marketplace-zarr.md

ds = xr.open_zarr(
     session.store,
     group="goes19_goes18/10m/C08/2026-03-10",
    zarr_format=3,
)
ds
<xarray.Dataset> Size: 136GB
Dimensions:           (time: 144, y: 5424, x: 5424)
Coordinates:
  * time              (time) datetime64[ns] 1kB 2026-03-10 ... 2026-03-10T23:...
  * y                 (y) float64 43kB 0.1518 0.1518 0.1517 ... -0.1518 -0.1518
  * x                 (x) float64 43kB -0.1518 -0.1518 -0.1517 ... 0.1518 0.1518
Data variables:
    chi_squared       (time, y, x) float32 17GB dask.array<chunksize=(1, 1356, 1356), meta=np.ndarray>
    quality_flag      (time, y, x) float32 17GB dask.array<chunksize=(1, 1356, 1356), meta=np.ndarray>
    sigma_h           (time, y, x) float32 17GB dask.array<chunksize=(1, 1356, 1356), meta=np.ndarray>
    v_wind            (time, y, x) float32 17GB dask.array<chunksize=(1, 1356, 1356), meta=np.ndarray>
    sigma_v           (time, y, x) float32 17GB dask.array<chunksize=(1, 1356, 1356), meta=np.ndarray>
    sigma_u           (time, y, x) float32 17GB dask.array<chunksize=(1, 1356, 1356), meta=np.ndarray>
    u_wind            (time, y, x) float32 17GB dask.array<chunksize=(1, 1356, 1356), meta=np.ndarray>
    cloud_top_height  (time, y, x) float32 17GB dask.array<chunksize=(1, 1356, 1356), meta=np.ndarray>
dt = xr.open_datatree(session.store, engine="zarr", zarr_format=3)
print(dt)
<xarray.DataTree>
Group: /
└── Group: /goes19_goes18
    ├── Group: /goes19_goes18/10m
...