15.3 Identifying Optimal Weather Conditions for Prescribed Fires in California

Thursday, 16 January 2025: 2:15 PM
202 (New Orleans Ernest N. Morial Convention Center)
Rochelle P. Worsnop, NOAA, Boulder, CO; and A. J. Hoell, M. L. Breeden, K. Blankenship, T. B. Chapman, Z. Tolby, B. J. Hatchett, and K. C. Short

The United States (US) Forest Service developed an ambitious national strategy, “Confronting the wildfire crisis: A 10-year implementation plan,” to reduce wildfire risk over 10 years beginning in 2022. The plan’s focus is an unprecedented treatment of up to 50 million additional acres of hazardous fuels, including through the use of prescribed fire to create more wildfire-resilient forests and communities. Quantifying when and where prescribed fire-weather criteria have been met in the past may give decision-makers better insight into the number of “good” burn days that they could typically expect during each season, helping them make preparations to reach annual prescription goals. In this presentation, we define a range of prescription criteria for local fire-weather and fire-indicator variables associated with a subset of successful prescribed fires from 2011–2022 within Geographic Area Coordination Centers (GACCs) across California (CA) and Arizona (AZ). This subset comes from a new prescribed-fire database developed by The Nature Conservancy; the novel dataset is based on issued burn permits of prescribed fires ignited on all lands (federal, tribal, state, and private) across 11 western states. For CA and AZ GACC regions, we examined the seasonality and frequency of occurrence of the prescription criteria for two prescribed fire types: pile and broadcast. We found that prescribed burns, especially pile burns, are regularly ignited multiple days in a row indicating a need for predictable windows-of-opportunity of these favorable conditions. Therefore, we also identify composites of the synoptic-scale weather patterns during which these prescribed fires occurred. Given the slower-evolving nature and better representation of these large-scale patterns within numerical forecast models, they may provide decision support for enhanced resource planning leading up to potential burn windows-of-opportunity weeks into the future.
- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner