Articles | Volume 14, issue 11
https://doi.org/10.5194/nhess-14-2951-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/nhess-14-2951-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Towards predictive data-driven simulations of wildfire spread – Part I: Reduced-cost Ensemble Kalman Filter based on a Polynomial Chaos surrogate model for parameter estimation
M. C. Rochoux
CERFACS, 42 avenue Gaspard Coriolis, 31057 Toulouse Cedex 01, France
SUC/CNRS-URA1875, 42 avenue Gaspard Coriolis, 31057 Toulouse CEDEX 01, France
Ecole Centrale Paris, Grande voie des vignes, 92295 Châtenay-Malabry, France
EM2C/CNRS-UPR288, Grande voie des vignes, 92295 Châtenay-Malabry, France
S. Ricci
CERFACS, 42 avenue Gaspard Coriolis, 31057 Toulouse Cedex 01, France
SUC/CNRS-URA1875, 42 avenue Gaspard Coriolis, 31057 Toulouse CEDEX 01, France
D. Lucor
Institut d'Alembert, Université Pierre et Marie Curie, CNRS-UMR7190, 4 place Jussieu, 75006 Paris, France
B. Cuenot
CERFACS, 42 avenue Gaspard Coriolis, 31057 Toulouse Cedex 01, France
A. Trouvé
Dept. of Fire Protection Engineering, University of Maryland, College Park, MD 20742, USA
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- Inferring energy incident on sensors in low-intensity surface fires from remotely sensed radiation and using it to predict tree stem injury M. Dickinson et al. 10.1071/WF18164
- A reduced order model based on Kalman filtering for sequential data assimilation of turbulent flows M. Meldi & A. Poux 10.1016/j.jcp.2017.06.042
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- Selection justification of the wood pulp and crown combustion parameters for the calculation of the crown forest fires impact on Vietnamese energy facilities L. Tuan et al. 10.1051/e3sconf/202342004022
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Latest update: 23 Nov 2024
Short summary
This paper presents a data-driven wildfire simulator for forecasting wildfire spread scenarios at a reduced computational cost that is consistent with operational systems. A wildfire spread simulator combined with an ensemble-based data assimilation algorithm is indeed a promising approach to reduce uncertainties in the forecast location of the fire front and to introduce a paradigm shift in the wildfire emergency response.
This paper presents a data-driven wildfire simulator for forecasting wildfire spread scenarios...
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