Grid Radar -> Plot Max-CAPPI#

We are using fast-barnes-py to grid the radar data. Please cite if you use it in your research.

[1]:

import fsspec
import radarx as rx
import xradar as xd
import cmweather  # noqa
import matplotlib.pyplot as plt

[2]:

file = "s3://noaa-nexrad-level2/2022/03/30/KGWX/KGWX20220330_234639_V06"
local_file = fsspec.open_local(
    f"simplecache::s3://{file}",
    s3={"anon": True},
    filecache={"cache_storage": "."},
)
dtree = xd.io.open_nexradlevel2_datatree(local_file)
dtree = rx.combine_nexrad_sweeps(dtree)
dtree = dtree.xradar.georeference()

/home/docs/checkouts/readthedocs.org/user_builds/radarx/conda/latest/lib/python3.12/site-packages/fsspec/registry.py:283: UserWarning: Your installed version of s3fs is very old and known to cause
severe performance issues, see also https://github.com/dask/dask/issues/10276

To fix, you should specify a lower version bound on s3fs, or
update the current installation.

  warnings.warn(s3_msg)
INFO:botocore.httpchecksum:Skipping checksum validation. Response did not contain one of the following algorithms: ['crc32', 'sha1', 'sha256'].
INFO:botocore.httpchecksum:Skipping checksum validation. Response did not contain one of the following algorithms: ['crc32', 'sha1', 'sha256'].
INFO:botocore.httpchecksum:Skipping checksum validation. Response did not contain one of the following algorithms: ['crc32', 'sha1', 'sha256'].
INFO:botocore.httpchecksum:Skipping checksum validation. Response did not contain one of the following algorithms: ['crc32', 'sha1', 'sha256'].
INFO:botocore.httpchecksum:Skipping checksum validation. Response did not contain one of the following algorithms: ['crc32', 'sha1', 'sha256'].

[3]:

dtree.groups

[3]:

('/',
 '/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',
 '/radar_parameters',
 '/georeferencing_correction',
 '/radar_calibration')

[4]:

def filter_radar(ds):
    ds = ds.where((ds.DBZH > -10) & (ds.DBZH < 75))
    return ds

[5]:

dtree = dtree.xradar.map_over_sweeps(filter_radar)

[6]:

# Create a figure and axis
fig, ax = plt.subplots(figsize=(7, 5))
dtree["sweep_2"]["DBZH"].plot.contourf(
    x="x",
    y="y",
    levels=range(-10, 75),
    cmap="NWSRef",
    ylim=(-200e3, 300e3),  # Adjust y-axis limits
    xlim=(-200e3, 300e3),  # Adjust x-axis limits
    ax=ax,  # Use the created axis
)
# Set the title
ax.set_title(
    f"{dtree.attrs['instrument_name']} {dtree['sweep_0']['time'].min().values}"
)
# Show the plot
plt.show()

[7]:

%%time
ds = dtree.radarx.to_grid(
    data_vars=["DBZH"],
    pseudo_cappi=True,
    x_lim=(-100000.0, 100000.0),
    y_lim=(-100000.0, 100000.0),
    z_lim=(0, 10000.0),
    x_step=1000,
    y_step=1000,
    z_step=250,
    x_smth=0.2,
    y_smth=0.2,
    z_smth=1,
)

CPU times: user 8.55 s, sys: 1.69 s, total: 10.2 s
Wall time: 11.2 s

[8]:

ds.radarx.plot_max_cappi("DBZH", cmap="ChaseSpectral", add_slogan=True)

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[8]:

[9]:

%%time
ds2 = dtree.radarx.to_grid(
    data_vars=["DBZH"],
    pseudo_cappi=False,
    x_lim=(-200000.0, 200000.0),
    y_lim=(-200000.0, 200000.0),
    z_lim=(0, 15000.0),
    x_step=1000,
    y_step=1000,
    z_step=250,
    x_smth=0.2,
    y_smth=0.2,
    z_smth=1,
)

CPU times: user 5.23 s, sys: 600 ms, total: 5.83 s
Wall time: 5.83 s

[10]:

ds2.radarx.plot_max_cappi("DBZH", cmap="ChaseSpectral", add_slogan=True)

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../_images/notebooks_Grid_Radar_11_1.png

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[10]:

../_images/notebooks_Grid_Radar_11_3.png

Grid Radar -> Plot Max-CAPPI#

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