Wind Rose

A wind rose is a circular diagram that shows the distribution of directional data, typically used for wind patterns. The chart displays how often values (like wind speed, frequency, or magnitude) occur from different directions. Each direction is represented by a slice, and the length or color intensity indicates the frequency or magnitude of occurrences in that direction. Wind roses make it easy to identify prevailing directions, seasonal patterns, and directional distributions at a glance.

Best used for:

• Wind speed and direction analysis (meteorology)
• Directional frequency distribution visualization
• Pollution dispersion and environmental studies
• Navigation and aviation planning
• Traffic flow analysis by direction
• Any data with directional components

Common Use Cases

Meteorology & Climate

• Wind speed and direction patterns
• Seasonal wind analysis
• Storm tracking and prediction
• Climate pattern visualization
• Weather forecasting support

Environmental Science

• Pollution dispersion modeling
• Air quality monitoring by direction
• Smoke or plume direction analysis
• Wave direction and height
• Ocean current patterns

Engineering & Planning

• Airport runway planning and design
• Wind turbine site selection
• Building ventilation design
• Urban planning and air flow
• HVAC system optimization

Other Applications

• Traffic flow direction analysis
• Sports analytics (ball trajectory, shot direction)
• Migration pattern visualization
• Signal strength by orientation
• Radar data visualization

Options

Direction/Angle

Required - Column containing directional data.

Values represent the direction (e.g., compass direction, angle in degrees). Can be categorical (N, NE, E, SE, S, SW, W, NW) or numerical (0-360 degrees).

Magnitude/Frequency

Required - Column containing the intensity or frequency values.

Column

Select the numerical column representing magnitude (e.g., wind speed) or frequency of occurrences.

Aggregation Function

Choose how to aggregate values:

Options:

• Sum - Total magnitude
• Mean - Average magnitude
• Count - Frequency count (most common for occurrence data)
• Min - Minimum magnitude
• Max - Maximum magnitude

Category (Optional)

Optional - Additional categorical dimension.

Use this to split data into categories (e.g., wind speed ranges: "Light", "Moderate", "Strong"). Each category is displayed as a different color or segment.

Settings

Show Direction Labels

Optional - Display labels for directions.

When enabled, shows direction labels (N, S, E, W, etc.) around the perimeter of the chart.

Starting Angle

Optional - Rotation angle for chart orientation.

Specify the rotation angle (0-360 degrees) to adjust the starting position of the chart. Typically set to 90 degrees so North is at the top.

Understanding Wind Rose Components

Radial Segments

• Direction slices: Each slice represents a compass direction
• Segment length: Proportional to frequency or magnitude
• Angular width: Divided into equal sectors (typically 8, 16, or 32)
• Colors/Layers: Different categories shown as nested rings or colors

Direction Conventions

• North (N): Typically at top (90° with default setting)
• East (E): Typically at right (0°)
• South (S): Typically at bottom (270°)
• West (W): Typically at left (180°)
• Cardinal directions: N, S, E, W
• Intercardinal: NE, SE, SW, NW
• Secondary intercardinal: NNE, ENE, ESE, SSE, SSW, WSW, WNW, NNW

Reading the Chart

1. Identify direction: Look at the angle of the segment
2. Check length: Longer segments = higher frequency/magnitude
3. Observe colors: Different colors show categories or intensity ranges
4. Compare sectors: Identify prevailing or dominant directions

Tips for Effective Wind Roses

1. Direction Data Preparation:

   • Ensure directions are consistent (all degrees OR all cardinal labels)
   • For degrees: 0-360 where 0/360 is North, 90 is East, 180 is South, 270 is West
   • For categorical: Use standard abbreviations (N, NE, E, SE, S, SW, W, NW)
   • Clean null or invalid direction values

2. Magnitude Selection:

   • Count: Best for showing frequency of occurrences
   • Sum: For total accumulated values
   • Mean: For average conditions per direction
   • Consider normalizing by observation count if needed

3. Category Usage:

   • Use categories to show intensity ranges (e.g., "0-5 mph", "5-10 mph", "10+ mph")
   • Keep categories to 3-5 for readability
   • Use meaningful, non-overlapping bins
   • Consider using standard scales (Beaufort scale for wind)

4. Orientation Settings:

   • Keep North at top (starting angle = 90°) for convention
   • Adjust only if specific domain conventions differ
   • Ensure direction labels match orientation

5. Visual Clarity:

   • Use sufficient directional bins (16 is common for wind data)
   • Choose contrasting colors for categories
   • Include legend for magnitude/category interpretation
   • Show gridlines for magnitude scale

6. Data Quality:

   • Remove calm conditions (zero magnitude) if appropriate
   • Handle missing directions properly
   • Ensure adequate sample size for reliable patterns
   • Consider seasonal or temporal subsets

Wind Rose vs Other Directional Plots

vs Polar Bar Chart

• Wind Rose: Shows frequency distribution by direction
• Polar Bar Chart: Shows values at specific angles
• Wind Rose advantage: Better for showing dominant patterns

vs Radar Chart

• Wind Rose: Directional frequency/magnitude distribution
• Radar Chart: Multiple variable comparison across categories
• Different purposes: Wind rose is specifically for directional data

vs Compass Plot

• Wind Rose: Aggregated frequency distribution
• Compass Plot: Individual point directions
• Choose Wind Rose: For pattern analysis of many observations

Example Scenarios

Wind Speed and Direction

Shows prevailing wind from southwest, with speed categories in different colors.

Pollution Source Analysis

Identifies directions from which pollution events originate.

Wave Direction and Height

Ocean wave patterns showing dominant wave directions and heights.

Traffic Flow by Direction

Vehicle traffic volume by approach direction at an intersection.

Interpreting Wind Roses

Identifying Patterns

• Prevailing direction: Longest segments indicate most common direction
• Calm conditions: Center or small segments indicate low frequency
• Bimodal patterns: Two dominant directions (seasonal changes)
• Uniform distribution: Similar lengths suggest no prevailing direction

Common Patterns

• Monsoon pattern: Strong seasonal reversal (opposing directions)
• Trade winds: Consistent easterly or westerly flow
• Sea breeze: Diurnal cycle with alternating land/sea winds
• Mountain valley winds: Upslope/downslope patterns

Key Questions Answered

• What is the prevailing direction?
• How consistent is the direction?
• What is the frequency distribution?
• Are there seasonal or temporal patterns?
• What are the dominant magnitude ranges by direction?

Troubleshooting

Issue: All segments are the same size

• Solution: Check that magnitude/frequency column has variation, verify aggregation function is appropriate, ensure direction values are correctly assigned.

Issue: Directions don't align with expected compass orientation

• Solution: Adjust "Starting Angle" setting (90° for North at top), verify direction values follow meteorological convention (direction wind comes FROM, not going TO).

Issue: Too many or too few direction bins

• Solution: Adjust directional resolution in data preprocessing, group fine directions into broader categories (e.g., 16 directions to 8), or use more precise bins.

Issue: Categories are overlapping or unclear

• Solution: Reduce number of categories to 3-5, ensure non-overlapping bins, use distinct colors, add legend for clarity.

Issue: Chart is not centered or looks distorted

• Solution: Verify all directions are represented (even if zero), check for missing direction bins, ensure equal angular spacing.

Issue: Can't distinguish magnitude differences

• Solution: Use color categories to show magnitude ranges, enable gridlines for reference, normalize by maximum if outliers compress scale.

Issue: North is not at the top

• Solution: Set "Starting Angle" to 90 degrees (default), verify that convention matches your data (meteorological vs mathematical angles).

Issue: Labels are cluttered or overlapping

• Solution: Reduce label density (show only cardinal directions), increase chart size, disable labels and use hover tooltips.