Using Python in Teaching Undergraduates NWP Concepts

Numerical weather prediction (NWP) models are vital tools to the 21^st century meteorologist, yet many undergraduates never fully understand how they work. This is at least in part due to the fact that many NWP concepts are rooted in high-level mathematical concepts not easily understood from simple derivation and statements of the relationships (e.g., Courant-Friedrichs-Lewy Criteria). To aid students in learning these important concepts a series of Python-based jupyter notebooks have been developed that can be used to demonstrate the concepts. In addition, the notebooks allow the students to change values to modify the behavior of the simplified system yielding different results. Currently, the following NWP concepts have been implemented: objective analysis (i.e., Cressman and Barnes schemes), time and space differencing, 1D physical parameterization schemes (radiation, surface energy balance, and boundary layer), and a barotropic model. This presentation will outline a few topics and how they are implemented in the jupyter notebook environment.