synthocean

📄 Description:

model2SWOT is an approach designed to interpolate model SSH (Sea Surface Height) data onto the SWOT (Surface Water and Ocean Topography) grid. Given a single daily model data, the script interpolates the SSH data onto a given SWOT swath.

Main Requered Inputs:

• model files containing SSH data.
• Model mask containing the longitude and latitude coordinates.
• SWOT data file containing the target longitude/latitude grid. It is recommended to use the "Expert" version of these files.
• Interpolator: The script offers two interpolation methods. Scipy interpolation method and Pyinterp interpolation method. Only one method can be chosen at a time, depending on user preference.

Other Inputs:

• latitude_var_name: The name of the latitude variable in the model dataset (e.g., "lat" or "latitude").
• longitude_var_name: The name of the longitude variable in the model dataset (e.g., "lon" or "longitude").
• time_name: The name of the time variable in the model dataset (e.g., "time" or "time_counter").
• model_ssh_var: The name of the SSH variable in the model dataset (e.g., "ssh" or "sossheig").
• time_index: The index of the variable time, must be an integer (e.g., 0 or 2 or 3).

By default, these variables are assumed to be named:

• latitude for latitude_var_name
• longitude for longitude_var_name
• time_counter for time_name
• ssh for model_ssh_var
• 0 for time_index Users should make sure to provide the correct variable names if their dataset uses different names.

🚀 Usage:

To use the tool, the user can clone the repository. Once the repository is cloned, the user can run the code in the model2SWOT/model2SWOT.py file, by executing the command line from a terminal using the following command (after navigating to the directory containing model2SWOT.py) :

./model2SWOT.py -m path_to_your_model_file -k path_to_your_model_mask_file -s path_to_swot_data_file -o path_to_output_file -i interpolator --model-lat-var latitude_var_name --model-lon-var longitude_var_name --model-time-var time_name --model_ssh_var the_model_ssh_variable_name --model_timestep_index time_index

Where: -m is the path to your model file containing the SSH data. -k is the path to your model mask file. -s is the path to the directory containing the SWOT data files. -o is the path to the output directory where results will be saved. -i specifies the interpolation method (choose between scipy_interpolation or pyinterp_interpolation).

⚡ Notes

• If the model mask and data are in the same file, you need to provide the path to this file twice — once for the data and once for the mask argument.
• Input file (model and mask) must be either a NetCDF or zarr file (.nc, .zarr).
• The output file must be a NetCDF file (.nc).

The tool is currently tested with eORCA25 and eNATL60 data in NetCDF and Zarr format.

The data needed for testing will soon be provided via link.

The tool will soon be available for installation via pip.

Tip

This code requires the use of the SWOT dataset, which is provided here

🐛 Issues and Contributions

If you encounter any issues or would like to contribute, please feel free to open an issue here.