text: Title: DataArray.rolling fails with chunk size of 1 or 2 (reemergence of issue #9862)
  Body: ### What happened?
  
  The problem is exactly as written in closed issue #9862, but I'm using:
   - xarray: 2025.1.2
   - dask: 2025.2.0
  
  Since everything is the same (including traceback and behavior when pasted into console or binder), please refer to original issue for complete description.
  
  I didn't click "new issue" since it's an old issue that was closed, but is not fixed.
  
  ### What did you expect to happen?
  
  We would expect the rolling mean to calculate correctly.
  
  ### Minimal Complete Verifiable Example
  
  ```Python
  import dask.array as da
  import xarray as xr
  import numpy as np
  
  # Dimensions and sizes
  nx, ny, nt = 100, 200, 50  # size of x, y, and time dimensions
  x = np.linspace(0, 10, nx)  # x-coordinates
  y = np.linspace(0, 20, ny)  # y-coordinates
  time = np.linspace(0, 1, nt)  # time coordinates
  
  # Generate a random Dask array with lazy computation
  data = da.random.random(size=(nx, ny, nt), chunks=(100, 200, 1))
  
  # Create an xarray DataArray with coordinates and attributes
  data_array = xr.DataArray(
      data,
      dims=["x", "y", "time"],
      coords={"x": x, "y": y, "time": time},
      name="dummy_data",
      attrs={"units": "arbitrary", "description": "Dummy 3D dataset"}
  )
  
  d_rolling = data_array.rolling(time=5).mean()
  d_rolling.compute()
  ```
  
  ### 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](https://mybinder.org/v2/gh/pydata/xarray/main?urlpath=lab/tree/doc/examples/blank_template.ipynb), returning the result.
  - [ ] New issue — a search of GitHub Issues suggests this is not a duplicate.
  - [x] Recent environment — the issue occurs with the latest version of xarray and its dependencies.
  
  ### Relevant log output
  
  ```Python
  Traceback (most recent call last):
  
    Cell In[6], line 24
      d_rolling.compute()
  
    File /srv/conda/envs/notebook/lib/python3.10/site-packages/xarray/core/dataarray.py:1206 in compute
      return new.load(**kwargs)
  
    File /srv/conda/envs/notebook/lib/python3.10/site-packages/xarray/core/dataarray.py:1174 in load
      ds = self._to_temp_dataset().load(**kwargs)
  
    File /srv/conda/envs/notebook/lib/python3.10/site-packages/xarray/core/dataset.py:900 in load
      evaluated_data: tuple[np.ndarray[Any, Any], ...] = chunkmanager.compute(
  
    File /srv/conda/envs/notebook/lib/python3.10/site-packages/xarray/namedarray/daskmanager.py:85 in compute
      return compute(*data, **kwargs)  # type: ignore[no-untyped-call, no-any-return]
  
    File /srv/conda/envs/notebook/lib/python3.10/site-packages/dask/base.py:662 in compute
      results = schedule(dsk, keys, **kwargs)
  
    File /srv/conda/envs/notebook/lib/python3.10/site-packages/dask/_task_spec.py:740 in __call__
      return self.func(*new_argspec, **kwargs)
  
  ValueError: Moving window (=5) must between 1 and 4, inclusive
  ```
  
  ### Anything else we need to know?
  
  _No response_
  
  ### Environment
  
  <details>
  INSTALLED VERSIONS
  ------------------
  commit: None
  python: 3.10.16 | packaged by conda-forge | (main, Dec  5 2024, 14:16:10) [GCC 13.3.0]
  python-bits: 64
  OS: Linux
  OS-release: 6.8.0-52-generic
  machine: x86_64
  processor: x86_64
  byteorder: little
  LC_ALL: en_US.UTF-8
  LANG: en_US.UTF-8
  LOCALE: ('en_US', 'UTF-8')
  libhdf5: 1.14.3
  libnetcdf: 4.9.2
  
  xarray: 2025.1.2
  pandas: 2.2.3
  numpy: 2.1.3
  scipy: 1.15.2
  netCDF4: 1.7.2
  pydap: 3.5.3
  h5netcdf: 1.5.0
  h5py: 3.13.0
  zarr: 2.18.3
  cftime: 1.6.4
  nc_time_axis: 1.4.1
  iris: 3.11.0
  bottleneck: 1.4.2
  dask: 2025.2.0
  distributed: 2025.2.0
  matplotlib: 3.10.1
  cartopy: 0.24.0
  seaborn: 0.13.2
  numbagg: 0.9.0
  fsspec: 2025.2.0
  cupy: None
  pint: 0.24.4
  sparse: 0.15.5
  flox: None
  numpy_groupies: None
  setuptools: 75.8.0
  pip: 25.0
  conda: None
  pytest: None
  mypy: None
  IPython: 8.32.0
  sphinx: None
  </details>
  