Predicting the evolution of geophysical fluids ( atmosphere, ocean, continental waters ) is an important social issue especially for countries with a strong potential to undergo extreme natural events (tornados, typhoons, flood) with severe impacts on the economical and social activities).
These last decades strong improvements have been realized in modelling these flows and reliable models now exist for predicting natural catastrophes related to geophysical flows.
To produce a good forecast it is necessary to use all the available information (in situ or remote observations, statistics, images, ..) to retrieve the state of the environment at an initial date: the methods used to achieve this goal are known as Data Assimilation.
Implementing these methods is a complex task requiring an important amount of computational resources and consequently they could not be used in most of the developing countries because of their high computational cost. The dramatic change in the cost of computing will change this situation in a near future and we can think that for many countries modelling and prediction of natural disaster will become a reachable task. Nevertheless, previously a work of formation of scientist with a good knowledge of modelling and data assimilation is necessary.
The participants will be selected among doctoral students in Applied Mathematics or in Geophysics and also the admission will be opened to scientists having a post doctoral position in these domains.