Radar - Volume#

Import Section#

import datetime as dt
import os

import matplotlib.pyplot as plt
import wradlib as wrl

Utility Functions#

import radarpolarimetry as rp

Load Radar Data Sweep#

Select time#

For a single volume a certain 5 minute interval is selected.

# recent boxpol event
start_time = dt.datetime(2018, 4, 10, 16, 15)
stop_time = dt.datetime(2018, 4, 10, 16, 20)

get file path#

# choose radar specific parameters
scan = "*ppi*"

path = rp.get_xpol_path(start_time=start_time)
file_path = os.path.join(path, scan)

print(file_path)

/radar/rp-data/scans/2018/2018-04/2018-04-10/*ppi*

get file list#

flist = list(rp.create_filelist(os.path.join(file_path, "*"), start_time, stop_time))
display(flist)

['/radar/rp-data/scans/2018/2018-04/2018-04-10/n_ppi_010deg/n_ppi_010deg_12345_20180410161835_00.h5',
 '/radar/rp-data/scans/2018/2018-04/2018-04-10/n_ppi_020deg/n_ppi_020deg_12345_20180410161800_00.h5',
 '/radar/rp-data/scans/2018/2018-04/2018-04-10/n_ppi_031deg/n_ppi_031deg_12345_20180410161734_00.h5',
 '/radar/rp-data/scans/2018/2018-04/2018-04-10/n_ppi_045deg/n_ppi_045deg_12345_20180410161709_00.h5',
 '/radar/rp-data/scans/2018/2018-04/2018-04-10/n_ppi_060deg/n_ppi_060deg_12345_20180410161652_00.h5',
 '/radar/rp-data/scans/2018/2018-04/2018-04-10/n_ppi_082deg/n_ppi_082deg_12345_20180410161636_00.h5',
 '/radar/rp-data/scans/2018/2018-04/2018-04-10/n_ppi_110deg/n_ppi_110deg_12345_20180410161619_00.h5',
 '/radar/rp-data/scans/2018/2018-04/2018-04-10/n_ppi_140deg/n_ppi_140deg_12345_20180410161604_00.h5',
 '/radar/rp-data/scans/2018/2018-04/2018-04-10/n_ppi_180deg/n_ppi_180deg_12345_20180410161549_00.h5',
 '/radar/rp-data/scans/2018/2018-04/2018-04-10/n_ppi_280deg/n_ppi_280deg_12345_20180410161533_00.h5']

load data#

As already learned in radar_timeseries_sweep.md we apply reindex to the data, as we finally want to merge all sweeps into one Dataset.

reindex_angle = dict(start_angle=0, stop_angle=360, angle_res=1.0, direction=1)
vol = rp.load_volume(flist, reindex_angle=reindex_angle)

Select single sweep and plot Reflectivity#

rp.plot_moment(vol["sweep_0"].DBZH, vmin=0)

<matplotlib.collections.QuadMesh at 0x7fdc9d7857f0>

../../_images/a2ef10ebaea39ae5bbf26a26c3fe4348f88ef48c0fd47f40a571c4bf0a25d711.png

Extract a single azimuth#

We can extract a certain azimuth angle by using the cross_section_ppi utility-function.

azimuth = 60
rec_rhi = wrl.util.cross_section_ppi(el, azimuth, method="nearest")

rec_rhi.DBZH.plot(
    x="gr", y="z", ylim=(0, 14000), xlim=(0, 140000), vmin=0, cmap="HomeyerRainbow"
)

<matplotlib.collections.QuadMesh at 0x7fdc98a12350>

../../_images/702b411a3bb31e16421f5006d1c9cd8ac13a7a1e283eb5787754ca3bc6c5188a.png

Select two points and create cross section#

p1 = (38000, 0)
p2 = (23000, 40000)

# Plot the chosen line over a PPI
vol["sweep_0"].DBZH.wrl.vis.plot(vmin=0)
plt.plot([p1[0], p2[0]], [p1[1], p2[1]], c="black")

[<matplotlib.lines.Line2D at 0x7fdc9890aad0>]

../../_images/ad901e5ef37dc691349acb07be005e26d971ac30838be9939b8af9daf629b8f3.png

# Extract cross section and plot result
rec_rhi = wrl.util.cross_section_ppi(el, (p1, p2))

# We have to use the new coordinate "xy" (meters along the line from p1 to p2) for plotting

rec_rhi.DBZH.plot(cmap="HomeyerRainbow", x="xy", y="z", ylim=(0, 10000), vmin=0)

<matplotlib.collections.QuadMesh at 0x7fdc986334d0>

../../_images/b7989a8e05dfc23636910b1c62d12370ed8f62cecf0c7f4bd7a2cc68d8ad7a99.png

Exercise 2: Select arbitrary cross section#

Select another (interesting) cut through this volume and plot the resulting cross section.

Solution 2: Select arbitrary cross section#

p1 = (70000, 0)
p2 = (23000, 40000)

# Plot the chosen line over a PPI
vol["sweep_0"].DBZH.wrl.vis.plot(vmin=0)
plt.plot([p1[0], p2[0]], [p1[1], p2[1]], c="black")

[<matplotlib.lines.Line2D at 0x7fdc9868ae90>]

../../_images/a563b2f5ba40297504d13db8a917a327100176a8b97894cf1a8f2c812f1fa412.png

# Extract cross section and plot result
rec_rhi = wrl.util.cross_section_ppi(el, (p1, p2))

# We have to use the new coordinate "xy" (meters along the line from p1 to p2) for plotting
rec_rhi.DBZH.plot(cmap="HomeyerRainbow", x="xy", y="z", ylim=(0, 10000), vmin=0)

<matplotlib.collections.QuadMesh at 0x7fdcb3373610>

../../_images/5b6edb830e058301dfaad6845cc61ad3a93a4dd59443715b752f7842191a7b27.png

Radar - Volume

Contents