Simulating regime structures in weather and climate prediction models

Authors

  • A. Dawson,

    Corresponding author
    1. Atmospheric, Oceanic and Planetary Physics, Department of Physics, University of Oxford, Oxford, UK
    • Corresponding author: A. Dawson, Atmospheric, Oceanic and Planetary Physics, Department of Physics, Parks Road, University of Oxford, Oxford OX1 3PU, UK. (dawson@atm.ox.ac.uk)

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  • T. N. Palmer,

    1. Atmospheric, Oceanic and Planetary Physics, Department of Physics, University of Oxford, Oxford, UK
    2. European Centre for Medium-Range Weather Forecasts, Reading, UK
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  • S. Corti

    1. European Centre for Medium-Range Weather Forecasts, Reading, UK
    2. Istituto di Scienze dell'Atmosfera e del Clima, Consiglio Nazionale delle Ricerche, Bologna, Italy
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Abstract

[1] It is shown that a global atmospheric model with horizontal resolution typical of that used in operational numerical weather prediction is able to simulate non-gaussian probability distributions associated with the climatology of quasi-persistent Euro-Atlantic weather regimes. The spatial patterns of these simulated regimes are remarkably accurate. By contrast, the same model, integrated at a resolution more typical of current climate models, shows no statistically significant evidence of such non-gaussian regime structures, and the spatial structure of the corresponding clusters are not accurate. Hence, whilst studies typically show incremental improvements in first and second moments of climatological distributions of the large-scale flow with increasing model resolution, here a real step change in the higher-order moments is found. It is argued that these results have profound implications for the ability of high resolution limited-area models, forced by low resolution global models, to simulate reliably, regional climate change signals.

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