Here, we explain how to prepare your dataset for this project.
-
Select the time period that you would like to share with us.
- If your simulation includes the year 2024, please include it.
- Otherwise, it would be best to select a neutral year (i.e. a year without extreme events).
Important
If you contribute with more than 1 year, please prepared one dataset for each year
- Interpolate your simulation outputs onto SWOT grid, using Synthocean.
- When interpolating the SWOT grid, if the year 2024 is not available, assume that the selected year corresponds to 2024 (using the dates closest to SWOT)
Important
To avoid spectral artifacts when using synthocean, please select the scipy interpolation option (scipy_interpolation).
./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 scipy_interpolation --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
- Please organize the files into separate folders for each cycle. Each folder should be named using cycle_XXX format, where XXX represents the three-digit cycle number (e.g., cycle_008, cycle_012).
Note
We expect to have a specific directory format and naming convention for each model output:
MODELNAME/cycle_(cyclenumber)/MODELNAME_GRID_L3_LR_SSH_(cyclenumber)_(passnumber)_(STARTDATE)_(ENDDATE)_v1.0.2.nc
(which is the same SWOT files format)
- Share your model data interpolated on SWOT grid through a S3 endpoint.