Hi NEMO users,
We are now using Nemo5 with XIos3 for our regional configuration. The model runs well and produces the right output but the produced NetCDF files have a weird behavior for the grid_U/V files. It seems that the time_counter values are filled with NetCDF missing values. See this Python code for example :
>>> import xarray as xr
>>> import glob
>>> files = glob.glob("out/BS_1m**grid_U**.nc")
>>> ds=xr.open_dataset(files[0], decode_times=False)
>>> ds["time_counter"]
<xarray.DataArray 'time_counter' (time_counter: 12)> Size: 96B
array([9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36,
9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36, 9.96921e+36,
9.96921e+36, 9.96921e+36])
Coordinates:
time_instant (time_counter) float64 96B ...
* time_counter (time_counter) float64 96B 9.969e+36 9.969e+36 ... 9.969e+36
time_centered (time_counter) float64 96B ...
Attributes:
axis: T
standard_name: time
long_name: Time axis
calendar: gregorian
units: seconds since 1900-01-01 00:00:00
time_origin: 1900-01-01 00:00:00
bounds: time_counter_bounds
>>> files = glob.glob("out/BS_1m**grid_T**.nc")
>>> ds=xr.open_dataset(files[0], decode_times=False)
>>> ds["time_counter"]
<xarray.DataArray 'time_counter' (time_counter: 12)> Size: 96B
array([1.705406e+09, 1.707955e+09, 1.710504e+09, 1.713139e+09, 1.715774e+09,
1.718410e+09, 1.721045e+09, 1.723723e+09, 1.726358e+09, 1.728994e+09,
1.731629e+09, 1.734264e+09])
Coordinates:
time_centered (time_counter) float64 96B ...
* time_counter (time_counter) float64 96B 1.705e+09 1.708e+09 ... 1.734e+09
time_instant (time_counter) float64 96B ...
Attributes:
axis: T
standard_name: time
long_name: Time axis
calendar: gregorian
units: seconds since 1900-01-01 00:00:00
time_origin: 1900-01-01 00:00:00
bounds: time_counter_bounds
Have anyone encoutered this issue ?
Kind regards,
Guillaume