new_contents: import numpy as np
  import matplotlib.pyplot as plt
  import cartopy.crs as ccrs
  
  from xmitgcm import open_mdsdataset
  from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER
  
  dir0 = '/homedata/bderembl/runmit/test_southatlgyre3'
  
  ds0 = open_mdsdataset(dir0,iters='all',prefix=['cheapAML'])
  
  # Average of Atmospheric Temperature
  
  Average_Tair = ds0.CH_TAIR.mean().values
  print('Case 4 : Average of Atmospheric Temperature')
  print(Average_Tair,'°C')
  Average_Tair_mask = ds0.CH_TAIR.where(ds0.hFacC>0).mean().values
  print('Case 4 : Average of Atmospheric Temperature without continents')
  print(Average_Tair_mask,'°C')
  
  # Uwind et Vwind : Winds
  
  Average_Uwind = ds0.CH_Uwind.mean().values
  print('Case 4 : Average of Atmospheric Zonal component - Uwind')
  print(Average_Uwind,'m/s')
  Average_Uwind_mask = ds0.CH_Uwind.where(ds0.hFacW>0).mean().values
  print('Case 4 : Average of Atmospheric Zonal component without continents')
  print(Average_Uwind_mask,'m/s')
  
  Average_Vwind = ds0.CH_Vwind.mean().values
  print('Case 4 : Average of Atmospheric Meridional component - Vwind')
  print(Average_Vwind,'m/s')
  Average_Vwind_mask = ds0.CH_Vwind.where(ds0.hFacS>0).mean().values
  print('Case 4 : Average of Atmospheric Meridional component without continents')
  print(Average_Vwind_mask,'m/s')
  
  
subject: Create E_Atmospheric_conditions.py