Abstract
Abstract. 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.
Highlights
Short-wavelength Doppler radars are well known as cloud radars for their high sensitivity, which is required to sense the cloud droplets or ice crystals to infer cloud properties at high resolution (e.g. Lhermitte, 1987; Pazmany et al, 1994; Frisch et al, 1995; Kollias and Albrecht, 2000; Sassen et al, 1999; Hogan et al, 2005)
In order to utilize the potential purpose of cloud radar for studying clouds, one needs to identify and preserve the true cloud echoes from the biota contamination that is mostly confined within the atmospheric boundary layer (ABL)
The ABL shallow/low-level cumulus clouds are strongly linked to the rainmaking mechanism at the lower region of the cloud vertical structure (CVS) and are a key factor in predicting cloud feedback in a changing climate (Tiedtke, 1989; Bony et al, 2006; Teixeira et al, 2008) but their representation remain unresolved in large-scale mode-ling
Summary
Short-wavelength (millimetre-wave) Doppler radars are well known as cloud radars for their high sensitivity, which is required to sense the cloud droplets or ice crystals to infer cloud properties at high resolution (e.g. Lhermitte, 1987; Pazmany et al, 1994; Frisch et al, 1995; Kollias and Albrecht, 2000; Sassen et al, 1999; Hogan et al, 2005). This study utilizes the high-resolution profile of cloud radar reflectivity factor (Z) to construct the cloud vertical structures by filtering out the returns from the noise and biota.
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