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Spatial variability in winter NAO–wind speed relationships in western Europe linked to concomitant states of the East Atlantic and Scandinavian patterns
Author(s) -
Zubiate Laura,
McDermott Frank,
Sweeney Conor,
O'Malley Mark
Publication year - 2016
Publication title -
quarterly journal of the royal meteorological society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.744
H-Index - 143
eISSN - 1477-870X
pISSN - 0035-9009
DOI - 10.1002/qj.2943
Subject(s) - teleconnection , north atlantic oscillation , climatology , wind power , weibull distribution , environmental science , wind speed , spatial distribution , arctic oscillation , empirical orthogonal functions , prevailing winds , global wind patterns , meteorology , geography , physical geography , geology , northern hemisphere , statistics , el niño southern oscillation , mathematics , remote sensing , electrical engineering , engineering
The 3‐hourly gridded ECMWF ERA‐Interim climate reanalysis dataset, spanning 1979–2013, was used to investigate the spatial stationarity of the previously documented relationships between wind speeds and the North Atlantic Oscillation (NAO) state in Europe. Over much of western Europe, wind speeds were found to be affected strongly by the concomitant states of the secondary and tertiary atmospheric teleconnections, namely the East Atlantic (EA) and the Scandinavian (SCA) patterns. These modify the geographic positions of the NAO dipole and modulate the influence of the NAO on wind statistics on regional scales, producing non‐stationarities in the NAO–wind speed relationships. The interactions of these teleconnections play an important role in modifying wind speeds within Europe. Finally, systematic north–south changes in the Weibull distribution scale and shape parameters are documented along the western margin of Europe, as a function of different states of the NAO, the EA and the SCA. These effects influence both monthly averaged wind speeds and the statistical distributions of 3‐hourly wind data, implying strong impacts on wind energy resources and expected wind power production. The results have implications for regional to continent‐scale long‐term planning of wind‐farm siting to minimise the impact of resource intermittency.