Outline

We’re now ready to start implementing an assimilation. As a reminder, before we can run a Kalman filter, we will first need to (1) build a state vector ensemble, and then (2) combine the ensemble with forward models to generate proxy estimates. In this next lesson, we’ll design and build a state vector ensemble using the stateVector class. The lesson includes:

Concepts

The process of designing state vectors will involve some new vocabulary, so we’ll begin by introducing some concepts for the design process.

Indices

Next, we’ll take a quick look “under-the-hood” to illustrate how the stateVector class builds and selects different ensemble members.

Coding 4

Finally, we’ll move into the next open-coding session. We’ll examine some of the key methods in the stateVector class, and then use the class to build a state vector ensemble.