The current work on WRF-Fire is a part of the NSF CDI Wildland fire modeling E-community project. The main goal of this project is to bring together multiple wildland fire models and data assimilation with web-based controls and visualization.
The primary purpose of the Gross cluster is to serve this project, which has provided a majority of the funding.
The ultimate objective is to build a real-time wildfire modeling system with data assimilation, i.e., adding new data as the model is running and the wildfire is in progress.
- Data assimilation - the Osimorph project
- new FFT-based methods
- new "morphing" methods for position correction
- Wildfire modeling - the WRF-Fire software
- Jan Mandel, Jonathan D. Beezley, Janice L. Coen, and Minjeong Kim, Data Assimilation for Wildland Fires: Ensemble Kalman filters in coupled atmosphere-surface models, IEEE Control Systems Magazine 29, Issue 3, June 2009, 47-65 arXiv:0712.3965
- Jonathan D. Beezley and Jan Mandel, Morphing Ensemble Kalman Filters, Tellus 60A, 131-140, 2008 arXiv:0705.3693
- Jan Mandel, Lynn S. Bennethum, Jonathan D. Beezley, Janice L. Coen, Craig C. Douglas, Minjeong Kim, and Anthony Vodacek, A wildland fire model with data assimilation, Mathematics and Computers in Simulation 79, 584-606, 2008, article, CCM Report 233 June 2006 revised January 2008
- Nina Dobrinkova, Georgi Jordanov, and Jan Mandel, WRF-Fire Applied in Bulgaria, Proceedings of 7th International Conference on Numerical Methods and Applications - NM&A'10, August 20 - 24, 2010, Borovets, Bulgaria. arXiv:1007.5347, July 2010. Accepted.
- Jan Mandel and Jonathan D. Beezley, An Ensemble Kalman-Particle Predictor-Corrector Filter for Non-Gaussian Data Assimilation, Proceedings ICCS 2009, Lecture Notes in Computer Science 5545, Springer, 2009, pp. 470-478. Also available at arXiv:0812.2290.
- Jan Mandel, Jonathan D. Beezley, and Volodymyr Y. Kondratenko, Fast Fourier Transform Ensemble Kalman Filter with Application to a Coupled Atmosphere-Wildland Fire Model. Anna M. Gil-Lafuente, Jose M. Merigo (Eds.) Computational Intelligence in Business and Economics (Proceedings of the MS'10 International Conference, Barcelona, Spain, 15-17 July 2010), World Scientific, pp. 777-784. Also available at arXiv:1001.1588.