【报告简介】  

This talk discusses a multi-scale data assimilation method for ocean and atmosphere geophysical fluid systems proposed by Kayo Ide's group at University of Maryland. The proposed approach explores a wide range of spatial and temporal scales of these geophysical fluid systems, it relies on multi-resolution sampled data obtained by a network of in-situ and remote sensing. The focuses of the talk are to address the filtering of multi-scale/resolution issues for data assimilation and to discuss the merits of the proposed mathematical and numerical assumptions and techniques and possible improvements. Numerical experiments will be presented to demonstrate the effectiveness of the multi-scale method and the multi-scale issues in the context of the global atmosphere numerical weather prediction will also be briefly discussed.