Load ODIM_H5 Volume data from German Weather Service

In this example, we obtain and read the latest 30 minutes of available volumetric radar data from German Weather Service available at opendata.dwd.de. Finally we do some plotting.

This retrieves 6 timesteps of the 10 sweeps (moments DBZH and VRADH) of the DWD volume scan of a distinct radar. This amounts to 120 data files which are combined into one volumetric Cf/Radial2 like xarray powered structure.

Exports to single file Odim_H5 and Cf/Radial2 format are shown at the end of this tutorial.

Note

The used open_odim_mfdataset implementation is based on xarray. It claims multiple data files and presents them in a simple structure. See also the notebook wradlib_odim_backend for further details.

import wradlib as wrl
import warnings
warnings.filterwarnings('ignore')
import matplotlib.pyplot as pl
import numpy as np
import xarray as xr
try:
    get_ipython().magic("matplotlib inline")
except:
    pl.ion()
from wradlib.io import open_odim_mfdataset

import urllib3
import os
import io
import glob
import shutil
import datetime

Download radar volumes of latest 30 minutes from server using wetterdienst

wetterdienst is a neat package for easy retrieval of data primarily from DWD. For further information have a look at their documentation.

from wetterdienst.provider.dwd.radar import DwdRadarDataFormat, DwdRadarDataSubset, DwdRadarParameter, DwdRadarValues
from wetterdienst.provider.dwd.radar.sites import DwdRadarSite

elevations = range(10)

end_date = datetime.datetime.utcnow()
start_date = end_date - datetime.timedelta(minutes=30)

results_velocity = []
results_reflectivity = []

for el in elevations:
    # Horizontal Doppler Velocity
    request_velocity = DwdRadarValues(
        parameter=DwdRadarParameter.SWEEP_VOL_VELOCITY_H,
        start_date=start_date,
        end_date=end_date,
        site=DwdRadarSite.ESS,
        elevation=el,
        fmt=DwdRadarDataFormat.HDF5,
        subset=DwdRadarDataSubset.POLARIMETRIC,
    )

    # Horizontal Reflectivity
    request_reflectivity = DwdRadarValues(
        parameter=DwdRadarParameter.SWEEP_VOL_REFLECTIVITY_H,
        start_date=start_date,
        end_date=end_date,
        elevation=el,
        site=DwdRadarSite.ESS,fmt=DwdRadarDataFormat.HDF5,
        subset=DwdRadarDataSubset.POLARIMETRIC,
    )

    # Submit requests.
    results_velocity.append(request_velocity.query())
    results_reflectivity.append(request_reflectivity.query())

Acquire data as memory buffer

%%time
volume_velocity = []
for item1 in results_velocity:
    files = []
    for item2 in item1:
        files.append(item2.data)
    volume_velocity.append(files)

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CPU times: user 5.39 s, sys: 104 ms, total: 5.49 s
Wall time: 21.2 s

%%time
volume_reflectivity = []
for item1 in results_reflectivity:
    files = []
    for item2 in item1:
        files.append(item2.data)
    volume_reflectivity.append(files)

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CPU times: user 5.65 s, sys: 77.5 ms, total: 5.73 s
Wall time: 19.8 s

Read the data into xarray powered structure

vol = wrl.io.RadarVolume()
for r, v in zip(volume_reflectivity, volume_velocity):
    ds0 = wrl.io.open_odim_mfdataset(r, group="dataset1",
                                     concat_dim="time",
                                     combine="nested",
                                    )
    ds1 = wrl.io.open_odim_mfdataset(v, group="dataset1",
                                     concat_dim="time",
                                     combine="nested",
                                    )

    vol.append(xr.merge([ds0, ds1], combine_attrs="override"))
    vol.sort(key=lambda x: x.time.min().values)

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Inspect structure

Root Group

vol.root

<xarray.Dataset>
Dimensions:              (sweep: 10)
Coordinates:
    sweep_mode           <U20 'azimuth_surveillance'
    longitude            float64 6.967
    altitude             float64 185.1
    latitude             float64 51.41
Dimensions without coordinates: sweep
Data variables:
    volume_number        int64 0
    platform_type        <U5 'fixed'
    instrument_type      <U5 'radar'
    primary_axis         <U6 'axis_z'
    time_coverage_start  <U20 '2022-05-19T11:15:35Z'
    time_coverage_end    <U20 '2022-05-19T11:47:30Z'
    sweep_group_name     (sweep) <U7 'sweep_0' 'sweep_1' ... 'sweep_8' 'sweep_9'
    sweep_fixed_angle    (sweep) float64 5.5 4.5 3.5 2.5 ... 8.0 12.0 17.0 25.0
Attributes:
    version:          None
    title:            None
    institution:      None
    references:       None
    source:           None
    history:          None
    comment:          im/exported using wradlib
    instrument_name:  None
    fixed_angle:      5.5

xarray.Dataset

• Dimensions:
  • sweep: 10
• Coordinates: (4)
  • sweep_mode
    ()
    <U20
    'azimuth_surveillance'

    array('azimuth_surveillance', dtype='<U20')

  • longitude
    ()
    float64
    6.967

    long_name :

    longitude

    units :

    degrees_east

    standard_name :

    longitude

    array(6.967111)

  • altitude
    ()
    float64
    185.1

    long_name :

    altitude

    units :

    meters

    standard_name :

    altitude

    array(185.11)

  • latitude
    ()
    float64
    51.41

    long_name :

    latitude

    units :

    degrees_north

    positive :

    up

    standard_name :

    latitude

    array(51.405649)

• Data variables: (8)
  • volume_number
    ()
    int64
    0

    array(0)

  • platform_type
    ()
    <U5
    'fixed'

    array('fixed', dtype='<U5')

  • instrument_type
    ()
    <U5
    'radar'

    array('radar', dtype='<U5')

  • primary_axis
    ()
    <U6
    'axis_z'

    array('axis_z', dtype='<U6')

  • time_coverage_start
    ()
    <U20
    '2022-05-19T11:15:35Z'

    array('2022-05-19T11:15:35Z', dtype='<U20')

  • time_coverage_end
    ()
    <U20
    '2022-05-19T11:47:30Z'

    array('2022-05-19T11:47:30Z', dtype='<U20')

  • sweep_group_name
    (sweep)
    <U7
    'sweep_0' 'sweep_1' ... 'sweep_9'

    array(['sweep_0', 'sweep_1', 'sweep_2', 'sweep_3', 'sweep_4', 'sweep_5',
           'sweep_6', 'sweep_7', 'sweep_8', 'sweep_9'], dtype='<U7')

  • sweep_fixed_angle
    (sweep)
    float64
    5.5 4.5 3.5 2.5 ... 12.0 17.0 25.0

    array([ 5.5,  4.5,  3.5,  2.5,  1.5,  0.5,  8. , 12. , 17. , 25. ])

• Attributes: (9)

  version :

  None

  title :

  None

  institution :

  None

  references :

  None

  source :

  None

  history :

  None

  comment :

  im/exported using wradlib

  instrument_name :

  None

  fixed_angle :

  5.5

vol.root.sweep_fixed_angle

<xarray.DataArray 'sweep_fixed_angle' (sweep: 10)>
array([ 5.5,  4.5,  3.5,  2.5,  1.5,  0.5,  8. , 12. , 17. , 25. ])
Coordinates:
    sweep_mode  <U20 'azimuth_surveillance'
    longitude   float64 6.967
    altitude    float64 185.1
    latitude    float64 51.41
Dimensions without coordinates: sweep

xarray.DataArray

'sweep_fixed_angle'

• sweep: 10

• 5.5 4.5 3.5 2.5 1.5 0.5 8.0 12.0 17.0 25.0

  array([ 5.5,  4.5,  3.5,  2.5,  1.5,  0.5,  8. , 12. , 17. , 25. ])

• Coordinates: (4)
  • sweep_mode
    ()
    <U20
    'azimuth_surveillance'

    array('azimuth_surveillance', dtype='<U20')

  • longitude
    ()
    float64
    6.967

    long_name :

    longitude

    units :

    degrees_east

    standard_name :

    longitude

    array(6.967111)

  • altitude
    ()
    float64
    185.1

    long_name :

    altitude

    units :

    meters

    standard_name :

    altitude

    array(185.11)

  • latitude
    ()
    float64
    51.41

    long_name :

    latitude

    units :

    degrees_north

    positive :

    up

    standard_name :

    latitude

    array(51.405649)

• Attributes: (0)

Sweep Groups

vol

<wradlib.RadarVolume>
Dimension(s): (sweep: 10)
Elevation(s): (5.5, 4.5, 3.5, 2.5, 1.5, 0.5, 8.0, 12.0, 17.0, 25.0)

vol[0]

<xarray.Dataset>
Dimensions:     (azimuth: 360, time: 7, range: 720)
Coordinates:
  * azimuth     (azimuth) float64 0.5 1.5 2.5 3.5 ... 356.5 357.5 358.5 359.5
    elevation   (azimuth) float64 dask.array<chunksize=(360,), meta=np.ndarray>
    rtime       (time, azimuth) datetime64[ns] dask.array<chunksize=(1, 360), meta=np.ndarray>
  * range       (range) float32 125.0 375.0 625.0 ... 1.796e+05 1.799e+05
  * time        (time) datetime64[ns] 2022-05-19T11:15:35 ... 2022-05-19T11:4...
    sweep_mode  <U20 'azimuth_surveillance'
    longitude   float64 6.967
    latitude    float64 51.41
    altitude    float64 185.1
Data variables:
    DBZH        (time, azimuth, range) float32 dask.array<chunksize=(1, 360, 720), meta=np.ndarray>
    VRADH       (time, azimuth, range) float32 dask.array<chunksize=(1, 360, 720), meta=np.ndarray>
Attributes:
    fixed_angle:  5.5

xarray.Dataset

• Dimensions:
  • azimuth: 360
  • time: 7
  • range: 720
• Coordinates: (9)
  • azimuth
    (azimuth)
    float64
    0.5 1.5 2.5 ... 357.5 358.5 359.5

    standard_name :

    ray_azimuth_angle

    long_name :

    azimuth_angle_from_true_north

    units :

    degrees

    axis :

    radial_azimuth_coordinate

    a1gate :

    53

    angle_res :

    1.0

    array([  0.5,   1.5,   2.5, ..., 357.5, 358.5, 359.5])

  • elevation
    (azimuth)
    float64
    dask.array<chunksize=(360,), meta=np.ndarray>

    standard_name :

    ray_elevation_angle

    long_name :

    elevation_angle_from_horizontal_plane

    units :

    degrees

    axis :

    radial_elevation_coordinate

    Array Chunk Bytes 2.81 kiB 2.81 kiB Shape (360,) (360,) Count 31 Tasks 1 Chunks Type float64 numpy.ndarray

  • rtime
    (time, azimuth)
    datetime64[ns]
    dask.array<chunksize=(1, 360), meta=np.ndarray>

    standard_name :

    time

    Array Chunk Bytes 19.69 kiB 2.81 kiB Shape (7, 360) (1, 360) Count 61 Tasks 7 Chunks Type datetime64[ns] numpy.ndarray

  • range
    (range)
    float32
    125.0 375.0 ... 1.796e+05 1.799e+05

    units :

    meters

    standard_name :

    projection_range_coordinate

    long_name :

    range_to_measurement_volume

    spacing_is_constant :

    true

    axis :

    radial_range_coordinate

    meters_to_center_of_first_gate :

    125.0

    meters_between_gates :

    250.0

    array([1.25000e+02, 3.75000e+02, 6.25000e+02, ..., 1.79375e+05, 1.79625e+05,
           1.79875e+05], dtype=float32)

  • time
    (time)
    datetime64[ns]
    2022-05-19T11:15:35 ... 2022-05-...

    standard_name :

    time

    array(['2022-05-19T11:15:35.000000000', '2022-05-19T11:20:35.000000000',
           '2022-05-19T11:25:35.000000000', '2022-05-19T11:30:35.000000000',
           '2022-05-19T11:35:35.000000000', '2022-05-19T11:40:35.000000000',
           '2022-05-19T11:45:35.000000000'], dtype='datetime64[ns]')

  • sweep_mode
    ()
    <U20
    'azimuth_surveillance'

    array('azimuth_surveillance', dtype='<U20')

  • longitude
    ()
    float64
    6.967

    long_name :

    longitude

    units :

    degrees_east

    standard_name :

    longitude

    array(6.967111)

  • latitude
    ()
    float64
    51.41

    long_name :

    latitude

    units :

    degrees_north

    positive :

    up

    standard_name :

    latitude

    array(51.405649)

  • altitude
    ()
    float64
    185.1

    long_name :

    altitude

    units :

    meters

    standard_name :

    altitude

    array(185.11)

• Data variables: (2)
  • DBZH
    (time, azimuth, range)
    float32
    dask.array<chunksize=(1, 360, 720), meta=np.ndarray>

    _Undetect :

    0.0

    long_name :

    Equivalent reflectivity factor H

    units :

    dBZ

    standard_name :

    radar_equivalent_reflectivity_factor_h

    Array Chunk Bytes 6.92 MiB 0.99 MiB Shape (7, 360, 720) (1, 360, 720) Count 28 Tasks 7 Chunks Type float32 numpy.ndarray

  • VRADH
    (time, azimuth, range)
    float32
    dask.array<chunksize=(1, 360, 720), meta=np.ndarray>

    _Undetect :

    0.0

    long_name :

    Radial velocity of scatterers away from instrument H

    units :

    meters per seconds

    standard_name :

    radial_velocity_of_scatterers_away_from_instrument_h

    Array Chunk Bytes 6.92 MiB 0.99 MiB Shape (7, 360, 720) (1, 360, 720) Count 28 Tasks 7 Chunks Type float32 numpy.ndarray

• Attributes: (1)

  fixed_angle :

  5.5

plot sweeps

DBZH

fig = pl.figure(figsize=(20, 30))
import matplotlib.gridspec as gridspec
gs = gridspec.GridSpec(4, 3, wspace=0.4, hspace=0.4)
for i, ts in enumerate(vol):
    swp = ts.isel(time=0)
    swp.DBZH.pipe(wrl.georef.georeference_dataset).wradlib.plot(ax=gs[i], fig=fig)
    ax = pl.gca()
    ax.set_title(vol.root.sweep_fixed_angle[i].values)

VRADH

fig = pl.figure(figsize=(20, 30))
import matplotlib.gridspec as gridspec
gs = gridspec.GridSpec(4, 3, wspace=0.4, hspace=0.4)
for i, ts in enumerate(vol):
    swp = ts.isel(time=0)
    swp.VRADH.pipe(wrl.georef.georeference_dataset).wradlib.plot(ax=gs[i], fig=fig)
    ax = pl.gca()
    ax.set_title(vol.root.sweep_fixed_angle[i].values)

Plot single sweep using cartopy

import cartopy
import cartopy.crs as ccrs
import cartopy.feature as cfeature

map_trans = ccrs.AzimuthalEquidistant(central_latitude=vol.root.latitude.values,
                                      central_longitude=vol.root.longitude.values)

vol[-1]

<xarray.Dataset>
Dimensions:     (azimuth: 360, time: 6, range: 240)
Coordinates:
  * azimuth     (azimuth) float64 0.5 1.5 2.5 3.5 ... 356.5 357.5 358.5 359.5
    elevation   (azimuth) float64 dask.array<chunksize=(360,), meta=np.ndarray>
    rtime       (time, azimuth) datetime64[ns] dask.array<chunksize=(1, 360), meta=np.ndarray>
  * range       (range) float32 125.0 375.0 625.0 ... 5.962e+04 5.988e+04
  * time        (time) datetime64[ns] 2022-05-19T11:18:51 ... 2022-05-19T11:4...
    sweep_mode  <U20 'azimuth_surveillance'
    longitude   float64 6.967
    latitude    float64 51.41
    altitude    float64 185.1
Data variables:
    DBZH        (time, azimuth, range) float32 dask.array<chunksize=(1, 360, 240), meta=np.ndarray>
    VRADH       (time, azimuth, range) float32 dask.array<chunksize=(1, 360, 240), meta=np.ndarray>
Attributes:
    fixed_angle:  25.0

xarray.Dataset

• Dimensions:
  • azimuth: 360
  • time: 6
  • range: 240
• Coordinates: (9)
  • azimuth
    (azimuth)
    float64
    0.5 1.5 2.5 ... 357.5 358.5 359.5

    standard_name :

    ray_azimuth_angle

    long_name :

    azimuth_angle_from_true_north

    units :

    degrees

    axis :

    radial_azimuth_coordinate

    a1gate :

    244

    angle_res :

    1.0

    array([  0.5,   1.5,   2.5, ..., 357.5, 358.5, 359.5])

  • elevation
    (azimuth)
    float64
    dask.array<chunksize=(360,), meta=np.ndarray>

    standard_name :

    ray_elevation_angle

    long_name :

    elevation_angle_from_horizontal_plane

    units :

    degrees

    axis :

    radial_elevation_coordinate

    Array Chunk Bytes 2.81 kiB 2.81 kiB Shape (360,) (360,) Count 26 Tasks 1 Chunks Type float64 numpy.ndarray

  • rtime
    (time, azimuth)
    datetime64[ns]
    dask.array<chunksize=(1, 360), meta=np.ndarray>

    standard_name :

    time

    Array Chunk Bytes 16.88 kiB 2.81 kiB Shape (6, 360) (1, 360) Count 52 Tasks 6 Chunks Type datetime64[ns] numpy.ndarray

  • range
    (range)
    float32
    125.0 375.0 ... 5.962e+04 5.988e+04

    units :

    meters

    standard_name :

    projection_range_coordinate

    long_name :

    range_to_measurement_volume

    spacing_is_constant :

    true

    axis :

    radial_range_coordinate

    meters_to_center_of_first_gate :

    125.0

    meters_between_gates :

    250.0

    array([  125.,   375.,   625., ..., 59375., 59625., 59875.], dtype=float32)

  • time
    (time)
    datetime64[ns]
    2022-05-19T11:18:51 ... 2022-05-...

    standard_name :

    time

    array(['2022-05-19T11:18:51.000000000', '2022-05-19T11:23:51.000000000',
           '2022-05-19T11:28:51.000000000', '2022-05-19T11:33:51.000000000',
           '2022-05-19T11:38:51.000000000', '2022-05-19T11:43:51.000000000'],
          dtype='datetime64[ns]')

  • sweep_mode
    ()
    <U20
    'azimuth_surveillance'

    array('azimuth_surveillance', dtype='<U20')

  • longitude
    ()
    float64
    6.967

    long_name :

    longitude

    units :

    degrees_east

    standard_name :

    longitude

    array(6.967111)

  • latitude
    ()
    float64
    51.41

    long_name :

    latitude

    units :

    degrees_north

    positive :

    up

    standard_name :

    latitude

    array(51.405649)

  • altitude
    ()
    float64
    185.1

    long_name :

    altitude

    units :

    meters

    standard_name :

    altitude

    array(185.11)

• Data variables: (2)
  • DBZH
    (time, azimuth, range)
    float32
    dask.array<chunksize=(1, 360, 240), meta=np.ndarray>

    _Undetect :

    0.0

    long_name :

    Equivalent reflectivity factor H

    units :

    dBZ

    standard_name :

    radar_equivalent_reflectivity_factor_h

    Array Chunk Bytes 1.98 MiB 337.50 kiB Shape (6, 360, 240) (1, 360, 240) Count 24 Tasks 6 Chunks Type float32 numpy.ndarray

  • VRADH
    (time, azimuth, range)
    float32
    dask.array<chunksize=(1, 360, 240), meta=np.ndarray>

    _Undetect :

    0.0

    long_name :

    Radial velocity of scatterers away from instrument H

    units :

    meters per seconds

    standard_name :

    radial_velocity_of_scatterers_away_from_instrument_h

    Array Chunk Bytes 1.98 MiB 337.50 kiB Shape (6, 360, 240) (1, 360, 240) Count 24 Tasks 6 Chunks Type float32 numpy.ndarray

• Attributes: (1)

  fixed_angle :

  25.0

map_proj = ccrs.AzimuthalEquidistant(central_latitude=vol.root.latitude.values,
                                      central_longitude=vol.root.longitude.values)
pm = vol[-1].isel(time=0).DBZH.pipe(wrl.georef.georeference_dataset).wradlib.plot_ppi(proj=map_proj)
ax = pl.gca()
ax.gridlines(crs=map_proj)
print(ax)

< GeoAxes: +proj=aeqd +ellps=WGS84 +lon_0=6.967111 +lat_0=51.405649 +x_0=0.0 +y_0=0.0 +no_defs +type=crs >

map_proj = ccrs.Mercator(central_longitude=vol.root.longitude.values)
fig = pl.figure(figsize=(10,8))
ax = fig.add_subplot(111, projection=map_proj)
pm = vol[-1].isel(time=0).DBZH.pipe(wrl.georef.georeference_dataset).wradlib.plot_ppi(ax=ax)
ax.gridlines(draw_labels=True)

<cartopy.mpl.gridliner.Gridliner at 0x7fa11f1a84c0>

fig = pl.figure(figsize=(10, 8))
proj=ccrs.AzimuthalEquidistant(central_latitude=vol.root.latitude.values,
                               central_longitude=vol.root.longitude.values)
ax = fig.add_subplot(111, projection=proj)
pm = vol[-1].isel(time=0).DBZH.pipe(wrl.georef.georeference_dataset).wradlib.plot_ppi(ax=ax)
ax.gridlines()

<cartopy.mpl.gridliner.Gridliner at 0x7fa11fcf8490>

Inspect radar moments

The DataArrays can be accessed by key or by attribute. Each DataArray inherits dimensions and coordinates of it’s parent dataset. There are attributes connected which are defined by Cf/Radial and/or ODIM_H5 standard.

vol[-1].isel(time=0).DBZH

<xarray.DataArray 'DBZH' (azimuth: 360, range: 240)>
dask.array<getitem, shape=(360, 240), dtype=float32, chunksize=(360, 240), chunktype=numpy.ndarray>
Coordinates:
  * azimuth     (azimuth) float64 0.5 1.5 2.5 3.5 ... 356.5 357.5 358.5 359.5
    elevation   (azimuth) float64 dask.array<chunksize=(360,), meta=np.ndarray>
    rtime       (azimuth) datetime64[ns] dask.array<chunksize=(360,), meta=np.ndarray>
  * range       (range) float32 125.0 375.0 625.0 ... 5.962e+04 5.988e+04
    time        datetime64[ns] 2022-05-19T11:18:51
    sweep_mode  <U20 'azimuth_surveillance'
    longitude   float64 6.967
    latitude    float64 51.41
    altitude    float64 185.1
Attributes:
    _Undetect:      0.0
    long_name:      Equivalent reflectivity factor H
    units:          dBZ
    standard_name:  radar_equivalent_reflectivity_factor_h

xarray.DataArray

'DBZH'

• azimuth: 360
• range: 240

• dask.array<chunksize=(360, 240), meta=np.ndarray>

  Array Chunk Bytes 337.50 kiB 337.50 kiB Shape (360, 240) (360, 240) Count 25 Tasks 1 Chunks Type float32 numpy.ndarray

• Coordinates: (9)
  • azimuth
    (azimuth)
    float64
    0.5 1.5 2.5 ... 357.5 358.5 359.5

    standard_name :

    ray_azimuth_angle

    long_name :

    azimuth_angle_from_true_north

    units :

    degrees

    axis :

    radial_azimuth_coordinate

    a1gate :

    244

    angle_res :

    1.0

    array([  0.5,   1.5,   2.5, ..., 357.5, 358.5, 359.5])

  • elevation
    (azimuth)
    float64
    dask.array<chunksize=(360,), meta=np.ndarray>

    standard_name :

    ray_elevation_angle

    long_name :

    elevation_angle_from_horizontal_plane

    units :

    degrees

    axis :

    radial_elevation_coordinate

    Array Chunk Bytes 2.81 kiB 2.81 kiB Shape (360,) (360,) Count 26 Tasks 1 Chunks Type float64 numpy.ndarray

  • rtime
    (azimuth)
    datetime64[ns]
    dask.array<chunksize=(360,), meta=np.ndarray>

    standard_name :

    time

    Array Chunk Bytes 2.81 kiB 2.81 kiB Shape (360,) (360,) Count 53 Tasks 1 Chunks Type datetime64[ns] numpy.ndarray

  • range
    (range)
    float32
    125.0 375.0 ... 5.962e+04 5.988e+04

    units :

    meters

    standard_name :

    projection_range_coordinate

    long_name :

    range_to_measurement_volume

    spacing_is_constant :

    true

    axis :

    radial_range_coordinate

    meters_to_center_of_first_gate :

    125.0

    meters_between_gates :

    250.0

    array([  125.,   375.,   625., ..., 59375., 59625., 59875.], dtype=float32)

  • time
    ()
    datetime64[ns]
    2022-05-19T11:18:51

    standard_name :

    time

    array('2022-05-19T11:18:51.000000000', dtype='datetime64[ns]')

  • sweep_mode
    ()
    <U20
    'azimuth_surveillance'

    array('azimuth_surveillance', dtype='<U20')

  • longitude
    ()
    float64
    6.967

    long_name :

    longitude

    units :

    degrees_east

    standard_name :

    longitude

    array(6.967111)

  • latitude
    ()
    float64
    51.41

    long_name :

    latitude

    units :

    degrees_north

    positive :

    up

    standard_name :

    latitude

    array(51.405649)

  • altitude
    ()
    float64
    185.1

    long_name :

    altitude

    units :

    meters

    standard_name :

    altitude

    array(185.11)

• Attributes: (4)

  _Undetect :

  0.0

  long_name :

  Equivalent reflectivity factor H

  units :

  dBZ

  standard_name :

  radar_equivalent_reflectivity_factor_h

vol[-1].isel(time=0).sweep_mode

<xarray.DataArray 'sweep_mode' ()>
array('azimuth_surveillance', dtype='<U20')
Coordinates:
    time        datetime64[ns] 2022-05-19T11:18:51
    sweep_mode  <U20 'azimuth_surveillance'
    longitude   float64 6.967
    latitude    float64 51.41
    altitude    float64 185.1

xarray.DataArray

'sweep_mode'

• 'azimuth_surveillance'

  array('azimuth_surveillance', dtype='<U20')

• Coordinates: (5)
  • time
    ()
    datetime64[ns]
    2022-05-19T11:18:51

    standard_name :

    time

    array('2022-05-19T11:18:51.000000000', dtype='datetime64[ns]')

  • sweep_mode
    ()
    <U20
    'azimuth_surveillance'

    array('azimuth_surveillance', dtype='<U20')

  • longitude
    ()
    float64
    6.967

    long_name :

    longitude

    units :

    degrees_east

    standard_name :

    longitude

    array(6.967111)

  • latitude
    ()
    float64
    51.41

    long_name :

    latitude

    units :

    degrees_north

    positive :

    up

    standard_name :

    latitude

    array(51.405649)

  • altitude
    ()
    float64
    185.1

    long_name :

    altitude

    units :

    meters

    standard_name :

    altitude

    array(185.11)

• Attributes: (0)

vol.root

<xarray.Dataset>
Dimensions:              (sweep: 10)
Coordinates:
    sweep_mode           <U20 'azimuth_surveillance'
    longitude            float64 6.967
    altitude             float64 185.1
    latitude             float64 51.41
Dimensions without coordinates: sweep
Data variables:
    volume_number        int64 0
    platform_type        <U5 'fixed'
    instrument_type      <U5 'radar'
    primary_axis         <U6 'axis_z'
    time_coverage_start  <U20 '2022-05-19T11:15:35Z'
    time_coverage_end    <U20 '2022-05-19T11:47:30Z'
    sweep_group_name     (sweep) <U7 'sweep_0' 'sweep_1' ... 'sweep_8' 'sweep_9'
    sweep_fixed_angle    (sweep) float64 5.5 4.5 3.5 2.5 ... 8.0 12.0 17.0 25.0
Attributes:
    version:          None
    title:            None
    institution:      None
    references:       None
    source:           None
    history:          None
    comment:          im/exported using wradlib
    instrument_name:  None
    fixed_angle:      5.5

xarray.Dataset

• Dimensions:
  • sweep: 10
• Coordinates: (4)
  • sweep_mode
    ()
    <U20
    'azimuth_surveillance'

    array('azimuth_surveillance', dtype='<U20')

  • longitude
    ()
    float64
    6.967

    long_name :

    longitude

    units :

    degrees_east

    standard_name :

    longitude

    array(6.967111)

  • altitude
    ()
    float64
    185.1

    long_name :

    altitude

    units :

    meters

    standard_name :

    altitude

    array(185.11)

  • latitude
    ()
    float64
    51.41

    long_name :

    latitude

    units :

    degrees_north

    positive :

    up

    standard_name :

    latitude

    array(51.405649)

• Data variables: (8)
  • volume_number
    ()
    int64
    0

    array(0)

  • platform_type
    ()
    <U5
    'fixed'

    array('fixed', dtype='<U5')

  • instrument_type
    ()
    <U5
    'radar'

    array('radar', dtype='<U5')

  • primary_axis
    ()
    <U6
    'axis_z'

    array('axis_z', dtype='<U6')

  • time_coverage_start
    ()
    <U20
    '2022-05-19T11:15:35Z'

    array('2022-05-19T11:15:35Z', dtype='<U20')

  • time_coverage_end
    ()
    <U20
    '2022-05-19T11:47:30Z'

    array('2022-05-19T11:47:30Z', dtype='<U20')

  • sweep_group_name
    (sweep)
    <U7
    'sweep_0' 'sweep_1' ... 'sweep_9'

    array(['sweep_0', 'sweep_1', 'sweep_2', 'sweep_3', 'sweep_4', 'sweep_5',
           'sweep_6', 'sweep_7', 'sweep_8', 'sweep_9'], dtype='<U7')

  • sweep_fixed_angle
    (sweep)
    float64
    5.5 4.5 3.5 2.5 ... 12.0 17.0 25.0

    array([ 5.5,  4.5,  3.5,  2.5,  1.5,  0.5,  8. , 12. , 17. , 25. ])

• Attributes: (9)

  version :

  None

  title :

  None

  institution :

  None

  references :

  None

  source :

  None

  history :

  None

  comment :

  im/exported using wradlib

  instrument_name :

  None

  fixed_angle :

  5.5

Plot Quasi Vertical Profile

vol

<wradlib.RadarVolume>
Dimension(s): (sweep: 10)
Elevation(s): (5.5, 4.5, 3.5, 2.5, 1.5, 0.5, 8.0, 12.0, 17.0, 25.0)

ts = vol[-1]
ts

<xarray.Dataset>
Dimensions:     (azimuth: 360, time: 6, range: 240)
Coordinates:
  * azimuth     (azimuth) float64 0.5 1.5 2.5 3.5 ... 356.5 357.5 358.5 359.5
    elevation   (azimuth) float64 dask.array<chunksize=(360,), meta=np.ndarray>
    rtime       (time, azimuth) datetime64[ns] dask.array<chunksize=(1, 360), meta=np.ndarray>
  * range       (range) float32 125.0 375.0 625.0 ... 5.962e+04 5.988e+04
  * time        (time) datetime64[ns] 2022-05-19T11:18:51 ... 2022-05-19T11:4...
    sweep_mode  <U20 'azimuth_surveillance'
    longitude   float64 6.967
    latitude    float64 51.41
    altitude    float64 185.1
Data variables:
    DBZH        (time, azimuth, range) float32 dask.array<chunksize=(1, 360, 240), meta=np.ndarray>
    VRADH       (time, azimuth, range) float32 dask.array<chunksize=(1, 360, 240), meta=np.ndarray>
Attributes:
    fixed_angle:  25.0

xarray.Dataset

• Dimensions:
  • azimuth: 360
  • time: 6
  • range: 240
• Coordinates: (9)
  • azimuth
    (azimuth)
    float64
    0.5 1.5 2.5 ... 357.5 358.5 359.5

    standard_name :

    ray_azimuth_angle

    long_name :

    azimuth_angle_from_true_north

    units :

    degrees

    axis :

    radial_azimuth_coordinate

    a1gate :

    244

    angle_res :

    1.0

    array([  0.5,   1.5,   2.5, ..., 357.5, 358.5, 359.5])

  • elevation
    (azimuth)
    float64
    dask.array<chunksize=(360,), meta=np.ndarray>

    standard_name :

    ray_elevation_angle

    long_name :

    elevation_angle_from_horizontal_plane

    units :

    degrees

    axis :

    radial_elevation_coordinate

    Array Chunk Bytes 2.81 kiB 2.81 kiB Shape (360,) (360,) Count 26 Tasks 1 Chunks Type float64 numpy.ndarray

  • rtime
    (time, azimuth)
    datetime64[ns]
    dask.array<chunksize=(1, 360), meta=np.ndarray>

    standard_name :

    time

    Array Chunk Bytes 16.88 kiB 2.81 kiB Shape (6, 360) (1, 360) Count 52 Tasks 6 Chunks Type datetime64[ns] numpy.ndarray

  • range
    (range)
    float32
    125.0 375.0 ... 5.962e+04 5.988e+04

    units :

    meters

    standard_name :

    projection_range_coordinate

    long_name :

    range_to_measurement_volume

    spacing_is_constant :

    true

    axis :

    radial_range_coordinate

    meters_to_center_of_first_gate :

    125.0

    meters_between_gates :

    250.0

    array([  125.,   375.,   625., ..., 59375., 59625., 59875.], dtype=float32)

  • time
    (time)
    datetime64[ns]
    2022-05-19T11:18:51 ... 2022-05-...

    standard_name :

    time

    array(['2022-05-19T11:18:51.000000000', '2022-05-19T11:23:51.000000000',
           '2022-05-19T11:28:51.000000000', '2022-05-19T11:33:51.000000000',
           '2022-05-19T11:38:51.000000000', '2022-05-19T11:43:51.000000000'],
          dtype='datetime64[ns]')

  • sweep_mode
    ()
    <U20
    'azimuth_surveillance'

    array('azimuth_surveillance', dtype='<U20')

  • longitude
    ()
    float64
    6.967

    long_name :

    longitude

    units :

    degrees_east

    standard_name :

    longitude

    array(6.967111)

  • latitude
    ()
    float64
    51.41

    long_name :

    latitude

    units :

    degrees_north

    positive :

    up

    standard_name :

    latitude

    array(51.405649)

  • altitude
    ()
    float64
    185.1

    long_name :

    altitude

    units :

    meters

    standard_name :

    altitude

    array(185.11)

• Data variables: (2)
  • DBZH
    (time, azimuth, range)
    float32
    dask.array<chunksize=(1, 360, 240), meta=np.ndarray>

    _Undetect :

    0.0

    long_name :

    Equivalent reflectivity factor H

    units :

    dBZ

    standard_name :

    radar_equivalent_reflectivity_factor_h

    Array Chunk Bytes 1.98 MiB 337.50 kiB Shape (6, 360, 240) (1, 360, 240) Count 24 Tasks 6 Chunks Type float32 numpy.ndarray

  • VRADH
    (time, azimuth, range)
    float32
    dask.array<chunksize=(1, 360, 240), meta=np.ndarray>

    _Undetect :

    0.0

    long_name :

    Radial velocity of scatterers away from instrument H

    units :

    meters per seconds

    standard_name :

    radial_velocity_of_scatterers_away_from_instrument_h

    Array Chunk Bytes 1.98 MiB 337.50 kiB Shape (6, 360, 240) (1, 360, 240) Count 24 Tasks 6 Chunks Type float32 numpy.ndarray

• Attributes: (1)

  fixed_angle :

  25.0

fig = pl.figure(figsize=(10, 4))
ax = fig.add_subplot(111)
ts.DBZH.median('azimuth').plot(x='time', vmin=-10, vmax=30, ax=ax)
ax.set_title(f"{np.datetime_as_string(ts.time[0].values, unit='D')}")
ax.set_ylim(0, 20000)

(0.0, 20000.0)

Export to OdimH5

This exports the radar volume at given timestep including all moments into one ODIM_H5 compliant data file.

vol.to_odim('dwd_odim.h5', timestep=0)

Export to Cf/Radial2

This exports the radar volume at given timestep including all moments into one Cf/Radial2 compliant data file.

vol.to_cfradial2('dwd_cfradial2.nc', timestep=0)

Import again and check equality

vol1 = wrl.io.open_odim_dataset('dwd_odim.h5')
vol2 = wrl.io.open_cfradial2_dataset('dwd_cfradial2.nc')

xr.testing.assert_equal(vol1.root, vol2.root)
for i in range(len(vol1)):
    xr.testing.assert_equal(vol1[i].drop_vars("rtime"), vol2[i].drop_vars("rtime"))