5240.03 07 — Special Topics in Oceanography: Data Assimilation
Prerequisites: None
Oceanographers and atmospheric scientists often have to deal with sparse, noisy observations. To make sense of such observations they often employ simplified representations of reality (i.e. models) which, by definition, are always wrong in some way. How do we extract the maximum information from inadequate observations and erroneous models? This module provides a review of data assimilation techniques as presently used in oceanography and atmospheric science. A common Bayesian framework will be used to fit the techniques into perspective, and also identify their strengths and weaknesses. Emphasis will be placed on the description of practical techniques that the students will be able to use in their future research.
