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import matplotlib.pyplot as plt
import cartopy.crs as ccrs
import cartopy.feature as cf
import numpy as np
import pandas as pd
import xarray as xr

var_name = "dis06"

ds = xr.open_dataset('./clim_2020111500.nc')

cmap = plt.cm.get_cmap('jet').copy()
cmap.set_under('white')

# set the coordinate reference system for EFAS
crs = ccrs.LambertAzimuthalEqualArea(central_longitude=10,central_latitude=52,false_easting=4321000,false_northing=3210000)

# define the filter for visualizing only discharge above that value
vmin = 20

# selecting a date
ds = ds[var_name].isel(time=1)

# Plot map discharge > 20 m/s 
fig, ax = plt.subplots(1,1,subplot_kw={'projection': crs}, figsize=(20,20) )
ax.gridlines(crs=crs, linestyle="-")
ax.coastlines()
ax.add_feature(cf.BORDERS)
sc = ds[var_name].plot(ax=ax,cmap=cmap,vmin=vmin,add_colorbar=False)
ax.set_title(f'{ds[var_name].long_name}> {vmin} $m^{3}s^{-1}$')
cbar = plt.colorbar(sc, shrink=.5,)
cbar.set_label(ds[var_name].GRIB_name)

In the code block below the soild depth will need to be loaded from the netCDF file:

xr.open_dataset('./sd_1.nc')

xr.open_dataset('./sd_2.nc')

xr.open_dataset('./sd_3.nc')

Update the operations accordingly