Minisymposium on
Recent Progress in Atmospheric Data Assimilation and Retrieval

Summary: Modern atmospheric data assimilation and retrieval constitute an important application of variational methods and optimal control theory. Model variables in a prediction model are obtained by minimizing their departure from observations, subject to dynamical constraints (e.g., the equations of motion). Recently, many theories have been developed to save computation times and to apply to complex problems including microphysical processes. In view of the increasing resolution of operational numerical weather prediction systems and the ever present need to improve prediction of hazardous small-scale weather events, the scope of the minisymposium will include methods appropriate for short-range prediction as well as for traditional medium- and longer-range prediction. Suitable topics include 3D and 4D variational techniques, use of adaptive observations, and use of satellite and Doppler radar data.

Purpose: The proposed minisymposium is broadly concerned with the theory of atmospheric data assimilation and retrieval techniques. Obtaining the optimal initial conditions through these techniques is one of the major factor to improve weather forecasting using numerical prediction models. As seen in the titles, major topics of our minisymposium presentations are highly related to the conferences themes, especially to optimization, atmospheric modeling, multiscale phenomena, and multiphysics aplications. In addition, these techniques can be applied to any optimization problems in general areas of geosciences.

Audience: The intended audience is those interested in atmospheric data assimilation per se or as an illustrative application of variational methods and optimal control theory to an applied problem (in this case one having profound societal relevance).