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Atmos. Meas. Tech., 11, 1417-1436, 2018
https://doi.org/10.5194/amt-11-1417-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
12 Mar 2018
A simple biota removal algorithm for 35 GHz cloud radar measurements
Madhu Chandra R. Kalapureddy1, Patra Sukanya1,3, Subrata K. Das1, Sachin M. Deshpande1, Govindan Pandithurai1, Andrew L. Pazamany2, Jha Ambuj K.1, Kaustav Chakravarty1, Prasad Kalekar1, Hari Krishna Devisetty1, and Sreenivas Annam4 1Indian Institute of Tropical Meteorology (IITM), Dr Homi Bhabha road, Pashan, Pune 411008, Maharashtra, India
2ProSensing Inc., 107 Sunderland road, Amherst, MA 01002, USA
3Savitribai Phule Pune University, Pune 411007, India
4VFSTR University, Vadlamudi 522213, India
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.
Citation: Kalapureddy, M. C. R., Sukanya, P., Das, S. K., Deshpande, S. M., Pandithurai, G., Pazamany, A. L., Ambuj K., J., Chakravarty, K., Kalekar, P., Devisetty, H. K., and Annam, S.: A simple biota removal algorithm for 35 GHz cloud radar measurements, Atmos. Meas. Tech., 11, 1417-1436, https://doi.org/10.5194/amt-11-1417-2018, 2018.
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Short summary
A new technique to separate cloud and non-hydrometeor returns from a cloud radar high-resolution reflectivity measurements is proposed. The TEST algorithm potentially identifies cloud height with the theoretical echo sensitivity curves and observed echo statistics for the cloud height tracing. TEST is more robust in identifying and filtering out the biota contributions by constraining further with spectral width and LDR measurements. This algorithm improves the monsoon cloud characterization.
A new technique to separate cloud and non-hydrometeor returns from a cloud radar high-resolution...
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