code: import importlib
  import xarray as xr
  import numpy as np
  import pandas as pd
  import sys
  
  from CASutils import filter_utils as filt
  from CASutils import readdata_utils as read
  from CASutils import calendar_utils as cal
  
  importlib.reload(filt)
  importlib.reload(read)
  importlib.reload(cal)
  
  
  expname=['SASK_CLM5_CLM5F_01.001.FSCAM.sask_1979_2014',
           'TOR_CLM5_CLM5F_01.001.FSCAM.tor_1979_2014',
           'SID_SNOWD_SNOWDF_01.001.FSCAM.sidsnowd1']
  
  outname='SCAM_CLM5_CLM5F_001'
  
  cityname=['Saskatoon','Toronto','Siderovsk']
  citylon=[253.330, 280.617, 82.3139]
  citylat=[52.1579, 43.6532, 66.5973]
  
  for icity in np.arange(0,3,1):
  
      basedir="/project/cas02/islas/CLM5_CLM4/raw/SCAM_new_lowrelax/"
      pathout="/project/cas/islas/python_savs/snowpaper/DATA_SORT/3cities/"
      
      fpath=basedir+expname[icity]+"/atm/hist/h0concat.nc"
      print(fpath)
      dat = read.read_sfc_cesm(fpath,"1979-01-01T12:00:00","2014-12-31T12:00:00")
     
      if (icity == 0): 
          trefht = xr.DataArray(np.zeros([dat.time.size, 3]), coords=[dat.time, cityname],
                                         dims=['time','city'], name='trefht')
      
      trefht[:,icity] = dat.TREFHT.isel(lon=0,lat=0)
      
      trefht.to_netcdf(path=pathout+"TREFHT_"+outname+".nc")
   import importlib
  import xarray as xr
  import numpy as np
  import pandas as pd
  import sys
  
  from CASutils import filter_utils as filt
  from CASutils import readdata_utils as read
  from CASutils import calendar_utils as cal
  
  importlib.reload(filt)
  importlib.reload(read)
  importlib.reload(cal)
  
  
  expname=['SASK_CLM5_CLM5F_01.001.FSCAM.sask_1979_2014',
           'TOR_CLM5_CLM5F_01.001.FSCAM.tor_1979_2014',
           'SID_CLM5_CLM5F_01.001.FSCAM.sid_1979_2014']
  
  outname='SCAM_CLM5_CLM5F_01'
  
  cityname=['Saskatoon','Toronto','Siderovsk']
  citylon=[253.330, 280.617, 82.3139]
  citylat=[52.1579, 43.6532, 66.5973]
  
  for icity in np.arange(0,3,1):
  
      basedir="/project/cas02/islas/CLM5_CLM4/raw/SCAM_CLM_INIT_60days_withclearsky/"
      pathout="/project/cas/islas/python_savs/snowpaper/DATA_SORT/3cities/SCAM_CLMINIT_60days_withclearsky/"
      
      fpath=basedir+expname[icity]+"/atm/hist/h0concat.nc"
      print(fpath)
      dat = read.read_sfc_cesm(fpath,"1979-01-01T12:00:00","2014-12-31T12:00:00")
     
      if (icity == 0): 
          flnsc = xr.DataArray(np.zeros([dat.time.size, 3]), coords=[dat.time, cityname],
                                         dims=['time','city'], name='flnsc')
      
      flnsc[:,icity] = dat.FLNSC.isel(lon=0,lat=0)
      
      flnsc.to_netcdf(path=pathout+"FLNSC_"+outname+".nc")
   import importlib
  import xarray as xr
  import numpy as np
  import pandas as pd
  import sys
  
  from CASutils import filter_utils as filt
  from CASutils import readdata_utils as read
  from CASutils import calendar_utils as cal
  
  importlib.reload(filt)
  importlib.reload(read)
  importlib.reload(cal)
  
  
  expname=['SASK_SNOWDa_CLM5F_02.001.FSCAM.sask2_1979_2014',
           'TOR_SNOWDa_CLM5F_02.001.FSCAM.tor2_1979_2014',
           'SID_SNOWDa_CLM5F_02.001.FSCAM.sid2_1979_2014']
  
  outname='SCAM_SNOWDa_CLM5F_02'
  
  cityname=['Saskatoon','Toronto','Siderovsk']
  citylon=[253.330, 280.617, 82.3139]
  citylat=[52.1579, 43.6532, 66.5973]
  
  for icity in np.arange(0,3,1):
  
      basedir="/project/cas02/islas/CLM5_CLM4/raw/SCAM_new_lowrelax/"
      pathout="/project/cas/islas/python_savs/snowpaper/DATA_SORT/3cities/SCAM/new_lowrelax/"
      
      fpath=basedir+expname[icity]+"/atm/hist/h0concat.nc"
      print(fpath)
      dat = read.read_sfc_cesm(fpath,"1979-01-01T12:00:00","2014-12-31T12:00:00")
     
      if (icity == 0): 
          trefht = xr.DataArray(np.zeros([dat.time.size, 3]), coords=[dat.time, cityname],
                                         dims=['time','city'], name='trefht')
      
      trefht[:,icity] = dat.TREFHT.isel(lon=0,lat=0)
      
      trefht.to_netcdf(path=pathout+"TREFHT_"+outname+".nc")
  
apis: numpy.arange numpy.zeros
apis: numpy.arange numpy.zeros
apis: numpy.arange numpy.zeros