id,node_id,number,title,user,state,locked,assignee,milestone,comments,created_at,updated_at,closed_at,author_association,active_lock_reason,draft,pull_request,body,reactions,performed_via_github_app,state_reason,repo,type
441222339,MDU6SXNzdWU0NDEyMjIzMzk=,2946,std interprets continents as zero not nan,10809480,closed,0,,,5,2019-05-07T13:06:32Z,2023-12-02T02:46:37Z,2023-12-02T02:46:36Z,NONE,,,,"hi there,

i couldnt find anything related yet.
My issue is that I have to calculated a large dataset of time series data of world wide datasets.
I always have this weird bug, that the std calculations interprets nan differently as mean caluculations.

Here is my typical code:

```python
import xarray as xr
import glob
import numpy as np

data = xr.open_mfdataset([r""C:\Users\atraumue\Desktop\test\dt_global_allsat_phy_l4_20170101_20180115.nc"",r""C:\Users\atraumue\Desktop\test\dt_global_allsat_phy_l4_20170102_20180115.nc""], parallel=True, concat_dim=""time"")
data = data.drop(""lon_bnds"")
data = data.drop(""lat_bnds"")
data = data.drop(""ugosa"")
data = data.drop(""ugos"")
data = data.drop(""sla"")
data = data.drop(""vgos"")
data = data.drop(""vgosa"")
data = data.drop(""err"")
data = data.drop(""ssh"")
data = data.drop(""nv"")

adt = data.drop(""velocity"")

adt.mean(dim=""time"", skipna=True).to_netcdf(r""C:\Users\atraumue\Desktop\calcsadt_mean_2004_2018_month5.nc"")
adt.std(dim=""time"", skipna=True,ddof=1).astype(np.float64).to_netcdf(r""C:\Users\atraumue\Desktop\calcsadt_std_2004_2018_month5.nc"")

data.close()
adt.close()
```
Dropbox to files:
https://www.dropbox.com/sh/yuf114u143mj2l3/AABuQfC5wu4nrWDH4GsGgFyJa?dl=0


I dont know why this occures, for mean calulcations there is no problem with the continents.
As a dirty work around i just overlay them.



#### Output of ``xr.show_versions()``

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.8 |Anaconda, Inc.| (default, Dec 30 2018, 18:50:55) [MSC v.1915 64 bit (AMD64)]
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 63 Stepping 2, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None
libhdf5: 1.10.4
libnetcdf: 4.6.2

xarray: 0.12.1
pandas: 0.24.1
numpy: 1.15.4
scipy: 1.2.0
netCDF4: 1.4.2
pydap: None
h5netcdf: 0.6.2
h5py: 2.9.0
Nio: None
zarr: None
cftime: 1.0.3.4
nc_time_axis: None
PseudonetCDF: None
rasterio: 1.0.13
cfgrib: None
iris: None
bottleneck: 1.2.1
dask: 1.1.1
distributed: 1.25.3
matplotlib: 3.0.2
cartopy: 0.17.0
seaborn: 0.9.0
setuptools: 40.7.3
pip: 19.0.1
conda: 4.6.14
pytest: 4.2.0
IPython: 7.2.0
sphinx: 1.8.4

</details>
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