TITLE:
Analysis of the Homogeneity of Wind Roses' Groups Employing Andrews’ Curves
AUTHORS:
Ratto Gustavo, Videla Fabián, Reyna Almandos Jorge
KEYWORDS:
Andrews’ Curves, Cluster, Group Homogeneity, Principal Component Analysis (PCA), Wind Roses
JOURNAL NAME:
Atmospheric and Climate Sciences,
Vol.4 No.3,
July
29,
2014
ABSTRACT: The homogeneity of groups of
16-dimensional wind direction roses (obtained by hierarchical clustering in a
previous report) is discussed through the application of Andrews’ Curves.
Principal Component Analysis (PCA) is employed to reduce dimensionality and to
provide an ordering of the variables to compute Andrews’ Curves. Our results
suggest that Andrews’ Curves greatly facilitate the visualization of
homogeneity as well as reveal information that allows improving the clusters’
arrangement. A combined analysis employing Andrews’ Curves and Calinkski and
Harabasz’ approach (a method for determining the optimal number of groups)
helps to assess the strength of the group structure of the data as well as to
detect anomalies such as misclassified objects or atypical values. Furthermore,
it allows finding out that the 24 original seasonal hourly roses (representing
the “day”) become better represented by 6 groups (rather than by 5 as proposed
in the previous report). The new group arrangement was consistent with the
dendogram for another cut-off distance. As a result the wind occurrences are
now represented by a more detailed and smooth pattern: there is a decrease in
northern wind between midday and twilight while eastern winds become more
important towards the evening. The methodology proposed is a subject to be
considered to become part of an automated system.