Geoscience Reference
In-Depth Information
and two parameters of radar beam: beam width and radar pulse length. Related quality index
may be determined from broadenings of the both beam cross section (Ośródka et al., 2012).
4.3 Ground clutter removal
The correction of radar data due to contamination by ground clutter is commonly made at a
level of radar system software which uses statistical or Doppler filtering (e.g. Selex, 2010). In
such situation the information about the correction is not available so generation of a
ground clutter map for the lowest (and higher if necessary) scan elevation must be
employed, e.g. using a digital terrain map (DTM). In order to determine areas contaminated
by ground clutter a diagram of partial beam blockage values
(
PBB
) is analysed. The
PBB
is
defined as a ratio of blocked beam cross section area to the whole one.
Gates where ground clutter was detected should be characterized by lowered quality index.
A simple formula for quality index
QI
GC
related to ground clutter presence can be written as:
a
ground clutter is detected
1no lu ter
(3)
QI
GC
where
a
is the constant, e.g. between 0 and 1 in the case of
QI
i
(0, 1). The quality index
decreases in each gate with detected clutter even if it was removed.
4.4 Removal of non-meteorological echoes
Apart from ground clutter other phenomena like: specks, external interference signals (e.g.
from sun and Wi-Fi emitters), biometeors (flock of birds, swarm of insects), anomalous
propagation echoes (so called anaprop), sea clutter, clear-air echoes, chaff, etc., are
considered as non-meteorological clutter. Since various types of non-precipitation echoes
can be found in radar observations, in practice individual subalgorithms must be developed
to address each of them. More effective removal of such echoes is possible using dual-
polarization radars and relevant algorithms for echo classification.
Removal of external interference signals
.
Signals coming from external sources that interfere
with radar signal have become source of non-meteorological echoes in radar data more and
more often. Their effect is similar to a spike generated by sun, but they are observed in any
azimuth at any time, mainly at lower elevations, and may reach very high reflectivity. The
spurious spike-type echoes are characterized by their very specific spatial structure that
clearly differs from precipitation field pattern (Peura, 2002; Ośródka et al., 2012): they are
observed along the whole or large part of a single or a few neighbouring radar beams.
Commonly reflectivity field structure is investigated to detect such echo on radar image
(Zejdlik & Novak, 2010). Recognition of such echo is not very difficult task unless it
interferes with a precipitation field: its variability is low along the beam and high across it.
The algorithm removes it from the precipitation field and replaces by proper (e.g.
interpolated) reflectivity values. In the algorithm of Ośródka et al. (2012) two stages of spike
removal are introduced: for “wide” and “narrow” types of spikes.
Removal of “high” spurious echoes.
“High” spurious echoes, not only spikes, are echoes
detected at altitudes higher than 20 km where any meteorological echo is not possible to
exist. All the “high” echoes are removed.
