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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.

NEWS

NextSim General Assembly and TC meeting

CERFACS |  16 September 2021

The General Assembly and TC Meeting took place on 15-16 September 2021. CERFACS is involved in the NextSim project (). The primary objective is to increase the capabilities of Computational Fluid Dynamics tools on extreme-scale parallel computing platforms for aeronautical design. 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. This project has received funding from the Agence Nationale de la Recherche (ANR) under grant agreement N° ANR-20-EHPC-0002-02. For more information, please visit Read more


Sophie Valcke from Cerfacs co-authored a new book on atmosphere-ocean modelling

CERFACS |  18 August 2021

new book "Atmosphere-Ocean Modelling - Couling and Couplers” by Prof. Carlos R Mechoso, Prof. Soon-Il An and Dr Sophie Valcke has just been published by World Scientific. The present book fills a void in the current literature by presenting a basic and yet rigorous treatment of how the models of the atmosphere and the ocean are put together into a coupled system. Details are available at  Abstract: Coupled atmosphere-ocean models are at the core of numerical climate models. There is an extraordinarily broad class of coupled atmosphere-ocean models ranging from sets of equations that can be solved analytically to highly detailed representations of Nature requiring the most advanced computers for execution. The models are applied to subjects including the conceptual understanding of Earth’s climate, predictions that support human activities in a variable climate, and projections aimed to prepare society for climate change. The present book fills a void in the current literature by presenting a basic and yet rigorous treatment of how the models of the atmosphere and the ocean are put together into a coupled system. The text of the book is divided into chapters organized according to complexity of the components that are coupled. Two full chapters are dedicated to current efforts on the development of generalist couplers and coupling methodologies all over the worldRead more

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