Confronting Earth System Model trends with observations.
Isla R Simpson, Tiffany A Shaw, Paulo Ceppi, Amy C Clement, Erich Fischer, Kevin M Grise, Angeline G Pendergrass, James A Screen, Robert C J Wills, Tim Woollings, Russell Blackport, Joonsuk M Kang, Stephen Po-Chedley
Author Information
Isla R Simpson: National Science Foundation National Center for Atmospheric Research, Boulder, CO, USA. ORCID
Tiffany A Shaw: The University of Chicago, Chicago, IL, USA. ORCID
Paulo Ceppi: Department of Physics, Imperial College London, London, UK. ORCID
Amy C Clement: University of Miami, Miami, FL, USA. ORCID
Erich Fischer: ETH Zurich, Zurich, Switzerland. ORCID
Kevin M Grise: University of Virginia, Charlottesville, VA, USA. ORCID
Angeline G Pendergrass: National Science Foundation National Center for Atmospheric Research, Boulder, CO, USA. ORCID
James A Screen: University of Exeter, Exeter, UK. ORCID
Robert C J Wills: ETH Zurich, Zurich, Switzerland. ORCID
Tim Woollings: University of Oxford, Oxford, UK. ORCID
Russell Blackport: Canadian Center for Climate Modelling and Analysis, Environment and Climate Change Canada, Victoria, BC, Canada. ORCID
Joonsuk M Kang: The University of Chicago, Chicago, IL, USA.
Stephen Po-Chedley: Lawrence Livermore National Laboratory, Livermore, CA, USA. ORCID
Anthropogenically forced climate change signals are emerging from the noise of internal variability in observations, and the impacts on society are growing. For decades, Climate or Earth System Models have been predicting how these climate change signals will unfold. While challenges remain, given the growing forced trends and the lengthening observational record, the climate science community is now in a position to confront the signals, as represented by historical trends, in models with observations. This review covers the state of the science on the ability of models to represent historical trends in the climate system. It also outlines robust procedures that should be used when comparing modeled and observed trends and how to move beyond quantification into understanding. Finally, this review discusses cutting-edge methods for identifying sources of discrepancies and the importance of future confrontations.
References
Nat Commun. 2022 Mar 3;13(1):1148
[PMID: 35241666]
