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Assessment of Cloudsat Reectivity Measurements and
Ice Cloud Properties Using Ground-Based and Airborne
Cloud Radar Observations
Alain Protat, D. Bouniol, Julien Delanoë, P.T. May, Artemio Plana-Fattori,
A. Hasson, E. O’Connor, U. Görsdorf, A.J. Heymseld
To cite this version:
Alain Protat, D. Bouniol, Julien Delanoë, P.T. May, Artemio Plana-Fattori, et al.. Assessment of
Cloudsat Reectivity Measurements and Ice Cloud Properties Using Ground-Based and Airborne
Cloud Radar Observations. Journal of Atmospheric and Oceanic Technology, American Meteorological
Society, 2009, 26 (9), pp.1717-1741. �10.1175/2009JTECHA1246.1�. �hal-00418423�
Assessment of Cloudsat Reflectivity Measurements and Ice Cloud Properties
Using Ground-Based and Airborne Cloud Radar Observations
A. PROTAT,* D. BOUNIOL,
1
J. DELANOE
¨
,
#
P. T. MAY,
@
A. PLANA-FATTORI,
&
A. HASSON,
&
E. O’C
ONNOR,
#
U. GO
¨
RSDORF,** AND A. J. HEYMSFIELD
11
* The Centre for Australian Weather and Climate Research, Melbourne, Victoria, Australia, and Centre d’e
´
tude
des Environnements Terrestre et Plane
´
taires, Ve
´
lizy, France
1
Centre National de Recherches Me
´
te
´
orologiques, Groupe d’e
´
tude de l’Atmosphe
`
re Me
´
te
´
orologique, Toulouse, France
#
University of Reading, Reading, United Kingdom
@
The Centre for Australian Weather and Climate Research, Melbourne, Victoria, Australia
&
Centre d’e
´
tude des Environnements Terrestre et Plane
´
taires, Ve
´
lizy, France
** Deutscher Wetterdienst, Meteorologisches Observatorium, Lindenberg, Germany
11
National Center for Atmospheric Research, Boulder, Colorado
(Manuscript received 17 October 2008, in final form 31 March 2009)
ABSTRACT
A quantitative assessment of Cloudsat reflectivities and basic ice cloud properties (cloud base, top, and
thickness) is conducted in the present study from both airborne and ground-based observations. Airborne
observations allow direct comparisons on a limited number of ocean backscatter and cloud samples, whereas
the ground-based observations allow statistical comparisons on much longer time series but with some ad-
ditional assumptions. Direct comparisons of the ocean backscatter and ice cloud reflectivities measured by an
airborne cloud radar and Cloudsat during two field experiments indicate that, on average, Cloudsat measures
ocean backscatter 0.4 dB higher and ice cloud reflectivities 1 dB higher than the airborne cloud radar. Five
ground-based sites have also been used for a statistical evaluation of the Cloudsat reflectivities and basic cloud
properties. From these comparisons, it is found that the weighted-mean difference Z
Cloudsat
2 Z
Ground
ranges
from 20.4 to 10.3 dB when a 61-h time lag around the Cloudsat overpass is considered. Given the fact that
the airborne and ground-based radar calibration accuracy is about 1 dB, it is concluded that the reflectivities of
the spaceborne, airborne, and ground-based radars agree within the expected calibration uncertainties of the
airborne and ground-based radars. This result shows that the Cloudsat radar does achieve the claimed sen-
sitivity of around 229 dBZ. Finally, an evaluation of the tropical ‘‘convective ice’’ profiles measured by
Cloudsat has been carried out over the tropical site in Darwin, Australia. It is shown that these profiles can be
used statistically down to approximately 9-km height (or 4 km above the melting layer) without attenuation
and multiple scattering corrections over Darwin. It is difficult to estimate if this result is applicable to all types
of deep convective storms in the tropics. However, this first study suggests that the Cloudsat profiles in
convective ice need to be corrected for attenuation by supercooled liquid water and ice aggregates/graupel
particles and multiple scattering prior to their quantitative use.
1. Introduction
A crucial factor to improve our ability to forecast fu-
ture climate change and short-range weather is a better
representation of convection and clouds in large-scale
models. This requires a better understanding of the sta-
tistical properties of clouds and deep convective storms,
as well as the variability of these properties as a function
of different temporal and spatial scales or physical pa-
rameters describing the large-scale environment (e.g.,
Protat et al. 2009). The A-Train mission (Stephens et al.
2002), which is a constellation of six satellites dedicated
to the observation of clouds, precipitation, and aerosols
from space, represents an unprecedented and unique
opportunity to address this broad objective both at re-
gional and global scales. Because this mission is the very
first of its kind, an extensive verification of the measure-
ments and standard products is required prior to using
these for quantitative studies. The prelaunch calibration
Corresponding author address: Alain Protat, Centre for Aus-
tralian Weather and Climate Research (CAWCR), 700 Collins
Street, Docklands, Melbourne, VIC 3008, Australia.
E-mail: a.protat@bom.gov.au
S
EPTEMBER 2009 P R O T A T E T A L . 1717
DOI: 10.1175/2009JTECHA1246.1
Ó 2009 American Meteorological Society
of Cloudsat, in-flight calibration, and stability over the
period of operations has been very recently reported in
Tanelli et al. (2008). This in-flight calibration relies on
monthly comparisons of ocean backscatter measured at
108 incidence off-nadir using dedicated Cloudsat ma-
neuvers and the corresponding ocean backscatter pre-
dicted by different theoretical models. A complementary
approach to that adopted in Tanelli et al. (2008) is to
compare Cloudsat observations with other radar mea-
surements, either collocated or in a statistical sense. For
this reason many international and national experiments
have been conducted following the launch of two of the
A-Train satellites, Cloudsat (95-GHz cloud radar) and
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite
Observation (CALIPSO), including dedicated A-Train
underflights with airborne passive and active remote
sensing and in situ instruments; for example, the CALIPSO-
Cloudsat Validation Experiment (CCVEX; available on-
line at http://airbornescience.nasa.gov/media/) in Florida
in July–August 2006, the Canadian Cloudsat/CALIPSO
Validation Project (C3VP; available online at http://
www.c3vp.org) in Canada from November 2006 to March
2007, the African Monsoon Multidisciplinary Analyses
(AMMA) over West Africa in June–September 2006,
and the French–German Cirrus Clouds Experiment-2
(CIRCLE-2; available online at http://www.pa.op.dlr.de/
pazi-falcon/circle2/) over Western Europe in May 2007.
Among the different validation campaigns, our team has
been involved with airborne radar, lidar, and in situ mi-
crophysical measurements during AMMA (Redelsperger
et al. 2006), CIRCLE-2, and very recently during a third
campaign in the Arctic. The main advantage of the air-
borne observations is that they allow direct comparisons
with the spaceborne measurements, because they sample
the cloud with approximately the same geometry as the
spaceborne instrument (from the top down) and with a
good temporal coincidence.
Ground-based continuous observations such as those
conducted in the framework of the U.S. Department of
Energy Atmospheric Radiation Measurement Program
(ARM; Stokes and Schwartz 1994) and the European
Union Cloudnet program (Illingworth et al. 2007) are
also relevant for spaceborne instrumentation assessment.
The main advantage of this is that long-term and multi-
sensor ground-based observations (radars, lidars, radi-
ometers, and in situ sensors) are readily available over
selected sites at midlatitudes and in the tropics. From the
combination of these instruments put together at those
sites, the morphological, microphysical, radiative, and
dynamical properties of clouds are routinely and accu-
rately retrieved. The accuracy of these cloud properties
retrieved from the ground-based stations provides a
reference for the evaluation of the spaceborne products.
However, it generally does not allow for direct compar-
isons but requires statistical assumptions. The geometry
of observations is also different, which introduces addi-
tional sources of discrepancy, including that observations
are not attenuated the same way into the cloud.
In the present paper, we exploit the specific advan-
tages of airborne and ground-based radar observations
by conducting both statistical and direct assessments
of the Cloudsat 95-GHz Cloud Profiling Radar (CPR)
observations. The paper is organized as follows: the
observations and methodology adopted are described in
section 2. In section 3, the Cloudsat reflectivity mea-
surements and macrophysical properties of ice clouds
are assessed using direct comparisons with airborne
observations. Statistical comparisons with ground-based
observations are analyzed in section 4. An assessment of
the reflectivity profiles measured by Cloudsat in the ice
part of convective systems is also conducted in section 5
by using unattenuated ground-based radar observations
and an estimate of the mean attenuation plus the mul-
tiple scattering profile is worked out. Conclusions and
perspectives of this work are given in section 6.
2. Observations and methodology
The assessment of Cloudsat ice cloud measurements
and products is conducted in the present study from both
airborne and ground-based observations. The Cloudsat
data used in the present paper are from the fourth re-
lease (R04) of the Cloudsat radar reflectivities given in
the so-called 2B-GEOPROF product. A review of the
performance, external calibration, and processing has
been published during the review process of the present
paper (Tanelli et al. 2008). The in-flight calibration of
Cloudsat relies on comparisons of ocean backscatter
measured at 108 incidence off nadir using dedicated
monthly Cloudsat calibration maneuvers and predicted
by different theoretical models. It has been clearly shown
in Tanelli et al. (2008) that the Cloudsat-derived ocean
backscatter is in very good agreement with the Cox and
Munk (1954) model modified following Li et al. (2005)
and with the Wu (1990) model. The absolute calibration
of Cloudsat is derived from these comparisons. The ap-
proach adopted in the present paper is very comple-
mentary, because it consists of comparing Cloudsat
observations to other radars, either statistically or by us-
ing direct comparisons. The rationale for using both air-
borne and ground-based observations is that they provide
very different ways of evaluating Cloudsat and using
different assumptions. Airborne observations allow for
direct comparisons on a limited number of collocated
ground return or cloud samples, whereas the ground-
based observations allow for statistical comparisons using
1718 JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY VOLUME 26
much longer time series. In addition, our aim is to assess
the Cloudsat products both for midlatitude and tropical
ice clouds in order to span a sample as representative as
possible of ice clouds at global scale. We are also currently
conducting an airborne radar–lidar experiment in arctic
mixed-phase clouds, which should soon be available to
extend the present assessment study to polar clouds.
Gaseous attenuation calculations at 95 GHz were
performed through the model developed by Liebe et al.
(1993) for all radar observations used in this study. The
input thermodynamic variables are from the European
Centre for Medium-Range Weather Forecasts (ECMWF)
model in all cases. The imaginary part of the complex re-
fractivity was computed as the sum of contributions asso-
ciated with molecular oxygen (the pressure-broadening
and nonresonant terms) and water vapor (the pressure-
broadening and continuum terms). Under relatively warm
and moist atmospheric conditions [e.g., the tropical model
presented by Ellingson et al. (1991)], the model by Ulaby
et al. (1981) produces two-way path-integrated attenuation
0.2-dB larger than that by Liebe et al. (1993) for a nadir-
viewing airborne radar at 95 GHz flying at 4 km. This
number is probably a good estimate of the error of these
corrections on path-integrated attenuation correction.
In the following subsections, we describe the metho-
dology used for the airborne and ground-based evalua-
tions and we describe which observations have been used.
a. The airborne cloud radar observations
The present evaluation is conducted using flights
performed under the A-Train track during the AMMA
(Redelsperger et al. 2006) and the French–German
CIRCLE-2 campaigns by the French Falcon 20 equip-
ped with the radar–lidar (RALI) instrument. This RALI
instrument (Protat et al. 2004) is the airborne combi-
nation of two instruments: a multiantenna (3 antennas
downward, 2 antennas upward) 95-GHz Doppler cloud
radar named Radar Ae
´
roporte
´
et Sol de Te
´
le
´
de
´
tection
des Proprie
´
te
´
s Nuageuses (RASTA) and a triple-wave-
length (355, 532, and 1064 nm) and dual-polarization
(532 nm) backscatter lidar.
Direct comparisons between spaceborne and airborne
cloud radars can be performed using collocated mea-
surements of clouds or the earth surface (ocean or land).
Regarding the surface of the earth, the comparisons are
known to be more challenging over land surface than
over ocean owing to the fact that the land surface
backscatter is a function of the incidence angle, the di-
electric constant, and the surface roughness parameter.
As a result, we have restricted the comparisons to the
ocean surface. Regarding clouds, the two main factors
that can produce differences between the spaceborne
and airborne radars are the differential attenuation of
the two beams (when looking upward with the airborne
radar) and the differential multiple scattering. To min-
imize these potential sources of discrepancies between
the spaceborne and airborne observations, the non-
precipitating ice clouds are the best targets, because they
are characterized by a negligible attenuation and there is
no significant multiple scattering occurring in the wider
Cloudsat beam. Therefore, in the following, we have
only retained flights in which nonprecipitating ice clouds
were sampled by both instruments. Table 1 summarizes
the main characteristics of the flights performed along the
track of the A-Train during the AMMA and CIRCLE-2
field campaigns. Among these flights, two flights have
been performed over the ocean during CIRCLE-2 and
three during AMMA. Given the degraded sensitivity of
RASTA during AMMA (for discussion, see Bouniol et al.
2008) and the fact that the flight altitude was very high
during the 20 and 21 September 2006 flights (11–12-km
altitude), the ocean surface backscatter during AMMA
was best measured during the 22 September AMMA
flight. Therefore, in our comparisons of the ocean
TABLE 1. List of Cloudsat validation flights with RASTA on board the Falcon 20 during AMMA and CIRCLE-2. Here, Ci indicates cirrus.
Date
Measurement period
Cloud type
RASTA suitable for Cloudsat
evaluation?
Start time
(UTC)
End time
(UTC)
AMMA
09 Sep 2006 1300 1450 Sporadic deep convection over land No
20 Sep 2006 1350 1635 Thin Ci over ocean No
21 Sep 2006 215 430 Thin Ci over ocean No
22 Sep 2006 1350 1650 MCS anvil over land and ocean Yes (ocean backscatter)
CIRCLE-2
13 May 2007 1110 1405 Convection over land No
16 May 2007 1220 1530 Thin frontal Ci over ocean Yes (ocean backscatter)
20 May 2007 1110 1415 Broken Ci 1 convection over land Yes (ice clouds)
25 May 2007 1120 1500 Thin Ci layer over ocean Yes (ice clouds and ocean backscatter)
26 May 2007 1100 1400 Outflow Ci over land Yes (ice clouds)
S
EPTEMBER 2009 P R O T A T E T A L . 1719
backscatter, we have retained only the 22 September 2006
flight from AMMA and the two CIRCLE-2 flights on 16
and 25 May 2007.
Regarding ice clouds, Bouniol et al. (2008) showed that
direct comparisons with Cloudsat within the 22 Septem-
ber 2006 thick anvil could not be quantitatively exploited,
because of the contamination of both radar measure-
ments by attenuation due to supercooled liquid water
and/or large ice particles and by the multiple scattering in
the Cloudsat beam. Among the CIRCLE-2 flights, three
of them included ice clouds at the approximate time of
overpass (see Table 1) and are therefore used in the
present study: the 20, 25, and 26 May 2007 cases.
b. The ground-based cloud radar observations
The ground-based observations selected for this
evaluation of Cloudsat have been collected over three
midlatitude sites and two tropical sites:
d
the 95-GHz RASTA radar at the Site Instrumental de
Recherche par Te
´
le
´
de
´
tection Atmosphe
´
rique (SIRTA)
site in Palaiseau, France (Haeffelin et al. 2005);
d
the 35.5-GHz millimeter-wave radar (MIRA) in Lin-
denberg, Germany;
d
the 95-GHz mobile facility W-band ARM cloud radar
(WACR) deployed during the Convective and Oro-
graphically induced Precipitation Study (COPS) ex-
periment in the Murg Valley, Germany;
d
the 35-GHz ARM millimeter-wave cloud radar (MMCR)
at Darwin, Australia; and
d
the 94-GHz mobile facility WACR radar at Niamey,
Niger.
The periods considered for the statistical analysis of the
cloud properties are described in Table 2. Generally, the
ground-based radars have a lower noise floor than
Cloudsat, which is around 229 dBZ for the whole tro-
posphere (Tanelli et al. 2008), except in the upper part of
the troposphere for some of them. As a result, we have
carefully degraded all radar observations to the same
detection level (sensitivity) prior to any comparison. To
compare ground-based and spaceborne radar observa-
tions, we have considered Cloudsat data from a radius of
200 km around the sites and different time intervals
around the time of satellite overpass. These numbers
result from a trade-off between a sufficiently large num-
ber of observations to reach statistical significance and a
reasonable invariance of the reflectivity and basic cloud
properties statistics. Sensitivity studies are reported in the
following to address this issue. Finally, the geometry of
observations is different (the spaceborne instrument
samples the cloud from top to base, whereas the ground-
based instrument does it the other way around). This has
particularly important implications for the comparison of
ground-based and spaceborne ice cloud observations.
Indeed, most ice cloud observations from space will be
reasonably unattenuated (except in mixed-phase clouds
characterized by significant amounts of supercooled
liquid water). In contrast, a significant portion of the ice
cloud observations from the ground will be strongly at-
tenuated by any liquid cloud below ice clouds or by the
liquid part of the deep convective systems to which they
belong. As a result, we have carefully separated in the
Cloudsat datasets the ‘‘ice cloud’’ profiles (which do not
have a liquid layer below) and the ‘‘convective ice’’
profiles (which are ice clouds above liquid layers or the
ice part of a convective system). This separation is ach-
ieved using a two-step procedure. First, we identify the
altitude of the 08C isotherm altitude from the Cloudsat
ECMWF auxiliary (AUX) product (which is an extrac-
tion of the ECMWF profiles collocated with the Cloud-
sat reflectivity profiles), and we assume that at altitudes
greater than this 08C isotherm altitude we have ice
clouds and below we have liquid clouds (the occurrences
of supercooled liquid water is therefore treated as ice in
the present study, but it is also what is done with the
ground-based observations). Second, if there is 90% or
more of the liquid water part of the profile filled with
Cloudsat reflectivities larger than the Cloudsat detec-
tion level, then we classify the ice part of this profile as
a convective ice profile; otherwise, the ice part of the
profile is classified as an ice cloud profile. A similar
(although much more elaborated) separation has been
carried out with the ground-based observations using
the ‘‘target categorization’’ approach (detailed docu-
mentation available online at http://www.met.rdg.ac.uk/
;swrhgnrj/publications/categorization.pdf; Delanoe
¨
and
TABLE 2. Ground-based radar observational periods selected for statistical comparisons with Cloudsat measurements and products.
Location (lat, lon)
Radar frequency
(name)
Radar sensitivity
(dBZ at 10 km) Observational period
Darwin, Australia (12.4258S, 130.8918E) 35 GHz (MMCR) 241 (cirrus mode) December 2006–April 2007
Darwin, Australia (12.4258S, 130.8918E) 5 GHz (CPOL) 221 December 2006–April 2007
Niamey, Niger (13.4778N, 2.1768E) 94 GHz (WACR) 234 21 June 2006–December 2006
Lindenberg, Germany (52.2098N, 14.1228E) 36 GHz (MIRA) 240 August 2006–April 2007
COPS site, Germany (48.5408N, 8.3978E) 94 GHz (WACR) 234 April 2007–December 2007
Palaiseau, France (48.7138N, 2.2088E) 95 GHz (RASTA) 230 December 2006–February 2007
1720 JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY VOLUME 26
