University of Warsaw, Warsaw, 02-097, Poland
  • 3Centre for Ecology and Hydrology, Wallingford, OX10 8BB, UK
  • 4Geography, College of Life and Environmental Sciences, University of Exeter, Exeter, EX4 4RJ, UK
  • 5Center for International Climate Research (CICERO), Oslo, NO-0318, Norway

Abstract. Global circulation models (GCMs) are the best tool to understand climate change, as they attempt to represent all the important Earth system processes, including anthropogenic perturbation through fossil fuel burning. However, GCMs are computationally very expensive, which limits the number of simulations that can be made. Pattern scaling is an emulation technique that takes advantage of the fact that local and seasonal changes in surface climate are often approximately linear in the rate of warming over land and across the globe. This allows interpolation away from a limited number of available GCM simulations, to assess alternative future emissions scenarios. In this paper, we present a climate pattern-scaling set consisting of spatial climate change patterns along with parameters for an energy-balance model that calculates the amount of global warming. The set, available for download, is derived from 22GCMs of the WCRP CMIP3 database, setting the basis for similar eventual pattern development for the CMIP5 and forthcoming CMIP6 ensemble. Critically, it extends the use of the IMOGEN (Integrated Model Of Global Effects of climatic aNomalies) framework to enable scanning across full uncertainty in GCMs for impact studies. Across models, the presented climate patterns represent consistent global mean trends, with a maximum of 4 (out of 22) GCMs exhibiting the opposite sign to the global trend per variable (relative humidity). The described new climate regimes are generally warmer, wetter (but with less snowfall), cloudier and windier, and have decreased relative humidity. Overall, when averaging individual performance across all variables, and without considering co-variance, the patterns explain one-third of regional change in decadal averages (mean percentage variance explained, PVE, 34.25±5.21), but the signal in some models exhibits much more linearity (e.g. MIROC3.2(hires): 41.53) than in others (GISS_ER: 22.67). The two most often considered variables, near-surface temperature and precipitation, have a PVE of 85.44±4.37 and 14.98±4.61, respectively. We also provide an example assessment of a terrestrial impact (changes in mean runoff) and compare projections by the IMOGEN system, which has one land surface model, against direct GCM outputs, which all have alternative representations of land functioning. The latter is noted as an additional source of uncertainty. Finally, current and potential future applications of the IMOGEN version 2.0 modelling system in the areas of ecosystem modelling and climate change impact assessment are presented and discussed.

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This paper describes the calibration of the IMOGEN (Integrated Model Of Global Effects of climatic aNomalies) impact modelling system against 22 global climate models (GCMs) in the CMIP3 database.

IMOGEN uses "pattern scaling" to emulate GCMs, and with such linearity enables projections to be made for alternative future scenarios of atmospheric greenhouse gas concentrations. It is also coupled to the JULES land surface model, to allow impact assessments.
This paper describes the calibration of the IMOGEN (Integrated Model Of Global Effects of...
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