Articles | Volume 12, issue 3
https://doi.org/10.5194/esd-12-899-2021
© Author(s) 2021. 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-12-899-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The potential for structural errors in emergent constraints
Benjamin M. Sanderson
CORRESPONDING AUTHOR
Climate Modeling and Global Change, CERFACS, Toulouse, France
Climate and Global Dynamics, National Center for Atmospheric Research, Boulder, CO, USA
Angeline G. Pendergrass
Earth and Atmospheric Sciences, Cornell University, Ithaca, NY, USA
Climate and Global Dynamics, National Center for Atmospheric Research, Boulder, CO, USA
Charles D. Koven
Earth and Environmental Sciences, Lawrence Berkeley National Lab, Berkeley CA, USA
Florent Brient
Dynamical Meteorology Department, LMD/IPSL, Sorbonne Université, Paris, France
Ben B. B. Booth
Hadley Centre for Climate Prediction and Research, Met Office, Exeter, UK
Rosie A. Fisher
Climate Modeling and Global Change, CERFACS, Toulouse, France
Climate and Global Dynamics, National Center for Atmospheric Research, Boulder, CO, USA
Reto Knutti
Dep. of Environmental Systems Science, ETH Zurich, Zurich, Switzerland
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- Understanding the diversity of the West African monsoon system change projected by CORDEX-CORE regional climate models A. Tamoffo et al. 10.1007/s00382-023-06690-1
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- Call for caution regarding the efficacy of large-scale afforestation and its hydrological effects H. Douville et al. 10.1016/j.scitotenv.2024.175299
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- RETRACTED ARTICLE: A constraint on historic growth in global photosynthesis due to increasing CO2 T. Keenan et al. 10.1038/s41586-021-04096-9
Latest update: 05 Oct 2024
Short summary
Emergent constraints promise a pathway to the reduction in climate projection uncertainties by exploiting ensemble relationships between observable quantities and unknown climate response parameters. This study considers the robustness of these relationships in light of biases and common simplifications that may be present in the original ensemble of climate simulations. We propose a classification scheme for constraints and a number of practical case studies.
Emergent constraints promise a pathway to the reduction in climate projection uncertainties by...
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