Missing examples for the map and map_dataarray methods of FacetGrid objects

The issue names no target file; start by locating the official FacetGrid documentation and existing examples for map and map_dataarray. Adapt the proposed air-temperature example to show both methods, and consider how the boolean overlay is represented. Done means newcomers can follow documented examples for adding hatching or stippling to faceted plots.

Faceted plots are a great feature of xarray, in my view, sometimes presented as a 'quick and dirty' way to plot data, while it could be instead the best way to produce high quality subplot panels without any tedious loop on matplotlib axes.
I have been struggling to understand how map and map_dataarray methods work to overlay, e.g. hatching or stippling to 2D faceted plots derived from xr.plot.pcolormesh or xr.plot.imshow . This is very useful to highlight values labelled as True after passing a statistical test for example.
I found a way to go with the map_dataarray method (Note that I have never succeeded in using the map method for datasets. I do not understand how it works).
Below, I propose an example based on the official documentation. Feel free to use it or adapt it to improve the Xarray documentation:

import numpy as np;
import pandas as pd;
import matplotlib.pyplot as plt;
import xarray as xr

airtemps = xr.tutorial.open_dataset("air_temperature")
air = airtemps.air - 273.15
t = air.isel(time=slice(0, 365 * 4, 250))
warm = t>15    #Suppose we want to hatch regions with temperature warmer than 15°C. Quite a dumb idea but this is just to illustrate
test = xr.concat([t,warm],dim='dummy')
g_simple = test.isel(dummy=0).plot(x="lon", y="lat", col="time", col_wrap=3)
g_simple.data = test.isel(dummy=1) #Here I just replace the temperature data of the FacetGrid object with the boolean data 
g_simple.map_dataarray(xr.plot.contourf,x='lon',y='lat', levels=3, hatches=[ '' , '////' ], alpha=0, add_colorbar=False)

plt.show()