xarray CfRadial2 backend

Contents

xarray CfRadial2 backend#

In this example, we read CfRadial2 data files using the xarray cfradial2 backend.

import wradlib as wrl
import wradlib_data
import warnings
from IPython.display import display

import matplotlib.pyplot as plt
import numpy as np
import xradar as xd
import xarray as xr

warnings.filterwarnings("ignore")

Load CfRadial2 Volume Data#

fpath = "netcdf/cfrad.20080604_002217_000_SPOL_v36_SUR_cfradial2.nc"
f = wradlib_data.DATASETS.fetch(fpath)
vol = xr.open_datatree(f)

Downloading file 'netcdf/cfrad.20080604_002217_000_SPOL_v36_SUR_cfradial2.nc' from 'https://github.com/wradlib/wradlib-data/raw/main/data/netcdf/cfrad.20080604_002217_000_SPOL_v36_SUR_cfradial2.nc' to '/home/docs/.cache/wradlib-data'.

# fix: remove when available in xradar
for k in vol.groups[1:]:
    vol[k].ds = (
        vol[k]
        .ds.assign(sweep_fixed_angle=vol[k].ds.attrs["fixed_angle"])
        .swap_dims(time="azimuth")
        .sortby("azimuth")
    )

Georeferencing#

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

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.

swp.DBZ.sortby("time").plot(x="range", y="time", add_labels=False)

<matplotlib.collections.QuadMesh at 0x7321c3d4a120>

../../../_images/5fdbf52c21b3122416c07550c9281f628804326df940e60162e7d8107551d26d.png

fig = plt.figure(figsize=(5, 5))
pm = swp.DBZ.wrl.vis.plot(crs={"latmin": 3e3}, fig=fig)

../../../_images/5dce0ac4c95aa5f1791944df49fb4f9822fb779f57a50d46ae58f1c56b730986.png