nextsim fully data-driven surrogate model
To install environment:
conda env create -f environment.yml
To activate the environment:
conda activate env
Original Files are download from nextsim NANUK outputs [1]. Those files are available through the SASIP github. link to neXtSIM outputs. Forcings were dowloaded from ERA5 file link
Dataset is build and save under netCDF file with make_dataset script.
python make_dataset.py
To build the dataset with a TFRecord architecture (), use make_tfrecord script
python make_tfrecord.py
Note, the dataset takes a susbstantial amount of place on disk: 360Go for the .nc file, 270Go as .tfrecords
The code is separated on two main section : data and src
- the data directory contains the code to build the dataset, once the original neXtSIM and ERA5 files are downloaded.
- the src file contains all the code to train the neurall network, and compute the test metrics.
To train the neural network:
python train.py
It takes around 18h on 1 GPU A100. All test metrics are computed with test.py and the Power Spectral Density is compute with
python compute_PSD.py
Code to plot the figure in the article is in the plot_article notebook.