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After working for more than a decade to tackle the challenges, NCAR and its research partners have developed the capability to build two new prediction systems — one for wildfires and one for floods. The systems can provide public safety officials with detailed, 12- to 24-hour predictions of these destructive disasters. The fire prediction system can also help guide tactics for prescribed burns. TO PREDICT WILDFIRES, scientists use a cutting-edge computer model developed at NCAR (CAWFE, the Coupled Atmosphere-Wildland Fire Environment) that simulates how weather drives fires and, in turn, how fires create their own weather. By restarting the model every 12 hours with the latest observations of the fire extent, including satellite data, scientists can issue 12- to 24-hour forecasts and update them regularly, as needed, for a long-lived fire. TO PREDICT FLOODS, scientists have built a system that relies on radar and stream gauge data, highly detailed computer model weather forecasts, advanced streamflow computer simulations, and a variety of statistical techniques. With detail never offered before, the system offers the potential to provide locally specific guidance for decision makers during the crucial 1-to 12-hour window, when there is still time for people to seek safety and for emergency management tools to be deployed. To create the flood prediction system, NCAR scientists worked with colleagues at the National Oceanic and Atmospheric Administration’s Earth System Research Laboratory, NASA, the Department of Energy, the Department of Defense, and partner universities. Updated March 20, 2015. NCAR is sponsored by the National Science Foundation. LEARN MORE Wildfire prediction: http://www2.ucar.edu/atmosnews/news/1... Flood prediction: http://www2.ucar.edu/atmosnews/perspe... (©UCAR. Video produced for NCAR/UCAR by Ryan Budnick, Legacy Mediaworks.) The University Corporation for Atmospheric Research manages the National Center for Atmospheric Research under sponsorship by the National Science Foundation. Any opinions, findings and conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.