Climate Dynamics

, Volume 38, Issue 7–8, pp 1301–1311 | Cite as

Statistical downscaling of historical monthly mean winds over a coastal region of complex terrain. II. Predicting wind components

  • Derek van der Kamp
  • Charles L. CurryEmail author
  • Adam H. Monahan


A regression-based downscaling technique was applied to monthly mean surface wind observations from stations throughout western Canada as well as from buoys in the Northeast Pacific Ocean over the period 1979–2006. A predictor set was developed from principal component analysis of the three wind components at 500 hPa and mean sea-level pressure taken from the NCEP Reanalysis II. Building on the results of a companion paper, Curry et al. (Clim Dyn 2011, doi: 10.1007/s00382-011-1173-3), the downscaling was applied to both wind speed and wind components, in an effort to evaluate the utility of each type of predictand. Cross-validated prediction skill varied strongly with season, with autumn and summer displaying the highest and lowest skill, respectively. In most cases wind components were predicted with better skill than wind speeds. The predictive ability of wind components was found to be strongly related to their orientation. Wind components with the best predictions were often oriented along topographically significant features such as constricted valleys, mountain ranges or ocean channels. This influence of directionality on predictive ability is most prominent during autumn and winter at inland sites with complex topography. Stations in regions with relatively flat terrain (where topographic steering is minimal) exhibit inter-station consistencies including region-wide seasonal shifts in the direction of the best predicted wind component. The conclusion that wind components can be skillfully predicted only over a limited range of directions at most stations limits the scope of statistically downscaled wind speed predictions. It seems likely that such limitations apply to other regions of complex terrain as well.


Wind Statistical downscaling Regional climate North America 



This work was supported by a Knowledge Synthesis Grant from the Canadian Foundation for Climate and Atmospheric Sciences. The authors would like to thank Gerd Buerger and Dave Rodenhuis of Pacific Climate Impacts Consortium for their input throughout the project, Bill Merryfield (CCCma) for commenting on an earlier version of the manuscript, and two anonymous referees for constructive suggestions.


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Copyright information

© Her Majesty the Queen in the Right of Canada as represented by the Minister of the Environment 2011

Authors and Affiliations

  • Derek van der Kamp
    • 1
    • 3
  • Charles L. Curry
    • 2
    • 3
    Email author
  • Adam H. Monahan
    • 3
  1. 1.Pacific Climate Impacts ConsortiumUniversity of VictoriaVictoriaCanada
  2. 2.Canadian Centre for Climate Modelling and AnalysisEnvironment Canada University of VictoriaVictoriaCanada
  3. 3.School of Earth and Ocean SciencesUniversity of VictoriaVictoriaCanada

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