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Earth System Dynamics An interactive open-access journal of the European Geosciences Union
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ESD | Articles | Volume 11, issue 1
Earth Syst. Dynam., 11, 139–159, 2020
https://doi.org/10.5194/esd-11-139-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Earth Syst. Dynam., 11, 139–159, 2020
https://doi.org/10.5194/esd-11-139-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 17 Feb 2020

Research article | 17 Feb 2020

Emulating Earth system model temperatures with MESMER: from global mean temperature trajectories to grid-point-level realizations on land

Lea Beusch et al.

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Cited articles

Abramowitz, G., Herger, N., Gutmann, E., Hammerling, D., Knutti, R., Leduc, M., Lorenz, R., Pincus, R., and Schmidt, G. A.: ESD Reviews: Model dependence in multi-model climate ensembles: weighting, sub-selection and out-of-sample testing, Earth Syst. Dynam., 10, 91–105, https://doi.org/10.5194/esd-10-91-2019, 2019. a
Alexeeff, S. E., Nychka, D., Sain, S. R., and Tebaldi, C.: Emulating mean patterns and variability of temperature across and within scenarios in anthropogenic climate change experiments, Climatic Change, 146, 319–333, https://doi.org/10.1007/s10584-016-1809-8, 2018. a, b, c, d, e
Allen, M. R. and Stott, P. A.: Estimating signal amplitudes in optimal fingerprinting, part I: Theory, Clim. Dynam., 21, 477–491, https://doi.org/10.1007/s00382-003-0313-9, 2003. a
Bao, J., McInerney, D. J., and Stein, M. L.: A spatial-dependent model for climate emulation, Environmetrics, 27, 396–408, https://doi.org/10.1002/env.2412, 2016. a, b, c
Beusch, L., Gudmundsson, L., and Seneviratne, S. I.: Emulating Earth System Model Temperatures, in: Proceedings of the 8th International Workshop on Climate Informatics: CI 2018, 19–21 September 2018, Boulder, CO, USA, edited by: Chen, C., Cooley, D., Runge, J., and Szekely, E., NCAR Technical Note, Boulder, 41–44, https://doi.org/10.5065/D6BZ64XQ, 2018. a
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Earth system models (ESMs) are invaluable to study the climate system but expensive to run. Here, we present a statistical tool which emulates ESMs at a negligible computational cost by creating stochastic realizations of yearly land temperature field time series. Thereby, 40 ESMs are considered, and for each ESM, a single simulation is required to train the tool. The resulting ESM-specific realizations closely resemble ESM simulations not employed during training at point to regional scales.
Earth system models (ESMs) are invaluable to study the climate system but expensive to run....
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