Climate Dynamics

, Volume 38, Issue 7–8, pp 1281–1299 | Cite as

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

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


Surface wind speed is a key climatic variable of interest in many applications, including assessments of storm-related infrastructure damage and feasibility studies of wind power generation. In this work and a companion paper (van der Kamp et al. 2011), the relationship between local surface wind and large-scale climate variables was studied using multiple regression analysis. The analysis was performed using monthly mean station data from British Columbia, Canada and large-scale climate variables (predictors) from the NCEP-2 reanalysis over the period 1979–2006. Two regression-based methodologies were compared. The first relates the annual cycle of station wind speed to that of the large-scale predictors at the closest grid box to the station. It is shown that the relatively high correlation coefficients obtained with this method are attributable to the dominant influence of region-wide seasonality, and thus contain minimal information about local wind behaviour at the stations. The second method uses interannually varying data for individual months, aggregated into seasons, and is demonstrated to contain intrinsically local information about the surface winds. The dependence of local wind speed upon large-scale predictors over a much larger region surrounding the station was also explored, resulting in 2D maps of spatial correlations. The cross-validated explained variance using the interannual method was highest in autumn and winter, ranging from 30 to 70% at about a dozen stations in the region. Reasons for the limited predictive skill of the regressions and directions for future progress are reviewed.


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, Greg Flato, Yanping He, and two anonymous referees for comments on the manuscript and Dave Rodenhuis for his encouragement and interest in this work.


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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

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

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