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Wildland fire propagation

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feuxWildland fire is a global issue for all climates, from mediterannean region to boreal ecosystems with 3-4% of continental vegetal surface burning each year. The risk associated with wildland fire relates to crisis management (for instance, charte internationale Espaces et Catastrophes majeures), air quality due to high emissions in the atmosphere (carbon dioxide, nitrogen oxide, organic volatile components, aerosols, …), for example in the Prev’Air system.

➤ Wildland fire modeling is a complex question as it couples numerous physical processes at a large range of spatial scales (from local vegetation scale to meso-scale atmospheric dynamics). As of today, the ability to forecast large scale wildland fire remains limited: major uncertainties relate to the description of environmental (vegetation, geomorphology, meteoroloy) conditions as well as approximate description of interactions between vegetation, fire and atmosphere. These uncertainties translate into errors in the simulation of the fire intensity, the generation, the transport and the chemical evolution of plumes of smoke.

➤ The Wildland fire research project is part of the MODEST challenge. It is at the crossroads of transversal axis at CERFACS such as “Data Assimilation” and “Uncertainty Quantification”.



Developed in collaboration between CERFACS and the University of Maryland, FireFly is a data-driven front-tracking simulator based on the assimilation of thermal-infrared imaging data, with the goal of improving wildfire spread forecasting for public safety and environmental protection. An ensemble-based data assimilation algorithm allows to sequentially correct input model parameters (surface wind, humidity and description of the vegetation properties) in order to improve wildland fire propagation forecast.

➤ Improve the wildland fire behavior in terms of surface propagation as well as in terms of emissions released to the atmosphere.

➤ Develop ensemble-based data assimilation methods while limiting the computational cost, for instance using uncertainty quantification methods, especially for stochastic estimate of error statistics.

➤ In the long term : apply data assimilation methods to surface fire/atmosphere coupled systems (ex : FOREFIRE-MesoNH)


Simulation de la propagation d’un incendie sur un terrain complexe avec FIREFLY


Tools and Methods

The FIREFLY platform is developed in collaboration between CERFACS and the University of Maryland. FireFly simulates wildfire spread scenarios at regional scales. FireFly is a data-driven front-tracking simulator based on the assimilation of thermal-infrared imaging data, with the goal of improving wildfire spread forecasting for public safety and environmental protection. An inverse modeling strategy is applied, based on the assimilation of the fire front location. The idea underlying the ensemble Kalman filter (EnKF) strategy is to translate the differences in the observed and simulated fire front locations into a correction of the environmental parameters (ex: biomass fuel moisture content, near-surface wind) or directly of the simulated fire front location. FIREFLY relies on the OpenPALM software developed by CERFACS and ONERA to combine the propagation model and the data assimilation algorithm.



• 2015 : Application of FIREFLY to the FIREFLUX experiment (controled fire over 30 acres) in the framework of Cong Zhang’s PhD (UMD).

• 2014 :
Comparison of parameter and state estimation in analysis and forecast mode.

• 2013 :
Extension of FIREFLY to the treatment of fire propagation over complex terrain topography.

• 2012 :
Participation in the CTR Summer Program, Stanford University : Implementation of a polunomial chaos strategy in the framework of ensemble-based data assimilation.

• 2011 :
Application of FIREFLY to controlled fire at reduced scales in the framework of Mélanie Rochoux’s PhD (CERFACS/Ecole Centrale Paris)

• 2010 :
Preliminary developments of FIREFLY (M2 internship, M. Rochoux, CERFACS-UMD



 UMD (University of Maryland)



  • LEFE MANU/CHAT (EMIFIRE : a new submitted project in collaboration with LMD)
  • ANR (IDEA 2010-2014)
  • NSF (WIFIRE 2013-2016)





Tribute to Françoise Chatelin

Brigitte Yzel |  23 July 2021

  Tribute to Françoise CHATELIN   Virtual & Face to Face event @ Cerfacs 14 October 2021, CERFACS, Toulouse (France) 2 pm - 6.30 pm   Cerfacs is organizing a half scientific day on Thursday October 14, 2021 in tribute to Françoise Chatelin who left us prematurely on May 14, 2020   After graduating from the Ecole Normale Supérieure in Paris (1960-63), and her PhD in Mathematics at Grenoble University (1971) , Françoise Chatelin led with worldwide recognition her research in many areas, from spectral theory for linear operators in Banach spaces and finite precision to Dickson algebras. Professor Chatelin taught at the Universities Grenoble 2 - Pierre Mendès-France and Paris 9 - Dauphine before moving to Toulouse in 1996. She became Emeritus Professor in 2015. She was a visiting researcher at Berkeley and Stanford Universities, IBM San Jose (Ca) and Yorktown Heights (NY). For almost a decade, she was a scientific manager in Industry (in charge of intensive computing) first at the Centre Scientifique IBM France in Paris (1985 -1992) and then in the Central Research Lab of Thales (known as Thomson-CSF at that time) near Paris (1992-95). Françoise Chatelin was Head of the Qualitative Computing group at the Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique (Cerfacs) in Toulouse, France. Professor Chatelin has authored four books; the first three are now classic references available from SIAM. Her second book Valeurs Propres de Matrices (Masson, Paris, 1988) has received the IBM - France prize for « Best Scientific and technical publication 1988 ». Beyond her scientific contribution, Françoise Chatelin played a structuring role on research at CERFACS through multiple thesis on innovative topics. This event is devoted to the human and scientific tribute of her life. As a faithful image of the active and passionate woman that...Read more

CERFACS is involved in the NextSim project

CERFACS |  19 July 2021

The primary objective is to increase the capabilities of Computational Fluid Dynamics tools on extreme-scale parallel computing platforms for aeronautical design. The Kick-Off Meeting took place on 12 March 2021. This project has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement N° 956104. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and Spain, France, Germany. For more information, please visit  EuroHPC website : Project webpage :Read more