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Data assimilation (DA) aims at determining as accurately as possible the state of a dynamical system by combining heterogeneous sources of information in an optimal way. Generally speaking, the mathematical methods of DA describe algorithms for forming optimal combinations of observations of a system, a numerical model that describes its evolution, and appropriate prior information. DA has a long history of application to high-dimensional geophysical systems dating back to the 60s, with application to estimation of initial conditions for weather forecasts. It has now become an intensive field of research, with applications in oceanography and atmospheric chemistry, and extensions to other geophysical sciences. DA is now a key issue in most numerical forecasting systems in geophysics. Because of the high dimensionality of these systems (in meteorological applications, up to 109 variables at present, and 107 scalar observations per 24-hour period), the mathematics employed should be relatively simple. However, it has been proven in operational meteorology that the use of advanced methods such as optimal control theory could improve data assimilation systems significantly. Since then, the DA community has contributed to both the applications on very high-dimensional and possibly operational systems, and at the same time to methodology.

Objectives of the school

In this context, this 3-week summer school will be strongly focused on methodology. However it will not ignore the applications' side since applications motivate and specify the kind of methodology is needed. The school will not be an introduction to data assimilation, but an advanced school, attended by students and young scientists with previous experience in data assimilation. A book of proceedings will be published, which will contain contributions from all speakers.

Attendees

This school is intended for a broad international audience: PhD students in their final year, postdoctoral scientists, and maybe young academics, for a total of 55 attendees, not including the speakers and organizers. The attendees will have a background in meteorology, oceanography, atmospheric chemistry, and/or applied mathematics, and will have some previous experience in DA.

Scientific direction

É. Blayo (University of Grenoble), M. Bocquet (École des Ponts ParisTech), E. Cosme (University of Grenoble)

Scientific advisory committee

C. Snyder (NCAR, Boulder), O. Talagrand (CNRS, Paris), J. Verron (CNRS, Grenoble)