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As a workaround you can use: python p = da.isel(time=[0]).plot.pcolormesh( col="time", transform=ccrs.PlateCarree(), subplot_kws={'projection': ccrs.Orthographic(-80, 35)} )

Note the time=[0] - using time=0 squezes the time dimension. Also note the .plot.pcolormesh. Using just .plot also calls daarray.squeeze().

https://github.com/pydata/xarray/blob/8fab5a2449d8368251f96fc2b9d1eaa3040894e6/xarray/plot/plot.py#L163

I think this is fixed in the latest master.

``` import xarray as xr import numpy as np import cartopy.crs as ccrs

da = xr.tutorial.open_dataset('air_temperature')['air']

p = da.isel(time=[0, 1]).plot( transform=ccrs.PlateCarree(), col='time', subplot_kws={'projection': ccrs.Orthographic(-80, 35)} )

for ax in p.axes.flat: ax.coastlines() ax.gridlines() ```

p = da.isel(time=0).plot( transform=ccrs.PlateCarree(), subplot_kws={'projection': ccrs.Orthographic(-80, 35)} )

However if you try iterating over the axes, it will crash because p is quadmesh type not a facetgrid type so I was wondering whether it'd be good to have an keyword like force_facetgrid_type=True which uses the FacetGrid class to plot a single map so that the user can keep the same code for single axes and facet axes? ``` p = da.isel(time=0).plot( transform=ccrs.PlateCarree(), subplot_kws={'projection': ccrs.Orthographic(-80, 35)} )

for ax in p.axes.flat: ax.coastlines() ax.gridlines() ```

I agree, this is unfortunate. I suspect the source of the discrepancy is that we use a totally different codepath if either col or row is supplied, creating our own subplot grid.