Students (undergraduate & graduate) often find dynamics the most challenging course in their atmospheric sciences curricula. Traditionally the material is presented from a mathematical physics perspective, and student work comprises derivations and pencil-and-paper analytic problem sets. Over my three decades teaching this material, I have found that this approach is less and less successful in guiding students towards the important physical insights and predictive understanding.

In response, I have developed a set of simple Python modules, implemented in the Google Colab platform, through which students can explore core concepts in atmospheric dynamics, such as balanced flow, potential vorticity, and wave propagation. In accompanying assignments, students, observe the modeled behavior, write code to diagnose key quantities, and make predictions of the outcomes of numerical experiments (for example, what happens if the Coriolis parameter is changed).

Here I demonstrate one example, a simulation of the Rossby adjustment problem, and present associated assignments and assessments.

I plan to disseminate these modules via GitHub and Teach the Earth, in the hope that other instructors will adopt and improve them, and that they will be brought into sufficiently wide use that their efficacy can be meaningfully evaluated.