Clutter detection by using space-born cloud images

Contents

Clutter detection by using space-born cloud images#

import matplotlib.pyplot as plt
import numpy as np
import wradlib as wrl
import wradlib_data
import xarray as xr
import xradar as xd
from IPython.display import display
from osgeo import osr

Construct collocated satellite data#

proj_radar = osr.SpatialReference()
proj_radar.ImportFromWkt(vol.crs_wkt.attrs["crs_wkt"])

filename = "hdf5/SAFNWC_MSG3_CT___201304290415_BEL_________.h5"
filename = wradlib_data.DATASETS.fetch(filename)

Downloading file 'hdf5/SAFNWC_MSG3_CT___201304290415_BEL_________.h5' from 'https://github.com/wradlib/wradlib-data/raw/main/data/hdf5/SAFNWC_MSG3_CT___201304290415_BEL_________.h5' to '/home/docs/.cache/wradlib-data'.

sat_gdal = wrl.io.read_safnwc(filename)
val_sat = wrl.georef.read_gdal_values(sat_gdal)
coord_sat = wrl.georef.read_gdal_coordinates(sat_gdal)
proj_sat = wrl.georef.read_gdal_projection(sat_gdal)
coord_sat = wrl.georef.reproject(coord_sat, src_crs=proj_sat, trg_crs=proj_radar)

coord_radar = np.stack((vol.x, vol.y), axis=-1)
coord_sat[..., 0:2].reshape(-1, 2).shape, coord_radar[..., 0:2].reshape(-1, 2).shape

((180000, 2), (1728000, 2))

interp = wrl.ipol.Nearest(
    coord_sat[..., 0:2].reshape(-1, 2), coord_radar[..., 0:2].reshape(-1, 2)
)

val_sat = interp(val_sat.ravel()).reshape(coord_radar.shape[:-1])

Estimate localisation errors#

timelag = 9 * 60
wind = 10
error = np.absolute(timelag) * wind

Identify clutter based on collocated cloudtype#

rscale = vol.range.diff("range").median().values
clutter = wrl.classify.filter_cloudtype(
    vol.DBZH, val_sat, scale=rscale, smoothing=error
)

Plot the results#

fig = plt.figure(figsize=(16, 8))

tilt = 0

ax = fig.add_subplot(131)
pm = vol.DBZH[tilt].wrl.vis.plot(ax=ax)
# plt.colorbar(pm, shrink=0.5)
plt.title("Radar reflectivity")

ax = fig.add_subplot(132)
pm = vol.sat[tilt].wrl.vis.plot(ax=ax)
# plt.colorbar(pm, shrink=0.5)
plt.title("Satellite cloud classification")

ax = fig.add_subplot(133)
pm = vol.clutter[tilt].wrl.vis.plot(ax=ax)
# plt.colorbar(pm, shrink=0.5)
plt.title("Detected clutter")

fig.tight_layout()

../../_images/8592be1e8171ad8b9e035f0bbd668f477a37e8333227c8e99f237ac59e7af099.png