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.
The present study is a first of its kind attempt in exploring the physical features (e.g., height, width, intensity, duration) of tropical Indian bright band using a Ka-band cloud radar under the ...influence of large-scale cyclonic circulation and attempts to explain the abrupt changes in bright band features, viz., rise in the bright band height by ~ 430 m and deepening of the bright band by about 300 m observed at around 14:00 UTC on Sep 14, 2016, synoptically as well as locally. The study extends the utility of cloud radar to understand how the bright band features are associated with light precipitation, ranging from 0 to 1.5 mm/h. Our analysis of the precipitation event of Sep 14–15, 2016 shows that the bright band above (below) 3.7 km, thickness less (more) than 300 m can potentially lead to light drizzle of 0–0.25 mm/h (drizzle/light rain) at the surface. It is also seen that the cloud radar may be suitable for bright band study within light drizzle limits than under higher rain conditions. Further, the study illustrates that the bright band features can be determined using the polarimetric capability of the cloud radar. It is shown that an LDR value of − 22 dB can be associated with the top height of bright band in the Ka-band observations which is useful in the extraction of the bright band top height and its width. This study is useful for understanding the bright band phenomenon and could be potentially useful in establishing the bright band-surface rain relationship through the perspective of a cloud radar, which would be helpful to enhance the cloud radar-based quantitative estimates of precipitation.
The observations of bright band carried out simultaneously with X- and Ka-band radars for the first time over the Indian region have been examined to reveal various contrasting characteristics of ...bright band at the two wavelengths. The study reports the bright band observations on September 12–13, 2015 at millimeter and centimeter wavelengths and brings out a comparative analysis of the bright band features (e.g., intensity, thickness, height, etc.) under three different rain conditions ranging from very light (<0.1 mm/hr) to light (0.1–3 mm/hr) to heavy (3–5 mm/hr). It is seen that the bright band region at Ka-band is always narrower and situated at a higher altitude than at X-band frequency. Our analysis shows that at Ka-band frequency, the polarimetric fields like LDR can be utilized to detect and determine the bright band features using an appropriate selection of a threshold value of LDR, which is found to be −22 dB in this study and could be associated reasonably with the top and bottom heights of the bright band. This study explores the potential of both radars, particularly the Ka-band radar for probing the bright band effect and estimating its features which would be helpful to improve the quantitative estimates of precipitation.
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