Campuses:

Coping with Multi-scale and Balance in Data Assimilation

Monday, November 18, 2013 - 1:30pm - 2:10pm
Lind 305
Kayo Ide (University of Maryland)
Geophysical fluid dynamics exhibit a wide range of spatial and temporal scales that are partially balanced. Observations, consisting in-situ and remote-sensing, are sampled at multi-resolution. To assimilate spatially high resolution and sparse observations together, a data assimilation scheme must fulfill two specific objectives while taking balances taking into account. First, the large scale flow components must be effectively constrained using the sparse observations. Second, small-scale features that are resolved by the high-resolution observations must be utilized to the maximum degree possible. In this talk, we present a practical, multi-scale approach to data assimilation and demonstrate advantage of multi-scale approach over conventional data assimilation.