Atmospheric Circulation Effects on Wind Speed Variability at Turbine Height

Katherine Klink Department of Geography, University of Minnesota, Minneapolis, Minnesota

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Abstract

Mean monthly wind speed at 70 m above ground level is investigated for 11 sites in Minnesota for the period 1995–2003. Wind speeds at these sites show significant spatial and temporal coherence, with prolonged periods of above- and below-normal values that can persist for as long as 12 months. Monthly variation in wind speed primarily is determined by the north–south pressure gradient, which captures between 22% and 47% of the variability (depending on the site). Regression on wind speed residuals (pressure gradient effects removed) shows that an additional 6%–15% of the variation can be related to the Arctic Oscillation (AO) and Niño-3.4 sea surface temperature (SST) anomalies. Wind speeds showed little correspondence with variation in the Pacific–North American (PNA) circulation index. The effect of the strong El Niño of 1997/98 on the wind speed time series was investigated by recomputing the regression equations with this period excluded. The north–south pressure gradient remains the primary determinant of mean monthly 70-m wind speeds, but with 1997/98 removed the influence of the AO increases at nearly all stations while the importance of the Niño-3.4 SSTs generally decreases. Relationships with the PNA remain small. These results suggest that long-term patterns of low-frequency wind speed (and thus wind power) variability can be estimated using large-scale circulation features as represented by large-scale climatic datasets and by climate-change models.

Corresponding author address: Katherine Klink, Department of Geography, 414 Social Sciences Bldg., 267 19th Ave. S, University of Minnesota, Minneapolis, MN 55455. Email: klink@umn.edu

Abstract

Mean monthly wind speed at 70 m above ground level is investigated for 11 sites in Minnesota for the period 1995–2003. Wind speeds at these sites show significant spatial and temporal coherence, with prolonged periods of above- and below-normal values that can persist for as long as 12 months. Monthly variation in wind speed primarily is determined by the north–south pressure gradient, which captures between 22% and 47% of the variability (depending on the site). Regression on wind speed residuals (pressure gradient effects removed) shows that an additional 6%–15% of the variation can be related to the Arctic Oscillation (AO) and Niño-3.4 sea surface temperature (SST) anomalies. Wind speeds showed little correspondence with variation in the Pacific–North American (PNA) circulation index. The effect of the strong El Niño of 1997/98 on the wind speed time series was investigated by recomputing the regression equations with this period excluded. The north–south pressure gradient remains the primary determinant of mean monthly 70-m wind speeds, but with 1997/98 removed the influence of the AO increases at nearly all stations while the importance of the Niño-3.4 SSTs generally decreases. Relationships with the PNA remain small. These results suggest that long-term patterns of low-frequency wind speed (and thus wind power) variability can be estimated using large-scale circulation features as represented by large-scale climatic datasets and by climate-change models.

Corresponding author address: Katherine Klink, Department of Geography, 414 Social Sciences Bldg., 267 19th Ave. S, University of Minnesota, Minneapolis, MN 55455. Email: klink@umn.edu

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