Observational evidence of European summer weather patterns predictable from spring
Forecasts of summer weather patterns months in advance would be of great value for a wide range of applications. However, seasonal dynamical model forecasts for European summers have very little skill, particularly for rainfall. It has not been clear whether this low skill reflects inherent unpredic...
| Published in: | Proceedings of the National Academy of Sciences |
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| Main Authors: | , , , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
National Academy of Sciences
2018
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| Subjects: | |
| Online Access: | https://centaur.reading.ac.uk/74646/ https://centaur.reading.ac.uk/74646/2/PNAS-2018-Oss%C3%B3-59-63.pdf |
| Summary: | Forecasts of summer weather patterns months in advance would be of great value for a wide range of applications. However, seasonal dynamical model forecasts for European summers have very little skill, particularly for rainfall. It has not been clear whether this low skill reflects inherent unpredictability of summer weather or, alternatively, is a consequence of weaknesses in current forecast systems. Here we analyze atmosphere and ocean observations and identify evidence that a specific pattern of summertime atmospheric circulation--the summer East Atlantic (SEA) pattern--is predictable from the previous spring. An index of North Atlantic sea-surface temperatures in March-April can predict the SEA pattern in July-August with a cross-validated correlation skill above 0.6. Our analyses show that the sea-surface temperatures influence atmospheric circulation and the position of the jet stream over the North Atlantic. The SEA pattern has a particularly strong influence on rainfall in the British Isles, which we find can also be predicted months ahead with a significant skill of 0.56. Our results have immediate application to empirical forecasts of summer rainfall for the United Kingdom, Ireland, and northern France and also suggest that current dynamical model forecast systems have large potential for improvement. |
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