Seminar: An Introduction to Ionospheric Data Assimilation

Abstract:

In this talk I will introduce the basic principles constraining data assimilation (DA) and prediction for the ionosphere. First, I will go over what makes ionospheric prediction problems different from that of traditional numerical weather prediction. As an example, the fact that the ionosphere consists of charged particles means that they are modified by electric and magnetic fields, which leads to radically different correlation structures for the common field variables describing ionospheric winds and densities. Geostrophy is nowhere to be found! Next, I will introduce a simple, heuristic model we’ve recently developed that allows for a basic understanding of the governing principles controlling prediction and DA for the ionosphere. This model setup relies on the fact that the ionosphere is a strongly forced system governed by solar forcing from above, chemistry, and atmospheric forcing from below. We verify the efficacy of this heuristic model by comparing what it’s telling us about the ionospheric DA system with the Navy’s operational ionospheric model, which we run with an ensemble Kalman filter.