<jupyter_start><jupyter_text>Here is the NCL code example:```;*************************************************; NCL Graphics: polar_1.ncl;; Concepts illustrated:;   - Drawing black-and-white contours over a polar stereographic map;   - Drawing the northern hemisphere of a polar stereographic map;;************************************************;; These files are loaded by default in NCL V6.2.0 and newer; load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/gsn_code.ncl"; load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/gsn_csm.ncl" ;************************************************begin;************************************************; read in netCDF file;************************************************  a = addfile("$NCARG_ROOT/lib/ncarg/data/cdf/uv300.nc","r");************************************************; read in zonal winds;************************************************  u = a->U(1,:,:)                                ; read July zonal winds;************************************************; create plot;************************************************  wks = gsn_open_wks("png","polar")              ; send graphics to PNG file  res            = True                          ; plot mods desired  res@gsnPolar   = "NH"                          ; specify the hemisphere  plot = gsn_csm_contour_map_polar(wks,u,res)    ; create the plotend```<jupyter_code>import numpy as np
import xarray as xr
import matplotlib.pyplot as plt
import cartopy
import cartopy.crs as ccrs
a = xr.open_dataset("/Users/brianpm/Documents/www.ncl.ucar.edu/Applications/Data/cdf/uv300.nc")
u = a["U"].isel(time=1)
u
fig, ax = plt.subplots(figsize=(10,10), subplot_kw={"projection":ccrs.NorthPolarStereo()})

# following https://scitools.org.uk/cartopy/docs/latest/gallery/always_circular_stereo.html#custom-boundary-shape
import matplotlib.path as mpath
# Compute a circle in axes coordinates, which we can use as a boundary
# for the map. We can pan/zoom as much as we like - the boundary will be
# permanently circular.
theta = np.linspace(0, 2*np.pi, 100)
center, radius = [0.5, 0.5], 0.5
verts = np.vstack([np.sin(theta), np.cos(theta)]).T
circle = mpath.Path(verts * radius + center)
ax.set_boundary(circle, transform=ax.transAxes)

ax.set_extent([-180, 180, 0, 90], ccrs.PlateCarree())
ax.add_feature(cartopy.feature.LAND, color='lightgray')
# ax.add_feature(cartopy.feature.OCEAN)
ax.gridlines()

# regular plotting
lons, lats = np.meshgrid(a['lon'], a['lat'])
lvls = np.arange(-12, 40+4, 4)
CS = ax.contour(lons, lats, u, transform=ccrs.PlateCarree(), colors='firebrick', levels=lvls)
ax.clabel(CS, CS.levels, inline=True, fontsize=10, fmt='%2.0f')

fig.text( 0.6, 0.1, f"CONTOUR FROM {min(CS.levels)} to {max(CS.levels)} by {CS.levels[1]-CS.levels[0]}", bbox=dict(facecolor='none', edgecolor='black'))

ax.set_title(u.long_name, loc='left')
ax.set_title(u.units, loc='right')

ax.text(0, 0, "HERE")
np.arange(-12, 40+4, 4)<jupyter_output><empty_output>
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