Articles | Volume 13, issue 11
Geosci. Model Dev., 13, 5389–5399, 2020
Geosci. Model Dev., 13, 5389–5399, 2020
Model description paper
09 Nov 2020
Model description paper | 09 Nov 2020

A computationally efficient method for probabilistic local warming projections constrained by history matching and pattern scaling, demonstrated by WASP–LGRTC-1.0

Philip Goodwin et al.

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Cited articles

Balmaseda, M. A., Mogensen, K., and Weaver, A. T.: Evaluation of the ECMWF ocean reanalysis system ORAS4, Q. J. Roy. Meteor. Soc., 139, 1132–1161, 2013. 
Brown, S., Nicholls, R., Goodwin, P., Haigh, I., Lincke, D., Vafeidis, A., and Hinkel, J.: Quantifying Land and People Exposed to Sea-Level Rise with No Mitigation and 1.5 and 2.0 C Rise in Global Temperatures to Year 2300, Earths Future, 6, 583–600,, 2018. 
Cheng, L., Trenberth, K. E., Fasullo, J., Boyer, T., Abraham, J., and Zhu, J.: Improved estimates of ocean heat content from 1960 to 2015, Sci. Adv., 3, e1601545,, 2017. 
Fordham, D. A., Wigley, T. M. L., Watts, M. J., and Brook, B. W.: Strengthening forecasts of climate change impacts with multi-model ensemble averaged projections using MAGICC/SCENGEN 5.3, Ecography 35, 4–8,, 2012. 
Frölicher, T. L., Winton, M., and Sarmiento, J. L.: Continued global warming after CO2 emissions stoppage. Nat. Clim. Change, 4, 40–44, 2014 
Short summary
Numerical climate models are used to make projections of future surface warming for different pathways of future greenhouse gas emissions, where future surface warming will vary from place to place. However, it is so expensive to run complex models using supercomputers that future projections can only be produced for a small number of possible future emissions pathways. This study presents an efficient climate model to make projections of local surface warming using a desktop computer.