Physically Consistent Sampling For Ocean Model Initialization - Dataset

This dataset gathers all data and codes needed to reproduce the figures in Physically Consistent Sampling For Ocean Model Initialization, submitted to Tackling Climate Change with Machine Leurning NeurIPS Workshop 2025. (Paper link will be added upon acceptation). 

Description of the files: 

generated_npy_files.zip gathers the npy temperature and salinity fields generated by the diffusion model for the 4 different cases used in the paper: no conditioning, temperature and salinity conditioning, C1 conditioning and C2 conditioning.

model_weights.zip gathers the weights of the trained diffusion model used to generate the npy files. 

emp_climatology_1_4deg.nc is need to run a NEMO simulation with our parameters.

restart_files_1_4deg.zip contains all the restart files generated from the npy files and the following codes, and some reference restart files. 

Additionnally, the codes to produce the Figures can be found in the following repositories: 

https://github.com/Etienne-Meunier/DINO-Fusion/tree/dev-diffusion

https://github.com/Etienne-Meunier/Dinonline/tree/diffusion

The first link contains the code of the constraint diffusion model, the tutorial to create the restart files needed to run the NEMO simulation from the npy files and the code to plot the zonally averaged density figures both before and after NEMO simulation.

The second link contains the files and scripts that are needed to run nemo simulations with our parameters.