MATLAB Implementation for Displaying Wind Rose Diagrams

In meteorology and wind energy resource assessment, wind rose diagrams serve as intuitive visualization tools for displaying wind direction and speed distributions. Using MATLAB, we can efficiently generate these diagrams for statistical analysis of meteorological data and evaluation of wind energy resources. ### Core Steps for Generating Wind Rose Diagrams Data Preparation: Begin by collecting observational data for wind direction and speed. Wind direction is typically represented in degrees (0°~360°), while wind speed contains measured values (e.g., meters per second). The data can consist of hourly observations or long-term statistical results. In MATLAB implementation, this data is often stored in arrays or tables, with separate columns for direction and speed measurements. Data Grouping and Processing: Classify wind direction data into specific angular intervals (e.g., 16 cardinal directions with 22.5° per sector) and statistically analyze wind speed distributions within each interval (using speed categories such as 0-2 m/s, 2-4 m/s, etc.). This can be implemented using MATLAB's discretize function for directional binning and histcounts for speed categorization. The algorithm typically involves calculating frequency percentages or average speeds for each directional sector. Plotting the Rose Diagram: Utilize MATLAB's polar coordinate plotting capabilities (polarplot function) or specialized toolboxes (like the WindRose function, which requires additional download). Each sector in the rose diagram represents a wind direction interval, where sector length indicates wind frequency or average speed, and colors differentiate various speed categories. Key programming aspects include converting Cartesian coordinates to polar coordinates and implementing stacked bar representations in polar format. Visual Enhancement and Labeling: Add legends, titles, and directional markers (such as north indication) to ensure clear interpretation. Adjust color mapping and scaling to make speed distributions immediately visible. This involves using MATLAB's colormap functions, legend customization, and annotation tools for directional markers. ### Application Scenarios Meteorological Analysis: Study predominant wind directions and seasonal variations in specific regions, supporting weather forecasting or climate research. Wind Resource Assessment: Analyze potential power generation and optimize turbine placement during wind farm site selection. Environmental Engineering: Evaluate pollutant dispersion directions or design ventilation corridors in urban planning. Through MATLAB's flexible programming capabilities and rich graphical functions, wind rose diagrams can not only be displayed statically but also generated as dynamic visualizations when combined with time-series data, further revealing long-term trends in wind patterns. Advanced implementations may include interactive features using MATLAB's App Designer or creating animated sequences using movie functions.