Articles | Volume 11, issue 2
https://doi.org/10.5194/gmd-11-541-2018
https://doi.org/10.5194/gmd-11-541-2018
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 Zelazowski, Chris Huntingford, Lina M. Mercado, and Nathalie Schaller

Related authors

Potential for equation discovery with AI in the climate sciences
Chris Huntingford, Andrew J. Nicoll, Cornelia Klein, and Jawairia A. Ahmad
Earth Syst. Dynam., 16, 475–495, https://doi.org/10.5194/esd-16-475-2025,https://doi.org/10.5194/esd-16-475-2025, 2025
Short summary
A rapid-application emissions-to-impacts tool for scenario assessment: Probabilistic Regional Impacts from Model patterns and Emissions (PRIME)
Camilla Mathison, Eleanor J. Burke, Gregory Munday, Chris D. Jones, Chris J. Smith, Norman J. Steinert, Andy J. Wiltshire, Chris Huntingford, Eszter Kovacs, Laila K. Gohar, Rebecca M. Varney, and Douglas McNeall
Geosci. Model Dev., 18, 1785–1808, https://doi.org/10.5194/gmd-18-1785-2025,https://doi.org/10.5194/gmd-18-1785-2025, 2025
Short summary
Future global water scarcity partially alleviated by vegetation responses to atmospheric CO2 and climate change
Jessica Stacey, Richard Betts, Andrew Hartley, Lina Mercado, and Nicola Gedney
EGUsphere, https://doi.org/10.5194/egusphere-2025-51,https://doi.org/10.5194/egusphere-2025-51, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
ESD Ideas: Climate tipping is not instantaneous – the duration of an overshoot matters
Paul David Longden Ritchie, Chris Huntingford, and Peter Cox
EGUsphere, https://doi.org/10.5194/egusphere-2024-3023,https://doi.org/10.5194/egusphere-2024-3023, 2024
Short summary
Testing the assumptions in emergent constraints: why does the “emergent constraint on equilibrium climate sensitivity from global temperature variability” work for CMIP5 and not CMIP6?
Mark S. Williamson, Peter M. Cox, Chris Huntingford, and Femke J. M. M. Nijsse
Earth Syst. Dynam., 15, 829–852, https://doi.org/10.5194/esd-15-829-2024,https://doi.org/10.5194/esd-15-829-2024, 2024
Short summary

Related subject area

Climate and Earth system modeling
Presentation, calibration and testing of the DCESS II Earth system model of intermediate complexity (version 1.0)
Esteban Fernández Villanueva and Gary Shaffer
Geosci. Model Dev., 18, 2161–2192, https://doi.org/10.5194/gmd-18-2161-2025,https://doi.org/10.5194/gmd-18-2161-2025, 2025
Short summary
Synthesizing global carbon–nitrogen coupling effects – the MAGICC coupled carbon–nitrogen cycle model v1.0
Gang Tang, Zebedee Nicholls, Alexander Norton, Sönke Zaehle, and Malte Meinshausen
Geosci. Model Dev., 18, 2193–2230, https://doi.org/10.5194/gmd-18-2193-2025,https://doi.org/10.5194/gmd-18-2193-2025, 2025
Short summary
Historical trends and controlling factors of isoprene emissions in CMIP6 Earth system models
Ngoc Thi Nhu Do, Kengo Sudo, Akihiko Ito, Louisa K. Emmons, Vaishali Naik, Kostas Tsigaridis, Øyvind Seland, Gerd A. Folberth, and Douglas I. Kelley
Geosci. Model Dev., 18, 2079–2109, https://doi.org/10.5194/gmd-18-2079-2025,https://doi.org/10.5194/gmd-18-2079-2025, 2025
Short summary
Investigating carbon and nitrogen conservation in reported CMIP6 Earth system model data
Gang Tang, Zebedee Nicholls, Chris Jones, Thomas Gasser, Alexander Norton, Tilo Ziehn, Alejandro Romero-Prieto, and Malte Meinshausen
Geosci. Model Dev., 18, 2111–2136, https://doi.org/10.5194/gmd-18-2111-2025,https://doi.org/10.5194/gmd-18-2111-2025, 2025
Short summary
From weather data to river runoff: using spatiotemporal convolutional networks for discharge forecasting
Florian Börgel, Sven Karsten, Karoline Rummel, and Ulf Gräwe
Geosci. Model Dev., 18, 2005–2019, https://doi.org/10.5194/gmd-18-2005-2025,https://doi.org/10.5194/gmd-18-2005-2025, 2025
Short summary

Cited articles

Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H., Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and Harding, R. J.: The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes, Geosci. Model Dev., 4, 677–699, https://doi.org/10.5194/gmd-4-677-2011, 2011. 
Booth, B. B. B., Jones, C. D., Collins, M., Totterdell, I. J., Cox, P. M., Sitch, S., Huntingford, C., Betts, R. A., Harris, G. R., and Lloyd, J.: High sensitivity of future global warming to land carbon cycle processes, Environ. Res. Lett., 7, 024002, https://doi.org/10.1088/1748-9326/7/2/024002, 2012. 
Burke, E. J., Ekici, A., Huang, Y., Chadburn, S. E., Huntingford, C., Ciais, P., Friedlingstein, P., Peng, S. S., and Krinner, G.: Quantifying uncertainties of permafrost carbon-climate feedbacks, Environ. Res. Lett., 14, 3051–3066, https://doi.org/10.5194/bg-14-3051-2017, 2017. 
Chadwick, R. and Good, P.: Understanding nonlinear tropical precipitation responses to CO2 forcing, Geophys. Res. Lett., 40, 4911–4915, https://doi.org/10.1002/grl.50932, 2013. 
Download
Short summary
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.
Share