xarray Rainbow5 backend#

In this example, we read Rainbow5 data files using the xradar rainbow xarray backend.

[1]:
import glob
import gzip
import io
import wradlib as wrl
import warnings

warnings.filterwarnings("ignore")
import matplotlib.pyplot as plt
import numpy as np
import xradar as xd
import xarray as xr

try:
    get_ipython().run_line_magic("matplotlib inline")
except:
    plt.ion()

Load Rainbow5 Volume Data#

[2]:
fpath = "rainbow/2013051000000600dBZ.vol"
f = wrl.util.get_wradlib_data_file(fpath)
vol = xd.io.open_rainbow_datatree(f, reindex_angle=False)
Downloading file 'rainbow/2013051000000600dBZ.vol' from 'https://github.com/wradlib/wradlib-data/raw/pooch/data/rainbow/2013051000000600dBZ.vol' to '/home/runner/work/wradlib/wradlib/wradlib-data'.

Inspect RadarVolume#

[3]:
display(vol)
<xarray.DatasetView> Size: 456B
Dimensions:              (sweep: 14)
Dimensions without coordinates: sweep
Data variables:
    volume_number        int64 8B 0
    platform_type        <U5 20B 'fixed'
    instrument_type      <U5 20B 'radar'
    time_coverage_start  <U20 80B '2013-05-10T00:00:06Z'
    time_coverage_end    <U20 80B '2013-05-10T00:03:14Z'
    longitude            float64 8B 6.38
    altitude             float64 8B 116.7
    latitude             float64 8B 50.86
    sweep_fixed_angle    (sweep) float64 112B 0.6 1.4 2.4 3.5 ... 21.3 25.4 30.0
    sweep_group_name     (sweep) int64 112B 0 1 2 3 4 5 6 7 8 9 10 11 12 13
Attributes:
    Conventions:      None
    instrument_name:  None
    version:          None
    title:            None
    institution:      None
    references:       None
    source:           None
    history:          None
    comment:          im/exported using xradar

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).

[4]:
vol.root
[4]:
<xarray.DatasetView> Size: 456B
Dimensions:              (sweep: 14)
Dimensions without coordinates: sweep
Data variables:
    volume_number        int64 8B 0
    platform_type        <U5 20B 'fixed'
    instrument_type      <U5 20B 'radar'
    time_coverage_start  <U20 80B '2013-05-10T00:00:06Z'
    time_coverage_end    <U20 80B '2013-05-10T00:03:14Z'
    longitude            float64 8B 6.38
    altitude             float64 8B 116.7
    latitude             float64 8B 50.86
    sweep_fixed_angle    (sweep) float64 112B 0.6 1.4 2.4 3.5 ... 21.3 25.4 30.0
    sweep_group_name     (sweep) int64 112B 0 1 2 3 4 5 6 7 8 9 10 11 12 13
Attributes:
    Conventions:      None
    instrument_name:  None
    version:          None
    title:            None
    institution:      None
    references:       None
    source:           None
    history:          None
    comment:          im/exported using xradar

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.).

[5]:
display(vol["sweep_0"])
<xarray.DatasetView> Size: 1MB
Dimensions:            (sweep: 14, azimuth: 361, range: 400)
Coordinates:
    elevation          (azimuth) float64 3kB ...
  * range              (range) float32 2kB 125.0 375.0 ... 9.962e+04 9.988e+04
    time               (azimuth) datetime64[ns] 3kB 2013-05-10T00:00:15.50000...
    longitude          float64 8B ...
    latitude           float64 8B ...
    altitude           float64 8B ...
  * azimuth            (azimuth) float64 3kB 0.5055 1.549 2.505 ... 358.5 359.5
Dimensions without coordinates: sweep
Data variables:
    DBZH               (azimuth, range) float64 1MB ...
    sweep_mode         <U20 80B ...
    sweep_number       int64 8B ...
    prt_mode           <U7 28B ...
    follow_mode        <U7 28B ...
    sweep_fixed_angle  float64 8B ...

Georeferencing#

[6]:
swp = vol["sweep_0"].ds.copy()
swp = swp.assign_coords(sweep_mode=swp.sweep_mode)
swp = swp.wrl.georef.georeference()

Inspect radar moments#

The DataArrays can be accessed by key or by attribute. Each DataArray has dimensions and coordinates of it’s parent dataset.

[7]:
display(swp.DBZH)
<xarray.DataArray 'DBZH' (azimuth: 361, range: 400)> Size: 1MB
[144400 values with dtype=float64]
Coordinates: (12/15)
    sweep_mode  <U20 80B 'azimuth_surveillance'
    elevation   (azimuth) float64 3kB 0.6 0.6 0.6 0.6 0.6 ... 0.6 0.6 0.6 0.6
  * range       (range) float32 2kB 125.0 375.0 625.0 ... 9.962e+04 9.988e+04
    time        (azimuth) datetime64[ns] 3kB 2013-05-10T00:00:15.500000 ... 2...
    longitude   float64 8B 6.38
    latitude    float64 8B 50.86
    ...          ...
    y           (azimuth, range) float64 1MB 125.0 375.0 ... 9.96e+04 9.985e+04
    z           (azimuth, range) float64 1MB 118.0 120.6 ... 1.745e+03 1.75e+03
    gr          (azimuth, range) float64 1MB 124.8 374.7 ... 9.96e+04 9.985e+04
    rays        (azimuth, range) float64 1MB 0.5055 0.5055 ... 359.5 359.5
    bins        (azimuth, range) float32 578kB 125.0 375.0 ... 9.988e+04
    crs_wkt     int64 8B 0
Attributes:
    units:          dBZ
    long_name:      Equivalent reflectivity factor H
    standard_name:  radar_equivalent_reflectivity_factor_h

Create simple plot#

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

For more details on plotting radar data see under Visualization.

[8]:
swp.DBZH.sortby("time").plot(x="range", y="time", add_labels=False)
[8]:
<matplotlib.collections.QuadMesh at 0x7f87badcac60>
../../../_images/notebooks_fileio_backends_rainbow_backend_16_1.png
[9]:
fig = plt.figure(figsize=(5, 5))
pm = swp.DBZH.wrl.vis.plot(crs={"latmin": 3e3}, fig=fig)
../../../_images/notebooks_fileio_backends_rainbow_backend_17_0.png

Retrieve explicit group#

[10]:
swp_b = xr.open_dataset(
    f, engine="rainbow", group="sweep_5", backend_kwargs=dict(reindex_angle=False)
)
display(swp_b)
<xarray.Dataset> Size: 1MB
Dimensions:            (azimuth: 361, range: 400)
Coordinates:
    elevation          (azimuth) float64 3kB ...
  * range              (range) float32 2kB 125.0 375.0 ... 9.962e+04 9.988e+04
    time               (azimuth) datetime64[ns] 3kB ...
    longitude          float64 8B ...
    latitude           float64 8B ...
    altitude           float64 8B ...
  * azimuth            (azimuth) float64 3kB 0.522 1.505 2.516 ... 358.5 359.5
Data variables:
    DBZH               (azimuth, range) float64 1MB ...
    sweep_mode         <U20 80B ...
    sweep_number       int64 8B ...
    prt_mode           <U7 28B ...
    follow_mode        <U7 28B ...
    sweep_fixed_angle  float64 8B ...