Since 2000, U.S. wildland fire suppression has cost more than $2 billion per year (2012 dollars). The economic impacts from natural resource loss, land rehabilitation, and lost business and recreation are far greater—as much as 10 to 50 times the fire suppression costs, according to some economists. Studies suggest that U.S. fire seasons as damaging as 2012’s could occur two to four times more often by midcentury. One example: Colorado’s most destructive fire on record struck near Colorado Springs in June 2013, killing two people and destroying more than 500 homes. Among the factors involved are
Wildland fires can degrade air quality for days to weeks across large areas, affecting the health of thousands of people located far from the flames. After a fire, flooding and water quality threats increase.
Models that simulate weather-and-fire interaction. NCAR develops, maintains, and supports two public-domain computer models that combine weather simulation with fire behavior, thus capturing not just wildfire response to environmental conditions but also how fires create their own weather. The models allow scientists to reproduce destructive fires and analyze the unique characteristics of each one. They are also being used as prototype forecasting systems to predict where and how quickly a particular wildland fire might grow during its lifetime. Fine-scale simulations can also shed light on extreme behaviors that can threaten firefighters and cause fires to grow especially rapidly, such as fingers of flame shooting well ahead of a fire’s core area.
Measuring smoke and chemical emissions from fire. A satellite-borne instrument based at NCAR has been measuring the global spread of carbon monoxide from wildfires and other sources for more than a decade. An online resource at http://www2.acd.ucar.edu/acresp provides observations from the MOPITT instrument, global fire emissions data using other satellite products as inputs, as well as global forecasts of atmospheric composition. NCAR also maintains a suite of high-end instruments (ground- and aircraft-based) to gather precise data on airborne chemicals and air quality for field campaigns and other focused observations.
Improving air quality and fire growth predictions. NCAR is a leader in data assimilation—incorporating diverse types of observations into forecast models to improve their skill. Researchers are developing techniques to integrate data collected by satellites, aircraft, and remotely piloted vehicles. Using such tools, NCAR carries out post-event analyses of the impacts of fires on air quality and health. These impacts models do not yet predict fire behavior. Coupling the two capabilities would create the capacity to predict wildfire impacts on air quality over periods of a few days. Simulations of large wildfires are being improved using new active fire detection via satellite monitoring and airborne fire mapping data.
Air quality modeling:
NSF (core funding, interdisciplinary grants, CISE support), NASA, FEMA
Seeking additional funding for the following goals:
Colorado Department of Public Health and Environment
USDA Forest Service
University of Maryland