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Probabilistic seasonal prediction of the winter North Atlantic Oscillation and its impact on near surface temperature

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Abstract

The North Atlantic Oscillation (NAO) is a major winter climate mode, describing one-third of the inter-annual variability of the upper-level flow in the Atlantic European mid-latitudes. It provides a statistically well-defined pattern to study the predictability of the European winter climate. In this paper, the predictability of the NAO and the associated surface temperature variations are considered using a dynamical prediction approach. Two state-of-the-art coupled atmosphere–ocean ensemble forecast systems are used, namely the seasonal forecast system 2 from the European Centre for Medium Range Weather Forecast (ECMWF) and the multi-model system developed within the joint European project DEMETER (Development of a European Multi-Model Ensemble Prediction System for Seasonal to Inter-annual Prediction). The predictability is defined in probabilistic space using the debiased ranked probability skill score with adapted discretization (RPSSD). The potential predictability of the NAO and its impact are also investigated in a perfect model approach, where each ensemble member is used once as “observation”. This approach assumes that the climate system is fully represented by the model physics.

Using the perfect model approach for the period 1959–2001, it is shown that the mean winter NAO index is potentially predictable with a lead time of 1 month (i.e. from 1st of November). The prediction benefit is rather small (6% skill relative to a reference climatology) but statistically significant. A similar conclusion holds for the near surface temperature variability related to the NAO. Again, the potential benefit is small (5%) but statistically significant. Using the forecast approach, the NAO skill is not statistically significant for the period 1959–2001, while for the period 1987–2001 the skill is surprisingly large (15% relative to a climate prediction). Furthermore, a weak relation is found between the strength of the NAO amplitude and the skill of the NAO. This contrasts with El Niño/Southern Oscillation (ENSO) variability, where the forecast skill is strongly amplitude dependent. In general, robust results are only achieved if the sensitivity with respect to the sample size (both the ensemble size and length of the period) is correctly taken into account.

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Notes

  1. http://www.ecmwf.int/research/era

  2. http://www.ecmwf. int/research/demeter/general/docmodel/index.html

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Acknowledgements

This study was supported by the Swiss NSF through Grant 2100-061631.00 and the National Centre for Competence in Research Climate (NCCR-Climate). We would like to thank the ECWMF seasonal forecast and the DEMETER team for providing the data. Special thanks are addressed to Francisco J. Doblas-Reyes, Mark Liniger, Mathias Rotach and Simon Scherrer for their critical review of the paper.

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Authors and Affiliations

  1. Swiss Federal Office of Meteorology and Climatology (MeteoSwiss), Zurich, Switzerland

    W. A. Müller & C. Appenzeller

  2. Institute for Atmospheric and Climate Science, ETH, Zurich, Switzerland

    C. Schär

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  1. W. A. Müller
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  2. C. Appenzeller
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  3. C. Schär
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Müller, W., Appenzeller, C. & Schär, C. Probabilistic seasonal prediction of the winter North Atlantic Oscillation and its impact on near surface temperature. Clim Dyn 24, 213–226 (2005). https://doi.org/10.1007/s00382-004-0492-z

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  • DOI: https://doi.org/10.1007/s00382-004-0492-z

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