69: K-MEANS CLUSTERING RESOLUTION OF DIURNAL WIND PATTERN MODES AND PATTERN EXTREMA FOR NASHVILLE, TN

Music City Center 

Applying K-Means Clustering Analysis on contiguous hourly 0000 LST to 2300 LST wind direction/speed data for Nashville, TN. (1948-2024), the following identifies the station's most prominent diurnal statistical sub-patterns or "modes". The daily observations are first converted into 24 pairs of north/south and east/west components, and saved in an array of N by 48 cases, where N is the number of complete daily hourly observations and 48 the (standardized) magnitudes of the "u" and "v" parameter values. The K-Means clustering routine is then run, integrated with the V-Fold Cross Validation algorithm which produces an "optimal" number of "K" clusters. Each of the 48-D centroids (five in number) are then transformed into arrays of hourly resultant wind directions and mean scalar speeds. The results exhibit physically meaningful, distinct diurnal patterns, with contrasting seasonal inclinations as well. Then, as a heuristic exercise, the extreme-most diurnal wind pattern is identified, based on squared Euclidean distances generated by a fixed K=1 (global) treatment of the data. A recent identical analysis such as this one yielded good results for Las Vegas, Phoenix, and Tucson.

K-MEANS CLUSTERING OF NORTH/SOUTH AND EAST\WEST WIND COMPONENTS

DIURNAL RESULTANT WINDS PATTERNS

SQURED EUCLIDEAN STATISTICAL DISTANCES

K=1 CLUSTER ANALYSIS MANIPULATION 

Section on Statistics and the Environment