Met Office College - Course Notes
Radar imagery
Contents
1. Basic principles
2. Presentation radar data
2.1 Plan position indicator (PPI)
Constant altitude plan position indicator (CAP)
2.3 Range–height indicator (RHI)
3. Problems in radar imagery interpretation
3.1 Spurious echoes
3.2 Anomalous propagation (anaprop)
3.3 Secondary radar echoes.
3.3.1 Second-trip echoes
3.3.2 Sidelobe echoes
3.3.3 Flare echoes
3.4 Screening of precipitation by hills
Growth and evaporation of precipitation below the beam.
3.6 Drop-size effects
Snow and ice: bright bands.
3.8 Adjustment of radar rainfall estimates using rain gauge data
These notes are extracts from ‘Images in Weather Forecasting’
by MJ Bader, GS Forbes, JR Grant, RBE Lilley and AJ Waters
 Crown Copyright. Permission to quote from this document must be obtained from The
Principal, Met Office College
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1. Basic principles
The distribution and intensity of precipitation can be measured using
weather radars which operate in the 3 to 10 cm wave-length range. With
radiation of this type the detection of cloud particles is virtually
impossible and most weather radars respond only to larger,
precipitation-sized, particles. A radar measures the power scattered
back to it from the multitude of precipitation-sized water droplets or
snow flakes in a volume of atmosphere. Such a volume, known as a
‘pulse volume’, and is defined by the pulse length l, the radar beamwidth  and the range r. Measurements are made virtually
simultaneously in pulse volumes at different ranges during the rotation
of the radar beam.
Figure 1.
Geometery of a
pulse volume,
Pulse length l,
range r and
beam-width .
Pulse volumes are not small, at a range of 100 km with typical values of
l = 1 km and  = 1°, the pulse volume is 1 km 3. Provided a pulse volume
is completely and uniformly filled with raindrops the average power
(Pr) returned from the raindrops at a range r is given by:
Pr 
C1C2 ZK
(radar equation)
r2
where:
r
Is the range.
Pr
Is the average power returned from the raindrops at range r.
C1
Depends on the calibration of the radar hardware.
C2
Depends on the type of precipitation (rain or snow).
Z
Is the radar reflectivity factor.
K
Is an attenuation coefficient accounting for energy loss as the
radar beam passes through intervening precipitation.
The radar reflectivity factor Z is defined as the sum over unit volume of
the sixth power of the raindrop diameters D (Z=D6)
The signal strength of successive radar echoes produced by
precipitation fluctuates rapidly due to the motion of the particles, and
the value of Pr has to be an average of some 25 independent sample
measurements. It is important to understand that the radar equation is a
very simplified relationship that depends on many assumptions.
These include:
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a) A pulse volume is completely filled with small, spherical, randomly
located precipitation particles.
b) The particles are either all water or all ice.
c) Z is uniform throughout the pulse volume and constant during the
sampling interval.
Any abnormalities either in the distribution of the meteorological
elements or in the performance of the radar hardware will detract from
the representivity of Pr or Z. Despite this limitation it is common
practice to convert Z into a corresponding rainfall rate, ‘R’. This is done
by using an empirical Z–R relationship of the type
Z = aRB where Z depends on D6
The value of R depends on several things:
 The liquid water content
 The fall speed of the raindrop, which is also a function of the
diameter of the drops
 The presence of updraughts or downdraughts
Strong updraughts may even keep precipitation suspended inside the
cloud. Accurate conversion of Z into R therefore requires a knowledge
of the drop-size spectrum and the vertical wind speed, both of which
vary in time and space. No simple relationship between Z and R can
therefore give accurate results in every situation.
Through experimentation the problem has been solved empirically and
typical values used are:
 for stratiform rain, a = 200 and B = 1.6
 for convective rain, a = 350 and B = 1.4.
In practice, real-time adjustments to the Z–R conversion are sometimes
made using readings from a number of rain gauges.
2. Presentation radar data
2.1 Plan position indicator (PPI)
This is the most common display of radar data, and the majority of
radar images are of this type. For a given elevation angle of the radar
beam, the data are projected on to the ground plane. The data come
from close to the ground at short ranges and from higher altitudes at
longer ranges. Figure 2 shows how the height of the beam changes with
distance. It is worth noting that many radars are sited on hilltops, so
away from the immediate vicinity of the radar the height of the beam
above ground may be greater than that shown in Figure 2.
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Figure 2. The variation in height and width of a radar beam with distance
given an elevation of 1.5o.
2.2 Constant altitude plan position indicator (CAP)
An alternative to a single PPI display is a constant altitude PPI, or
CAPPI, display. This is constructed in a computer from a series of
circular sweeps at different elevation angles, low at long ranges and
high at short ranges, so that the beam centres are all at nearly the same
altitude above the radar site level and the rate of rainfall at that altitude
is displayed.
2.3 Range–height indicator (RHI)
An RHI display is a vertical cut through the atmosphere, made by
nodding the radar antenna up and down at a specific azimuth. This
form of display shows the vertical extent of precipitation elements
within a cloud system and of certain micro-physical processes
associated with them. For example, the level of the melting layer can
usually be readily detected by the enhanced returns from wet snow,
known as the ‘bright band’. The vertical pattern of reflectivity can also
be used to classify rainfall events into stratiform, convective or severe
storm types.
3. Problems in radar imagery interpretation
The interpretation of radar images in terms of rainfall intensity at the
ground is complicated by several factors. These require the modification
of observed patterns of radar echoes from within a cloud. Although
useful corrections for these factors can be made automatically, both for
single radars and in an operational network, they cannot be wholly
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eliminated and an understanding of their effects constitutes an
important step in improving the usefulness of the imagery to
forecasters.
3.1 Spurious echoes
Not all echoes on a weather radar are due to rain or snow. Nonmeteorological returns may be caused by:
 The Earth’s surface and stationary objects on it.
 Transient objects such as ships, aircraft, birds, insects.
 Technical problems with the radar equipment.
 Interference from other sources, such as nearby radars.
On PPI displays the patterns produced by many of these effects are so
different from real meteorological echoes that their occurrences are
easily identifiable and do not mislead forecasters. The most common of
the non-meteorological echoes are ground echoes, or ‘clutter’. These
occur when a radar beam intersects any surface feature, such as high
ground, buildings and trees. The echoes mainly occur close to the radar
site, where the beam is at a low elevation and they can be identified by
their persistence. Ground clutter, shown in Figure 3, can be substantially
reduced by the automated use of the following.
i. A ground clutter map generated from the echoes received on a
cloudless day. Echoes from the clutter regions on subsequent rainy
days can then be ignored, and interpolated data from surrounding
areas can be used.
ii. A higher beam elevation at close range, or a CAPPI presentation at
an elevation above the level of the terrain.
iii. Doppler radar, picking out and eliminating stationary clutter from
moving rain.
Figure 3. An example of ground clutter from a single radar site on a cloudless day.
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3.2 Anomalous propagation (anaprop)
Anomalous propagation occurs during conditions of strong static
stability in the lower atmosphere. Figure. 4 (a) shows a typical structure,
with a strong temperature inversion and marked hydrolapse at a level
of a few thousand feet (1–2 km). Within the inversion layer the radar
beam is refracted downwards relative to its initial path, and an
abnormal increase in ground clutter is then observed. Over land,
anaprop produces a chaotic, speckled display of echoes with large
changes of intensity. Over the sea the effect is often less pronounced,
but with rough seas it may be as strong as over land. Anaprop is most
common in anticyclonic conditions or when there is a deep (100–200 m)
nocturnal inversion from the surface. In the latter situation its onset and
cessation can often be rapid, especially during the formation or
breakdown of the inversion. An animated display can be helpful in
identifying anaprop, which usually either appears stationary or moves
erratically. Occasionally, however, echoes due to anaprop can move
systematically like real rain. PPIs at high elevation angles, or CAPPIs at
higher altitudes, usually show no returns and are effective in
eliminating the problem from a single radar display. With a network,
the marked differences observed by the overlapping radars may enable
some of the anaprop to be identified.
Radar
Ground echoes
Returned
Figure 4. The top diagram (a) shows a typical vertical temperature structure
associated with anaprop. The bottom diagram shows the path of the radar beam.
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3.3 Secondary radar echoes.
The term ‘secondary echoes’ is used here to summarize some
comparatively rare effects deriving from the non-standard performance
of a radar system or from multiple reflections of a radar beam in hail
storms. These echoes are rarely a problem in northern Europe.
3.3.1 Second-trip echoes
A radar has a maximum effective range for determining rainfall rates
and this depends on its pulse repetition frequency, or the time interval
between successive pulses. Only those echoes that return during the
interval between the transmission of one pulse and the next can have
their locations unambiguously interpreted. Echoes from targets beyond
this maximum range return to the radar after the next pulse has been
transmitted. Their distances are then determined from the short time
interval elapsing since the most recent transmission, rather than from
the longer time interval since the transmission of the original pulse. A
false, elongated echo emanating from the radar site may then be
displayed, see Figure 5. Such effects are known as second-trip echoes,
and may be very unexpected and unnerving for an inexperienced user.
Figure 5 Second trip echoes from beyond the normal maximum range of the radar
shown by X.
The top diagram (a) show a range height indication diagram where the rain clouds are
within and partly beyond the maximum range.
The bottom diagram(b) shows is a schematic Plan Position Indicator with real echoes A
and B1, there is also a false echo shown by B2.
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3.3.2 Sidelobe echoes
Radars transmit energy along a mainbeam having a typical beam-width
of about 1°. There are also secondary power transmissions along side
lobes located a few degrees from the main beam centre. Normally the
side lobe returns are too weak to be significant. An exception may occur
with very highly reflective targets, such as columns of heavy rain or hail
within a cumulonimbus cloud. Figure 6. shows a schematic range height
indicator presentation through a distant cumulonimbus, with the main
radar beam drawn at a high elevation that passes above the physical
echo top. The side lobe transmission, however, is still striking the hail
column within the cloud, and the resulting echo is associated by the
radar with the main beam. Thus an apparent ‘spike’ is produced, up to
the main beam level, giving an exaggerated estimate of where the true
echo top lies.
Figure 6 The main radar beam overshoots the cloud top but the sidelobe transmission
is reflected. The true top of the cloud is given by T and T’ is the observed top.
3.3.3 Flare echoes
Another effect which can cause a ‘hailspike’ to appear on a PPI display,
as in Figure 7 (a), is the result of lengthening the path of the returning
echo through multiple reflections from the hail and the ground. This is
shown schematically in Figure 7 (b). The extra time taken for the signal
to return is interpreted by the radar as a more distant echo and is
represented as a radial spike extending away from the storm, as at H in
Figure 7.
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H
Figure 7 The top diagram (a) shows a flare echo indicated by H. The bottom diagram
(b) indicates the process of multi-reflection of radar signal from hail and ground.
3.4 Screening of precipitation by hills
Screening, or occultation, of precipitation by hills results in a reduction
of the rainfall that is estimated by a radar at places beyond the high
ground, as illustrated in Figure 8. Provided that the screening is only
partial, corrections to the estimated rainfall can be applied routinely
from a knowledge of the topography, according to the percentage of the
total beam that is blocked by the hills.
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Figure 8 The effect of hills blocking a radar beam
3.5 Growth and evaporation of precipitation below the beam.
The best estimate of the surface rainfall intensity is obtained when the
radar beam elevation is as low as possible, compatible with the
screening and ground clutter problems discussed above. But, as shown
in Figure 9 (a), even at the lowest angle of elevation some rainfall
detected within a cloud (at L) may evaporate in dry air below the level
of the beam. This will lead to an overestimate of the rainfall rate at the
surface (O). A practical consequence of this evaporation may be a forecast error of one to two hours for the start of rain at the surface,
especially at the leading edge of warm fronts. The effect is most
noticeable at long ranges, where the beam may be several kilometres
above the ground. A process leading to the opposite effect is illustrated
in Figure 9 (b). The low-level enhancement of rainfall beneath the radar
beam is common over wind-facing slopes. Light rain (L), formed in
higher level clouds and falling through very moist, cloudy air near the
surface can lead to a large increase in the rainfall rate (H) at very low
levels. This is the ‘seeder-feeder’ mechanism of rainfall intensification.
The enhancement is frequently not detected by radar over hilly terrain
where the beam must be high to avoid the effects of ground clutter.
3.6 Drop-size effects
The Z–R relationships quoted in Section 1 contain an implicit
assumption concerning the drop sizes at different rain-fall rates. They
tend to overestimate the actual rainfall rate from clouds such as
cumulonimbus, which have a greater proportion of larger raindrops
than assumed. Equally, those layer clouds which contain smaller
raindrops than assumed will have their rainfall underestimated. A
correction for this non-uniformity may be made by comparing the radar
estimates of rainfall with those observed in a local rain gauge network
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Figure 9 Variation in rainfall rates below cloud. Top diagram (a) shows the
evaporation of rain below the radar beam. The bottom diagram (b) shows the
increased rainfall by orographic enhancement below the radar beam.
3.7 Snow and ice: bright bands.
Snow flakes and ice particles have a refractive index and fallspeed
which are significantly different from those of raindrops. Z–R
relationships which have been established for snow are different from
those for rain (see Section 1). A typical relationship is
Z = 2000 R2.
This relationship implies that radars operating at a wavelength of about
10 cm are insensitive to light snowfalls. Coupled with the shallow depth
of cloud associated with many snowfalls this means that 3 cm radars,
which have a high sensitivity and narrow beam-width, are preferable
for obtaining the best results under these conditions. In temperate
climates, much of the precipitation that reaches the ground as rain is
originally formed as ice and snow at high levels inside a cloud. As they
fall to Earth the frozen crystals become coated with liquid water at the
melting level and for a short distance below. In this form their radar
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reflectivity is much higher than that of either the snow at higher levels
or the rain below. A band of high reflectivity known as a bright band is
formed. On PPI displays a bright band takes the form of a ring of
spuriously high rain-fall. It is often identifiable in an extensive
stratiform rain area by its roughly circular arc shape, as in Figure 10.
Figure 10 Bright band (circular echo in centre of the picture) due to melting
snow indicating heavier rain than actually occurred
Hailstones in Cumulonimbus clouds can become very large. Just a few
of these, particularly if covered with a layer of water, can give every
large reflectivities. For operational forecasters this response may
provide a very useful signal on a radar display of the occurrence of
severe weather. However, it will not be a good guide to the equivalent
rate of rainfall, as the scattering of the radar beam by large hailstones
does not obey the same law as scattering by smaller sized rain or snow
particles. Without special calibration a radar tends to overstate the
rainfall rate, for, although hail may be very damaging in its effects, it
may nevertheless produce only modest amounts of precipitation.
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3.8 Adjustment of radar rainfall estimates using rain gauge data
Radar estimates of rainfall are liable to all the sources of error
mentioned above in Section 3. Even though corrective measures are
taken, there will always be some level of error remaining in the radar
estimates, and a comparison between them and some relevant rain
gauge values is both wise and necessary. It is quite impractical to
compare every detail of the rainfall distribution over a radar’s target
area, of some 30,000 km2 , as this would require a huge number of
gauges. In practice, therefore, some three or four gauges are connected
to a radar’s on-site computer, and calibration is carried out
automatically on the basis of the telemetered readings from this very
restricted network. Research has shown that the ratio averaged over
periods of an hour varies significantly with the meteorological character
of the rain (stratiform or convective)and with the presence or absence of
bright band effects on the radar display. An important step in an
automated operational system is therefore the identification of the
precipitation type(showers, frontal precipitation, orographic
precipitation in warm sectors) and bright band from the variations in B
observed at each of the telemetering rain gauges during the course of
each hour. It has been possible to derive a method that gives acceptable,
but obviously not perfect, results. It is possible to define areas of
particular rainfall types, and thus to adjust the radar measurements
within them accordingly. There is a strong empirical element in the
details of the procedure, but its justification lies in the practical value of
the results, which have been shown to be useful in certain synoptic
situations (e.g. with orographic enhancement). Much further work can
be done, especially in more northerly regions where bright band effects
are frequent because of the low altitude of the melting level.
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