In order to construct a netcdf file with a 2D field on a monthly resolution (for X number of years), I currently use the lines of code mentioned below. Since I do not care about the type of calendar, I just use 360_day, in which each month of the year has 30 days. Perhaps this can be useful for others. In case a better solution is available, please let me know!

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

51 years, saving first day of each month.

mmhours = np.arange(0,(5136024),30*24) attrs = {'units': 'Hours since 1955-01-01T12:00:00', 'calendar' : '360_day'}

target = np.random.rand(len(mmhours),10,10) lat = np.arange(50,51,0.1) lon = np.arange(3,4,0.1)

target_xr = xr.Dataset({'test': (['time', 'lat', 'lon'], target)}, coords={'time': ('time', mmhours, attrs) ,'lat': lat, 'lon': lon})

target_xr.to_netcdf('test.nc', encoding={'test': {'zlib': True}})

```