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Modelling mid-Holocene tropical climate and ENSO variability: towards constraining predictions of future change with palaeo-data
Authors:Josephine Brown  Matthew Collins  Alexander W. Tudhope  Thomas Toniazzo
Affiliation:(1) School of Geography and Environmental Science, Monash University, Clayton, VIC, 3800, Australia;(2) Department of Meteorology, University of Reading, Reading, UK;(3) Hadley Centre, Met Office, Exeter, UK;(4) School of Geosciences, University of Edinburgh, Edinburgh, UK
Abstract:Palaeoclimate simulations provide an opportunity for climate model evaluation as well as having a potential role in assigning relative likelihood to different ensemble members in probabilistic climate change prediction, supplementing constraints provided by the instrumental record. Here we take some initial steps towards such an approach by performing ensemble experiments with the Hadley Centre HadCM3 model under pre-industrial and mid-Holocene (6,000 years before present) forcing conditions. We examine the changes in both mean tropical climate and El Niño-Southern Oscillation (ENSO) variability, as palaeoclimate records suggest that ENSO amplitude was reduced in the mid-Holocene. Experiments are performed with perturbations to physical parameters in the atmosphere–surface component of the model, and with different implementations of heat and freshwater flux adjustments. Heat flux adjustments are required to stabilise model versions in which perturbations cause a net radiative imbalance. While we find broad agreement between different model versions in terms of changes in mean climate in the mid-Holocene, a detailed and quantitative comparison with the geographically-sparse palaeo-record is limited by systematic model biases. In the simulations without seasonally-varying flux adjustments there are modest reductions in ENSO amplitude of the order of 10–15%, lower than the range of reductions inferred from coral proxy records. We examine the mechanisms for these changes, and discuss the implications for the design of future ensemble experiments to formally quantify uncertainty in climate change predictions using palaeoclimate simulations.
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