Confusing error message when reducing over non-existent dimension

What happened?

When reducing a DataArray after using groupby, and reducing over a dimension that does not exist, the given error is

ValueError: cannot reduce over dimensions ['<missing dimension>']. expected either '...' to reduce over all dimensions or one or more of (<existing dimension). Alternatively, install the `flox` package.

Doing the same but without using groupby gives a much more clear error

ValueError: '<missing dimension>' not found in array dimensions (<existing dimensions>)

What did you expect to happen?

I'd expect both examples to give the error

ValueError: '<missing dimension>' not found in array dimensions (<existing dimensions>)

which is a much more clear indication of what caused the error

Minimal Complete Verifiable Example

import numpy as np
import xarray as xr
ds = xr.DataArray(np.reshape(range(27), (3, 3, 3)),
                  coords=dict(lon=range(3),
                              lat=range(3),
                              time=xr.date_range('2025-10-01 00:00', '2025-10-01 02:00', freq='h')))
ds.std(dim='lon')  # OK
ds.groupby('time').std(dim='lon')  # OK
ds.std(dim='longitude')  # ValueError: 'longitude' not found in array dimensions ('lon', 'lat', 'time')
ds.groupby('time').std(dim='longitude')  # ValueError: cannot reduce over dimensions ['longitude']. expected either '...' to reduce over all dimensions or one or more of ('lon', 'lat', 'time'). Alternatively, install the `flox` package.

Steps to reproduce

No response

MVCE confirmation

• Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
• Complete example — the example is self-contained, including all data and the text of any traceback.
• Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
• New issue — a search of GitHub Issues suggests this is not a duplicate.
• Recent environment — the issue occurs with the latest version of xarray and its dependencies.

Relevant log output

Anything else we need to know?

No response

Environment

Run the supplied xarray DataArray example and compare the plain std(dim='longitude') error with the groupby('time').std(dim='longitude') error. Trace the groupby reduction path that produces the misleading message; the work is done when the grouped case reports the missing dimension and existing dimensions as shown in the expected error.