Abstract
Seasonal forecast models exhibit only modest skill in predicting extreme summer temperatures across the eastern US. Anomalies in sea surface temperature and monthly-resolution rainfall have, however, been correlated with hot days in the US, and seasonal persistence of these anomalies suggests potential for long-lead predictability. Here we present a clustering analysis of daily maximum summer temperatures from US weather stations between 1982–2015 and identify a region spanning most of the eastern US where hot weather events tend to occur synchronously. We then show that an evolving pattern of sea surface temperature anomalies, termed the Pacific Extreme Pattern, provides for skillful prediction of hot weather within this region as much as 50 days in advance. Skill is demonstrated using out-of-sample predictions between 1950 and 2015. Rainfall deficits over the eastern US are also associated with the occurrence of the Pacific Extreme Pattern and are demonstrated to offer complementary skill in predicting high temperatures. The Pacific Extreme Pattern appears to provide a cohesive framework for improving seasonal prediction of summer precipitation deficits and high temperature anomalies in the eastern US.
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Acknowledgements
The authors acknowledge funding from the NSF GRFP, NASA NESSF, NCAR ASP, and NSF grant 1304309, and thank B. Farrell, C. Wunsch, C. Bitz, C. Deser, D. Schrag, D. Battisti, J. Mitrovica, M. Cane, P. Hassanzadeh and Z. Kuang for their valuable comments.
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The authors contributed equally in designing the study and contributing analysis tools, K.A.M. and A.R. analysed data, and K.A.M. led the writing.
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McKinnon, K., Rhines, A., Tingley, M. et al. Long-lead predictions of eastern United States hot days from Pacific sea surface temperatures. Nature Geosci 9, 389–394 (2016). https://doi.org/10.1038/ngeo2687
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DOI: https://doi.org/10.1038/ngeo2687
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