new_contents: import numpy as np
  
  # Set up an NCSS query from thredds using siphon
  query = ncss.query()
  query.accept('netcdf4')
  query.variables('Temperature_isobaric', 'Geopotential_height_isobaric')
  query.vertical_level(50000)
  now = datetime.utcnow()
  query.time_range(now, now + timedelta(days=1))
  query.lonlat_box(west=-110, east=-45, north=50, south=10)
  
  # Download data using NCSS
  data = ncss.get_data(query)
  ds = xr.open_dataset(NetCDF4DataStore(data))
  
  temp_var = ds.metpy.parse_cf('Temperature_isobaric')
  height_var = ds.metpy.parse_cf('Geopotential_height_isobaric')
  longitude = temp_var.metpy.x
  latitude = temp_var.metpy.y
  time_index = 0
  
  # Plot using CartoPy and Matplotlib
  fig = plt.figure(figsize=(12, 8))
  ax = fig.add_subplot(1, 1, 1, projection=ccrs.LambertConformal())
  
  contours = np.arange(5000, 6000, 80)
  ax.pcolormesh(longitude, latitude, temp_var[time_index].squeeze(),
                transform=data_projection, zorder=0)
  ax.contour(longitude, latitude, height_var[time_index].squeeze(), contours, colors='k',
             transform=data_projection, linewidths=2, zorder=1)
  ax.set_title(temp_var.metpy.time[time_index].values)
  
  # add some common geographic features
  ax.add_feature(cfeature.COASTLINES)
  ax.add_feature(cfeature.STATES, edgecolor='black')
  ax.add_feature(cfeature.BORDERS)
  
  # add some lat/lon gridlines
  ax.gridlines()
subject: Add solutions script for ModelOutput