The Constrained Spectral Approximation Method (CSAM) is a physically sound and robust method for approximating the spectrum of subgrid-scale orography. It operates under the following constraints:
- Utilises a limited number of spectral modes (no more than 100)
- Significantly reduces the complexity of physical terrain by over 500 times
- Maintains the integrity of physical information to a large extent
- Compatible with unstructured geodesic grids
- Inherently scale-aware
This method is primarily used to represent terrain for weather forecasting purposes, but it also shows promise for broader data analysis applications.
See requirements.txt
NOTE: The Sphinx dependencies can be found in
docs/conf.py.
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The user-defined input parameters are in the inputs subpackage. These parameters are imported into the run scripts in runs.
A simple setup can be found in runs.idealised_isosceles. To execute this run script:
python3 ./runs/idealised_isosceles.pyHowever, the codebase is structured such that the user can easily assemble a run script to define their own experiments. Refer to the documentation for the available APIs.
GNU GPL v3 (tentative)
Refer to the open issues that require attention.
Any changes, improvements, or bug fixes can be submitted to upstream via a pull request.