2011 Workshop: Student Tutorial on Data Assimilation

GOAL: Inform students about the basics of data assimilation, and explain step by step how each component (model, observation, principles of statistical inference) works together to yield an optimal analysis. We will also provide examples from specific applications to high-latitude ionospheric electrodynamics.

Topics:

• Fundamentals of data assimilation (Bayes’ Rule)
• Variance, correlation, and covariance
• Observations
• Background (empirical) models
• Roles of background and observational error covariance

This presentation will be offered at the “101 Level”, and will emphasize data assimilation techniques for the high latitude ionospheric electrodynamics that do not involve dynamical forecast models.

This joint workshop will be held primarily for the benefit of students but also anyone who is interested in learning basics of data assimilation and space science applications. The basics of data assimilation will be presented step-by-step, how each component (model, observation, principles of statistical inference such as Bayes's rule, covariances etc) works together to yield an optimal analysis. We will offer *three* 30-minute tutorial presentations that cover different DA applications in space sciences, ranging from the ionosphere and high-latitude ionospheric electrodynamics to the radiation belt.