What happened?

The skipna parameter appears to have no effect while annually resampling a monthly DataArray. I'm not sure if this is related to #6772

What did you expect to happen?

I expected da_yrA to be NaN since I am not skipping NaN values.

Minimal Complete Verifiable Example

```Python import numpy as np import pandas as pd import xarray as xr

data = np.arange(12) month_index = pd.date_range("2022-01","2022-12-31", freq="M") df = pd.DataFrame(index=month_index, data=data) df.index.name = "time" df.columns.name = "value" df.loc["2022-01":"2022-02"] = np.nan da = xr.DataArray(df)

these unexpectedly produce the same result

da_yrA = (da).resample(time="A-Dec", skipna=False).mean() da_yrB = (da).resample(time="A-Dec", skipna=True).mean()

print(da_yrA) print(da_yrB) ```

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?

No response

Environment

``` scipy: 1.10.0 netCDF4: 1.6.2 pydap: None h5netcdf: None h5py: None Nio: None zarr: None cftime: 1.6.2 nc_time_axis: 1.4.1 PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: None dask: 2023.2.0 distributed: 2023.2.0 matplotlib: 3.7.0 cartopy: 0.21.1 seaborn: None numbagg: None fsspec: 2023.1.0 cupy: None pint: None sparse: 0.13.0 flox: None numpy_groupies: None setuptools: 67.3.2 pip: 23.0.1 conda: None pytest: None mypy: None IPython: 8.10.0 sphinx: None ```