RIOMAR → HEALPix (DGGS) regridding notebooks

This folder contains the end-to-end workflow to:

1. Define a Region Of Interest (ROI) from a lon/lat bounding box\
2. Prepare a temporary small Zarr dataset (for fast iteration and reproducible testing)\
3. Regrid variables to HEALPix using regrid_to_healpix (via xarray.apply_ufunc)\
4. (Later) Scale the same workflow to the full dataset on HPC and publish the resulting Zarr

The workflow assumes geographic coordinates in EPSG:4326 and HEALPix (WGS84) nested indexing.

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Workflow (recommended order)

A. Create ROI from lon/lat bbox

Notebook: Create_ROI_from_bbox.ipynb

Purpose - Convert a lon/lat bounding box (EPSG:4326) into a HEALPix (nested) ROI\

• Export parent-level cell IDs for fast indexing and masking\
• Export an outer boundary footprint (GeoJSON) for plotting and polygon masking

Input - Bounding box (min_lon, min_lat, max_lon, max_lat) in EPSG:4326\

• child_level\
• parent_level\
• edge_level

Output - HEALPix ROI cells at parent level: parent_ids.npz\

• Boundary footprint (for masking/subsetting before regridding): outer_boundary.geojson

Notes - The notebook computes child-level cells covering the bbox, then maps them to the parent level and builds polygons.

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B. Prepare a temporary Zarr (fast iteration dataset)

Notebook: Prep_regrid.ipynb

Purpose - Open RiOMar data via a Kerchunk catalog (HPC filesystem or HTTPS export)\

• Apply a spatial subset or mask using the ROI from step A\
• Write a lightweight Zarr locally (or on HPC scratch) to speed up development

Output - A temporary Zarr dataset (e.g. small.zarr) used as input for the regridding notebook

Tip - Set OUT_ZARR to an existing path on your machine or HPC scratch.

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C. Regrid to HEALPix using apply_ufunc

Notebook: regrid_apply_ufunc.ipynb

Purpose - Load the temporary Zarr created in B\

• Build the HEALPix operator once (from nav_lon_* / nav_lat_*)\
• Regrid selected variables with xarray.apply_ufunc\
• Align output to ROI-derived cell_ids (drop extra cells, fill missing with np.nan)\
• Save a HEALPix-aligned, chunked Zarr

Output - A HEALPix-indexed dataset with a cell_ids coordinate (nested indexing)

TODO - align may be better to be taken care of in the function used in apply_u_func..

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Scaling to HPC ("big scale" run)

(Documentation to be added.)

Planned publication target (once validated):

https://data-fair2adapt.ifremer.fr/riomar-zarr/small_hp.zarr

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Conventions / Expected Variables

• Geographic coordinates: nav_lon_*, nav_lat_* in degrees\
• HEALPix:
  • Nested indexing\
  • cell_ids coordinate\
  • level attribute (e.g. 13)\
  • WGS84 ellipsoid

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Troubleshooting

• ROI boundary "edge" artifact
  Increase edge_level in Create_ROI_from_bbox.ipynb.

• Memory spikes
  Write intermediate results to Zarr and rechunk. Avoid premature .compute() calls.

• Mismatch between stacked dims and ufunc core dims
  Ensure stack(point=(...)) matches input_core_dims=[["point"]].

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Extra notebooks

• Define_healpix_parent_chunk.ipynb
  Experiments on parent levels together with bounding boxes.

• simple_regrid.ipynb
  Tests alternative regridding methods available in regrid_to_healpix.

• Notebooks experimenting with Kerchunk creation and loading on Datarmor
  M1_Kerchunk_Create_Virtualizarr_Gamar.ipynb M2_Icechunk_Create_Virtualizarr_Gamar_withDask.ipynb M1_Kerchunk_Create_Virtualizarr_Gamar_withDask.ipynb M2_Icechunk_Use_Virtualizarr_Gamar.ipynb M1_bof_Kerchunk_Create_Virtualizarr_Gamar-MultiZarr.ipynb