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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union

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https://doi.org/10.5194/amt-2017-254
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
22 Aug 2017
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).
A simple insect removal algorithm for 35-GHz cloud radar measurements
Madhu Chandra R. Kalapureddy1, Sukanya Patra1, Subrata K. Das1, Sachin M. Deshpande1, Kaustav Chakravarty1, Ambuj K. Jha1, Prasad Kalekar1, Hari Krishna Devisetty1, Andrew L. Pazamany2, and Pandithurai Govindan1 1Indian Institute of Tropical Meteorology (IITM), Dr Homi Bhabha road, Pashan, Pune 411008, Maharastra, India
2Prosesning Inc., 107 Sunderland road, Amherst, MA 01002, USA
Abstract. One of the key parameters that must be included in the analysis of atmospheric constituents (gases and particles) and clouds is the vertical structure of the atmosphere. Therefore high-resolution vertical profile observations of the atmospheric targets are required for both theoretical and practical evaluation and as inputs to increase accuracy of atmospheric models. Cloud radar reflectivity profiles can be an important measurement for the investigation of cloud vertical structure in a resourceful way. However, extracting intended meteorological cloud content from the overall 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 returns from a cloud radar measurements. Firstly the observed cloud reflectivity profile must be evaluated against the theoretical radar sensitivity curves. This step helps to determine the range of receiver noise floor above which it can be identified as signal or an atmospheric echo. However it should be noted that the signal above the noise floor may be contaminated by the air-borne non-meteorological targets such as insects, birds, or airplanes. The second step in this analysis statistically reviews the continual radar echoes to determine the signal de-correlation period. Cloud echoes are observed to be temporally more coherent, homogenous and have a longer de-correlation period than insects and noise. This step critically helps in separating the clouds from insects and noise which show shorter de-correlation periods. The above two steps ensure the identification and removal of non-hydrometeor contributions from the cloud radar reflectivity profile which can then be used for inferring unbiased vertical cloud structure. However these two steps are insufficient for recovering the weakly echoing cloud boundaries associated with the sharp reduction in cloud droplet size and concentrations. In the final step in order to obtain intact cloud height information, identified cloud echo peak(s) needs to be backtracked along the either sides on the reflectivity profile till its value falls close to the mean noise floor. The proposed algorithm potentially identify cloud height solely through the characterization of high resolution cloud radar reflectivity measurements with the theoretical echo sensitivity curves and observed echo statistics for the cloud tracking (TEST). This technique is found to be more robust in identifying and filtering out the contributions due to insects and noise which may contaminate a cloud reflectivity profile. With this algorithm it is possible to improve monsoon tropical cloud characterization using cloud radar.

Citation: Kalapureddy, M. C. R., Patra, S., Das, S. K., Deshpande, S. M., Chakravarty, K., Jha, A. K., Kalekar, P., Devisetty, H. K., Pazamany, A. L., and Govindan, P.: A simple insect removal algorithm for 35-GHz cloud radar measurements, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2017-254, in review, 2017.
Madhu Chandra R. Kalapureddy et al.
Madhu Chandra R. Kalapureddy et al.
Madhu Chandra R. Kalapureddy et al.

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Short summary
A new technique to separate cloud and non- hydrometeor returns from a cloud radar measurements is proposed. The algorithm potentially identifies cloud height solely by characterizing high resolution reflectivity measurements with the Theoretical Echo sensitivity curves and observed Echo Statistics for the cloud height Tracking. It is found to be more robust in identifying and filtering out the contributions due to insects and noise. This algorithm improves the monsoon cloud characterization.
A new technique to separate cloud and non- hydrometeor returns from a cloud radar measurements...
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