ocean-SR-data-preprocess

Converting NetCDF to NPY involves transforming high-resolution ocean NC files into split-ready NPY arrays. The pipeline preserves time and spatial structure, handling dynamic and static variables to prepare deterministic datasets for SR model training.

Yes, the NC to NPY conversion supports configurable dynamic variables (dyn_vars), mask variables (mask_vars), and statistical variables (stat_vars), allowing precise control over extracted ocean data features for SR model training.

Yes, the preprocessing pipeline supports deterministic dataset splits, ensuring converted NPY arrays divide consistently and reproducibly for reliable downstream SR model training and evaluation.

Use the quick data inspection scenario to examine static and dynamic variables in high-resolution ocean NetCDF files before committing to the full NC to NPY preprocessing pipeline.

Ensure reproducible preprocessing by utilizing the pipeline's deterministic dataset splits and optional date-naming conventions, which maintain consistent NPY output arrays across multiple runs.