Plotting grid_mapping : Lambert_Azimuthal_Grid

[dominichr1]

Sea ice data is given in a Lambert Azimuthal Grid. Such that the main coordinates are as followed:
x (xc), y (yc),
and additional coordinates are:
lat (yc, xc), lon (yc, xc)

The only way I've been able to plot it is -

def make_simple_plot(XR_all_years, var='ice_conc', time_index=0):
    proj = ccrs.LambertAzimuthalEqualArea(central_latitude=90.0)
    fig = plt.figure(figsize=(8,4))
    ax = plt.axes(projection=proj)
    
    xc_max = XR_all_years['xc'].max()
    xc_min = XR_all_years['xc'].min()
    yc_max = XR_all_years['yc'].max()
    yc_min = XR_all_years['yc'].min()
    
    ease_extent = [ xc_min, xc_max, yc_min, yc_max]
    ease_extent = [x*1000 for x in ease_extent] #km to metres
    
    ax.set_extent(ease_extent, crs=proj) 
    ax.coastlines(resolution="110m",linewidth=1)
    ax.gridlines(linestyle='--',color='black')
    
    ice_conc = XR_all_years.variables['ice_conc'][time_index,:,:]    
    mapped_grid = ax.imshow(ice_conc, extent=ease_extent, transform=proj, 
              origin='upper', cmap='gist_rainbow')
    
    plt.title(str(var)+' time: '+str(time_index), size=14)
    cb = plt.colorbar(mapped_grid, orientation="vertical", pad=0.02, 
                      aspect=16, shrink=0.8)
    cb.set_label('%',size=12,rotation=0,labelpad=15)
    cb.ax.tick_params(labelsize=10)
    plt.tight_layout()
    plt.show()
    return fig

[adagj]

Hi,
you can try something like:

fig = plt.figure(1, figsize=[7,5])
ax = plt.subplot(projection=ccrs.LambertAzimuthalEqualArea(central_latitude=90.0))
ax.coastlines()
ax.set_extent([minlon, maxlon, minlat, maxlat], crs=ccrs.PlateCarree())
XR_all_years['ice_conc'].isel(time = time_index).plot.contourf(ax=ax, transform=ccrs.PlateCarree(), x='lon', y='lat')