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From 8 November 2021 to 10 November 2021

Data assimilation

nasri |  

Announced
Deadline for registration: 15 days before the starting date of each training
Duration : 3 days / (21 hours)

Before signing up, you may wish to report us any particular constraints  (schedules, health, unavailability…) 

at the following e-mail address : training@cerfacs.fr

Satisfaction index

 

In June 2019, 100% of participants were satisfied or very satisfied

(results collected from 5 respondents out of 5 participants, a response rate of 100%)

Abstract

Data assimilation is an important component of modelling in a number of applications in the geosciences and in engineering. This training course will provide an overview of the theory and practice of data assimilation. First, the basic concepts from statistical estimation theory and nonlinear optimization will be given. The classical variational and Kalman filtering approaches to data assimilation will then be described. The lectures will also touch upon more specialized topics including covariance modelling and estimation, advanced minimization algorithms, preconditioning, and hybrid ensemble-variational methods. The lectures on the theory will be complemented by both practical exercises and presentations on specific applications at CERFACS in the geosciences (oceanography, atmospheric chemistry, and/or hydrology/hydraulics).

Objective of the training

The objectives are to learn the key aspects of data assimilation, to understand the theory behind the methodologies, and to make the link with state estimation in the geosciences through specific applications.

Learning outcomes

On completion of this training you will be able to:

  • give a grounded opinion about advanced methods in data assimilation: variational assimilation, the Kalman filter, and their ensemble variants;
  • apply data assimilation and covariance modelling methods to simple problems;
  • appreciate the importance of and critical issues in data assimilation for real-world applications.

Teaching methods

The training is an alternation of theoretical presentations and practical work. A multiple choice question allows the final evaluation. The training room is equipped with computers, the work can be done in sub-groups of two people.

Target participants

This training session is for engineers, physicists, computer scientists and numerical analysts wishing to learn the fundamentals of data assimilation and the numerical methods to develop data assimilation applications.

Prerequisites and registration

In order to follow this course, you need to:

  • know basics methods in numerical linear algebra,
  • have a background in statistics and probability theory,
  • have level B2 of CEFR (training can take place in French or English depending on the audience)

To verify that the prerequisites are satisfied, the following questionnaires must be completed. You need to get at least 75% of correct answers in order to be authorized to follow this training session. If you don’t succeed it, your subscription will not be validated. You only have two chances to complete them.

Questionnaire 1 : Numerical Analysis

Questionnaire 2 : Statistical Analysis

After completing the pre-requisite tests and obtaining at least 75% correct answers, you can register:

Pre-registration

Referent teacher: Selime Gürol

Fee

  • Trainees/PhDs/PostDocs : 210 € excl. tax
  • CERFACS shareholders/CNRS/INRIA : 600 € excl. tax
  • Public : 1200 € excl. tax

Program

(Every day from 9h to 17h30)

Day 1:

Basic concepts and methodologies of data assimilation
Application from Earth sciences
Hands-on

Day 2:

Variational data assimilation
Covariance modelling and estimation
Hands-on

Day 3:

The Kalman filter and Ensemble Kalman filter
Hybrid ensemble-variational methods
Application from Earth sciences
Hands-on

Evaluation of learning

A final exam will be conducted during the training.

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