Community detection analysis in wind speed-monitoring systems using mutual information-based complex network

Area of Science:

• Environmental Science
• Network Analysis
• Climatology

Background:

• Understanding regional climate variations is crucial for Switzerland's diverse topography.
• Wind speed data from extensive monitoring networks provides insights into atmospheric dynamics.

Purpose of the Study:

• To apply network analysis to a wide wind speed-monitoring system in Switzerland.
• To detect and characterize communities within the sensor network.

Main Methods:

• Utilized a mutual information-based weighted network representation.
• Employed community detection algorithms to identify clusters of sensors.
• Applied the silhouette measure for evaluating community structure and sensor membership.

Main Results:

• Identified two distinct communities within the wind speed sensor network.
• Correlated these communities with geographical locations: the Alps and the Jura-Plateau.
• Confirmed that these clusters represent Switzerland's two major climatic zones.

Conclusions:

• Network analysis effectively delineates climatic zones based on wind speed data.
• The study successfully identified and validated distinct regional patterns in Swiss wind conditions.