Evaluation of climate models using palaeoclimatic data

Pascale Braconnot (), Sandy P. Harrison, Masa Kageyama, Patrick J. Bartlein, Valerie Masson-Delmotte, Ayako Abe-Ouchi, Bette Otto-Bliesner and Yan Zhao
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Pascale Braconnot: Insitut Pierre Simon Laplace/Laboratoire des Sciences du Climat et de l'Environnement, unité mixte de recherches CEA-CNRS-UVSQ
Sandy P. Harrison: School of Biological Sciences, Macquarie University
Masa Kageyama: Insitut Pierre Simon Laplace/Laboratoire des Sciences du Climat et de l'Environnement, unité mixte de recherches CEA-CNRS-UVSQ
Patrick J. Bartlein: University of Oregon
Valerie Masson-Delmotte: Insitut Pierre Simon Laplace/Laboratoire des Sciences du Climat et de l'Environnement, unité mixte de recherches CEA-CNRS-UVSQ
Ayako Abe-Ouchi: Center for Climate System Research, University of Tokyo
Bette Otto-Bliesner: National Center for Atmospheric Research
Yan Zhao: School of Biological Sciences, Macquarie University

Nature Climate Change, 2012, vol. 2, issue 6, 417-424

Abstract: Abstract There is large uncertainty about the magnitude of warming and how rainfall patterns will change in response to any given scenario of future changes in atmospheric composition and land use. The models used for future climate projections were developed and calibrated using climate observations from the past 40 years. The geologic record of environmental responses to climate changes provides a unique opportunity to test model performance outside this limited climate range. Evaluation of model simulations against palaeodata shows that models reproduce the direction and large-scale patterns of past changes in climate, but tend to underestimate the magnitude of regional changes. As part of the effort to reduce model-related uncertainty and produce more reliable estimates of twenty-first century climate, the Palaeoclimate Modelling Intercomparison Project is systematically applying palaeoevaluation techniques to simulations of the past run with the models used to make future projections. This evaluation will provide assessments of model performance, including whether a model is sufficiently sensitive to changes in atmospheric composition, as well as providing estimates of the strength of biosphere and other feedbacks that could amplify the model response to these changes and modify the characteristics of climate variability.

Date: 2012
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DOI: 10.1038/nclimate1456

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