Open AccessOn the application of hierarchical cluster analysis for synthesizing low‐level wind fields obtained with a mesoscale boundary layer model
Author(s) -
Ratto Gustavo,
Berri Guillermo J.,
Maronna Ricardo
Publication year - 2014
Publication title -
meteorological applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.672
H-Index - 59
eISSN - 1469-8080
pISSN - 1350-4827
DOI - 10.1002/met.1396
Subject(s) - mesoscale meteorology , shore , cluster (spacecraft) , meteorology , planetary boundary layer , wind speed , hierarchical clustering , boundary layer , cluster analysis , boundary (topology) , wind direction , distribution (mathematics) , field (mathematics) , environmental science , computer science , geography , geology , mathematics , physics , mathematical analysis , oceanography , machine learning , pure mathematics , turbulence , thermodynamics , programming language
Hierarchical clustering is applied to a boundary layer model output that describes the low‐level wind field over the L a P lata R iver region of S outh A merica. The model output consists of 180 17‐dimensional vectors per season that include wind direction frequencies, calms and mean wind speeds per wind sector. The cluster approach is intended to assist the discussion of meteorological phenomena, and is also employed to define regionality. Results show that the 180 original vectors can be well represented by a small number of vectors, and the 18, 12 and 6 group cluster solutions share a similar layout. However, the 12 and the 6 group clusters seem both appropriate solutions when a threshold of 10% in wind direction frequency, including calms, is taken as a reference in order to decide significant differences between groups. All solutions show more groups along the northeastern than along the southwestern river shore, evidencing a complex sea‐land breeze circulation pattern. The analysis of the observations at nine weather stations supports the findings of the cluster analysis conducted with the model outputs. The advantage of the hierarchical cluster analysis in synthesizing information becomes clearly evident when compared to the traditional method of visual inspection. Besides, the actual distribution of weather stations in the region is not very far from the regionality that suggests the obtained cluster distribution. However, in order to match the latter, more observing points would be needed particularly over the river and towards the northeastern shore.