What happened?

Calling rolling().mean() on a dask-backed array sometimes outputs a different dtype than with a numpy backed array, for example with a float32 input. This is due to the optimized _mean function introduced in #4915.

What did you expect to happen?

This is a simple enough operation that if you start with float32 I would expect to get float32 back.

Minimal Complete Verifiable Example

```Python

import xarray as xr da = xr.DataArray([1,2,3], coords={'x':[1,2,3]}).astype('float32') da.rolling(x=3, min_periods=1).mean().dtype dtype('float32') da.chunk({'x':1}).rolling(x=3, min_periods=1).mean().dtype dtype('float64') ```

MVCE confirmation

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

Relevant log output

No response

Anything else we need to know?

5877 is somewhat related.

Environment