cupy-xarray does not handle chunked dask arrays with NaNs #9195

    # Avoid calling array_type("cupy") repeatidely in the any check
    array_type_cupy = array_type("cupy")
    if any(isinstance(x, array_type_cupy) for x in scalars_or_arrays):
        import cupy as cp

        xp = cp
    elif xp is None:
        xp = get_array_namespace(scalars_or_arrays)
    print('=======', xp.__name__, scalars_or_arrays)

### 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.
- [X] 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
======= cupy [array([0., 0.]), array([ 1., nan])]
======= cupy [nan, array(1.)]
a = <xarray.DataArray ()> Size: 8B
array(1.)
b = <xarray.DataArray 'asarray-a8e500e046402975cc20971c9b97fd57' ()> Size: 8B
dask.array<sum-aggregate, shape=(), dtype=int64, chunksize=(), chunktype=cupy.ndarray>
======= numpy [dask.array<zeros_like, shape=(2,), dtype=float64, chunksize=(2,), chunktype=cupy.ndarray>, dask.array<asarray, shape=(2,), dtype=float64, chunksize=(2,), chunktype=cupy.ndarray>]
======= numpy [nan, dask.array<sum-aggregate, shape=(), dtype=float64, chunksize=(), chunktype=cupy.ndarray>]
c = <xarray.DataArray 'asarray-a913867b040846d481995bbceaf8efdf' ()> Size: 8B
dask.array<where, shape=(), dtype=float64, chunksize=(), chunktype=numpy.ndarray>