06 Dec 2022
 | 06 Dec 2022
Status: a revised version of this preprint is currently under review for the journal AMT.

Doppler power spectrum processing methods for a vertical sensing 94 GHz millimeter-wavelength cloud radar

Hai Lin, Jie Wang, Zhenhua Chen, and Junxiang Ge

Abstract. A set of Doppler power spectrum processing methods for TJ-II, a vertical sensing 94 GHz millimeter-wave cloud radar(MMCR), is proposed to distinguish clouds and enhance the data quality. The noise level is estimated by a modified segment method with 2-D segments. A two-step cloud signal mask method is proposed to distinguish clouds and noise. A Gaussian filter with adaptive standard variance is used to improve detection performance at the boundary of clouds and noise. Square signal blocks were constructed to test our method. Velocity dealiasing is carried out combined with a pre-dealiasing processing and the dual Pulse Repetition Frequency (PRF) technique to address a particular phenomenon called half-folded in MMCRs, which can not be fixed by post-processing at the base datum stage. Some observations of TJ-II are used to demonstrate our method. A comparison between our method as pre-processing and the method as post-processing proposed by Key Laboratory for Semi-Arid Climate Change of the Ministry of Education and College of Atmospheric Sciences, Lanzhou University, was carried out using one-day observation. It was found that our method shows some advantages in cloud base detection.

Hai Lin et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2022-302', Anonymous Referee #1, 01 Jan 2023
    • AC1: 'Reply on RC1', Hai Lin, 07 Jan 2023
  • RC2: 'Comment on amt-2022-302', Anonymous Referee #2, 08 Mar 2023
    • AC2: 'Reply on RC2', Hai Lin, 21 Mar 2023

Hai Lin et al.

Hai Lin et al.


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Short summary
This manuscript presents a set of Doppler power spectrum processing methods for vertical sensing 94GHz millimeter-wave cloud radar, including noise level estimation based on segment method, cloud signal detection with two-step mask processing, and velocity dealiasing based on dual pulse repetition frequency. The special velocity aliasing phenomena show the necessity of Doppler power spectrum processing. Our method shows advantages in cloud base detection from our cloud radar observations.