This dashboard delivers a comprehensive, data-driven overview of how climate factors, especially temperature and drought, drive wildfire frequency, severity, and risk across regions and seasons. Key metrics highlight recent record-breaking wildfire years, such as the 8.9 million acres burned in the US in 2020, and quantify the sensitivity of wildfire occurrence to temperature, with studies showing that a 1°C rise in daily temperature can increase fire starts by up to 22% and burned area by 25%. Detailed tables break down wildfire seasonality, showing how most fires cluster in peak dry months, and analyze fire duration and size, revealing that while most fires are small and short-lived, large fires can persist for days and cause outsized damage. Correlation analysis demonstrates that temperature is the strongest predictor of wildfire risk (correlation coefficients up to +0.91), followed by precipitation, humidity, wind, and soil moisture, while spatial risk indices illustrate how regions like Northern California face persistently high risk due to the combined effects of heat and drought. The dashboard synthesizes insights from satellite analytics, climate models, and peer-reviewed research, concluding that rising global temperatures and shifting weather patterns are amplifying wildfire risk worldwide, and that targeted monitoring of climate variables is essential for effective wildfire management and policy response.
Wildfire Climate Dashboard: Frequency, Temperature, and Risk
This dashboard tracks wildfire activity, seasonality, and climate drivers using recent analytics and satellite data.
See how temperature, drought, and weather conditions shape fire risk and outcomes in the US and globally.
See how temperature, drought, and weather conditions shape fire risk and outcomes in the US and globally.
US Wildfire Acres Burned (2020)
8.9M
Record-breaking year for area burned[1]
Change in Fire Frequency
-58%
Fewer fires vs. last year (global sample)[3]
Change in Area Burned
-63%
Smaller burned area vs. last year (global)[3]
Wildfire-Temperature Sensitivity
+22% / °C
More fires per 1°C rise (summer, US West)[4]
Wildfire Events by Month (Example: Australia, 2022)
| Month | Number of Fires | Dominant Fire Type | Notes |
|---|---|---|---|
| July | 8 | Grassland | Early season, mostly small events |
| August | 15 | Forest | Onset of peak fire season |
| September | 21 | Forest | Peak fire activity |
| October | 18 | Forest/Grassland | High winds, fast spread |
| November | 32 | Grassland/Forest | Most fires and largest burned area |
| December | 12 | Forest | Season tapering off |
Insight: Most wildfires in eastern Australia occurred in November 2022, with forest and grassland fires dominating. Seasonality is key for preparedness and resource allocation[3].
Fire Duration and Size Distribution (Global Sample)
| Fire Size (ha) | Median Duration (days) | Notes |
|---|---|---|
| <10 | 1 | Often lightning or small human-caused, quickly contained |
| 10-100 | 2 | May require more effort to suppress |
| 100-1000 | 3 | Can last several days, moderate suppression effort |
| >1000 | 5+ | Large, complex fires, often in remote areas |
Insight: Most fires last less than a day, but large fires (>1000 ha) can burn for five days or more. Early detection is crucial for reducing damage and cost[3].
Climate Variables and Wildfire Correlation
| Variable | Correlation with Wildfire | Direction | Key Findings |
|---|---|---|---|
| Temperature (°C) | +0.76 to +0.91 | Positive | Strongest single predictor; 1°C rise = 19-22% more fires[4][5] |
| Precipitation | -0.55 to -0.65 | Negative | Less rain = drier fuels, more fires[4][5] |
| Relative Humidity | -0.60 | Negative | Lower humidity increases risk[4][5] |
| Wind Speed | +0.40 | Positive | Higher winds spread fires faster[6][8] |
| Soil Moisture | -0.50 | Negative | Drier soils = greater fire risk[4][5] |
| Vapor Pressure Deficit | +0.55 | Positive | Drier air = more intense wildfires[4][5] |
Key Takeaway: Temperature is the strongest driver, but drought, low humidity, and wind are also critical. A 1°C increase in daily temperature can raise fire probability by 19-22% and burned area by 22-25%[4].
Spatial Wildfire Risk Index (California Example, 2020)
| Region | Annual Risk Level | Dominant Climate Driver | Notes |
|---|---|---|---|
| North California | Very High | Temperature, Drought | Most area burned in 2020; no "Very Low" risk zones[5] |
| Central California | High | Temperature, Wind | Frequent large fires, especially in dry years |
| South California | Medium-High | Wind, Urban Interface | Fewer but fast-moving fires, driven by Santa Ana winds |
Insight: In 2020, all regions of California faced elevated wildfire risk, with North California most affected due to higher temperatures and drought. No region had "Very Low" risk[5].
Summary and Insights
- Wildfire risk is strongly linked to temperature, drought, and humidity, with a 1°C rise in daily temperature increasing fire starts by up to 22% and burned area by 25%.
- Seasonality and spatial variation matter: most fires cluster in peak dry months and high-risk regions.
- Early detection and risk mapping are key for response and prevention. Satellite analytics now enable region- and time-specific planning[3][5].
Conclusion: Climate change is amplifying wildfire risk worldwide, making temperature and drought the most important variables for monitoring and management.
Sources:
[1] US EPA: Climate Change Indicators-Wildfires
[2] NOAA: Wildfire Climate Connection
[3] OroraTech: Wildfire Analytics Dashboard
[4] PMC: Wildfire Response to Changing Daily Temperature Extremes
[5] CARTO: Wildfire Risk Mapping
[6] AGU: Wildfires Temperature Estimation
[7] MDPI: Wildfire Prediction Model
[8] ScienceDirect: Forest Fire Dashboard
[1] US EPA: Climate Change Indicators-Wildfires
[2] NOAA: Wildfire Climate Connection
[3] OroraTech: Wildfire Analytics Dashboard
[4] PMC: Wildfire Response to Changing Daily Temperature Extremes
[5] CARTO: Wildfire Risk Mapping
[6] AGU: Wildfires Temperature Estimation
[7] MDPI: Wildfire Prediction Model
[8] ScienceDirect: Forest Fire Dashboard