Assimilation of observations in numerical models of geophysical processes is becoming an increasingly more important component of geosciences. More and more observations (in particular, satellite observations, as well as all forms of tomographic observations) are 'indirect' observations, bearing on complicated combinations (often, integrals over some line in space) of the physical parameters to be estimated. The associated 'data retrieval' procedures are either an integral part of assimilation, or a necessary preliminary step preceding assimilation proper.
This session will be devoted to the presentation and discussion of methods for data assimilation, and more generally, for inverse problems, in ocean and atmosphere dynamics, remote sensing, solid earth geophysics, atmospheric chemistry, hydrology and in all fields of geophysics. The presentation and discussion of recent progress due to the use of data assimilation in geophysics will be of particular interest.
Special emphasis will be put on methods and recent developments of mathematical aspects of data assimilation and inverse problems, particularly in situations when a local linear hypothesis is not valid. Contributions dealing with algorithmic aspects and numerical implementation of data assimilation are welcome.