February 10, 15:15, University of Potsdam,
Physics building, room 415
We address the general problem of estimating the state of a large spatio-temporally chaotic system from limited noisy data and a knowledge of a system model. For large systems, state estimation can be particularly challenging because straightforward application of the conventional technique may become infeasible due to computer limitations. This problem has very general interest, but is perhaps most evident in current weather forecasting. This talk will present background material, a proposed solution for treating large systems, and results from application of our method to weather and to a labortory experiment.