Classification of Mesoscale Wind Fields in the MISTRAL Field Experiment

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  • 1 Paul Scherrer Institute, Villigen, Switzerland
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Abstract

A two-stage classification scheme with outlier detection is proposed to find groups of wind fields. A hierarchical cluster analysis according to the complete linkage method is combined with a k-means procedure with detection and exclusion of outliers. The classification method is applied to a 1-yr dataset of 1-h mean wind observations from the MISTRAL field experiment. A small number of typical regional flow patterns is identified. An analysis of temperature observations shows that some of the 12 regional flow patterns have thermally forced wind systems. The main spatial forcing patterns are revealed by a principal component analysis of temperature observations. A comparison of the regional flow patterns and the synoptic-scale weather types of the Alpine region shows that only weak connections between the local flow and the synoptic-scale weather type exist.

Abstract

A two-stage classification scheme with outlier detection is proposed to find groups of wind fields. A hierarchical cluster analysis according to the complete linkage method is combined with a k-means procedure with detection and exclusion of outliers. The classification method is applied to a 1-yr dataset of 1-h mean wind observations from the MISTRAL field experiment. A small number of typical regional flow patterns is identified. An analysis of temperature observations shows that some of the 12 regional flow patterns have thermally forced wind systems. The main spatial forcing patterns are revealed by a principal component analysis of temperature observations. A comparison of the regional flow patterns and the synoptic-scale weather types of the Alpine region shows that only weak connections between the local flow and the synoptic-scale weather type exist.

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