How to filter rays

Corrections/Data Quality
, ,
1

How to filter rays coming mentioned inside black boundry, I not sure but I think these problem beacause of antenna transition. I have given google drive link netcdf file inside that,this radar have reflectivity, velocity, spectral width

BHP210601105223
BHP210601105223994×668 201 KB

2

Since the data is already filtered, at this moment, the easiest is to mask the reflectivity using the mask of spectrum width.

def apply_mask(radar):
    radar.fields['reflectivity']['data'] = np.ma.masked_where(
        radar.fields['spectrum_width']['data'].mask, radar.fields["reflectivity"]['data'])
    return radar
files = glob.glob("BHP*nc")
files.sort()
for file in files:
    radar = pyart.io.read(file)
    radar = apply_mask(radar)
#     pyart.io.write(os.path.join(out_dir ,file))

image
image883×409 48.9 KB

image
image883×409 49.1 KB

3

You can also try wradlib data quality — Project Pythia Cookbook Template, and tweak the thresholds.

import xarray as xr
def extract_clutter(da, wsize=3, thrsnorain=0, tr1=6.0, n_p=6, tr2=1.3, rm_nans=False):
    return xr.apply_ufunc(
        wrl.clutter.filter_gabella,
        da,
        input_core_dims=[["azimuth", "range"]],
        output_core_dims=[["azimuth", "range"]],
        dask="parallelized",
        kwargs=dict(
            wsize=wsize,
            thrsnorain=thrsnorain,
            tr1=tr1,
            n_p=n_p,
            tr2=tr2,
            rm_nans=rm_nans,
        ),
    )

vol = wrl.io.open_cfradial1_dataset("BHP210601104223.nc")
swp0 = vol[0].pipe(wrl.georef.georeference_dataset)

clmap = swp0.reflectivity.pipe(
    extract_clutter, wsize=3, thrsnorain=0.0, tr1=14, n_p=2, tr2=1.5, rm_nans=False
)

swpx = swp0.assign({"CMAP": clmap})
fig = plt.figure(figsize=(15, 12))

ax1 = fig.add_subplot(221)
swpx.reflectivity.plot(x="x", y="y", ax=ax1, vmin=0, vmax=60)
ax1.set_title("Reflectivity raw")

ax2 = fig.add_subplot(222)
swpx.CMAP.plot(x="x", y="y", ax=ax2)
ax2.set_title("Cluttermap")

ax3 = fig.add_subplot(223)
swpx.reflectivity.where(swpx.CMAP == 1).plot(
    x="x", y="y", ax=ax3, vmin=0, vmax=60
)
ax3.set_title("Clutter")

ax4 = fig.add_subplot(224)
swpx.reflectivity.where(swpx.CMAP < 1).plot(
    x="x", y="y", ax=ax4, vmin=0, vmax=60
)
ax4.set_title("Reflectivity clutter removed")

image
image1269×1007 105 KB

1 Like
4

@kmuehlbauer can help you to apply it on full volume and export the data to the desired format.

1 Like
5

Thanks @syedhamidali, great writeup an nice link to the ERAD2022 workshop. I’ll try to get to this the next days.

2 Likes
6

deeply thanks @syedhamidali

7

@sanjayyadav3184 First, welcome to openradar community and discourse.

Thanks to the fine work of @syedhamidali I was able to quickly transform this to using next generation Python packages.

Please have a look at this gist: Jupyter Notebook Viewer

1 Like
8

thank you sho much Sir

9

You are welcome, @sanjayyadav3184. Glad, we were able to help.