[Journal of Geophysical Research Atmospheres
Supporting Information for
Low-Cloud Characteristics over the Tropical Western Pacific
from ARM Observations and CAM5 Simulations
Arunchandra S. Chandra1, Chidong Zhang1, Stephen A. Klein2, His-Yen Ma2
1
Rosenstiel School of Marine and Atmospheric Sciences, University of Miami,
Miami, Florida, USA
2
Atmospheric, Earth and Energy Division, Lawrence Livermore National Laboratory,
Livermore, California, USA
Contents of this file
Text S1
Figures S1
Table S1
References
Introduction
This supporting information provides a methodology and correction for Ka-Band
(frequency of 35GHz) radar-derived cloud-top heights due to rain attenuation. The effect
of rain attenuation on the Ka-band cloud tops is examined using the data from the
scanning radar with polarimetric and dual wavelength S- and Ka-band capabilities (i.e the
S-Polka radar), Ka-band zenith pointing radar (KAZR), and rain gauges collected during
the Dynamics of Madden-Julian Oscillation (DYNAMO) field campaign (Yoneyama et
al., 2013). The description of the datasets used and their sources used are given in Table
S1.
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The operating frequency of the KAZR (35 GHz, 8.66 mm) is more affected by
attenuation from water vapor, cloud and hydrometeors than those of the centimeter
wavelength precipitation radars (e.g., S- and C-and). The total attenuation from the
KAZR is a function of water vapor, cloud and rain. In cases when rain is present it will
dominate the attenuation, but the other elements will still contribute. Our focus is on the
effect of the rain attenuation on the KAZR-observed cloud tops. In reality, an integral of
the rain rate over the rain layer is what causes the attenuation. Based on the observations
from the DYNAMO, we found that the comparison of integral of the rain rate (averaged
over 0-5 km) and the surface rain rate shows good agreement and also the depth of the
rain layers doesn’t vary much with the rain rates (not shown here). Based on these two
facts, we have made a simplification to express the cloud top attenuation as a function of
surface rain rates instead of the integral of the rain rate.
The S-Polka and KAZR were separated by 8.26 km during the DYNAMO field
campaign. The S-Polka made RHI scans over the KAZR once every 15 minutes. The SPolka and KAZR reflectivity profiles are obtained from KAZR-S-Polka combined data
product and KAZR-ARSCL data product respectively. The KAZR-S-Polka combined
data contains KAZR reflectivity profiles averaged over 15-min and S-Polka reflectivity
instantaneous vertical scans (i.e RHI scans: Range Height Indicator) profiles for every 15
minute at the resolution of 90 m. Since the 15-min averaged KAZR reflectivity profiles
from the combined data product may not be representative of the instantaneous S-Polka
profiles, we have only used S-Polka reflectivity profiles from the combined data product.
KAZR reflectivity profiles from the KAZR-ARSCL reflectivity profiles is gridded to 90
m vertical resolution, and 30-sec in time, and KAZR smoothed profiles nearest to the SPolka scans were selected for the comparison. The cloud tops from the KAZR and SPolka are retrieved based on the reflectivity profile. The S-Polka radar is also sensitive to
Bragg echoes (scattering due to humidity gradients) in addition to hydrometeors. S-Polka
reflectivity profiles were visually screened for Bragg echoes and a masking was applied
to retain the profiles when there was KAZR data reported. After eliminating Bragg
echoes and excluding missing echoes from either of the radars, a total of 180 rain profiles
(covering rain rates from 0.01 to 50 mm hr-1) were selected for the comparison.
2
Text S1
Figure S1 shows the difference between S-Polka and KAZR cloud-top heights
expressed as a function of surface rain rates. The solid line indicates the power law
(y=axb with a=1.019 and b=0.5894) fitted to the data. Errors in KAZR cloud-top height
for low rain rates (< 1 mm h-1) are with in 1 km, but they increase exponentially with rain
rates greater than 1 mmh-1. The root mean square error in the cloud-top height correction
is about 0.6845 km.
Figure S1. Scatter plot of differences between attenuated cloud-top heights (from the
KAZR) and unattenuated cloud-top heights (from the S-Polka) as a function of surface
rain rates at Addu Atoll during DYNAMO. The black line indicate the power law (y=axb)
fitted to the data.
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Datastream and identifier
Measurement Frequency
used for the
study
Site
Remarks
KAZR ARSCL
Cloud
boundaries,
Addu Atoll
ARM
4-sec
Value-added
reflectivity
S-Polka-KAZR combined
data
gankazrspolcombinedM1.c1
Rain rate,
reflectivity,
cloud tops
product
15 mins
Addu Atoll
RHIs over
KAZR
Only S-Polka
data is used
Feng et al.,
2014
Rain
Rain-rate
30-sec min
ganrainM1.b1
Addu Atoll
Optical rain
gauge
Table S1. Data used from the DYNAMO observations
References
Yoneyama, K., C. Zhang, and C. N. Long (2013), Tracking Pulses of the Madden–Julian
Oscillation. Bull. Amer. Meteor. Soc., 94(12), 1871–1891.
Feng. Z., S. A. McFarlane, C. Schumacher, S. Ellis, J. Comstock, and N. Bharadwaj
(2014), Constructing a Merged Cloud-Precipitation Radar daset for Tropical Convective
Clouds during the DYNAMO/AMIE Experiment at Addu Atoll. J. Atmos. Oceanic.
Technol, 31, 1021-1042.
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