Funding Bolsters Fire Weather Forecasting
Recent funding has been allocated for the creation of dedicated fire weather teams, including leads and Warning Coordination Meteorologists (WCM). A fire meteorologist in training explained that this investment will improve the quality and specificity of forecasting available for fire responses. This reflects a growing emphasis on integrating specialized scientific support into fireground operations.
- A significant portion of the new funding comes from a $34 million investment through the Bipartisan Infrastructure Law, which will be distributed over five years to six universities to enhance wildfire behavior modeling and prediction. The receiving institutions are the University of Colorado, Colorado State University, the University of Maryland, the University of Wisconsin, Princeton University, and the University of Oklahoma. - The University of Oklahoma received $1.4 million of this funding for two major studies: "Probabilistic Fire Weather Guidance" and "Fire Weather Observation Analysis," conducted by its Cooperative Institute for Severe and High-Impact Weather Research and Operations. - A key initiative from this funding is the creation of the NOAA Fire Weather Testbed, headquartered at the Global Systems Laboratory in Boulder, Colorado, which will accelerate the transition of new forecasting technologies and applications to operational use. - The U.S. Forest Service is increasingly utilizing drones in wildfire response, with the number of drone flights jumping from 734 in 2019 to over 17,000 in 2024. These drones are used for tasks like creating thermal maps to identify hot spots, which allows for safer and more efficient dispatch of ground crews. - Researchers are developing "digital twin" technology for wildfires, which uses AI and machine learning to create high-resolution, real-time models of fire spread and smoke, aiming for a spatial resolution of 10-to-30 meters per pixel. - New AI-driven systems are being developed to forecast wildfire emissions weeks in advance, a significant improvement over current models that often assume the previous day's emissions will continue. This will enhance the accuracy of air quality and smoke trajectory forecasts. - In the Pacific Northwest, there is ongoing research to incorporate upper-air patterns into near-term fire danger models, which has been shown to improve the accuracy of subregional wildfire risk assessments. - Smoke forecasting models are rapidly improving, with NOAA's Air Quality Model (AQM v7) becoming operational in 2024 to provide hourly pollution forecasts, including from wildfires, up to three days in advance. For longer-range predictions, NASA's GEOS-FP model offers smoke forecasts up to ten days out.
