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DDM- Data Assimilation and Optimisation

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.

Optimization 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.

The current actions in Data Assimilation at CERFACS are organized in actions :

  • Develop advanced algorithms for variational and ensemble-variational DA
  • Develop advanced methods for modelling and estimating error covariances
  • Develop ensemble generation and surrogate model methodologies for DA
  • Improve and extend the use of in situ and remotely-sensed data in DA

These actions are implemented on Use Cases

  • Use Case #1: Extending methodologies in variational and ensemble-variational DA: Accounting for nonlinearity; model error estimation & representation; preconditioning; developing robust minimization for extreme-valued observations. Implementation & evaluation in OOPS-based and other systems.
  • Use Case #2: Development of flexible and efficient covariance models for B: multi-variate; accounting for rotational anisotropy in correlations; multi-scale; ensembles; localization; SPDEs; preconditioning; hybrid; coupled; estimation procedures; MLMC. Implementation & evaluation in OOPS-based systems including NEMOVAR for ocean DA, and other systems.
  • Use Case #3: Development of flexible and efficient covariance models for R: unstructured meshes; SPDEs; FEMs; 2D, 3D and 4D (space + inter-channel + time); R-1; preconditioning; estimation procedures. Implementation & evaluation in existing Matlab framework and OOPS-based systems.
  • Use Case #4: Development of efficient ensemble-based DA: Ensemble generation & validation methodologies; surrogate models for stochastic covariance estimation. Development for hydraulics, wildfire & pollutant dispersion.
  • Use Case #5: Assimilation of satellite and image data: high-resolution altimeter (SWOT) and SST; high-resolution & hyper-spectral sounders (IASI); patterns/fronts. Developments for hydraulics & hydrology, ocean, atmospheric chemistry, history matching and wildfire applications.

NEWS

Catherine Lambert awarded Officer in the national order of Merit

Brigitte Yzel |  31 May 2022

Catherine LAMBERT, President of Cerfacs, has been promoted to the grade of officer in the national order of Merit, on the proposal of Mrs. Frédérique Vidal, Minister of Higher Education, Research and Innovation. Antoine PETIT, President and CEO of the CNRS, presented the insignia to Catherine LAMBERT during a ceremony that brought together many actors from the space, aeronautics, environment and digital sectors. Antoine PETIT: "Catherine's interpersonal skills, her ability to step back and understand very different environments (research, industry, politics) in order to develop a collective vision are the hallmarks of her career. Catherine is one of those people with whom you naturally feel confident, with whom you want to build something that goes beyond all of us to go further. With this honor, the Cerfacs teams are also rewarded.Read more


Sparse Days in Saint-Girons IV

Brigitte Yzel |  29 March 2022

Sparse Days Meeting 2022 🗓️  20-22 June 2022  @ Saint-Girons, France   🌐   Sparse Days 2022 will be held in Saint-Girons, Ariège, from 20-22 June. This enhanced version of Sparse Days is being co-organized by Cerfacs and ENSEEIHT/IRIT. It will be the fourth meeting in Saint- Girons following the tradition of the previous meetings held in 1994, 2003, and 2015. The tradition involves coupling our highly successful annual technical meeting with the ambience and hospitality of this wonderful Pyrenean town which encourages fruitful informal exchanges between participants.    Read more

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