issue_comments

2D lat/lon arrays could be as expensive to store as the image itself, even though the values can be computed on the fly with very cheap arithmetic.

Just wanted to mention in case it comes up later, this is true for some datasets and for others the lon/lats are not uniformly spaced so they can't be calculated (just based on the way the satellite instrument works). They have to be loaded from the original dataset (on-disk file). For a while in the Satpy library we were storing 2D dask arrays for the lon/lat coordinates until we realized xarray was sometimes computing them and we didn't want that.

For reference for how rioxarray does things: https://corteva.github.io/rioxarray/stable/getting_started/crs_management.html

```

import xarray, rioxarray xda = xarray.DataArray(1) xda.rio.write_crs(4326, inplace=True) <xarray.DataArray ()> array(1) Coordinates: spatial_ref int64 0 Attributes: grid_mapping: spatial_ref xda.spatial_ref <xarray.DataArray 'spatial_ref' ()> array(0) Coordinates: spatial_ref int64 0 Attributes: crs_wkt: GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["... semi_major_axis: 6378137.0 semi_minor_axis: 6356752.314245179 inverse_flattening: 298.257223563 reference_ellipsoid_name: WGS 84 longitude_of_prime_meridian: 0.0 prime_meridian_name: Greenwich geographic_crs_name: WGS 84 grid_mapping_name: latitude_longitude spatial_ref: GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["... ```

It's great to be able to follow along with the discussion here! I'm definitely interested in seeing where the duck array index support ends up.

One use-case motivated question: the flexible indexes refactoring has also been pointed to as the resolution to https://github.com/pydata/xarray/issues/2233, where multidimensional coordinates have the same name as one of their dimensions. I wasn't quite able to tell through the narrative here if that has been addressed along the way yet or not ("A. only 1D coordinates with a name matching their dimension name" for implicit index creation does seem to get close though). So, would it be worth directly addressing https://github.com/pydata/xarray/issues/2233 here, or should that wait?