Global atmospheric general circulation models with simplified physics and boundary conditions are powerful tools that help us to understand fundamental climate dynamics and diagnose more comprehensive modeling systems.

Experimenting with simplified models is a valuable exercise for students, allowing insight into climate dynamics and experience with the modeling mechanics. While even simple models have some technical challenges, they also hold great potential for exploring climate dynamics in ways that are more accessible than with more complex modeling tools. Here, the authors introduce a global atmospheric model based on primitive equations with simplified physics that can be used for both educational purposes and original research in climate dynamics.

Abstract

We have implemented three distinct innovations. First, the underlying dynamic core is entirely based in Python (as opposed to Fortran with a Python wrapper), making the model more accessible to both undergraduate and graduate students. The model can easily be run on a laptop without concerns such as compiler options or operating systems, thus removing common technical barriers to access. Second, the background state can be specified within the same framework as “strong,” where the model equations have been modified into an anomaly model, or “weak,” where the original full-field model is relaxed to the background state. Third, the “forcing” is described in terms of prescribed latent heat release in the troposphere, the topography, and the background state. Forcing and resolution changes are easily implemented using one preprocessing script that supports a wide range of hypothesis-driven experimentation options. This paper includes an exploration of the model’s mean state, some sensitivity experiments, and an example diagnosis of ENSO teleconnections.

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