Simulating weather regimes: impact of model resolution and stochastic parameterization
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The simulation of quasi-persistent regime structures in an atmospheric model with horizontal resolution typical of the Intergovernmental Panel on Climate Change fifth assessment report simulations, is shown to be unrealistic. A higher resolution configuration of the same model, with horizontal resolution typical of that used in operational numerical weather prediction, is able to simulate these regime structures realistically. The spatial patterns of the simulated regimes are remarkably accurate at high resolution. A model configuration at intermediate resolution shows a marked improvement over the low-resolution configuration, particularly in terms of the temporal characteristics of the regimes, but does not produce a simulation as accurate as the very-high-resolution configuration. It is demonstrated that the simulation of regimes can be significantly improved, even at low resolution, by the introduction of a stochastic physics scheme. At low resolution the stochastic physics scheme drastically improves both the spatial and temporal aspects of the regimes simulation. These results highlight the importance of small-scale processes on large-scale climate variability, and indicate that although simulating variability at small scales is a necessity, it may not be necessary to represent the small-scales accurately, or even explicitly, in order to improve the simulation of large-scale climate. It is argued that these results could have important implications for improving both global climate simulations, and the ability of high-resolution limited-area models, forced by low-resolution global models, to reliably simulate regional climate change signals.
KeywordsCirculation regimes Stochastic physics Cluster analysis European weather regimes Horizontal resolution GCM
This work was funded by the Natural Environment Research Council TEMPEST (Testing and Evaluating Model Predictions of European Storms) project. TP is funded by an ERC grant (Towards the Prototype Probabilistic Earth-System Model for Climate Prediction, project number 291406). Thanks to Jim Kinter, Thomas Jung and colleagues for their hard work on the Athena project which enabled this research. We are also grateful to Nils Wedi and Mirek Andrejczuk for performing additional numerical experiments on our behalf. AD is grateful for useful discussions with David Straus, Susanna Corti and Christophe Cassou. The twentieth century Reanalysis V2 data were provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their website at http://www.esrl.noaa.gov/psd/. Support for the Twentieth century Reanalysis Project dataset is provided by the U.S. Department of Energy, Office of Science Innovative and Novel Computational Impact on Theory and Experiment (DOE INCITE) program, and Office of Biological and Environmental Research (BER), and by the National Oceanic and Atmospheric Administration Climate Program Office. We thank two anonymous reviewers whose comments helped to improve the manuscript.
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