If you are still with us - thank you! Just as the title of this course reflects:
Learning Numerical Weather Prediction with CPAS: Theory, Practice and Visualization
You learned using the CPAS online platform to conduct numerical weather prediction hands-on. The CPAS model’s additional features, HTS and CUMG, try to control the computational resource to spend for specific atmospheric simulation purposes like using high resolution for a local area out of a global model. While the theories for NWP are vast and deep, this course touches only some glimpses of theories for explaining the stability condition that directly affects computational cost. Learners are advised to seek more sources for learning NWP more completely.
Given a software implementation of an atmospheric model, users of the model have to understand what model options are available to use practically. For the variable-resolution model MPAS-A, on which CPAS is based, the options are mostly on mesh selection/design and physics parameterization schemes. This course introduced the MPAS-A/CPAS unstructured grid, and some basic knowledge of physics parameterization. This provides the background for a new user of CPAS to understand what he or she is using.
A significant port of the course is on the NetCDF files containing the model data, and using python libraries to do plotting, data manipulation, visualization and analysis. These are indeed practical skills needed by students and workers in the field, who spend a lot of time handling data and plotting.
Putting all the above together, I hope this course is beneficial to your curiosities in numerical atmospheric modeling, as well as career development if you are entering a related profession or industry.
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