Toward a Diurnal Climatology of Cold-Season Turbulence Statistics in Continental Stratocumulus as Observed by the Atmospheric Radiation Millimeter- Wavelength Cloud Radars Page: 2 of 7
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Fifteenth ARM Science Team Meeting Proceedings, Daytona Beach, Florida, March 14-18, 2005
Methodology
We make use of the ARSCL VAP (Active Remote Sensing of Cloud Layers Value Added Product;
Clothiaux et al. 2000, Clothiaux et al. 2001) to identify cloud base and cloud top. We classify
nonprecipitating PBL clouds as having:
" cloud top below 1500 m
" column maximum reflectivity of -20 dBZ
The -20 dBZ threshold conservatively identifies nondrizzling cases. However, ice phase precipitation is
sometimes present at reflectivities lower than this threshold, generally when at least some part of the
cloud is colder than -5 C, the warm side of the range for the nucleation of ice phase particles. Some
cloudy segments that obviously belong in the classification are excluded because of occasional radar
hardware malfunctions or problems with incorrectly identified cloud boundaries (particularly cloud
base). Any velocity in an echo whose reflectivity is <-35 dBZ is excluded from the analysis. While the
-35 dBZ threshold is arbitrary and well within the theoretical sensitivity of the radar, Doppler velocity
estimates at these low reflectivity values, particularly near cloud boundaries, are often unphysical.
Enough energy may be backscattered to produce sensible reflectivities, though the velocity spectra may
be seriously in error. Imposing a threshold in signal-to-noise ratio, rather than reflectivity, may screen
out these unrepresentative moments in a more physically meaningful way.
Once the initial data processing is complete, the vertical coordinate is transformed to a nondimensional,
cloud-normalized height. In this coordinate, "0" corresponds to cloud base and "1" to cloud top. The
data can then be analyzed on a segment-by-segment basis or by compositing into hour-by-hour bins in
order to evaluate the diurnal cycle. We show examples of each.
The effective data sampling frequency lies somewhere between the frequency of the data in the archive
(10 s) and the time it takes the radar to cycle through the four operational modes (-40 s). This range is
generally thought to be too long to capture coherent boundary layer eddy structures, but profiles may be
independent samples and should provide sensible statistics. In spite of conventional wisdom, a time
series below shows more coherent behavior than one might expect from such a sampling strategy. One
must also be aware that some form of averaging over each operational mode (-10 s) is involved in each
scan, either of the profiles themselves or coherent integration to enhance the radar sensitivity. Thus
some smoothing of the moments takes place.
Examples of Turbulence Statistics from Continental
Stratocumulus
Four hours of reflectivity and Doppler velocity data from 29 March 2001 are shown in Figure 1. Cloud
top and base are remarkably stable over the period. Radar echo below cloud base hints at the presence
of precipitation, particularly from 0000-0100 Universal Time Coordinates (UTC) where the vertical
velocities in the lower part of the cloud are predominantly negative. Soundings during this period imply
the possibility of a mixed-phase cloud.2
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Mechem, D. B.; Kogan, Y. L.; Childers, M. E. & Donner, K. M. Toward a Diurnal Climatology of Cold-Season Turbulence Statistics in Continental Stratocumulus as Observed by the Atmospheric Radiation Millimeter- Wavelength Cloud Radars, article, March 18, 2005; Norman, Oklahoma. (https://digital.library.unt.edu/ark:/67531/metadc779680/m1/2/: accessed March 30, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT Libraries Government Documents Department.