We are working on advanced mathematical modeling and information technology in the area of Dynamic Data Driven Application Systems, to help fight and manage wildfires. Here is project summary.
The purpose of the project is to provide a continously updated prediction how the fire will move in the next few hours or days and to predict the likely effect of firefighting strategies. Such technology in the field might save lives and property both in fighting fires and by better control of prescribed burns.
This is a research project which will culminate in a field demo in Summer 2009. This will be a proof of the principle demo, not yet an actual use in the field, though we of course hope that our results will be used in the field in the future.
The mathematical model of fire and weather was developed at NCAR earlier, based on the Clark-Hall atmospheric code. The fire model is based on propagation of the fireline curve in the normal direction and exponential decay of fuel. We have now developed a new code that implements this validated fire model using a level set method. The new code is suitable for data assimilation (modification of its state by new data). We are in the process of coupling the new fire code with WRF, which is a de-facto standard in weather modeling, and with our data assimilation code.
We are developing mathematical and statistical methods to update predictions by injecting data into a model continously and we have tested them on simplified mathematical models. Our new morphing filter, which combines correction to position with correction to intensity of physical fields is particularly promising. We work on information techology to manage the different kinds of data that will be coming in the weather/fire application and adding software components for injecting the data into the existing software. We are also developing a new fire model based on reaction-diffusion partial differential equations.
Next comes reanalysis of an actual wildfire from observed data and injecting
data into a weather-fire model that will run continuously on our local
computers for the mountains near
Stabilized data assimilation into a fire model
Simulations of wildfire coupled with a mesoscale weather model (Janice Coen)
Forest Fire Imaging Experimental System (Tony Vodacek)
Fire on the Mountain! Run,
Boys, Run! Sensors Online, September 2004
Researchers Receive Funds to Create High-tech Wildfire Fighting Solutions Press
release, April 15, 2004, UCD, UCAR,
NSF
Real-time
'Movies' Will Predict Wildfire Behavior For One Hour Science Daily,
September 26, 2003
$300K
grant continues remote-sensing research News and Events, RIT, September 25,
2003
Natural Hazards
Observer, University of Colorado at Boulder, November 2003
Lynn S.
Bennethum, University of Colorado at
Denver
Janice L. Coen,
National Center for Atmospheric Research
Craig C. Douglas, University of Kentucky
Leopoldo P. Franca, University of Colorado at Denver
Craig Johns, University of Colorado at Denver
Robert Kremens, Rochester Institute of Technology
Jan Mandel, University of Colorado at Denver
Anthony Vodacek, Rochester Institute of Technology
Guan Qin,
Texas A&M University
Wei Zhao, Texas A&M University
This project was funded by the National Science Foundation under these grants:
ITR/NGS:
Collaborative Research: DDDAS: Data Dynamic Simulation for Disaster Management,
Lead PI Jan Mandel, 2003-2008
University of Colorado at Denver 0325314
Rochester Institute of Technology 0324989
Texas A&M University 0324988
University of Kentucky 0324876
National Center for Atmospheric Research 0324910
CSR-CSI:
Collaborative Research: Dynamic Sensor/Computation Network for Wildfire
Management, Lead PI Craig
University of Colorado at Denver 0719641
Rochester Institute of Technology 0719626
University
of Kentucky 0720454
Data Assimilation
in Atmospheric Sciences, PI Jan Mandel, 2007-2008
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