Cloud radar reflectivity profiles can be an important measurement
for the investigation of cloud vertical structure (CVS). However, extracting
intended meteorological cloud content from the ...measurement often demands an
effective technique or algorithm that can reduce error and observational
uncertainties in the recorded data. In this work, a technique is proposed to
identify and separate cloud and non-hydrometeor echoes using the radar
Doppler spectral moments profile measurements. The point and volume
target-based theoretical radar sensitivity curves are used for removing the
receiver noise floor and identified radar echoes are scrutinized according
to the signal decorrelation period. Here, it is hypothesized that cloud
echoes are observed to be temporally more coherent and homogenous and have a
longer correlation period than biota. That can be checked statistically
using ∼ 4 s sliding mean and standard deviation value of
reflectivity profiles. The above step helps in screen out clouds critically
by filtering out the biota. The final important step strives for the
retrieval of cloud height. The proposed algorithm potentially identifies
cloud height solely through the systematic characterization of Z variability
using the local atmospheric vertical structure knowledge besides to the
theoretical, statistical and echo tracing tools. Thus, characterization of
high-resolution cloud radar reflectivity profile measurements has been done
with the theoretical echo sensitivity curves and observed echo statistics
for the true cloud height tracking (TEST). TEST showed superior performance in
screening out clouds and filtering out isolated insects. TEST constrained with
polarimetric measurements was found to be more promising under high-density biota
whereas TEST combined with linear depolarization ratio and spectral width perform potentially to
filter out biota within the highly turbulent shallow cumulus clouds in the
convective boundary layer (CBL). This TEST technique is promisingly simple
in realization but powerful in performance due to the flexibility in
constraining, identifying and filtering out the biota and screening out the
true cloud content, especially the CBL clouds. Therefore, the TEST algorithm is superior for screening out the low-level clouds that are strongly linked to the
rainmaking mechanism associated with the Indian Summer Monsoon region's
CVS.
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