How to plot models bias/difference in Python?

Question

#read data
dset = xr.open_dataset('/badc/cmip6/data/CMIP6/ScenarioMIP/BCC/BCC-CSM2-MR/ssp370/r1i1p1f1/Amon/tas/gn/v20190314/tas_Amon_BCC-CSM2-MR_ssp370_r1i1p1f1_gn_201501-210012.nc', parallel=True)

#define timescale
time = dset.time
clim_ta = clim_set_t['tas'].groupby('time.month').mean('time', keep_attrs=True)
clim_ta_c = (clim_ta - 273.15)

# define areas
lat = dset.lat
lon = dset.lon
lon_range = lon[(lon>60) & (lon<150)]
lat_range = lat[(lat>10) & (lat<60)]

#plot
clim_ta_c.sel(lon=lon_range, lat=lat_range, month = 1).plot.contourf(ax=ax,
                                          levels=np.arange(-30, 30 + 1, 1),
                                          transform=ccrs.PlateCarree(),
                                          cmap='Spectral_r',
                                          cbar_kwargs={'orientation': 'vertical',   #colorbar
                                                   'label': 'temperature (℃)',
                                                   'ticks': np.arange(-30, 30 + 5, 5),
                                                   'pad': 0.05,
                                                   'shrink': 0.8})

model = dset.attrs['source_id']
title = f'{model} near-surface temperature climatology 2015-2100 (1)'
plt.title(title, fontsize = 13)

The code above is the main part to plot climatology. I have plotted the BCC model in ssp126 scenario BCC in ssp126 and All models ensemble mean ensemble mean near-surface temperature climatology for January. I want to plot the model bias/difference ( bcc in ssp126 substract ensemble mean) monthly model bias but don't know how. Any help will be appreciated.