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Info

One can download the auxiliary data by simplying requesting the data through a CDS API request.

Using the API request shown on the CDS data download form, it is possible to request one variable at a time

Code Block

language	py
title	Retrieving a single auxiliary file
collapse	true

import cdsapi

c = cdsapi.Client()

c.retrieve(
    'efas-forecast',
    {
        'variable': 'upstream_area_v4_0',
        'model_levels': 'surface_level',
        'format': 'netcdf',
        'area': [
            72, -35, 24,
            74,
        ],
    },
    'download.nc')

Warning

title	MARS url adaptor

Currently, we are developing a MARS URL adaptor. It is functioning but needs the review process on the content of the overview page. When the marsurl is made available in production, one can download the auxiliary data by simply requesting the data through a CDS API request:

Note: with the marsurl adaptor, the soil depth is now included as part of the auxiliary data. Therefore you should remove the soil depth from the CDS API request above (forecast volumetric soil moisture and soil depth).

Code Block

language	py
title	Retrieve multiple auxiliary files
collapse	true

import cdsapi

c = cdsapi.Client()

c.retrieve(
    'efas-forecast,
    {

    'efas-forecast',
    {
        'variable': ['soil_depth_v4_0','field_capacity_v4_0','wilting_point_v4_0'],
          'formatmodel_levels': 'netcdfsoil_levels',
        'variablesoil_level': [
   '2',
         'field_capacityformat',: 'wilting_pointnetcdf', 'soil_depth'
        ],'area': [
        'soil_level': [
      72, -35, 24,
          '1', '2', '3' 74,
        ],
    },
    'auxiliary.zip')

Note that area sub-selection is not currently possible for the auxiliary (or time-invariant) data. Therefore any 'area' included in the CDS API request will be ignored and the data downloaded will cover the full EFAS domain.

And then unzip the auxiliary.zip

Code Block

language	bash
theme	Emacs
title	unzip

$ unzip auxiliary.zip

Archive:  auxiliary.zip
 extracting: thmaxsd_2_1.nc
 extracting: thmin_14.0.nc
 extracting: thmax_2_4.0.nc
 extracting: thmin_2.nc
 extracting: thmax_3.nc
 extracting: thmin_3_4.0.nc

Plot map discharge

Code Block

language	py
title	Discharge map
collapse	true

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)

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Old Version 43

New Version 44

Key

Plot map discharge