Cloud radar observations of vertical drafts and microphysics in convective rain
←
→
Page content transcription
If your browser does not render page correctly, please read the page content below
JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 107, NO. 0, XXXX, doi:10.1029/2001JD002033, 2002
Cloud radar observations of vertical drafts and microphysics in
convective rain
Pavlos Kollias and B. A. Albrecht
Division of Meteorology and Physical Oceanography, University of Miami, Miami, Florida, USA
F. D. Marks Jr.
NOAA/AOML, Miami, Florida, USA
Received 21 December 2001; revised 1 May 2002; accepted 6 May 2002; published XX Month 2002.
[1] Observations of convective precipitation using a 94-GHz cloud radar are presented.
Due to Mie scattering, the Doppler power spectra collected at vertical incidence contains
characteristics of the scatterers (hydrometeors). These characteristics are used for the
retrieval of the vertical air motion and the associated raindrop size distribution in an
attempt to accurately map the time-height structure of the vertical air motion and raindrop
fields within intense convective precipitation. The data provide strong evidence of the
interaction between draft intensity and raindrop size distribution and highlight the
variability of convective precipitation at small scales. Horizontal sorting of the raindrops
caused by the air motion is documented. Signal attenuation measured at 94 GHz is shown
to be well correlated to rainfall rates. The observations demonstrate the capability of 94-
GHz cloud radars for studies of precipitation processes at low altitudes even under intense
convective conditions. INDEX TERMS: 3314 Meteorology and Atmospheric Dynamics: Convective
processes; 3354 Meteorology and Atmospheric Dynamics: Precipitation (1854); 3394 Meteorology and
Atmospheric Dynamics: Instruments and techniques
Citation: Kollias, P., B. A. Albrecht, and F. D. Marks Jr., Cloud radar observations of vertical drafts and microphysics in convective
rain, J. Geophys. Res., 107(0), XXXX, doi:10.1029/2001JD002033, 2002.
1. Introduction ating without polarization provide little information on the
spatial variability of DSDs. Often, the radar reflectivity,
[2] Accurate measurements of Drop-Size Distributions
which depends on the sixth power of the diameter (Rayleigh
(DSD) are fundamental for understanding the processes
scattering), is used to characterize the spatial homogeneity
governing cloud microphysics and improving precipitation
of the precipitation field. Such interpretation can lead to
representation in numerical models [e.g., Grabowski et al.
erroneous conclusions about the nature and variability of the
[1999]]. Especially at small scales, microphysical processes
precipitation field. Thus, most observational efforts focus on
such as condensation of water vapor, collision and coales-
the monitoring and classification of precipitating systems
cence between the droplets, evaporation in unsaturated air,
and surface rainfall measurements [e.g., Houze, 1993;
and droplet breakup contribute to the final product –the
Williams et al., 1995; Tokay et al., 1999; Cifelli et al.,
hydrometeor DSD [Feingold et al., 1988; Hu and Srivas-
2000; Kummerov et al., 2000; Williams et al., 2000]. Cloud
tava, 1995]. Furthermore, these processes are embedded in
modelers, however, require information on the evolution
vertical air drafts that influence the final shapes of the DSD
and modification of raindrop spectra under the action of
[Kollias et al., 2001]. As a result, and despite their impor-
physical processes operating on a very small scale in the
tance, the small-scale variability of DSD and their inter-
presence of vertical drafts. Several researchers in the past
action with air drafts remains unknown, especially at scales
[Srivastava, 1971; Carbone and Nelson, 1978; List et al.,
unresolved by most active and passive remote sensing
1987; Hu and Srivastava, 1995] have investigated the form
instruments.
of the equilibrium DSD under the influence of various
[3] Doppler radars are traditionally used to study precip-
microphysical processes. Apart from the complexity of the
itation. In a scanning mode they are excellent tools for
microphysical processes, observations of these small-scale
monitoring the intensity and motion of precipitating sys-
interactions in the presence of vertical motions are very
tems, but the quantitative rainfall rate retrievals are based on
difficult. As a result, these numerical studies cannot be
numerous assumptions. Nevertheless, knowledge of the
compared with observations, since these scales are unre-
spatial distribution of rainfall rates can be useful for a wide
solved. Therefore, over the last 20 years a gap between
range of applications. Unfortunately, scanning radars oper-
observations and modeling of precipitation processes has
developed.
Copyright 2002 by the American Geophysical Union. [4] Vertically pointing radars can provide excellent verti-
0148-0227/02/2001JD002033$09.00 cal and temporal resolution. Furthermore, their mean Dop-
XX X-1XX X-2 KOLLIAS ET AL.: CLOUD RADAR OBSERVATIONS OF CONVECTIVE RAIN
pler velocity can be related to the sum of the air motion and
raindrop’s terminal velocity. Wind profilers, in particular,
can detect both Bragg scattering (clear-air scattering) and 0
Rayleigh scattering (hydrometeors) [e.g., Rogers et al., 10
1993] and therefore, under certain conditions, can success-
fully decompose the velocity measurements. When it is
σb/(pir2)
feasible, such decomposition [e.g., Wakasugi et al., 1986; –1
10
Gossard, 1988], can provide more information and at higher
resolution sampling compared with scanning radars. Under
precipitating conditions, profilers can provide the wind –2
10
profile at a single point and also map the vertical profile
of the overhead cloud system, since the attenuation at these
wavelengths is negligible. Despite the apparent potential for
–3
accurate measurements of vertical air motion and raindrop 10
spectra, the retrievals from wind profilers are subject to
many assumptions, therefore increasing the uncertainty of 0 0.1 0.2 0.3 0.4 0.5 0.6
Diameter (cm)
these measurements. Main sources of uncertainty are the
assumption on the maximum raindrop size observed; wind Figure 1. Normalized backscattering cross-section as a
shear induced Doppler spectra broadening and poor Doppler function of the diameter for oblate spheroids at 94 GHz and
spectrum velocity resolution. vertical incident.
[5] Observations of both the vertical air velocities and
raindrop fall speeds are very rare. Aircraft observations
[e.g., Beard et al., 1986; Szumowski et al., 1998; Atlas et performance of the technique under intense convective
al., 2000] are capable of this type of measurement, but they conditions is evaluated.
lack vertical coverage and are difficult to obtain near the
surface. Further, the sampling volume of aircraft micro-
physical probes is very small, thus results in under sampling 2. Background
of large raindrops in the DSD due to their low concen- 2.1. Millimeter-Wavelength Radars and Precipitation
tration. In addition, the horizontal sampling path is rela- [7] The use of millimeter wavelength radiation for pre-
tively large (700 – 800 m) and the lack of another dimension cipitating system studies overcomes a significant obstacle in
makes the interpretation of the data difficult. Despite these the DSD retrievals by accurately measuring the vertical air
sampling problems, aircraft penetrations are still the most motion. Figure 1 shows the 94-GHz normalized backscat-
reliable way to collect simultaneous measurements of the tering cross section sb as a function of raindrop diameter at
vertical air motion and raindrop size distributions. 20C. At 94 GHz, the backscattering cross-section versus
[6] In this paper, a new technique using a 94-GHz size function for raindrops with a diameter greater than 1
Doppler radar and a 915-MHz wind profiler is applied in mm oscillates. The raindrop diameters for which these
heavy convective rain [Lhermitte, 1987; Firda et al., 1999; minima and maxima occur are well predicted by Mie theory
Kollias et al., 1999, 2001]. Millimeter wave radars have [Mie, 1908]. The first minimum is well defined and occurs
been primarily used for cloud observations due to their high at a raindrop diameter of 1.7 mm. The vertical air velocity
sensitivity to small droplets and their ability to make high- can then be deduced from the simple difference between the
resolution observations of weak targets [Miller and terminal velocity of a raindrop with diameter 1.7 mm and
Albrecht, 1995; Vali et al., 1998; Kollias and Albrecht, the value of the first minimum in the Doppler spectrum
2000]. Lhermitte [1988] proposed an unexpected applica- (Figure 2) observed at vertical incidence with the millimeter
tion of millimeter radar based on the presence of Mie wave Doppler radar. Lhermitte [1988] first mentioned this
scattering due to the very short wavelength (3-mm) of 94- innovative technique in the context of stratiform rain
GHz radars. This technique capitalizes on the modulation of observations. Recently, Firda et al. [1999] and Kollias et
the Doppler spectrum by the backscattering function that in al. [1999, 2001] used this approach to study the retrieval of
the Mie regime oscillates between fixed maxima and precipitation and vertical air motion in stratiform rain and
minima. Under precipitating conditions at 94 GHz, these light convective rain using a vertically pointing 94-GHz
oscillations are apparent in the observed Doppler spectrum Doppler radar.
and can be used as reference points for the retrieval of the [8] The use of millimeter radars for the retrieval of
vertical air motion and subsequently the DSD. Using this raindrop spectra offers more advantages besides the accu-
94-GHz technique, high spatial and temporal measurements rate decomposition of the observed Doppler velocity. Milli-
of vertical air motion structures and DSDs in precipitating meter wave radars are designed as research tools, rather than
clouds were obtained. Unique observations of updrafts and weather warning and monitoring platforms. While their
downdrafts in convective systems are presented and their spatial coverage is no match for conventional radars and
interaction with the raindrop size distributions is docu- wind profilers, the short pulse width and the very narrow
mented. Signal attenuation is a prohibiting factor and affects beam width beam results in small sampling volumes. As a
the penetration of the 94-GHz radiation under high rainfall result, the effects of turbulence and wind shear on the
rates. In this paper, measurements of attenuation of 94-GHz Doppler spectrum are minimized [Kollias et al., 2002].
electromagnetic (EM) radiation in convective precipitation [9] Apart from the advantages in the use of millimeter
as a function of rainfall rates are presented. Thus, the radars for precipitation studies, strong attenuation of the 94-KOLLIAS ET AL.: CLOUD RADAR OBSERVATIONS OF CONVECTIVE RAIN XX X-3
88
Observed location of the st
Location of the 1 Mie
st minimum at VAIR = 0
86 1 Mie minimum
2nd
84
1st
82
3rd
80
Power
78
76
74
72
70
14 12 10 8 6 4 2 0 2 4
–1
Doppler Velocity (ms )
Figure 2. Example of Doppler spectrum from convective rain observed at vertical incidence with the
University of Miami 94-GHz Doppler radar. The modulating affect of Mie scattering is illustrated on the
Doppler spectrum. The velocity difference between the observed position of the 1st Mie minima and its
theoretically calculated location in still air provides the air motion.
GHz Electro-Magnetic (EM) waves in heavy rain is a section. Therefore, it is important to correct the Doppler
serious disadvantage. Lhermitte [1990] reports that the spectra corresponding to spherical raindrops to more real-
one-way attenuation can reach 7 – 8 dB km 1 for a rainfall istic oblate spheroid raindrops (Figure 1). The T-matrix
rate of 10 mm h 1. Hence, it is unlikely that the mm- [Mishchenko and Travis, 1994; Mishchenko, 2000]
wavelength radar can penetrate convective systems from the approach (or the extended boundary condition method), is
ground to the cloud top height in intense rainfall. In the used to solve the problem of scattering from nonspherical
region of cloud observed by the 94-GHz radar, the strong particles. The method uses the phase-scattering matrix that
attenuation makes the accurate measurement of reflectivity relates the intensity of the incident and scattered radiation.
values difficult. As a result, the retrieved DSD from the [11] The difference between the Doppler spectra for oblate
Doppler spectra are unscaled. However, reflectivity profiles spheroids and spherical raindrops is shown in Figure 3. Up
from a collocated 915-MHz wind profiler (the approach to 4 m s 1 the differences in the Doppler spectrum are
taken here) or other longer wavelength radars can be used to negligible, but beyond this limit the deviation is substantial.
scale the retrieved DSD. In a later section, the relationship The use of the Mie solutions for spherical particles can lead
between attenuation and rainfall rate is evaluated. to an overestimate of the large raindrops concentration
[Aydin and Lure, 1991]. In addition, the use of the Mie
2.2. Raindrop Distortion solutions for spherical particles will lead to an overestimate
[10] It is well known that the raindrop shape, especially of downdraft intensity. Using the T-matrix method, the
that of large raindrops (D 2 mm), deviates significantly location of the first Mie minimum is at D = 1.71 mm rather
from sphericity [e.g., Beard and Chuang, 1987]. Large than D = 1.67 mm for spherical particles. This difference
raindrops falling at terminal velocity exhibit an asymmetric causes a 7 cm s 1 shift in the location of the first minimum in
shape with a flattened base. This deviation of the equili- the terminal fall speed (5.95 m s 1 instead of 5.88 m s 1).
brium shape from sphericity and the use of very short
wavelength (l = 3.2 mm) requires the use of a scattering
model for nonspherical particles. The hydrostatic model 3. Instrumentation and Data Processing
proposed by Green [1975] is used to describe the equili- [12] During the summer and autumn of 1999 a combina-
brium shape of falling raindrops. This deviation from tion of instruments that included the University of Miami
sphericity creates differences in the backscattering cross- 94-GHz Cloud Radar (MCR) and a 915-MHz wind profilerXX X-4 KOLLIAS ET AL.: CLOUD RADAR OBSERVATIONS OF CONVECTIVE RAIN
1 time series of the rainfall rate during the observing period.
10
The rainfall rate record is essential for rain intensity
0 Oblate spheriods determination and comparison with the retrieved rainfall
10 Spheres rates from the radars. Since both the 94-GHz radar and the
wind profiler were vertical pointing, data from the Miami
–1 WSR-88D (KAMX) weather radar, operating at l = 10 cm
10
and located 28.4 km southwest of the MCR site were used
σv /(πr 2)
–2
for monitoring the evolution and horizontal structure of the
10 observed precipitating systems.
[16] The WSR-88D radar completes volume scans in
–3 multiple elevations within 5 – 6 min. However, due to it’s
10
coarse spatial and temporal resolution, the reflectivity
–4
values at the location of the site are of less significance
10 than the vertical profiles of reflectivity deduced by the
vertical pointing radars. In this study the WSR-88D pro-
–5 vides monitoring capability and continuous sampling cover-
10
0 2 4 6 8 10 age of large areas to map the horizontal structure, motion,
Velocity (ms–1)
and evolution of the precipitating systems.
Figure 3. Mie backscattering normalized cross-section at
a function of raindrops fall velocity for oblate spheroids 3.3. Data Postprocessing
(solid) and spheres (dashed). At large raindrops, dD [17] The basic data sets used in this study are the vertical
dv is very
large and causes accumulating effects, i.e., compression of profiles of Doppler spectra from the 915-MHz wind profiler
the Mie oscillations in the velocity domain and subsequent and the 94-GHz cloud radar. Initial processing included de-
accumulation of power density. aliasing of the Doppler spectra due to frequency folding and
noise-thresholding. Aliasing occurs if the actual frequencies
were used to observe convective and stratiform precipitating (velocities) exceed the Nyquist frequency (velocity).
systems passing over Virginia Key, Miami, Florida. [18] Once the de-aliased Doppler spectrum is recovered,
it is centered and a noise thresholding technique is applied
3.1. Vertically Pointing Radars that uses the edges of the Doppler spectrum [Lhermitte and
[13] A single-antenna Doppler radar operating at 94 GHz Kollias, 1999].
[Albrecht et al., 1999], is the principal source of observa- [19] The next step is the spectral peak detection. The peak
tions made in this study. The radar was operated with a 10 detection methods for the wind profiler and the cloud radar
kHz Pulse Repetition Frequency (PRF) to give a unambig- Doppler spectra are different. In the case of the wind profiler,
uous Doppler velocity window of ±8 m s 1. Doppler the method searches for possible bimodality arising from the
spectra measurements were based on the integration of coexistence of Bragg and precipitation spectral peaks. Two
10,000 samples (1-s dwell time). The recorded Doppler spectral peaks are often observed by the profiler under strati-
spectra had 512 points with 3.2 cm s 1 velocity resolution. form conditions, where the intensities from clear air echoes
In the radar observations reported here, the vertical reso- and light precipitation are of the same order of magnitude. In
lution is 30 m, thus providing a fine vertical resolution most cases there is no sign of the clear air echo in the 915-MHz
mapping of the cloud structure and boundaries. The antenna profiler spectra above 2 km [Rajopadhyaya et al., 1999]. The
beam width is 0.24, so that the radar horizontal resolution spectral peak detection algorithm is based on fitting a high
is about 8 m at 2 km range. For a 1-s dwell time and a order polynomial (up to 12th order) to the Doppler spectra.
typical cloud motion of 10 m s 1, the effective beam cross The high order in the polynomial fit is essential to capture the
section is approximately doubled. In the applications bimodality of the observed spectrum [Sato et al., 1990]. The
described in this paper, a 1-s signal sampling is followed first and second derivatives of the polynomial fit are calcu-
by a 2 to 3.5 s FFT processing so that a new vertical profile lated, and the local maxima and minima are located.
is obtained every 3 to 4.5 s. [20] The 94-GHz radar spectra are treated in a slightly
[14] The 915-MHz wind profiler collocated with the different manner. In addition to the identification of the local
cloud radar was operated in vertical incidence mode (beam maxima and minima, it is necessary to identify the spectral
width of about 9) to give a temporal resolution of 20 s. The peaks created by the modulation of the Doppler spectrum by
range gate spacing was 210 m and the Doppler spectra were the Mie backscattering function (Figure 2). This procedure is
recorded in all cases. The 64-point recorded Doppler spectra more complex than that applied to the 915-MHz spectra,
had 32.8 cm s 1 velocity resolution over a range of ±10.5 m since one, two or three peaks can be detected depending on
s 1. The 915-MHz and 94-GHz radars were collocated the turbulence intensity and the shape of the DSD. If only
within 10 m to provide overlapping sample volumes of one peak is detected, then no retrieval of the vertical air
the overlying vertical atmospheric column. motion and the DSD is computed. In this case, either the drop
size distribution does not contain large enough raindrops to
3.2. Supplementary Observations give returns beyond the first Mie minima (Dmax 1.7 mm),
[15] In addition to the vertically pointing radars, a tip- or the attenuation of the signal is so strong that radar receiver
ping-bucket rain gauge and a surface meteorology station noise overwhelms the atmospheric return. For cases where
were available to complement the radar observations. The there are two or more peaks, the relative spacing of the peaks
resolution of the tipping bucket is 0.254 mm and provides a is used to identify which are real peaks generated by theKOLLIAS ET AL.: CLOUD RADAR OBSERVATIONS OF CONVECTIVE RAIN XX X-5
Figure 4. (a) 915-MHz radar reflectivity mapping of the precipitating system (b) Surface observations
of qe (dashed line) and rainfall (solid line).
scattering mechanisms, and which are artifacts created by Atmospheric Science (RSMAS) site. Figure 4a shows a
processes related to the noisy nature of the Doppler spectrum. time-height cross-section of reflectivity from the 915-MHz
Once the peaks are correctly identified, the displacement of wind profiler. The convective system sampled, formed
the first Mie minimum is used to estimate the mean air inland from the site, and was observed for almost 3 hours
motion. The observed Doppler spectrum is shifted to zero air as a substantial trailing stratiform area moved overhead after
velocity conditions. A nonlinear least squares fitting proce- the passage of a convective core. The rainfall rate measured
dure, similar to the one used in the retrieval of the DSD in the by the rain gauge collocated with the radars ranged between
wind profiler is applied. As in the case of the wind profiler, 30 and 80 mm h 1during the passage of the high reflectivity
there are limits to the applicability of the technique. It is core.
applicable as long as the signature of the Mie oscillation is [23] The arrival of the storm was indicated by a sudden
apparent in the observed spectrum. Throughout this study, a 15 K drop of the equivalent potential temperature, qe (Figure
conservative approach was pursued, applying the method 4b). A wind shift and the lower qe values occurred 30 min
only in spectra with well defined Mie maxima and minima. ahead of the storm, before any rain was detected at the site.
[21] Signal attenuation has no effect on the Doppler spec- The drop in qe was associated with storm outflow caused by
trum shape and dynamic range. Consequently, the retrieved downdrafts. The lower elevation scan data from the Miami
DSD shape from the 94-GHz Doppler spectra is not affected WSR-88D (KAMX) verified that the observed precipitating
by the signal attenuation and an accurate reflectivity measure- system was part of a convective line triggered by outflows
ment is needed in order to scale properly the DSD. of other convective regions further inland and propagating
in a southeast direction. The first cloud detected by the
profiler (Figure 4a) was a shelf cloud at 2325 UTC, nearly
4. Observations coincident with the qe drop. Convective precipitation was
4.1. High Reflectivity Core detected at 2345 UTC as illustrated by the vertically
[22] The data for this case were collected on 7 and 8 oriented high reflectivity area and the high rainfall rates.
September 1999, at the Rosenstiel School of Marine and The convective part of the storm lasted almost 30 min, andXX X-6 KOLLIAS ET AL.: CLOUD RADAR OBSERVATIONS OF CONVECTIVE RAIN
Figure 5. (a) 915-MHz radar reflectivity mapping of the convective core. The reflectivity exceeds 50
dBZ at levels between 1.5 and 4 km. The box defined by the white lines indicates the area where the
millimeter radar data were used for microphysics and air motion retrievals, (b) Vertical air motion field
retrieved by the millimeter radar.
after a short transition period, stratiform precipitation was values observed by the wind profiler (Figure 5a) were
observed for more than 2 hours (0045 – 0245 UTC) with the verified by the WSR-88D. There are two high reflectivity
915-MHz wind profiler. A bright band signature was cores (dBZ 50) at levels between 1.5 and 4.0 km. The
observed during the stratiform rain (Figure 4a) at an altitude presence of such high values is likely related to the
of 4.5 km. Rainfall rates during this period were very low existence of large raindrops at these levels. Due to strong
with values 1 mm h 1, suggesting strong evaporation as attenuation, the cloud radar could not penetrate higher than
indicated by the weak reflectivity values at low levels. 1.5 km in the convective part of the cloud. However, DSD
Bragg scattering is evident at these levels, creating a noisy and w analysis was possible in the domain shown in Figure
image during the last hour of 915-MHz observations. 5a. The retrieved vertical motion field within this domain is
[24] The analysis focuses on the convective core, since shown in Figure 5b. The vertical resolution of the cloud
the stratiform part of the system was very weak and radar for this case was 60 m, and the temporal resolution
associated with few 1.7 mm drops (e.g., no retrieval). was 4.8 s, providing 300 profiles of Doppler spectra to
As a result, the Mie minimum was detectable only in a few define the structure of the air motion field. Each Doppler
locations, making the analysis difficult. The reflectivity spectrum was analyzed independently without any inputKOLLIAS ET AL.: CLOUD RADAR OBSERVATIONS OF CONVECTIVE RAIN XX X-7
250.99 250.995 251 251.005 251.01
55 100
90
50
80
70
45
Rainfall (mmh )
–1
dBZ 60
40 50
40
35
30
20
30
10
25 0
23:48 23:52 23:56 00:00 00:04 00:08
Time (UTC)
Time (UTC)
250.99 250.9985 251.007
4
3
0.3
2
Air Velocity (ms–1)
1
D (cm)
0.2
0 o
–1
0.1
–2
–3
23:48 23:52 23:56 00:00 00:04 00:08
Time (UTC)
Figure 6. (a) Cross section of radar reflectivity from the wind profiler at 1.3 km (squares) and surface
rainfall (solid) during the convective event, (b) Cross section of vertical air motion (dashed) and medium
volume diameter Do (solid) at 1.3 km retrieved by the cloud radar Doppler spectra.
from nearby Doppler spectra in the time-height domain. The signal is severely attenuated, and the reflectivity measure-
results (Figure 5b) show a narrow updraft at the approach- ments are not reliable. The retrieval method captures the
ing side of the convective core. The interior of the con- DSD shape. However, scaling of the raindrop size distribu-
vective system at these levels is dominated by two weak tion requires accurate measurements of reflectivity. Since
downdrafts separated by a narrow, weak updraft area. The there is little attenuation of the wind profiler radiation by
magnitude of the updraft reaches 4 m s 1 and the main precipitation particles, the wind profiler reflectivity values
downdraft approaches 3 m s 1. In general, the retrieval of are used to scale the raindrop spectra retrieved by the 94-
the vertical air motion under these conditions (R between GHz radar. To compensate for the lower temporal resolution
30– 80 mm h 1) at different levels is coherent in time and of the wind profiler, we assume a homogeneous reflectivity
space. field within a 20 s time interval.
[25] After retrieving the vertical air motion, the Doppler [26] A reflectivity cross section at 1.3 km from the wind
spectrum is used to retrieve DSDs, which illustrate the profiler and the corresponding surface rainfall rates are
different nature of the two downdrafts. The cloud radar shown in Figure 6a. Initially, a high reflectivity regionXX X-8 KOLLIAS ET AL.: CLOUD RADAR OBSERVATIONS OF CONVECTIVE RAIN
Figure 7. (a) Lowest elevation scan reflectivity mapping of Hurricane Irene from the Miami WSR-88D
radar, (b) 915-MHz radar time-height reflectivity mapping of Hurricane Irene at Virginia Key during the
same time period. The MCR data collected at 1430– 1510 UTC were used for retrievals.
(2348 – 2354 UTC) is observed that corresponds to the area rainfall rate is observed during the reflectivity plateau (R =
of high reflectivity (dBZ 50) observed within the con- 60– 80 mm h 1).
vective rain core (Figure 5a). Later, a plateau of reflectivity [27] Figure 6b shows the medium volume diameter (Do)
is observed (45 dBZ) until the end of the convective core and the vertical air motion at the same height retrieved from
where a sharp decrease of the radar reflectivity is observed. the 94-GHz Doppler spectra. Do can be estimated by the
The corresponding surface rainfall rate shows a bimodal retrieved DSD shapes without reflectivity scaling. Despite
structure with time within the convective core. A relative the differences in the sampling volume, the reflectivity from
minimum is observed during the transition from the high the wind profiler and the Do retrievals from the cloud radar
reflectivity region to the reflectivity plateau. The maximum Doppler spectra show consistent variability. The observedKOLLIAS ET AL.: CLOUD RADAR OBSERVATIONS OF CONVECTIVE RAIN XX X-9
Do vs Rainfall ( Hurricane Irene)
315.61 315.615 315.62 315.625 315.63
0.25 100 100
90 90 Rain gauge
80 80 Radar
70 70
Rainfall (mm/hr)
Rainfall (mm/hr)
0.2
60 60
Do (cm)
50 50
40 40
0.15 30
30
20 20
10 10
0.1 0 0
14:40 14:45 14:50 14:55 15:00 15:05 14:40 14:50 15:00
Time (UT) Time ( UTC)
Figure 8. (a) Retrieved Do (solid) at 200 m from the mm-wavelength radar Doppler spectra and surface
rainfall rate (dashed line) (b) retrieved rainfall rate (solid) and observed rainfall rate (dashed line).
high reflectivity region (2348 – 2354 UTC), overlaps with of microphysical retrievals from the 94-GHz Doppler spec-
high Do values. After a very sharp transition area, lower tra from the lowest radar gate (200 m).
reflectivity values (45 dBZ) are observed by the wind [31] The retrievals from the MCR show exceptional
profiler. During the same period (2355– 0003 UTC), the Do correlation with the rainfall rate collected from the rain
values are slightly lower (Do 2 mm). Figure 6b, also gauge. In Figure 8a, the retrieved Do time series at the
shows the vertical air motion retrieved by the cloud radar. A lowest gate (200 m) and the rainfall rate are shown. During
weak downdraft area is adjacent to the strong updraft the convective reflectivity core, high rainfall rates were
observed at the leading edge of the convective core. The observed. The burst-type variability of the surface rainfall
transition between the updraft and the downdraft is very data during that convective event was consistent with the
sharp and is followed by a sharp increase in the Do values. variability of the wind profiler reflectivity, showing four
[28] Most of the rain falls within the wider and stronger reflectivity maxima within the convective core (35 dBZ).
downdraft (2355 – 0003 UTC). This observation is sup- The retrieved values of Do vary with the fine scale varia-
ported by the tipping bucket rainfall data. In the area of bility of the reflectivity within the core. Figure 8b shows a
the main downdraft, the raindrops have smaller sizes and comparison between the rainfall rate calculated using the
the maximum observed sizes did not exceed 3 mm in retrieved N(D) from the mm-wavelength Doppler spectra
diameter. In addition to the variability of Do induced by scaled using the 915-MHz reflectivity and the observed
the drafts, small-scale variability in Do is observed. Other surface rainfall rate. This comparison is encouraging since
processes, and especially turbulence in the interior of the the retrieved rainfall reasonably tracks the gauge record.
convective core, may contribute to this variability. The retrieval performs better during the stratiform periods,
where the assumption of homogeneity in the reflectivity
4.2. Hurricane Irene field is valid. In the convective core, the fine-scale varia-
[29] On 15 October 1999, Hurricane Irene made landfall bility is resolved, but there are differences between the
in Southwest Florida. Figure 7a shows the lowest elevation retrieved and the actual rainfall measurements. In general,
scan (0.5) mapping the reflectivity of the hurricane from however, the retrieved rainfall rates capture the observed
the Miami WSR-88D. At 1440 UTC, the center of the small-scale variability.
hurricane was located in the lower Florida Keys and a
rainband passed over the radar site (Virginia Key, Miami). 4.3. 94-GHz Attenuation
The WSR-88D data indicate reflectivity values of 40– 45 [32] In the introduction, we discuss the prohibiting effect
dBZ within the hurricane rainband. Figure 7b, shows a of attenuation on the use of a 94-GHz Doppler radar for
time-height section through the rainband as observed by the precipitation studies. In an effort to quantify and evaluate
vertical beam of the 915-MHz profiler. The observations the signal attenuation at 94 GHz, attenuation data obtained
also show a bright-band radar signature at a height of 4.7 during heavy rainfall rates observed during Hurricane Irene
km. are used. The attenuation was estimated from the observed
[30] During the same period, and despite the intense signal decrease (in dBm) in the lowest 300 m above the
rainfall and sustained horizontal wind of 20– 25 m s 1, radar near field (200 m). Assuming homogeneous condi-
the 94-GHz cloud radar was used to collect high-resolution tions for the precipitation targets in the 200– 500 m layer,
Doppler spectra profiles. During the high reflectivity peri- the signal drop was attributed to attenuation. In Figure 9, the
ods the cloud radar signal was totally attenuated within the attenuation A (dB km 1) of the radar signal is plotted with
lowest 2 km, while during the stratiform period the radar the observed surface rainfall rate R (mm h 1). In addition to
signal reached the melting layer. Figure 8 show a time series the attenuation versus surface rainfall observations, model-XX X - 10 KOLLIAS ET AL.: CLOUD RADAR OBSERVATIONS OF CONVECTIVE RAIN
2
10 profiler. In addition, the low-level retrieval of the cloud
radar can be used to correct the wind profiler data and with
A = α Rβ assumptions, extrapolate these measurements to higher
JD
altitudes where the wind profiler is able to penetrate.
Attenuation (dBkm –1)
1
10 5. Discussion and Conclusions
JT
[34] In this paper, the potential of using a 94-GHz radar
for precipitation studies is demonstrated. Emphasis is given
to convective rain observations. The observations clearly
0
10
demonstrated that a 94-GHz radar, combined with a lower
frequency radar, is a very useful tool for looking at micro-
MP physics and kinematics associated with both convective and
stratiform rain. The time-height retrieval of vertical air
motion and DSDs, and the superior sampling (temporal
and spatial resolution) relative to other remote sensors,
0 1 2
10 10 10 makes the cloud radar a unique instrument for resolving
–1
Rainfall (mmh ) small-scale variability in the interior of convective cores
when attenuation is not a major problem. The complexity of
Figure 9. Observed signal attenuation A (dB km 1) at 94 the convective structures implies that we need horizontal
GHz as a function of rainfall rate R (mm h 1) (diamonds), winds as well as vertical profiles of w and DSDs to under-
theoretical relationships for a variety of DSD (solid lines) stand these structures. Such an observing platform can be
and the best fit to A = aRb fit (dashed line). the basis for future precipitation research, especially at small
scales.
[35] Interesting vertical draft structures were observed for
ing results of signal attenuation at 94 GHz for a variety of the two cases studied. The spatial resolution of the observed
exponential raindrop size distribution (N = Noe D) are updraft and downdraft structures goes well beyond any
shown. For modeling purposes three different No values other previous observations of the lower part of convective
were. These are the Marshall-Palmer (MP, No = 0.08 cm 4) updrafts. The two-dimensional view provided by the radar
[Marshall and Palmer, 1948], the Joss Thunderstorm (JT, adds one more dimension to that provided by aircraft
No = 0.014 cm 4) and Joss Drizzle (JD, No = 0.3 cm 4) penetrations. In the first case studied, strong evidences of
[Joss and Gori, 1978] for an ambient temperature of 20C. drop sorting effects due to the kinematics of the interior of
The dashed line shows the best regression fit A = the convective core was found. The size-sorting of raindrops
0.89R0.827. As expected, there is strong correlation between in space due to convective updrafts was also documented by
the signal attenuation at 94 GHz and rainfall rate. The Kollias et al. [2001] using the same retrieval technique. The
strong attenuation suggests that signal attenuation at 94 elevated high reflectivity cores (Figure 5a) are consistent
GHz, observed in a shallow precipitation layer can be used with the suspension of raindrops at high levels until they
for rainfall measurements. reach terminal velocities large enough to overcome the
4.4. Comparison of Vertical Air Motion Retrievals upward motion. The vertical air motion retrievals (Figure
[33] Wind profilers are widely used for quantitative 5b) verify the presence of a strong updraft. The results in
measurements of air motion and precipitation. An interest-
ing application is the collocation of a 915 MHz wind 1
profiler with the MCR. This configuration was implemented 915 Mhz (squares)
0.8 94 Ghz (stars)
during our observations. Comparison of the vertical air
motion retrievals can be performed only in stratiform rain, 0.6
since the Bragg scattering is overwhelmed by the precip- 0.4
itation return in convective rain. A comparison is shown in
Air Motion (ms–1)
Figure 10. The stratiform rain data were collected during the 0.2
high reflectivity core case (0130 –0200 UTC). The MCR 0
data are more dense and coherent and a general trend from a
weak updraft to a weak downdraft is observed. The wind –0.2
profiler air motion measurements follow the same trend, but –0.4
overestimate the magnitude of the vertical air motion. Such
a comparison can greatly enhance our understanding of –0.6
wind profilers data and their accuracy. Similar comparisons –0.8
can be made for the estimation of the turbulence intensity
and drop size distribution. This is a very important dimen- –10 2 4 6 8 10
sion of the cloud radar, since there is already an extensive Time (min)
database of wind profilers data. Such a comparison tests the
assumptions required for retrievals with wind profilers and Figure 10. Comparison of vertical air motion measure-
other radars. The high sampling cloud radar can document ments from the MCR (stars) and the 915-MHz wind profiler
the homogeneity of the sampling volume of the wind (squares) in stratiform rain.KOLLIAS ET AL.: CLOUD RADAR OBSERVATIONS OF CONVECTIVE RAIN XX X - 11
Figure 6b show very large raindrops (Do 2.4 mm) for a [38] An important issue for the application of 94-GHz
3-minute interval inside the area of the first weak down- radar in convective rain is signal attenuation. If it were not
draft. Although we are limited to a two-dimensional snap- for attenuation, 94-GHz radar would be the ideal tool for
shot of the air motion field and we cannot easily explain precipitation studies. Under convective conditions, how-
existence of the large raindrops next to the main updraft, ever, the radar signal experiences severe attenuation. The
the observations provide a physical model of the role of attenuation as a function of rainfall rate observed during
convective updrafts in the precipitation process. Szumowski Hurricane Irene, are within the theoretical limits estimated
et al. [1998] observed a similar behavior using combined using different exponential distributions. At such high radar
radar and aircraft observations. If the main updraft is tilted frequencies, scattering contributes as much to the attenu-
in three-dimensions or is weakening, the large drops will ation as the signal absorption.
escape and fall rapidly from the higher levels of the cloud. [39] Despite this serious disadvantage of short wave-
Actually, this is evident in the high reflectivity tail of the length radars under precipitating conditions, the information
first high reflectivity core (Figure 5a). Since the large contained from the Doppler spectrum (vertical air motion
raindrops are observed at lower altitudes, they somehow and DSDs) makes a 94-GHz Doppler radar a valuable tool
avoid collisional breakup with small raindrops during their for precipitation research. In particular, during low to
fall from higher altitudes. A tilted updraft can create this moderate stratiform rain conditions (R 3 mm h 1), the
type of drop separation due to the different terminal fall 94-GHz Doppler radar retrieval technique is applicable from
velocities of raindrops of different sizes. Thus, the large the ground to the melting layer (4– 4.5 km in the tropics).
drops must be falling through regions with small concen- Using its current configuration the MCR can retrieve the air
trations of small raindrops [Rauber et al., 1991]. In motion and DSD in stratiform rain with 60 m vertical
addition, the region where the large raindrops are observed resolution and 3 s temporal resolution [Kollias et al.,
is adjacent to the strong updraft. Thus, recirculation and 2002]. Under the same conditions the wind profiler retrieval
further growth of some of the raindrops is a plausible technique is applicable at the lower 2 – 2.5 km. At higher
mechanism for the generation of large raindrops and high rainfall rates (R 10– 20 mm h 1), a surface based 94-GHz
reflectivity values. The vertical structure from the obser- Doppler radar with peak power 1 kW and 1 m antenna can
vations provides a more complete picture than possible penetrate the lower 2 km of the convective precipitation
from in situ measurements and facilitates the interpretation [Kollias et al., 2001]. The 915-MHz wind profiler retrieval
of the data. While more observations of this type are technique is not applicable under convective rain since the
required, the observations underline the need for higher Bragg scattering return is overwhelm by the Rayleigh
spatial resolution precipitation models with explicit micro- scattering from the raindrops. Thus, the 94-GHz Doppler
physics so the effects of updrafts on raindrop spectra can radar is the only remote sensing tool that can retrieve the
be simulated. vertical air motion and DSD in convective rain. Collocated
[36] In addition to highlighting the interaction between with a lower frequency Doppler radar, 94-GHz radars can
convective drafts and raindrops, the observations demon- overcome to a great extent the uncertainties related to the
strated that convective cores have internal variability. DSD retrievals of vertical air motion and DSDs [Kollias and
and vertical air velocity variability are not highly correlated Albrecht, 2002]. With simplicity and a minimum set of
at one level (even though in the vertical each field is assumptions, this type of research radar can provide impor-
coherent), and exhibits fine-scale structure (10s of m) that tant, fundamental details of the precipitation processes.
has been unresolved by other measurement tools. The
small-scale variability observed, indicates that other remote [40] Acknowledgments. We are grateful to the technical assistance
sensors like wind profilers with inherently large spatial provided by Tom Snowdon during the collection of the data used in this
filters will be ineffective in describing this variability. In study. This work was supported by NSF grant ATM9730119 and DOE
addition, a comparison of the Z-R time series within the grant DEFG0297ER62337.
convective core (Figure 6a) exemplifies the difficulty of
predicting rainfall rates in convective cores using reflectiv-
References
ity data.
Albrecht, B. A., P. Kollias, R. Lhermitte, and R. Peters, Observations of
[37] The DSD shapes and subsequently the Do retrievals tropical cloud systems with a mm-wavelength Doppler radar—An over-
are independent of reflectivity measurements. Conse- view, Preprints, 29th International Conference on Radar Meteorology,
quently, the fact that Do variability retrieved by the cloud pp. 454 – 456, Montreal, 1999.
radar is correlated with reflectivities from the wind profiler, Atlas, D., C. W. Ulbrich, F. D. Marks Jr., R. A. Black, E. Amitai, P. T.
Willis, and C. E. Samsury, Partitioning tropical oceanic convective and
is strong support for the validity of the retrievals. The data stratiform rains by draft strength, J. Geophys. Res., 105, 2259 – 2267,
within one of Hurricane Irene’s rainbands underline another 2000.
important application of using a 94-GHz radar for precip- Aydin, K., and Y.-M. Lure, Millimeter wave scattering and propagation in
rain: A computational study at 94 and 140 GHz for oblate spheroidal and
itation studies. Due to its sampling volume (3000 m3, which spherical raindrops, IEEE Trans. Geosci. Remote Sens., 29, 593 – 601,
is significantly larger than the sampling volume of aircraft 1991.
microphysical probes) and the strong signature of the Mie Beard, K. V., and C. Chuang, A new model for the equilibrium shape of
raindrops, J. Atmos. Sci., 44, 1509 – 1524, 1987.
scattering oscillations on the Doppler spectra, the 94-GHz Beard, K. V., D. B. Johnson, and D. Baumgardner, Aircraft observations of
radar is an excellent tool for the detection of large raindrops large raindrops in warm, shallow, convective clouds, Geophys. Res. Lett.,
(D 3 mm) in precipitation. The presence of a single large 13, 991 – 994, 1986.
raindrop within the radar sampling volume will create a Carbone, R. E., and L. D. Nelson, The evolution of raindrop spectra in
warm-based convective storms as observed and numerically modeled,
strong third Mie peak signature (see Figure 2) in the J. Atmos. Sci., 35, 2302 – 2314, 1978.
Doppler spectrum. Cifelli, R., C. R. Williams, D. K. Rajopadhyaya, S. K. Avery, K. S. Gage,XX X - 12 KOLLIAS ET AL.: CLOUD RADAR OBSERVATIONS OF CONVECTIVE RAIN and P. T. May, Drop-size distribution characteristics in tropical mesoscale Mie, G., Beitrage zur Optic truber Medien, speziell kolloidaler Metallosun- convective systems, J. Appl. Meteorol., 39, 760 – 777, 2000. gen, Ann. Phys., 30, 377 – 442, 1908. Feingold, G., S. Tzivion, and Z. Levin, Evolution of raindrop spectra, part I, Miller, M. A., and B. A. Albrecht, Surface-based observations of mesoscale Solution to the stochastic collection/breakup equation using the method cumulus-stratocumulus interaction during ASTEX, J. Atmos. Sci., 52, of moments, J. Atmos. Sci., 45, 3387 – 3399, 1988. 2809 – 2826, 1995. Firda, J. M., S. M. Sekelsky, and R. E. McIntosh, Application of dual- Mishchenko, M. I., Calculations of the amplitude matrix for a nonspherical frequency millimeter wave Doppler spectra for the retrieval of drop size particle in the fixed orientation, Appl. Opt., 39, 1026 – 1031, 2000. distributions and vertical air motion in rain, J. Atmos. Oceanic Technol., Mishchenko, M. I., and L. D. Travis, T-matrix computations of light 16, 216 – 236, 1999. scattering by large spheroidal particles, Opt. Commun., 109, 16 – 21, Gossard, E. E., Measuring drop size distributions in cloud with a clear-air 1994. sensing Doppler radar, J. Atmos. Oceanic Technol., 5, 640 – 649, 1988. Rajopadhyaya, D. K., P. T. May, and R. C. Cifelli, Comparison of precipi- Grabowski, W. W., X. Wu, and M. W. Moncrieff, Cloud resolving modeling tation estimation using single- and dual-frequency wind profilers: Simu- of tropical cloud systems during phase III of GATE, part III, Effects of lations and experimental results, J. Atmos. Oceanic Technol., 16, 165 – cloud microphysics, J. Atmos. Sci., 56, 2384 – 2402, 1999. 173, 1999. Green, A. W., An approximation for the shapes of large raindrops, J. Appl. Rauber, R. M., K. V. Beard, and B. M. Andrews, A mechanism for giant Meteorol., 14, 1578 – 1583, 1975. raindrop formation in warm, shallow convective clouds, J. Atmos. Sci., Houze, R. A., Cloud Dynamics, 573 pp., Academic, San Diego, Calif., 48, 1791 – 1797, 1991. 1993. Rogers, R. R., W. L. Ecklund, D. A. Carter, K. S. Gage, and S. A. Ethier, Hu, Z., and R. C. Srivastava, Evolution of raindrop size distribution Research applications of a boundary-layer wind profiler, Bull. Am. Me- by coalescence, breakup and evaporation: Theory and observations, teorol. Soc., 74, 567 – 580, 1993. J. Atmos. Sci., 52, 1761 – 1783, 1995. Sato, T., H. Doji, H. Iwai, I. Kimura, S. Fukao, M. Yamamoto, T. Tsuda, Joss, J., and E. G. Gori, Shapes of raindrop size distributions, J. Appl. and S. Kato, Computer processing for deriving drop-size distributions Meteorol., 17, 1054 – 1061, 1978. and vertical air velocities from VHF Doppler radar spectra, Radio Sci., Kollias, P., and B. A. Albrecht, The turbulent structure in a continental 25, 961 – 973, 1990. stratocumulus cloud from millimeter radar wavelength radar observa- Srivastava, R. C., Size distribution of raindrops generated by their breakup tions, J. Atmos. Sci., 57, 2417 – 2434, 2000. and coalescence, J. Atmos. Sci., 28, 410 – 415, 1971. Kollias, P., and B. A. Albrecht, A multi-frequency ground-based radar Szumowski, M. J., R. B. Rauber, H. T. Ochs III, and K. V. Beard, The facility in South Florida for small-scale precipitation observations, Pre- microphysical structure and evolution of Hawaiian rainband cloud, part prints, 82nd Annual Meeting of the American Meteorological Society, II, Aircraft measurements within rainbands containing high reflectivity Orlando, Fla., 2002. cores, J. Atmos. Sci., 55, 208 – 226, 1998. Kollias, P., R. Lhermitte, and B. A. Albrecht, Vertical air motion and rain- Tokay, A., D. A. Short, C. R. Williams, W. L. Ecklund, and K. S. Gage, drop size distributions in convective systems using a 94 GHz radar, Tropical rainfall associated with convective and stratiform clouds: inter- Geophys. Res. Lett., 26, 3109 – 3112, 1999. comparison of disdrometer and profiler measurements, J. Appl. Kollias, P., B. A. Albrecht, and F. Marks Jr., Raindrop sorting induced by Meteorol., 38, 302 – 320, 1999. convective updrafts, Geophys. Res. Lett., 28, 2787 – 2790, 2001. Vali, G., R. D. Kelly, J. French, S. Haimov, D. Leon, R. E. McIntosh, and Kollias, P., B. A. Albrecht, and F. Marks Jr., Accurate observations of A. Pazmany, Fine-scale structure and microphysics of coastal stratus, vertical air velocities and rain drops using a cloud radar—Why Mie?, J. Atmos. Sci., 55, 3550 – 3564, 1998. Bull. Am. Meteorol. Soc., in press, 2002. Wakasugi, K., A. Mizutani, M. Matsuo, S. Fukao, and S. Kato, A direct Kummerov, C., et al., The status of the Tropical Rainfall Measuring Mis- method for deriving drop-size distributions and vertical air motions from sion (TRMM) after two years in orbit, J. Appl. Meteorol., 39, 1965 – VHF Doppler radar spectra, J. Atmos. Oceanic Technol., 3, 623 – 629, 1982, 2000. 1986. Lhermitte, R., Observations of rain at vertical incidence with a 94 GHz Williams, C. R., W. L. Ecklund, and K. S. Gage, Classification of precipi- Doppler radar: An insight of Mie scattering, Geophys. Res. Lett., 15, tating clouds in the Tropics using 915-MHz wind profilers, J. Atmos. 1125 – 1128, 1988. Oceanic Technol., 12, 996 – 1012, 1995. Lhermitte, R., Attenuation and scattering of millimeter wavelength radia- Williams, C. R., W. L. Ecklund, P. E. Johnston, and K. S. Gage, Cluster tion by clouds and precipitation, J. Atmos. Oceanic Technol., 7, 464 – analysis techniques to separate air motion and hydrometeors in vertical 479, 1990. incident profiler observations, J. Atmos. Oceanic Technol., 17, 949 – 962, Lhermitte, R., and P. Kollias, Processing of millimeter wave Doppler radar 2000. signals in low signal to noise conditions, Preprints, 29th International Conference on Radar Meteorology, pp. 517 – 521, Montreal, 1999. Lhermitte, R. M., A 94-GHz Doppler radar for cloud observations, J. Atmos. Oceanic Technol., 4, 36 – 48, 1987. B. A. Albrecht and P. Kollias, Rosenstiel School of Marine and List, R., N. R. Donaldson, and R. E. Stewart, Temporal evolution of drop Atmospheric Science, Division of Meteorology and Physical Oceanogra- spectra to collisional equilibrium in steady and pulsating rain, J. Atmos. phy, University of Miami, 4600 Rickenbacker Cswy, Miami, FL 33149- Sci., 44, 362 – 372, 1987. 1031, USA. (pkollias@rsmas.miami.edu) Marshall, J. S., and W. M. Palmer, The distribution of raindrops with size, F. D. Marks Jr., Hurricane Research Division, NOAA/AOML, Miami, J. Meteorol., 5, 165 – 166, 1948. FL, USA.
You can also read
