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license: other
pretty_name: DepthDif GeoTIFF raster and aligned ARGO dataset
tags:
- oceanography
- argo
- glorys
- ostia
- sea-level
- sea-surface-salinity
- geotiff
- zarr
configs:
- config_name: profile-index
data_files:
- split: profiles
path: indices/profiles.parquet
- split: variables
path: indices/variables.parquet
---
# DepthDif GeoTIFF Raster and Aligned ARGO Dataset
This dataset package contains the model-ready DepthDif GeoTIFF raster store and
the enriched ARGO profile Zarr used to create it.
## Dataset Overview
<p align="center">
<img src="assets/figures/depthdif_schema.png" width="85%" alt="DepthDif dataset and model overview" />
</p>
## Layout
```text
assets/
figures/depthdif_schema.png
data/geotiff_dataset_random100_surface.png
data/argo_on_glorys_grid_3D.gif
data/profile_comparison_good_alignment.png
data/profile_comparison_bad_alignment.png
rasters/
glorys/thetao/
glorys/so/
ostia/analysed_sst/
sealevel/adt/
sss/sos/
sss/dos/
argo/
argo_profiles_on_grid.zarr/
data/
argo_glors_ostia_ssh.zarr/
indices/
profiles.parquet
variables.parquet
metadata/
dataset_description.json
citation.cff
stac-item.json
examples/
open_with_xarray.py
subset_by_region_time.py
manifest.yaml
masks/
```
The `rasters/` directory is intentionally at the repository root. It contains
the aligned uint8 GeoTIFF products used by the pixel-space dataloader. The
compact `argo/argo_profiles_on_grid.zarr` store is the grid-indexed ARGO input
used by that dataloader.
The package intentionally contains two ARGO Zarr stores with different roles.
`argo/argo_profiles_on_grid.zarr` is the compact grid-indexed store meant to be
used together with the GeoTIFF raster dataset. `data/argo_glors_ostia_ssh.zarr`
is the full enriched profile-level store and holds the complete ARGO
collocation dataset, including the sampled GLORYS, OSTIA, sea-level, and
sea-surface-salinity context.
## Raster Example
Representative surface-level training patches from the exported GeoTIFF store:
<p align="center">
<img src="assets/data/geotiff_dataset_random100_surface.png" width="85%" alt="Random surface-level training dataset patches" />
</p>
## Raster Products
All GeoTIFF rasters are exported on the GLORYS 0.1 degree global grid
(`EPSG:4326`, 3600 x 1800 pixels, west-to-east longitudes from -180 to 180 and
north-to-south latitudes from 90 to -90). The current package contains 761
weekly target dates per raster product, from 2010-01-01 through 2024-07-26.
Files are named `<variable>_YYYYMMDD.tif`.
The GLORYS variables are depth-resolved 50-band GeoTIFFs:
- `rasters/glorys/thetao/`: potential temperature, encoded as Kelvin.
- `rasters/glorys/so/`: salinity, encoded as PSU.
The surface products are single-band GeoTIFFs aggregated to the same weekly
target dates with a centered 7-day mean window:
- `rasters/ostia/analysed_sst/`: OSTIA analysed sea-surface temperature in Kelvin.
- `rasters/sealevel/adt/`: absolute dynamic topography in meters.
- `rasters/sss/sos/`: sea-surface salinity in PSU.
- `rasters/sss/dos/`: sea-surface density in kg/m3.
Raster pixels are stored as `uint8` with `255` reserved for nodata. Valid codes
`0..254` are linearly decoded using the stretch ranges in `manifest.yaml`;
per-file statistics, source filenames, compression, target dates, and the full
depth axis are also recorded there.
## ARGO Alignment Examples
ARGO profiles are projected onto the fixed 50-level GLORYS depth axis before
spatial rasterization. The examples below show the grid-indexed ARGO
representation and profile-level alignment quality.
<p align="center">
<img src="assets/data/argo_on_glorys_grid_3D.gif" width="70%" alt="Depth-aligned ARGO values on the GLORYS grid" />
</p>
<p align="center">
<img src="assets/data/profile_comparison_good_alignment.png" width="72%" alt="Example of good ARGO-to-GLORYS profile alignment" />
</p>
<p align="center">
<img src="assets/data/profile_comparison_bad_alignment.png" width="72%" alt="Example of weaker ARGO-to-GLORYS profile alignment" />
</p>
The full enriched profile-level ARGO collocation dataset is available at:
```python
import xarray as xr
ds = xr.open_zarr("data/argo_glors_ostia_ssh.zarr", consolidated=None)
```
The lightweight Parquet indices are included for preview and filtering:
```python
import pandas as pd
profiles = pd.read_parquet("indices/profiles.parquet")
variables = pd.read_parquet("indices/variables.parquet")
```
Coverage:
- Raster target dates: 2010-01-01 to 2024-07-26
- Enriched ARGO profile dates: 2010-01-01 to 2024-07-31
- GLORYS depth levels: 50
Upstream product licenses and citation requirements for EN4/ARGO, GLORYS,
OSTIA, sea-level, and sea-surface-salinity products still apply.
|