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Data Assimilation and Optimization

The development of data assimilation methods and optimization algorithms is of particular interest for applications in the Earth sciences, aerodynamics and space dynamics.

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Data assimilation deals with the problem of estimating model parameters or model state variables by combining prior estimates and observations, together with information about their uncertainties, in a statistically optimal manner. CERFACS has well-established data assimilation activities in oceanography, atmospheric chemistry, hydrology/hydraulics and wildfires, which are conducted in close collaboration with CERFACS partners, and leading operational centres and research institutes in forecasting and retrospective analysis.

cmaes_mean_meanOptimization concerns the development of numerical algorithms for solving diverse linear and nonlinear problems. It involves studying the properties of the algorithms, such as convergence and complexity, as well as improving their performance through preconditioning techniques. CERFACS develops derivative-based and derivative-free algorithms for a variety of applications including data assimilation, Earth imaging and aerodynamics design.

Accuracy, efficiency, scalability, robustness and practicability are important considerations when designing methods for data assimilation and optimization. To develop effective methods requires a good understanding of the underlying application and problem characteristics.

 

Applications in data assimilation :fig_da_website

Hydrology/hydraulics: Water resource management and flood risk monitoring associated with the dynamics of continental waters are of first importance for public safety and financial . Flood and inundation forecasting relies on numerical modeling tools for hydraulics and hydrology combined with a wide range of observations (in situ and spaceborne). CERFACS is developing in collaboration with EDF, CNES, SCHAPI, CNRM, …, variational and ensemble data assimilation methods based on hydrologic/hydraulic solvers (among whom MASCARET and TELEMAC-2D). These implementations are part of active research activities and of their transfer to operational level.

Wildfires: Real-time prediction of wildfire spread and emissions has been identified as a valuable rsearch objective with direct applications in both fire risk management, fire emergency response and fire-induced environmental impact in the context of climate change. The predictive capability for wildfire behavior at regional scales relies on a semi-empirical modeling of a propagating front (i.e. interface between burnt and unburnt areas) at land surface, which involves biomass, topographical and meteorological data that are embedded with uncertainties. CERFACS is currently developing in collaboration with UMD and SPE an ensemble-based data assimilation system named FIREFLY, in order to sequentially estimate input parameters and the simulated fire front position when fire front position observations are available and thereby to improve the forecast performance of fire spread models.

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NEWS

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

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