Search from over 60,000 research works

Advanced Search

Observational evidence of European summer weather patterns predictable from spring

[thumbnail of Open Access]
Preview
PNAS-2018-Ossó-59-63.pdf - Published Version (1MB) | Preview
Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

Osso, A., Sutton, R. orcid id iconORCID: https://orcid.org/0000-0001-8345-8583, Shaffrey, L. orcid id iconORCID: https://orcid.org/0000-0003-2696-752X and Dong, B. orcid id iconORCID: https://orcid.org/0000-0003-0809-7911 (2018) Observational evidence of European summer weather patterns predictable from spring. Proceedings of the National Academy of Sciences of the United States of America, 115 (1). pp. 59-63. ISSN 0027-8424 doi: 10.1073/pnas.1713146114

Abstract/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.

Altmetric Badge

Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/74646
Item Type Article
Refereed Yes
Divisions Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Uncontrolled Keywords climate variability, predictability, seasonal forecast, sea–air interactions
Publisher National Academy of Sciences
Download/View statistics View download statistics for this item

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Search Google Scholar