xarray ODIM backend

In this example, we read ODIM_H5 (HDF5) data files using the xarray odim backend.

import glob
import os
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_dataset

Load ODIM_H5 Volume Data

fpath = 'hdf5/knmi_polar_volume.h5'
f = wrl.util.get_wradlib_data_file(fpath)
vol = wrl.io.open_odim_dataset(f)

Inspect RadarVolume

display(vol)

<wradlib.RadarVolume>
Dimension(s): (sweep: 14)
Elevation(s): (0.3, 0.4, 0.8, 1.1, 2.0, 3.0, 4.5, 6.0, 8.0, 10.0, 12.0, 15.0, 20.0, 25.0)

Inspect root group

The sweep dimension contains the number of scans in this radar volume. Further the dataset consists of variables (location coordinates, time_coverage) and attributes (Conventions, metadata).

vol.root

<xarray.Dataset>
Dimensions:              (sweep: 14)
Coordinates:
    time                 datetime64[ns] 2011-06-10T11:40:02
    sweep_mode           <U20 'azimuth_surveillance'
    longitude            float64 4.79
    altitude             float64 50.0
    latitude             float64 52.95
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 '2011-06-10T11:40:02Z'
    time_coverage_end    <U20 '2011-06-10T11:43:54Z'
    sweep_group_name     (sweep) <U8 'sweep_0' 'sweep_1' ... 'sweep_13'
    sweep_fixed_angle    (sweep) float64 0.3 0.4 0.8 1.1 ... 12.0 15.0 20.0 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:      0.30000001192092896

xarray.Dataset

• Dimensions:
  • sweep: 14
• Coordinates: (5)
  • time
    ()
    datetime64[ns]
    2011-06-10T11:40:02

    standard_name :

    time

    array('2011-06-10T11:40:02.000000000', dtype='datetime64[ns]')

  • sweep_mode
    ()
    <U20
    'azimuth_surveillance'

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

  • longitude
    ()
    float64
    4.79

    long_name :

    longitude

    units :

    degrees_east

    standard_name :

    longitude

    array(4.78996992)

  • altitude
    ()
    float64
    50.0

    long_name :

    altitude

    units :

    meters

    standard_name :

    altitude

    array(50.)

  • latitude
    ()
    float64
    52.95

    long_name :

    latitude

    units :

    degrees_north

    positive :

    up

    standard_name :

    latitude

    array(52.95333862)

• 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
    '2011-06-10T11:40:02Z'

    array('2011-06-10T11:40:02Z', dtype='<U20')

  • time_coverage_end
    ()
    <U20
    '2011-06-10T11:43:54Z'

    array('2011-06-10T11:43:54Z', dtype='<U20')

  • sweep_group_name
    (sweep)
    <U8
    'sweep_0' 'sweep_1' ... 'sweep_13'

    array(['sweep_0', 'sweep_1', 'sweep_2', 'sweep_3', 'sweep_4', 'sweep_5',
           'sweep_6', 'sweep_7', 'sweep_8', 'sweep_9', 'sweep_10', 'sweep_11',
           'sweep_12', 'sweep_13'], dtype='<U8')

  • sweep_fixed_angle
    (sweep)
    float64
    0.3 0.4 0.8 1.1 ... 15.0 20.0 25.0

    array([ 0.30000001,  0.40000001,  0.80000001,  1.10000002,  2.        ,
            3.        ,  4.5       ,  6.        ,  8.        , 10.        ,
           12.        , 15.        , 20.        , 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 :

  0.30000001192092896

Inspect sweep group(s)

The sweep-groups can be accessed via their respective keys. The dimensions consist of range and time with added coordinates azimuth, elevation, range and time. There will be variables like radar moments (DBZH etc.) and sweep-dependend metadata (like fixed_angle, sweep_mode etc.).

display(vol[0])

<xarray.Dataset>
Dimensions:     (azimuth: 360, range: 320)
Coordinates:
  * azimuth     (azimuth) float32 0.5 1.5 2.5 3.5 ... 356.5 357.5 358.5 359.5
    elevation   (azimuth) float32 0.3 0.3 0.3 0.3 0.3 ... 0.3 0.3 0.3 0.3 0.3
    rtime       (azimuth) datetime64[ns] 2011-06-10T11:40:17.361118208 ... 20...
  * range       (range) float32 500.0 1.5e+03 2.5e+03 ... 3.185e+05 3.195e+05
    time        datetime64[ns] 2011-06-10T11:40:02
    sweep_mode  <U20 'azimuth_surveillance'
    longitude   float64 4.79
    latitude    float64 52.95
    altitude    float64 50.0
Data variables:
    DBZH        (azimuth, range) float32 ...
Attributes:
    fixed_angle:  0.30000001192092896

xarray.Dataset

• Dimensions:
  • azimuth: 360
  • range: 320
• Coordinates: (9)
  • azimuth
    (azimuth)
    float32
    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 :

    84

    angle_res :

    1.0

    array([  0.5,   1.5,   2.5, ..., 357.5, 358.5, 359.5], dtype=float32)

  • elevation
    (azimuth)
    float32
    ...

    standard_name :

    ray_elevation_angle

    long_name :

    elevation_angle_from_horizontal_plane

    units :

    degrees

    axis :

    radial_elevation_coordinate

    array([0.3, 0.3, 0.3, ..., 0.3, 0.3, 0.3], dtype=float32)

  • rtime
    (azimuth)
    datetime64[ns]
    2011-06-10T11:40:17.361118208 .....

    standard_name :

    time

    array(['2011-06-10T11:40:17.361118208', '2011-06-10T11:40:17.416673792',
           '2011-06-10T11:40:17.472229376', ..., '2011-06-10T11:40:17.194451456',
           '2011-06-10T11:40:17.250007040', '2011-06-10T11:40:17.305562624'],
          dtype='datetime64[ns]')

  • range
    (range)
    float32
    500.0 1.5e+03 ... 3.195e+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 :

    500.0

    meters_between_gates :

    1000.0

    array([   500.,   1500.,   2500., ..., 317500., 318500., 319500.],
          dtype=float32)

  • time
    ()
    datetime64[ns]
    2011-06-10T11:40:02

    standard_name :

    time

    array('2011-06-10T11:40:02.000000000', dtype='datetime64[ns]')

  • sweep_mode
    ()
    <U20
    ...

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

  • longitude
    ()
    float64
    ...

    long_name :

    longitude

    units :

    degrees_east

    standard_name :

    longitude

    array(4.78997)

  • latitude
    ()
    float64
    ...

    long_name :

    latitude

    units :

    degrees_north

    positive :

    up

    standard_name :

    latitude

    array(52.953339)

  • altitude
    ()
    float64
    ...

    long_name :

    altitude

    units :

    meters

    standard_name :

    altitude

    array(50.)

• Data variables: (1)
  • DBZH
    (azimuth, range)
    float32
    ...

    _Undetect :

    0.0

    standard_name :

    radar_equivalent_reflectivity_factor_h

    long_name :

    Equivalent reflectivity factor H

    units :

    dBZ

    [115200 values with dtype=float32]

• Attributes: (1)

  fixed_angle :

  0.30000001192092896

Goereferencing

swp = vol[0].copy().pipe(wrl.georef.georeference_dataset)

Plotting

swp.DBZH.plot.pcolormesh(x='x', y='y')
pl.gca().set_aspect('equal')

fig = pl.figure(figsize=(10,10))
swp.DBZH.wradlib.plot_ppi(proj='cg', fig=fig)

<matplotlib.collections.QuadMesh at 0x7f859c526b90>

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

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

map_proj = ccrs.AzimuthalEquidistant(central_latitude=swp.latitude.values,
                                      central_longitude=swp.longitude.values)
pm = swp.DBZH.wradlib.plot_ppi(proj=map_proj)
ax = pl.gca()
ax.gridlines(crs=map_proj)
print(ax)

< GeoAxes: +proj=aeqd +ellps=WGS84 +lon_0=4.7899699211120605 +lat_0=52.953338623046875 +x_0=0.0 +y_0=0.0 +no_defs +type=crs >

map_proj = ccrs.Mercator(central_longitude=swp.longitude.values)
fig = pl.figure(figsize=(10,8))
ax = fig.add_subplot(111, projection=map_proj)
pm = swp.DBZH.wradlib.plot_ppi(ax=ax)
ax.gridlines(draw_labels=True)

<cartopy.mpl.gridliner.Gridliner at 0x7f8598ded900>

import cartopy.feature as cfeature
def plot_borders(ax):
    borders = cfeature.NaturalEarthFeature(category='physical',
                                           name='coastline',
                                           scale='10m',
                                           facecolor='none')
    ax.add_feature(borders, edgecolor='black', lw=2, zorder=4)

map_proj = ccrs.Mercator(central_longitude=swp.longitude.values)
fig = pl.figure(figsize=(10,8))
ax = fig.add_subplot(111, projection=map_proj)

DBZH = swp.DBZH
pm = DBZH.where(DBZH > 0).wradlib.plot_ppi(ax=ax)
plot_borders(ax)
ax.gridlines(draw_labels=True)

<cartopy.mpl.gridliner.Gridliner at 0x7f8598e63fd0>

import matplotlib.path as mpath
theta = np.linspace(0, 2*np.pi, 100)
center, radius = [0.5, 0.5], 0.5
verts = np.vstack([np.sin(theta), np.cos(theta)]).T
circle = mpath.Path(verts * radius + center)

map_proj = ccrs.AzimuthalEquidistant(central_latitude=swp.latitude.values,
                                     central_longitude=swp.longitude.values,
                                    )
fig = pl.figure(figsize=(10,8))
ax = fig.add_subplot(111, projection=map_proj)
ax.set_boundary(circle, transform=ax.transAxes)

pm = swp.DBZH.wradlib.plot_ppi(proj=map_proj, ax=ax)
ax = pl.gca()
ax.gridlines(crs=map_proj)

<cartopy.mpl.gridliner.Gridliner at 0x7f859c3cd270>

fig = pl.figure(figsize=(10, 8))
proj=ccrs.AzimuthalEquidistant(central_latitude=swp.latitude.values,
                               central_longitude=swp.longitude.values)
ax = fig.add_subplot(111, projection=proj)
pm = swp.DBZH.wradlib.plot_ppi(ax=ax)
ax.gridlines()

<cartopy.mpl.gridliner.Gridliner at 0x7f85a47c0430>

swp.DBZH.wradlib.plot_ppi()

<matplotlib.collections.QuadMesh at 0x7f85a474d780>

Inspect radar moments

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

display(swp.DBZH)

<xarray.DataArray 'DBZH' (azimuth: 360, range: 320)>
array([[ 22. ,  17. ,  -8. , ..., -31.5, -31.5, -31.5],
       [ 24. ,  24.5,  -9. , ..., -31.5, -31.5, -31.5],
       [ 35.5,  42. ,  12. , ..., -31.5, -31.5, -31.5],
       ...,
       [ 23. ,  14. , -13. , ..., -31.5, -31.5, -31.5],
       [ 23. ,  14. ,  -9. , ..., -31.5, -31.5, -31.5],
       [ 22. ,  18.5, -11.5, ..., -31.5, -31.5, -31.5]], dtype=float32)
Coordinates: (12/15)
  * azimuth     (azimuth) float32 0.5 1.5 2.5 3.5 ... 356.5 357.5 358.5 359.5
    elevation   (azimuth) float32 0.3 0.3 0.3 0.3 0.3 ... 0.3 0.3 0.3 0.3 0.3
    rtime       (azimuth) datetime64[ns] 2011-06-10T11:40:17.361118208 ... 20...
  * range       (range) float32 500.0 1.5e+03 2.5e+03 ... 3.185e+05 3.195e+05
    time        datetime64[ns] 2011-06-10T11:40:02
    sweep_mode  <U20 'azimuth_surveillance'
    ...          ...
    x           (azimuth, range) float32 4.363 13.09 ... -2.777e+03 -2.786e+03
    y           (azimuth, range) float32 500.0 1.5e+03 ... 3.183e+05 3.193e+05
    z           (azimuth, range) float32 53.0 58.0 64.0 ... 7.691e+03 7.734e+03
    gr          (azimuth, range) float32 500.0 1.5e+03 ... 3.183e+05 3.193e+05
    rays        (azimuth, range) float32 0.5 0.5 0.5 0.5 ... 359.5 359.5 359.5
    bins        (azimuth, range) float32 500.0 1.5e+03 ... 3.185e+05 3.195e+05
Attributes:
    _Undetect:      0.0
    standard_name:  radar_equivalent_reflectivity_factor_h
    long_name:      Equivalent reflectivity factor H
    units:          dBZ

xarray.DataArray

'DBZH'

• azimuth: 360
• range: 320

• 22.0 17.0 -8.0 23.0 -7.5 44.0 ... -31.5 -31.5 -31.5 -31.5 -31.5 -31.5

  array([[ 22. ,  17. ,  -8. , ..., -31.5, -31.5, -31.5],
         [ 24. ,  24.5,  -9. , ..., -31.5, -31.5, -31.5],
         [ 35.5,  42. ,  12. , ..., -31.5, -31.5, -31.5],
         ...,
         [ 23. ,  14. , -13. , ..., -31.5, -31.5, -31.5],
         [ 23. ,  14. ,  -9. , ..., -31.5, -31.5, -31.5],
         [ 22. ,  18.5, -11.5, ..., -31.5, -31.5, -31.5]], dtype=float32)

• Coordinates: (15)
  • azimuth
    (azimuth)
    float32
    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 :

    84

    angle_res :

    1.0

    array([  0.5,   1.5,   2.5, ..., 357.5, 358.5, 359.5], dtype=float32)

  • elevation
    (azimuth)
    float32
    0.3 0.3 0.3 0.3 ... 0.3 0.3 0.3 0.3

    standard_name :

    ray_elevation_angle

    long_name :

    elevation_angle_from_horizontal_plane

    units :

    degrees

    axis :

    radial_elevation_coordinate

    array([0.3, 0.3, 0.3, ..., 0.3, 0.3, 0.3], dtype=float32)

  • rtime
    (azimuth)
    datetime64[ns]
    2011-06-10T11:40:17.361118208 .....

    standard_name :

    time

    array(['2011-06-10T11:40:17.361118208', '2011-06-10T11:40:17.416673792',
           '2011-06-10T11:40:17.472229376', ..., '2011-06-10T11:40:17.194451456',
           '2011-06-10T11:40:17.250007040', '2011-06-10T11:40:17.305562624'],
          dtype='datetime64[ns]')

  • range
    (range)
    float32
    500.0 1.5e+03 ... 3.195e+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 :

    500.0

    meters_between_gates :

    1000.0

    array([   500.,   1500.,   2500., ..., 317500., 318500., 319500.],
          dtype=float32)

  • time
    ()
    datetime64[ns]
    2011-06-10T11:40:02

    standard_name :

    time

    array('2011-06-10T11:40:02.000000000', dtype='datetime64[ns]')

  • sweep_mode
    ()
    <U20
    'azimuth_surveillance'

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

  • longitude
    ()
    float64
    4.79

    long_name :

    longitude

    units :

    degrees_east

    standard_name :

    longitude

    array(4.78997)

  • latitude
    ()
    float64
    52.95

    long_name :

    latitude

    units :

    degrees_north

    positive :

    up

    standard_name :

    latitude

    array(52.953339)

  • altitude
    ()
    float64
    50.0

    long_name :

    altitude

    units :

    meters

    standard_name :

    altitude

    array(50.)

  • x
    (azimuth, range)
    float32
    4.363 13.09 ... -2.786e+03

    array([[ 4.36319351e+00,  1.30895739e+01,  2.18159409e+01, ...,
             2.76879565e+03,  2.77750610e+03,  2.78621680e+03],
           [ 1.30882359e+01,  3.92646866e+01,  6.54411011e+01, ...,
             8.30553320e+03,  8.33166211e+03,  8.35779199e+03],
           [ 2.18092918e+01,  6.54278412e+01,  1.09046326e+02, ...,
             1.38397412e+04,  1.38832803e+04,  1.39268203e+04],
           ...,
           [-2.18093681e+01, -6.54280701e+01, -1.09046707e+02, ...,
            -1.38397900e+04, -1.38833291e+04, -1.39268691e+04],
           [-1.30881338e+01, -3.92643776e+01, -6.54405899e+01, ...,
            -8.30546875e+03, -8.33159668e+03, -8.35772656e+03],
           [-4.36314964e+00, -1.30894423e+01, -2.18157215e+01, ...,
            -2.76876782e+03, -2.77747827e+03, -2.78618896e+03]], dtype=float32)

  • y
    (azimuth, range)
    float32
    500.0 1.5e+03 ... 3.193e+05

    array([[   499.97098,   1499.9121 ,   2499.8518 , ..., 317271.6    ,
            318269.72   , 319267.88   ],
           [   499.8187 ,   1499.4552 ,   2499.0903 , ..., 317174.97   ,
            318172.78   , 319170.62   ],
           [   499.51416,   1498.5416 ,   2497.5676 , ..., 316981.72   ,
            317978.9    , 318976.16   ],
           ...,
           [   499.51416,   1498.5416 ,   2497.5676 , ..., 316981.72   ,
            317978.9    , 318976.16   ],
           [   499.8187 ,   1499.4552 ,   2499.0903 , ..., 317174.97   ,
            318172.78   , 319170.62   ],
           [   499.97098,   1499.9121 ,   2499.8518 , ..., 317271.6    ,
            318269.72   , 319267.88   ]], dtype=float32)

  • z
    (azimuth, range)
    float32
    53.0 58.0 ... 7.691e+03 7.734e+03

    array([[  53.,   58.,   64., ..., 7648., 7691., 7734.],
           [  53.,   58.,   64., ..., 7648., 7691., 7734.],
           [  53.,   58.,   64., ..., 7648., 7691., 7734.],
           ...,
           [  53.,   58.,   64., ..., 7648., 7691., 7734.],
           [  53.,   58.,   64., ..., 7648., 7691., 7734.],
           [  53.,   58.,   64., ..., 7648., 7691., 7734.]], dtype=float32)

  • gr
    (azimuth, range)
    float32
    500.0 1.5e+03 ... 3.193e+05

    array([[   499.99002,   1499.9691 ,   2499.947  , ..., 317283.7    ,
            318281.84   , 319280.03   ],
           [   499.99002,   1499.9692 ,   2499.947  , ..., 317283.72   ,
            318281.84   , 319280.03   ],
           [   499.99002,   1499.9692 ,   2499.947  , ..., 317283.72   ,
            318281.84   , 319280.03   ],
           ...,
           [   499.99005,   1499.9692 ,   2499.947  , ..., 317283.72   ,
            318281.84   , 319280.03   ],
           [   499.99002,   1499.9692 ,   2499.947  , ..., 317283.72   ,
            318281.84   , 319280.03   ],
           [   499.99002,   1499.9691 ,   2499.947  , ..., 317283.7    ,
            318281.84   , 319280.03   ]], dtype=float32)

  • rays
    (azimuth, range)
    float32
    0.5 0.5 0.5 ... 359.5 359.5 359.5

    array([[  0.5,   0.5,   0.5, ...,   0.5,   0.5,   0.5],
           [  1.5,   1.5,   1.5, ...,   1.5,   1.5,   1.5],
           [  2.5,   2.5,   2.5, ...,   2.5,   2.5,   2.5],
           ...,
           [357.5, 357.5, 357.5, ..., 357.5, 357.5, 357.5],
           [358.5, 358.5, 358.5, ..., 358.5, 358.5, 358.5],
           [359.5, 359.5, 359.5, ..., 359.5, 359.5, 359.5]], dtype=float32)

  • bins
    (azimuth, range)
    float32
    500.0 1.5e+03 ... 3.195e+05

    array([[   500.,   1500.,   2500., ..., 317500., 318500., 319500.],
           [   500.,   1500.,   2500., ..., 317500., 318500., 319500.],
           [   500.,   1500.,   2500., ..., 317500., 318500., 319500.],
           ...,
           [   500.,   1500.,   2500., ..., 317500., 318500., 319500.],
           [   500.,   1500.,   2500., ..., 317500., 318500., 319500.],
           [   500.,   1500.,   2500., ..., 317500., 318500., 319500.]],
          dtype=float32)

• Attributes: (4)

  _Undetect :

  0.0

  standard_name :

  radar_equivalent_reflectivity_factor_h

  long_name :

  Equivalent reflectivity factor H

  units :

  dBZ

Create simple plot

Using xarray features a simple plot can be created like this. Note the sortby('rtime') method, which sorts the radials by time.

swp.DBZH.sortby('rtime').plot(x="range", y="rtime", add_labels=False)

<matplotlib.collections.QuadMesh at 0x7f8598b88eb0>

fig = pl.figure(figsize=(5,5))
pm = swp.DBZH.wradlib.plot_ppi(proj={'latmin': 33e3}, fig=fig)

Mask some values

swp['DBZH'] = swp['DBZH'].where(swp['DBZH'] >= 0)
swp['DBZH'].plot()

<matplotlib.collections.QuadMesh at 0x7f859c284490>

Export to ODIM and CfRadial2

vol.to_odim('knmi_odim.h5')
vol.to_cfradial2('knmi_odim_as_cfradial.nc')

Import again

vola = wrl.io.open_odim_dataset('knmi_odim.h5')

volb = wrl.io.open_cfradial2_dataset('knmi_odim_as_cfradial.nc')

Check equality

xr.testing.assert_allclose(vol.root, vola.root)
xr.testing.assert_equal(vol[0], vola[0])
xr.testing.assert_allclose(vol.root, volb.root)
xr.testing.assert_equal(vol[0], volb[0])
xr.testing.assert_allclose(vola.root, volb.root)
xr.testing.assert_equal(vola[0], volb[0])

More ODIM loading mechanisms

Use xr.open_dataset to retrieve explicit group

swp = xr.open_dataset(f, engine="odim", group="dataset14")
display(swp)

<xarray.Dataset>
Dimensions:     (azimuth: 360, range: 240)
Coordinates:
  * azimuth     (azimuth) float32 0.5 1.5 2.5 3.5 ... 356.5 357.5 358.5 359.5
    elevation   (azimuth) float32 25.0 25.0 25.0 25.0 ... 25.0 25.0 25.0 25.0
    rtime       (azimuth) datetime64[ns] 2011-06-10T11:43:48.763874560 ... 20...
  * range       (range) float32 250.0 750.0 1.25e+03 ... 1.192e+05 1.198e+05
    time        datetime64[ns] 2011-06-10T11:43:45
    sweep_mode  <U20 'azimuth_surveillance'
    longitude   float64 4.79
    latitude    float64 52.95
    altitude    float64 50.0
Data variables:
    DBZH        (azimuth, range) float32 -31.5 -0.5 0.0 ... -31.5 -31.5 -31.5
Attributes:
    fixed_angle:  25.0

xarray.Dataset

• Dimensions:
  • azimuth: 360
  • range: 240
• Coordinates: (9)
  • azimuth
    (azimuth)
    float32
    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 :

    225

    angle_res :

    1.0

    array([  0.5,   1.5,   2.5, ..., 357.5, 358.5, 359.5], dtype=float32)

  • elevation
    (azimuth)
    float32
    ...

    standard_name :

    ray_elevation_angle

    long_name :

    elevation_angle_from_horizontal_plane

    units :

    degrees

    axis :

    radial_elevation_coordinate

    array([25., 25., 25., ..., 25., 25., 25.], dtype=float32)

  • rtime
    (azimuth)
    datetime64[ns]
    ...

    standard_name :

    time

    array(['2011-06-10T11:43:48.763874560', '2011-06-10T11:43:48.791652096',
           '2011-06-10T11:43:48.819429888', ..., '2011-06-10T11:43:48.680541440',
           '2011-06-10T11:43:48.708319232', '2011-06-10T11:43:48.736096768'],
          dtype='datetime64[ns]')

  • range
    (range)
    float32
    250.0 750.0 ... 1.192e+05 1.198e+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 :

    250.0

    meters_between_gates :

    500.0

    array([   250.,    750.,   1250., ..., 118750., 119250., 119750.],
          dtype=float32)

  • time
    ()
    datetime64[ns]
    ...

    standard_name :

    time

    array('2011-06-10T11:43:45.000000000', dtype='datetime64[ns]')

  • sweep_mode
    ()
    <U20
    ...

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

  • longitude
    ()
    float64
    ...

    long_name :

    longitude

    units :

    degrees_east

    standard_name :

    longitude

    array(4.78997)

  • latitude
    ()
    float64
    ...

    long_name :

    latitude

    units :

    degrees_north

    positive :

    up

    standard_name :

    latitude

    array(52.953339)

  • altitude
    ()
    float64
    ...

    long_name :

    altitude

    units :

    meters

    standard_name :

    altitude

    array(50.)

• Data variables: (1)
  • DBZH
    (azimuth, range)
    float32
    ...

    _Undetect :

    0.0

    standard_name :

    radar_equivalent_reflectivity_factor_h

    long_name :

    Equivalent reflectivity factor H

    units :

    dBZ

    array([[-31.5,  -0.5,   0. , ..., -31.5, -31.5, -31.5],
           [-31.5,   1. ,   0.5, ..., -31.5, -31.5, -31.5],
           [-31.5,  -2.5,   0. , ..., -31.5, -31.5, -31.5],
           ...,
           [-31.5,  -2. ,   2.5, ..., -31.5, -31.5, -31.5],
           [-31.5,  -2. ,  -0.5, ..., -31.5, -31.5, -31.5],
           [-31.5,   1. ,  -0.5, ..., -31.5, -31.5, -31.5]], dtype=float32)

• Attributes: (1)

  fixed_angle :

  25.0

Use xr.open_mfdataset to retrieve timeseries of explicit group

fpath = os.path.join(wrl.util.get_wradlib_data_path(), "hdf5/71*.h5")
f = glob.glob(fpath)
ts = xr.open_mfdataset(f, engine="odim", concat_dim="time", combine="nested", group="dataset1")
display(ts)

<xarray.Dataset>
Dimensions:     (time: 2, azimuth: 360, range: 1200)
Coordinates:
  * azimuth     (azimuth) float32 0.5 1.5 2.5 3.5 ... 356.5 357.5 358.5 359.5
    elevation   (azimuth) float32 dask.array<chunksize=(360,), meta=np.ndarray>
    rtime       (time, azimuth) datetime64[ns] 2018-12-20T06:12:41.009703424 ...
  * range       (range) float32 125.0 375.0 625.0 ... 2.996e+05 2.999e+05
  * time        (time) datetime64[ns] 2018-12-20T06:12:28 2018-12-20T06:06:28
    sweep_mode  <U20 'azimuth_surveillance'
    longitude   float64 151.2
    latitude    float64 -33.7
    altitude    float64 195.0
Data variables:
    DBZH        (time, azimuth, range) float32 dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>
    DBZH_CLEAN  (time, azimuth, range) float32 dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>
    VRADDH      (time, azimuth, range) float32 dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>
    VRADH       (time, azimuth, range) float32 dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>
    WRADH       (time, azimuth, range) float32 dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>
    TH          (time, azimuth, range) float32 dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>
    ZDR         (time, azimuth, range) float32 dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>
    RHOHV       (time, azimuth, range) float32 dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>
    PHIDP       (time, azimuth, range) float32 dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>
    KDP         (time, azimuth, range) float32 dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>
    SNRH        (time, azimuth, range) float32 dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>
Attributes:
    fixed_angle:  0.5

xarray.Dataset

• Dimensions:
  • time: 2
  • azimuth: 360
  • range: 1200
• Coordinates: (9)
  • azimuth
    (azimuth)
    float32
    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 :

    199

    angle_res :

    1.0

    array([  0.5,   1.5,   2.5, ..., 357.5, 358.5, 359.5], dtype=float32)

  • elevation
    (azimuth)
    float32
    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 1.41 kiB 1.41 kiB Shape (360,) (360,) Count 5 Tasks 1 Chunks Type float32 numpy.ndarray

  • rtime
    (time, azimuth)
    datetime64[ns]
    2018-12-20T06:12:41.009703424 .....

    standard_name :

    time

    array([['2018-12-20T06:12:41.009703424', '2018-12-20T06:12:41.090258944',
            '2018-12-20T06:12:41.170814208', '2018-12-20T06:12:41.251369728',
            '2018-12-20T06:12:41.331925248', '2018-12-20T06:12:41.412480512',
            '2018-12-20T06:12:41.493036032', '2018-12-20T06:12:41.573591552',
            '2018-12-20T06:12:41.654146816', '2018-12-20T06:12:41.734702336',
            '2018-12-20T06:12:41.815257856', '2018-12-20T06:12:41.895813120',
            '2018-12-20T06:12:41.976368640', '2018-12-20T06:12:42.056924160',
            '2018-12-20T06:12:42.137479424', '2018-12-20T06:12:42.218034944',
            '2018-12-20T06:12:42.298590464', '2018-12-20T06:12:42.379145984',
            '2018-12-20T06:12:42.459701248', '2018-12-20T06:12:42.540256768',
            '2018-12-20T06:12:42.620812288', '2018-12-20T06:12:42.701367552',
            '2018-12-20T06:12:42.781923072', '2018-12-20T06:12:42.862478592',
            '2018-12-20T06:12:42.943033856', '2018-12-20T06:12:43.023589376',
            '2018-12-20T06:12:43.104144896', '2018-12-20T06:12:43.184700160',
            '2018-12-20T06:12:43.265255680', '2018-12-20T06:12:43.345811200',
            '2018-12-20T06:12:43.426366464', '2018-12-20T06:12:43.506921984',
            '2018-12-20T06:12:43.587477504', '2018-12-20T06:12:43.668032768',
            '2018-12-20T06:12:43.748588288', '2018-12-20T06:12:43.829143808',
            '2018-12-20T06:12:43.909699328', '2018-12-20T06:12:43.990254592',
            '2018-12-20T06:12:44.070810112', '2018-12-20T06:12:44.151365632',
    ...
            '2018-12-20T06:06:47.051361280', '2018-12-20T06:06:47.131916800',
            '2018-12-20T06:06:47.212472320', '2018-12-20T06:06:47.293027584',
            '2018-12-20T06:06:47.373583104', '2018-12-20T06:06:47.454138624',
            '2018-12-20T06:06:47.534693888', '2018-12-20T06:06:47.615249408',
            '2018-12-20T06:06:47.695804928', '2018-12-20T06:06:47.776360192',
            '2018-12-20T06:06:47.856915712', '2018-12-20T06:06:47.937471232',
            '2018-12-20T06:06:48.018026496', '2018-12-20T06:06:48.098582016',
            '2018-12-20T06:06:48.179137536', '2018-12-20T06:06:48.259692800',
            '2018-12-20T06:06:48.340248320', '2018-12-20T06:06:48.420803840',
            '2018-12-20T06:06:48.501359104', '2018-12-20T06:06:48.581914624',
            '2018-12-20T06:06:48.662470144', '2018-12-20T06:06:48.743025664',
            '2018-12-20T06:06:48.823580928', '2018-12-20T06:06:48.904136448',
            '2018-12-20T06:06:48.984691968', '2018-12-20T06:06:49.065247232',
            '2018-12-20T06:06:49.145802752', '2018-12-20T06:06:49.226358272',
            '2018-12-20T06:06:49.306913536', '2018-12-20T06:06:49.387469056',
            '2018-12-20T06:06:49.468024576', '2018-12-20T06:06:49.548579840',
            '2018-12-20T06:06:49.629135360', '2018-12-20T06:06:49.709690880',
            '2018-12-20T06:06:49.790246144', '2018-12-20T06:06:49.870801664',
            '2018-12-20T06:06:49.951357184', '2018-12-20T06:06:50.031912448']],
          dtype='datetime64[ns]')

  • range
    (range)
    float32
    125.0 375.0 ... 2.996e+05 2.999e+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, ..., 2.99375e+05, 2.99625e+05,
           2.99875e+05], dtype=float32)

  • time
    (time)
    datetime64[ns]
    2018-12-20T06:12:28 2018-12-20T0...

    standard_name :

    time

    array(['2018-12-20T06:12:28.000000000', '2018-12-20T06:06:28.000000000'],
          dtype='datetime64[ns]')

  • sweep_mode
    ()
    <U20
    'azimuth_surveillance'

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

  • longitude
    ()
    float64
    151.2

    long_name :

    longitude

    units :

    degrees_east

    standard_name :

    longitude

    array(151.20899963)

  • latitude
    ()
    float64
    -33.7

    long_name :

    latitude

    units :

    degrees_north

    positive :

    up

    standard_name :

    latitude

    array(-33.70080185)

  • altitude
    ()
    float64
    195.0

    long_name :

    altitude

    units :

    meters

    standard_name :

    altitude

    array(195.)

• Data variables: (11)
  • DBZH
    (time, azimuth, range)
    float32
    dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>

    _Undetect :

    0.0

    standard_name :

    radar_equivalent_reflectivity_factor_h

    long_name :

    Equivalent reflectivity factor H

    units :

    dBZ

    Array Chunk Bytes 3.30 MiB 1.65 MiB Shape (2, 360, 1200) (1, 360, 1200) Count 8 Tasks 2 Chunks Type float32 numpy.ndarray

  • DBZH_CLEAN
    (time, azimuth, range)
    float32
    dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>

    _Undetect :

    1.0

    standard_name :

    radar_equivalent_reflectivity_factor_h

    long_name :

    Equivalent reflectivity factor H

    units :

    dBZ

    Array Chunk Bytes 3.30 MiB 1.65 MiB Shape (2, 360, 1200) (1, 360, 1200) Count 8 Tasks 2 Chunks Type float32 numpy.ndarray

  • VRADDH
    (time, azimuth, range)
    float32
    dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>

    _Undetect :

    1.0

    standard_name :

    radial_velocity_of_scatterers_away_from_instrument_h

    long_name :

    Radial velocity of scatterers away from instrument H

    units :

    meters per seconds

    Array Chunk Bytes 3.30 MiB 1.65 MiB Shape (2, 360, 1200) (1, 360, 1200) Count 8 Tasks 2 Chunks Type float32 numpy.ndarray

  • VRADH
    (time, azimuth, range)
    float32
    dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>

    _Undetect :

    0.0

    standard_name :

    radial_velocity_of_scatterers_away_from_instrument_h

    long_name :

    Radial velocity of scatterers away from instrument H

    units :

    meters per seconds

    Array Chunk Bytes 3.30 MiB 1.65 MiB Shape (2, 360, 1200) (1, 360, 1200) Count 8 Tasks 2 Chunks Type float32 numpy.ndarray

  • WRADH
    (time, azimuth, range)
    float32
    dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>

    _Undetect :

    0.0

    standard_name :

    radar_doppler_spectrum_width_h

    long_name :

    Doppler spectrum width H

    units :

    meters per seconds

    Array Chunk Bytes 3.30 MiB 1.65 MiB Shape (2, 360, 1200) (1, 360, 1200) Count 8 Tasks 2 Chunks Type float32 numpy.ndarray

  • TH
    (time, azimuth, range)
    float32
    dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>

    _Undetect :

    0.0

    standard_name :

    radar_linear_equivalent_reflectivity_factor_h

    long_name :

    Linear total power H (uncorrected reflectivity)

    units :

    unitless

    Array Chunk Bytes 3.30 MiB 1.65 MiB Shape (2, 360, 1200) (1, 360, 1200) Count 8 Tasks 2 Chunks Type float32 numpy.ndarray

  • ZDR
    (time, azimuth, range)
    float32
    dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>

    _Undetect :

    0.0

    standard_name :

    radar_differential_reflectivity_hv

    long_name :

    Log differential reflectivity H/V

    units :

    dB

    Array Chunk Bytes 3.30 MiB 1.65 MiB Shape (2, 360, 1200) (1, 360, 1200) Count 8 Tasks 2 Chunks Type float32 numpy.ndarray

  • RHOHV
    (time, azimuth, range)
    float32
    dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>

    _Undetect :

    0.0

    standard_name :

    radar_correlation_coefficient_hv

    long_name :

    Correlation coefficient HV

    units :

    unitless

    Array Chunk Bytes 3.30 MiB 1.65 MiB Shape (2, 360, 1200) (1, 360, 1200) Count 8 Tasks 2 Chunks Type float32 numpy.ndarray

  • PHIDP
    (time, azimuth, range)
    float32
    dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>

    _Undetect :

    0.0

    standard_name :

    radar_differential_phase_hv

    long_name :

    Differential phase HV

    units :

    degrees

    Array Chunk Bytes 3.30 MiB 1.65 MiB Shape (2, 360, 1200) (1, 360, 1200) Count 8 Tasks 2 Chunks Type float32 numpy.ndarray

  • KDP
    (time, azimuth, range)
    float32
    dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>

    _Undetect :

    0.0

    standard_name :

    radar_specific_differential_phase_hv

    long_name :

    Specific differential phase HV

    units :

    degrees per kilometer

    Array Chunk Bytes 3.30 MiB 1.65 MiB Shape (2, 360, 1200) (1, 360, 1200) Count 8 Tasks 2 Chunks Type float32 numpy.ndarray

  • SNRH
    (time, azimuth, range)
    float32
    dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>

    _Undetect :

    0.0

    standard_name :

    signal_noise_ratio_h

    long_name :

    Signal Noise Ratio H

    units :

    unitless

    Array Chunk Bytes 3.30 MiB 1.65 MiB Shape (2, 360, 1200) (1, 360, 1200) Count 8 Tasks 2 Chunks Type float32 numpy.ndarray

• Attributes: (1)

  fixed_angle :

  0.5

Use wrl.io.open_odim_mfdataset to retrieve volume timeseries

fpath = os.path.join(wrl.util.get_wradlib_data_path(), "hdf5/71*.h5")
f = glob.glob(fpath)
ts = wrl.io.open_odim_mfdataset(f)
display(ts)

100%|██████████| 14/14 [00:02<00:00,  5.38it/s]

<wradlib.RadarVolume>
Dimension(s): (sweep: 14)
Elevation(s): (0.5, 0.9, 1.3, 1.8, 2.4, 3.1, 4.2, 5.6, 7.4, 10.0, 13.3, 17.9, 23.9, 32.0)

display(ts[0])

<xarray.Dataset>
Dimensions:     (time: 2, azimuth: 360, range: 1200)
Coordinates:
  * azimuth     (azimuth) float32 0.5 1.5 2.5 3.5 ... 356.5 357.5 358.5 359.5
    elevation   (azimuth) float32 dask.array<chunksize=(360,), meta=np.ndarray>
    rtime       (time, azimuth) datetime64[ns] 2018-12-20T06:12:41.009703424 ...
  * range       (range) float32 125.0 375.0 625.0 ... 2.996e+05 2.999e+05
  * time        (time) datetime64[ns] 2018-12-20T06:12:28 2018-12-20T06:06:28
    sweep_mode  <U20 'azimuth_surveillance'
    longitude   float64 151.2
    latitude    float64 -33.7
    altitude    float64 195.0
Data variables:
    DBZH        (time, azimuth, range) float32 dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>
    DBZH_CLEAN  (time, azimuth, range) float32 dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>
    VRADDH      (time, azimuth, range) float32 dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>
    VRADH       (time, azimuth, range) float32 dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>
    WRADH       (time, azimuth, range) float32 dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>
    TH          (time, azimuth, range) float32 dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>
    ZDR         (time, azimuth, range) float32 dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>
    RHOHV       (time, azimuth, range) float32 dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>
    PHIDP       (time, azimuth, range) float32 dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>
    KDP         (time, azimuth, range) float32 dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>
    SNRH        (time, azimuth, range) float32 dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>
Attributes:
    fixed_angle:  0.5

xarray.Dataset

• Dimensions:
  • time: 2
  • azimuth: 360
  • range: 1200
• Coordinates: (9)
  • azimuth
    (azimuth)
    float32
    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 :

    199

    angle_res :

    1.0

    array([  0.5,   1.5,   2.5, ..., 357.5, 358.5, 359.5], dtype=float32)

  • elevation
    (azimuth)
    float32
    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 1.41 kiB 1.41 kiB Shape (360,) (360,) Count 5 Tasks 1 Chunks Type float32 numpy.ndarray

  • rtime
    (time, azimuth)
    datetime64[ns]
    2018-12-20T06:12:41.009703424 .....

    standard_name :

    time

    array([['2018-12-20T06:12:41.009703424', '2018-12-20T06:12:41.090258944',
            '2018-12-20T06:12:41.170814208', '2018-12-20T06:12:41.251369728',
            '2018-12-20T06:12:41.331925248', '2018-12-20T06:12:41.412480512',
            '2018-12-20T06:12:41.493036032', '2018-12-20T06:12:41.573591552',
            '2018-12-20T06:12:41.654146816', '2018-12-20T06:12:41.734702336',
            '2018-12-20T06:12:41.815257856', '2018-12-20T06:12:41.895813120',
            '2018-12-20T06:12:41.976368640', '2018-12-20T06:12:42.056924160',
            '2018-12-20T06:12:42.137479424', '2018-12-20T06:12:42.218034944',
            '2018-12-20T06:12:42.298590464', '2018-12-20T06:12:42.379145984',
            '2018-12-20T06:12:42.459701248', '2018-12-20T06:12:42.540256768',
            '2018-12-20T06:12:42.620812288', '2018-12-20T06:12:42.701367552',
            '2018-12-20T06:12:42.781923072', '2018-12-20T06:12:42.862478592',
            '2018-12-20T06:12:42.943033856', '2018-12-20T06:12:43.023589376',
            '2018-12-20T06:12:43.104144896', '2018-12-20T06:12:43.184700160',
            '2018-12-20T06:12:43.265255680', '2018-12-20T06:12:43.345811200',
            '2018-12-20T06:12:43.426366464', '2018-12-20T06:12:43.506921984',
            '2018-12-20T06:12:43.587477504', '2018-12-20T06:12:43.668032768',
            '2018-12-20T06:12:43.748588288', '2018-12-20T06:12:43.829143808',
            '2018-12-20T06:12:43.909699328', '2018-12-20T06:12:43.990254592',
            '2018-12-20T06:12:44.070810112', '2018-12-20T06:12:44.151365632',
    ...
            '2018-12-20T06:06:47.051361280', '2018-12-20T06:06:47.131916800',
            '2018-12-20T06:06:47.212472320', '2018-12-20T06:06:47.293027584',
            '2018-12-20T06:06:47.373583104', '2018-12-20T06:06:47.454138624',
            '2018-12-20T06:06:47.534693888', '2018-12-20T06:06:47.615249408',
            '2018-12-20T06:06:47.695804928', '2018-12-20T06:06:47.776360192',
            '2018-12-20T06:06:47.856915712', '2018-12-20T06:06:47.937471232',
            '2018-12-20T06:06:48.018026496', '2018-12-20T06:06:48.098582016',
            '2018-12-20T06:06:48.179137536', '2018-12-20T06:06:48.259692800',
            '2018-12-20T06:06:48.340248320', '2018-12-20T06:06:48.420803840',
            '2018-12-20T06:06:48.501359104', '2018-12-20T06:06:48.581914624',
            '2018-12-20T06:06:48.662470144', '2018-12-20T06:06:48.743025664',
            '2018-12-20T06:06:48.823580928', '2018-12-20T06:06:48.904136448',
            '2018-12-20T06:06:48.984691968', '2018-12-20T06:06:49.065247232',
            '2018-12-20T06:06:49.145802752', '2018-12-20T06:06:49.226358272',
            '2018-12-20T06:06:49.306913536', '2018-12-20T06:06:49.387469056',
            '2018-12-20T06:06:49.468024576', '2018-12-20T06:06:49.548579840',
            '2018-12-20T06:06:49.629135360', '2018-12-20T06:06:49.709690880',
            '2018-12-20T06:06:49.790246144', '2018-12-20T06:06:49.870801664',
            '2018-12-20T06:06:49.951357184', '2018-12-20T06:06:50.031912448']],
          dtype='datetime64[ns]')

  • range
    (range)
    float32
    125.0 375.0 ... 2.996e+05 2.999e+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, ..., 2.99375e+05, 2.99625e+05,
           2.99875e+05], dtype=float32)

  • time
    (time)
    datetime64[ns]
    2018-12-20T06:12:28 2018-12-20T0...

    standard_name :

    time

    array(['2018-12-20T06:12:28.000000000', '2018-12-20T06:06:28.000000000'],
          dtype='datetime64[ns]')

  • sweep_mode
    ()
    <U20
    'azimuth_surveillance'

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

  • longitude
    ()
    float64
    151.2

    long_name :

    longitude

    units :

    degrees_east

    standard_name :

    longitude

    array(151.20899963)

  • latitude
    ()
    float64
    -33.7

    long_name :

    latitude

    units :

    degrees_north

    positive :

    up

    standard_name :

    latitude

    array(-33.70080185)

  • altitude
    ()
    float64
    195.0

    long_name :

    altitude

    units :

    meters

    standard_name :

    altitude

    array(195.)

• Data variables: (11)
  • DBZH
    (time, azimuth, range)
    float32
    dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>

    _Undetect :

    0.0

    standard_name :

    radar_equivalent_reflectivity_factor_h

    long_name :

    Equivalent reflectivity factor H

    units :

    dBZ

    Array Chunk Bytes 3.30 MiB 1.65 MiB Shape (2, 360, 1200) (1, 360, 1200) Count 8 Tasks 2 Chunks Type float32 numpy.ndarray

  • DBZH_CLEAN
    (time, azimuth, range)
    float32
    dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>

    _Undetect :

    1.0

    standard_name :

    radar_equivalent_reflectivity_factor_h

    long_name :

    Equivalent reflectivity factor H

    units :

    dBZ

    Array Chunk Bytes 3.30 MiB 1.65 MiB Shape (2, 360, 1200) (1, 360, 1200) Count 8 Tasks 2 Chunks Type float32 numpy.ndarray

  • VRADDH
    (time, azimuth, range)
    float32
    dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>

    _Undetect :

    1.0

    standard_name :

    radial_velocity_of_scatterers_away_from_instrument_h

    long_name :

    Radial velocity of scatterers away from instrument H

    units :

    meters per seconds

    Array Chunk Bytes 3.30 MiB 1.65 MiB Shape (2, 360, 1200) (1, 360, 1200) Count 8 Tasks 2 Chunks Type float32 numpy.ndarray

  • VRADH
    (time, azimuth, range)
    float32
    dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>

    _Undetect :

    0.0

    standard_name :

    radial_velocity_of_scatterers_away_from_instrument_h

    long_name :

    Radial velocity of scatterers away from instrument H

    units :

    meters per seconds

    Array Chunk Bytes 3.30 MiB 1.65 MiB Shape (2, 360, 1200) (1, 360, 1200) Count 8 Tasks 2 Chunks Type float32 numpy.ndarray

  • WRADH
    (time, azimuth, range)
    float32
    dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>

    _Undetect :

    0.0

    standard_name :

    radar_doppler_spectrum_width_h

    long_name :

    Doppler spectrum width H

    units :

    meters per seconds

    Array Chunk Bytes 3.30 MiB 1.65 MiB Shape (2, 360, 1200) (1, 360, 1200) Count 8 Tasks 2 Chunks Type float32 numpy.ndarray

  • TH
    (time, azimuth, range)
    float32
    dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>

    _Undetect :

    0.0

    standard_name :

    radar_linear_equivalent_reflectivity_factor_h

    long_name :

    Linear total power H (uncorrected reflectivity)

    units :

    unitless

    Array Chunk Bytes 3.30 MiB 1.65 MiB Shape (2, 360, 1200) (1, 360, 1200) Count 8 Tasks 2 Chunks Type float32 numpy.ndarray

  • ZDR
    (time, azimuth, range)
    float32
    dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>

    _Undetect :

    0.0

    standard_name :

    radar_differential_reflectivity_hv

    long_name :

    Log differential reflectivity H/V

    units :

    dB

    Array Chunk Bytes 3.30 MiB 1.65 MiB Shape (2, 360, 1200) (1, 360, 1200) Count 8 Tasks 2 Chunks Type float32 numpy.ndarray

  • RHOHV
    (time, azimuth, range)
    float32
    dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>

    _Undetect :

    0.0

    standard_name :

    radar_correlation_coefficient_hv

    long_name :

    Correlation coefficient HV

    units :

    unitless

    Array Chunk Bytes 3.30 MiB 1.65 MiB Shape (2, 360, 1200) (1, 360, 1200) Count 8 Tasks 2 Chunks Type float32 numpy.ndarray

  • PHIDP
    (time, azimuth, range)
    float32
    dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>

    _Undetect :

    0.0

    standard_name :

    radar_differential_phase_hv

    long_name :

    Differential phase HV

    units :

    degrees

    Array Chunk Bytes 3.30 MiB 1.65 MiB Shape (2, 360, 1200) (1, 360, 1200) Count 8 Tasks 2 Chunks Type float32 numpy.ndarray

  • KDP
    (time, azimuth, range)
    float32
    dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>

    _Undetect :

    0.0

    standard_name :

    radar_specific_differential_phase_hv

    long_name :

    Specific differential phase HV

    units :

    degrees per kilometer

    Array Chunk Bytes 3.30 MiB 1.65 MiB Shape (2, 360, 1200) (1, 360, 1200) Count 8 Tasks 2 Chunks Type float32 numpy.ndarray

  • SNRH
    (time, azimuth, range)
    float32
    dask.array<chunksize=(1, 360, 1200), meta=np.ndarray>

    _Undetect :

    0.0

    standard_name :

    signal_noise_ratio_h

    long_name :

    Signal Noise Ratio H

    units :

    unitless

    Array Chunk Bytes 3.30 MiB 1.65 MiB Shape (2, 360, 1200) (1, 360, 1200) Count 8 Tasks 2 Chunks Type float32 numpy.ndarray

• Attributes: (1)

  fixed_angle :

  0.5