Scientists Turn To The Sky To Forecast Wildfires

Weather Forecasting NOAA Satellites Used To Improve Data Accuracy

By Kendra Pierre-Louis on November 16, 2013 6:51 PM EST

Marion Doss
Marion Doss

Fighting fires is a tough job, and fighting wild fires is no exception. While urban fire fighters have to deal with collapsing roofs, and gun-toting civilians, wild land firefighters have to deal with falling trees, shifting winds, variable terrain, and fire systems so large they can occasionally form their own weather systems. This constantly shifting landscape makes it difficult for firefighters to effectively fight fires and to stay safe. Earlier this year 19 members of the elite Granite Mountain Hotshot crew died in a Yarnell, Ariz. wildfire when a wind event combined with hot dry conditions fenced the team in leaving them no escape route.

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Attempts to accurately predict a wildfire's path have proven unreliable. Existing modeling techniques remain accurate for roughly half a day at best, providing a limited benefit to fires that can blaze for days, even weeks.

The problem with existing models is in finding ways to update the models with new, information about a fire's evolution, which would allow the model to correct the inconsistencies that can build up over time. This problem may have disappeared, however, this week when scientists from Colorado's National Center for Atmospheric Research (NCAR) in Boulder, in partnership with the University of Maryland, unveiled a new predictive model that may aid in future battles against wildfires.

According to Janice Coen, an NCAR scientist who led the team, the models were improved by looking upwards. Specifically, the team looked to the Suomi NPP, a weather satellite operated by the National Oceanic and Atmospheric Administration. The Suomi NPP carries a special infrared sensor capable of capturing high resolution images at a much finer scale than your typical satellite sensor. This is exactly the kind of data, in conjunction with forestry data on monitoring fuel impacts and terrains on wildfires that can make predictive models more accurate. Further, since the Suomi NPP is in sun-synchronous orbit with the Earth, it passes over the same spot on earth twice a day allowing it to feed updated data into the models effect providing a consistent source of data for regular mid-course-corrections.

The model was tested retrospectively against last year's three week long Little Bear fire in New Mexico. The results were promising enough that the team is currently working with national firefighting team to modify their methods to meet the on-the-ground needs of firefighters. The team hopes to release a practical model next year.

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