Inverse Problems are encountered in most fields of the Geosciences, either for the purpose of prediction or inference. One class of inverse problems, in the context of predictability, is assimilation of observations in dynamical models of the system under study.

This session will be devoted to the presentation and discussion of methods for inverse problems and data assimilation, in ocean and atmosphere dynamics, solid earth geophysics, atmospheric chemistry, hydrology and, more generally, in all fields of geophysics.

We encourage reports on methods and recent developments of mathematical aspects of inverse problems, particularly in situations when a local linear hypothesis is not valid. Contributions dealing with algorithmic aspects and numerical implementation of the solution of inverse problems are welcome.

While prediction and inference in the geosciences are difficult in their own right, assessing uncertainty is proving to become more and more important. We specifically encourage contributions which quantify the uncertainty in inverse and data assimilation problems.