Here is code used to read/write a masked_array with the netCDF4 and xarray modules. As seen if you run the code, for 3 cases the masked_value is read as a np.nan. However, for the netcdf file written by netCDF4 and read by xarray, the masked_value is the default _FillValue of 9.96920997e+36.

I wonder if this is expected or if I am doing something wrong.

```python import xarray as xr import netCDF4 as nc import numpy as np import os data = np.ma.array([1.,2.], mask = [True, False])

create file with netcdf$

nc_file = 'ncfile.nc' if os.path.exists(nc_file): os.remove(nc_file) ds = nc.Dataset(nc_file, 'w') ds.createDimension('dim1', 2) var = ds.createVariable('data', 'f8', dimensions = ('dim1')) var[:] = data ds.close()

create file with xarray

da = xr.DataArray(data, name = 'data', dims = {'dim1':2}) nc_file = 'xrfile.nc' if os.path.exists(nc_file): os.remove(nc_file) da.to_netcdf(nc_file, 'w') da.close()

print('original data: {}'.format(data))

da = xr.open_dataset('ncfile.nc').data print('data from nc read by xr: {}'.format(da.values)) da = xr.open_dataset('xrfile.nc').data print('data from xr read by xr: {}'.format(da.values))

data = nc.Dataset('ncfile.nc').variables['data'][:] print('data from nc read by nc: {}'.format(da.values)) data = nc.Dataset('xrfile.nc').variables['data'][:] print('data from xr read by nc: {}'.format(da.values))

print('done')

``` Here is the output I get:

``` original data: [-- 2.0] data from nc read by xr: [9.96920997e+36 2.00000000e+00] data from xr read by xr: [nan 2.] data from nc read by nc: [nan 2.] data from xr read by nc: [nan 2.] done

```

Output of xr.show_versions()

I am trying to extract data for a specific station from data observations accessed via THREDDS. At first I got an error but a colleague found a way to make it work. In the code below it works if APPLY_PATCH=True but it crashes if APPLY_PATCH=False.

I do not know if this behaviour is expected and/or linked to the way the data is 'served' via THREDDS but I would never have found the way around it by myself.

``` import xarray as xr

CLEF_STATION = "MONTREAL" NOM_VAR = 'prsn' APPLY_PATCH = False

url_pavics = "http://pavics.ouranos.ca:8083/twitcher/ows/proxy/thredds/dodsC" url_donnees_homo = "/".join((url_pavics, "datasets/station_obs/ECCC_AHCCD_gen2_precipitation.ncml"))

ds = xr.open_dataset(url_donnees_homo)

data for specific station(s)

dsr = ds.sel(station=ds.station_name.str.contains(CLEF_STATION))

apply patch

if APPLY_PATCH: for var in dsr.variables: if dsr[var].dtype == 'O': dsr[var].encoding = {}

save to a netcdf file

dsr.to_netcdf("out.nc", format="NETCDF4_CLASSIC") ```

What happened:

When running this I get the following error

``` runfile('/Users/sbiner/cloud/OneDrive - Ouranos inc/job/stagiaires_etudiants/2021_tempete_neige/code/issue_xaray.py', wdir='/Users/sbiner/cloud/OneDrive - Ouranos inc/job/stagiaires_etudiants/2021_tempete_neige/code') Traceback (most recent call last):

File "src/netCDF4/_netCDF4.pyx", line 4931, in netCDF4._netCDF4.Variable.setitem

ValueError: cannot reshape array of size 7 into shape (1,1)

During handling of the above exception, another exception occurred:

Traceback (most recent call last):

File "/Users/sbiner/cloud/OneDrive - Ouranos inc/job/stagiaires_etudiants/2021_tempete_neige/code/issue_xaray.py", line 14, in <module> dsr.to_netcdf("out.nc", format="NETCDF4_CLASSIC")

File "/Users/sbiner/anaconda3/envs/py38/lib/python3.8/site-packages/xarray/core/dataset.py", line 1689, in to_netcdf return to_netcdf(

File "/Users/sbiner/anaconda3/envs/py38/lib/python3.8/site-packages/xarray/backends/api.py", line 1107, in to_netcdf dump_to_store(

File "/Users/sbiner/anaconda3/envs/py38/lib/python3.8/site-packages/xarray/backends/api.py", line 1154, in dump_to_store store.store(variables, attrs, check_encoding, writer, unlimited_dims=unlimited_dims)

File "/Users/sbiner/anaconda3/envs/py38/lib/python3.8/site-packages/xarray/backends/common.py", line 255, in store self.set_variables(

File "/Users/sbiner/anaconda3/envs/py38/lib/python3.8/site-packages/xarray/backends/common.py", line 297, in set_variables writer.add(source, target)

File "/Users/sbiner/anaconda3/envs/py38/lib/python3.8/site-packages/xarray/backends/common.py", line 146, in add target[...] = source

File "/Users/sbiner/anaconda3/envs/py38/lib/python3.8/site-packages/xarray/backends/netCDF4_.py", line 64, in setitem data[key] = value

File "src/netCDF4/_netCDF4.pyx", line 4933, in netCDF4._netCDF4.Variable.setitem

File "<array_function internals>", line 5, in broadcast_to

File "/Users/sbiner/anaconda3/envs/py38/lib/python3.8/site-packages/numpy/lib/stride_tricks.py", line 411, in broadcast_to return _broadcast_to(array, shape, subok=subok, readonly=True)

File "/Users/sbiner/anaconda3/envs/py38/lib/python3.8/site-packages/numpy/lib/stride_tricks.py", line 348, in _broadcast_to it = np.nditer(

ValueError: operands could not be broadcast together with remapped shapes [original->remapped]: (1,7) and requested shape (1,1) ``` What you expected to happen:

I expect a netcdf file to be written

Environment:

I like the automatic decoding of the time variable when reading netcdf files but I often need to keep the calendar attribute of the time variable.

Could it be possible to keep those attributes in the DataSet/DataArray return by open_dataset?

I am trying to use xarray with different types of calendars. I made a few tests and wonder if somebody can help me make sense of the results. In my test, I generate a DataArray da time series with a 365_day calendar using cftime. I then write that DataArray in a netCDF file and read it in another DataArray da2

Code Sample, a copy-pastable example if possible

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

generate data for 365_days calendar

units = 'days since 2000-01-01 00:00' time_365 = cftime.num2date(np.arange(0, 10 * 365), units, '365_day') da = xr.DataArray(np.arange(time_365.size), coords = [time_365], dims = 'time', name = 'data')

write dataArray in netcdf and read it in new DataArray

da.to_netcdf('data_365.nc', 'w') da2 = xr.open_dataset('data_365.nc').data

try resample da

try: mean = da.resample(time='Y').mean() print(mean.values) except TypeError: print('got TypeError for da')

try resample da2

mean = da2.resample(time = 'Y').mean() print (mean.values) ```

Problem description

As seen in the code the resampledoes not work for da while it does for da2. The problem is related to the the type of da.time which is cftime.DatetimeNoLeap while da2.time is a datetime64. I thought that xarray is using cftime to make the conversion from time numerical values to dates but it looks to me as if it is not the case.

I wonder if this makes sense or if it is something that should eventually be corrected.

INSTALLED VERSIONS In [6]: print (cftime.version) 1.0.1

Code Sample

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

create netcdf file

data = np.random.rand(4, 3) foo = xr.DataArray(data) foo.to_netcdf('test.nc')

f_nc = 'a.nc' shutil.copy('test.nc', f_nc) while 1: print '{:05n} characteres'.format(len(f_nc)) ds1 = xr.open_dataset(f_nc) ds1.close() nf_nc = 'a' + f_nc shutil.move(f_nc, nf_nc) f_nc = nf_nc

if len(f_nc) == 100:
    break

```

Problem description

On my linux machine (CentOS) this code crashes (memory corrruption) when the filename length hits 32 characters.

On my OSX machine it is fine until 255 character and stops with an IOError

Output of xr.show_versions()