Advances and Challenges in Wildland Fire Monitoring and Prediction
SessionInvited Talks - Shankar and Coen
Session ChairPaul Messina
Presenter
Event Type
Invited Talk
Applications
Architectures
Introductory
TimeThursday, November 17th11:15am - 12pm
LocationBallroom-EFGHIJ
DescriptionThe culture of fire suppression reveres tradition, standardized training, and organizational hierarchy. Yet, the past two decades have seen the infusion of technology that has transformed the understanding, observation, and prediction of wildland fires and their behavior, as well as provided a much greater appreciation of its frequency, occurrence, and attribution in a global context. These advances arose through cross fertilization from numerical weather prediction - reflecting advances in numerical weather prediction, data assimilation, and high performance computing - as well as new remote sensing instrumentation and platforms from satellite to unmanned aerial systems, mathematical algorithms, computer science, ecology, and the access to and interpretation of vast datasets on fires, fuels, and weather. This wave of technology has brought many goals within sight – rapid fire detection, nearly ubiquitous monitoring, and recognition that much of the distinctive characteristics of fire events are reproducible and perhaps predictable in real time. Concurrently, these more complex innovations raise new challenges, as only marginal improvement may be generated by further refinements in algorithms and model resolution; legal and safety considerations limit observations of dangerous phenomena and introduction of new technology; predictions face limits to predictability; and the complexity of identifying and forecasting the statistically rare megafire event among the 40,000–100,000 yearly wildfire events in the U.S., of which only a few percent will grow beyond a hundred hectares. This talk will highlight current research in integrated weather – wildland fire computational modeling, fire detection and observation, and their application to understanding and prediction.
