Jonathan D. Beezley1,2, Soham Chakraborty3, Janice L. Coen2, Craig C. Douglas3,5, Jan Mandel1,2, Anthony Vodacek4, and Zhen Wang4
1University of Colorado Denver, Denver, CO 80217-3364, USA
2National Center for Atmospheric Research, Boulder, CO 80307-3000, USA
3University of Kentucky, Lexington, KY 40506-0045, USA
4Rochester Institute of Technology, Rochester, NY 14623-5603, USA
5Yale University, New Haven, CT 06520-8285, USA
Abstract. We are developing a wildland fire model based on semi-empirical relations that estimate the rate of spread of a surface fire and post-frontal heat release, coupled with WRF, the Weather Research and Forecasting atmospheric model. A level set method identifies the fire front. Data are assimilated using both amplitude and position corrections using a morphing ensemble Kalman filter. We will use thermal images of a fire for observations that will be compared to synthetic image based on the model state.
Keywords: Dynamic data driven application systems, data assimilation, wildland fire modeling, remote sensing, ensemble Kalman filter, image registration, morphing, level set methods, Weather Research and Forecasting model, WRF