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- Title
Performance of Fire Danger Indices and Their Utility in Predicting Future Wildfire Danger Over the Conterminous United States.
- Authors
Yu, Guo; Feng, Yan; Wang, Jiali; Wright, Daniel B.
- Abstract
Predicting current and future wildfire frequency and size is central to wildfire control and management. Multiple fire danger indices (FDIs) that incorporate weather and fuel conditions have been developed and utilized to support wildfire predictions and risk assessment. However, the scale‐dependent performance of individual FDIs remains poorly understood, which leads to large uncertainty in the estimated fire sizes under climate change. Here, we calculate four commonly used FDIs over the conterminous United States using high‐resolution (4 km) climate and fuel data sets for the 1984–2019 period. The relationships of these four FDIs to the observed wildfire sizes show that higher values of FDIs correlate to larger total fire sizes; this correlation is more robust at larger spatial scales. Sensitivity analysis indicates that the daily minimum relative humidity and precipitation are the most important drivers of the annual mean fire danger. In the instances of extreme fire danger, wind speed becomes a critical factor and should be considered in the calculation of the FDI. To assess the impact of climate change on future fire size, we calculate the present‐day and end‐of‐century FDIs using the 12 km regional climate model simulations. The four FDIs generally predict consistent changes in future fire potential, suggesting an overall higher fire potential in conjunction with a prolonged wildfire season in future climate. Regionally, the four FDIs also reveal similar seasonal patterns as the enhancement arises mostly in spring and summer over the southwest US while in summer and fall over the northern and eastern US. Plain Language Summary: Fire danger index (FDI), a measure used to assess the risk and severity, relies on a combination of weather and fuel conditions. Multiple FDIs have been frequently used to predict and manage the risk of wildfire. However, it is unclear how well these indices work at different scales, causing uncertainty in predicting the likelihood of fire ignition and the potential size of a fire. Here, we analyzed four commonly used FDIs and conducted sensitivity analysis (SA) to determine their most important drivers. SA results indicate that daily minimum relative humidity, precipitation, and wind speed as the most important drivers. In addition, FDIs highly correlate with total fire size at annual and conterminous United States (CONUS) scale and such correlation decreases at finer spatial and temporal scales. We also used a regional climate model simulation to derive FDIs for current and future climate conditions. Our results suggest an overall increase in fire potential and a prolonged wildfire season in the future climate. Moreover, the enhanced fire frequency is projected to occur in spring and summer over the southwest US whereas in summer and fall over the northern and eastern CONUS. Key Points: The correlation between fire danger indices (FDIs) and observed wildfire size are scale dependentSensitivity analysis indicates that the daily minimum relative humidity and wind speed are the most important drivers of fire dangerCoupling FDIs with regional climate model simulation show higher fire potential in US in future climate
- Subjects
UNITED States; WILDFIRES; FIRE risk assessment; WILDFIRE prevention; WEATHER; ATMOSPHERIC models; SPRING; WIND speed
- Publication
Earth's Future, 2023, Vol 11, Issue 11, p1
- ISSN
2328-4277
- Publication type
Article
- DOI
10.1029/2023EF003823