This notebook is part of the $$\omega radlib$$ documentation: https://docs.wradlib.org.

Copyright (c) $$\omega radlib$$ developers. Distributed under the MIT License. See LICENSE.txt for more info.

# Simple fuzzy echo classification from dual-pol moments¶

In [1]:

import wradlib
import os
import numpy as np
import matplotlib.pyplot as plt
import warnings
warnings.filterwarnings('ignore')
try:
get_ipython().magic("matplotlib inline")
except:
plt.ion()


## Setting the file paths¶

In [2]:

rhofile = get_wradlib_data_file('netcdf/TAG-20120801-140046-02-R.nc')


## Read the data (radar moments and static clutter map)¶

In [3]:

# We need to organize our data as a dictionary
dat = {}


## Identify non-meteorological echoes using fuzzy echo classification¶

See Crisologo et al. (2015) and Vulpiani et al. (2012) for details.

In [4]:

weights = {"zdr": 0.4,
"rho": 0.4,
"rho2": 0.4,
"phi": 0.1,
"dop": 0.1,
"map": 0.5}
weights=weights,
thresh=0.5)


## View classfication results¶

In [5]:

fig = plt.figure(figsize=(18,16))

#   Horizontal reflectivity
ax = plt.subplot(121, aspect="equal")
ranges=[80,160,240])
plt.xlim(-240,240)
plt.ylim(-240,240)
plt.xlabel("# bins from radar")
plt.ylabel("# bins from radar")
cbar = plt.colorbar(pm, shrink=0.3)
cbar.set_label("dBZ", fontsize = "large")

#   Echo classification
ax = plt.subplot(122, aspect="equal")