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Skilful multi-year predictions of Atlantic hurricane frequency

Nature Geoscience volume 3, pages 846–849 (2010)Cite this article

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Abstract

North Atlantic hurricane activity has increased substantially since the 1970s (refs 1, 2), but whether this is attributable to natural internal variability1,3 or external forcing4,5,6,7 has not been resolved8. Either way, hurricane frequency is potentially predictable, because climate models can directly simulate year-to-year variations in Atlantic tropical storm frequency, if forced by observed sea surface temperatures9. However, skilful predictions have been limited to lead times of one season10, and evidence for external forcing of hurricane frequency has been indirect, relying on statistical relationships4 or external influences on related environmental factors5,6,7. Here we extend skilful climate model predictions of hurricane frequency to lead times of several years, using decadal predictions11 with nine variants of a general circulation model. In our experiments, the recent increase in tropical storm numbers was not caused by internal variability alone. This provides physically based model evidence of externally forced changes in hurricane frequency, albeit from a single modelling system. Initialization of the model with the observed state of the climate improves forecast skill, mainly through better predictions of tropical Pacific and North Atlantic ocean conditions, in line with previously documented teleconnections1,3,12,13,14,15. Our results show that predictions of hurricane frequency are viable beyond the seasonal scale, and further elucidate causes of hurricane variability.

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Figure 1: Seasonal hindcasts of Atlantic tropical storm frequency.
Figure 2: Multi-annual hindcasts of Atlantic tropical storm frequency.
Figure 3: Skill and impact of initialization for five-year mean surface air temperature.
Figure 4: Remote influences on hurricanes.

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Acknowledgements

We thank many colleagues in the Met Office for developing the climate models, and for help and advice during the course of this work. Thanks also to M. McVean at ECMWF for carrying out the hindcasts. We are grateful to M. Bender for comments that improved this paper. This work was supported by the Joint DECC and Defra Integrated Climate Programme—DECC/Defra (GA01101)UK, and by the EU FP6 ENSEMBLES project.

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Authors and Affiliations

  1. Met Office Hadley Centre, FitzRoy Road, Exeter EX1 3PB, UK

    Doug M. Smith, Rosie Eade, Nick J. Dunstone, David Fereday, James M. Murphy, Holger Pohlmann & Adam A. Scaife

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  1. Doug M. Smith
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  2. Rosie Eade
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  3. Nick J. Dunstone
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Contributions

D.M.S. led the analysis and interpretation. D.F. developed the storm tracking algorithm, which R.E. used to analyse storm counts. D.M.S., R.E., H.P. and N.J.D. conducted the analysis. D.M.S. and J.M.M. developed DePreSys and designed the experiments. D.M.S. and A.A.S. wrote the paper with contributions from all authors.

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Correspondence to Doug M. Smith.

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The authors declare no competing financial interests.

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Smith, D., Eade, R., Dunstone, N. et al. Skilful multi-year predictions of Atlantic hurricane frequency. Nature Geosci 3, 846–849 (2010). https://doi.org/10.1038/ngeo1004

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