Articles | Volume 11, issue 1
https://doi.org/10.5194/esd-11-139-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-11-139-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Emulating Earth system model temperatures with MESMER: from global mean temperature trajectories to grid-point-level realizations on land
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Lukas Gudmundsson
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Sonia I. Seneviratne
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
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- Sequential learning of climate change via a physical-parameter-based state-space model and Bayesian inference Y. Lai & M. Pozzi 10.1007/s10584-024-03739-w
- The climate in climate economics D. Folini et al. 10.2139/ssrn.3885021
- Modeling the non-CO2 contribution to climate change C. Smith & T. Gasser 10.1016/j.oneear.2022.11.007
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- Responsibility of major emitters for country-level warming and extreme hot years L. Beusch et al. 10.1038/s43247-021-00320-6
- Large-scale emulation of spatio-temporal variation in temperature under climate change X. Yuan et al. 10.1088/1748-9326/abd213
- Toward Efficient Calibration of Higher‐Resolution Earth System Models C. Fletcher et al. 10.1029/2021MS002836
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- Machine learning for weather and climate are worlds apart D. Watson-Parris 10.1098/rsta.2020.0098
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- Partitioning climate projection uncertainty with multiple large ensembles and CMIP5/6 F. Lehner et al. 10.5194/esd-11-491-2020
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- Effect of Carbon Chain Length on Nascent Yields of Stabilized Criegee Intermediates in Ozonolysis of a Series of Terminal Alkenes L. Yang & J. Zhang 10.1021/jacs.4c08051
- The Value of Initial Condition Large Ensembles to Robust Adaptation Decision‐Making J. Mankin et al. 10.1029/2020EF001610
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- Crossbreeding CMIP6 Earth System Models With an Emulator for Regionally Optimized Land Temperature Projections L. Beusch et al. 10.1029/2019GL086812
- STITCHES: a Python package to amalgamate existing Earth system model output into new scenario realizations A. Snyder et al. 10.21105/joss.05525
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- Pangeo-Enabled ESM Pattern Scaling (PEEPS): A customizable dataset of emulated Earth System Model output B. Kravitz et al. 10.1371/journal.pclm.0000159
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- The inherent uncertainty of precipitation variability, trends, and extremes due to internal variability, with implications for Western US water resources K. McKinnon & C. Deser 10.1175/JCLI-D-21-0251.1
- From emission scenarios to spatially resolved projections with a chain of computationally efficient emulators: coupling of MAGICC (v7.5.1) and MESMER (v0.8.3) L. Beusch et al. 10.5194/gmd-15-2085-2022
- Interactions between atmospheric composition and climate change – progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP S. Fiedler et al. 10.5194/gmd-17-2387-2024
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2 citations as recorded by crossref.
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Short summary
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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