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Abstract

The Great Lakes region has been the subject of numerous climate related research studies. The seasonal wind and circulation patterns are critical to understanding how weather patterns propagate as well as for potential wind energy generation. Furthermore, wind is a critical component in weather forecasting; thus, additional information on atmospheric circulation tendencies in this area can lead to improvements in weather forecasting. By utilizing monthly average wind speed data from 46 Great Lakes stations, augmented with NCEP/NCAR reanalysis data (Kalnay, et al. 1996; Kistler, et al. 2001), the seasonal differences in wind speeds throughout the region can be analyzed. To better comprehend these changes in wind patterns, a rotated principal component analysis (PCA) was used to identify spatial patterns within the Great Lakes region. Five general eigenvectors were classified: the Great Lakes, the Ohio Valley, the Atlantic Ocean, the Wisconsin, and the Great Plains. By analyzing the loading values, the geographical extent of the grouping can be mapped and comparisons between winter, spring, summer, and fall extents can be discussed. Additionally, regime shift analysis, first proposed by Rodinov (2004), was conducted on the data to determine when a new climate regime in wind became established. These regime shifts can provide further insight as to the strengthening or weakening tendency of wind speeds across the region. Three different regime shifts occurred during the period of 1990-2009: an initial weakening during the mid-90s, a second weakening around the early 2010s, and a strengthening during the mid-2010s. Identification of seasonal variations and year-to-year variations of wind speed can provide a more robust understanding of the wind climatology of the region as well as how the climate may be changing over time.

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