Reply on RC1

Abstract

Lidar and Ka-band Millimeter-Wave Cloud Radar (MMCR) are powerful equipment to detect the height distribution of cloud boundaries, which can monitor the whole life cycle of cloud layers. In this paper, we employ lidar and MMCR to jointly detect cloud boundaries under different conditions (e.g., single-layer clouds, multilayer clouds, and precipitating clouds). By enhancing the echo signal of lidar @1064 nm and combining its SNR, he cloud signal can be accurately extracted from the aerosol signals and background noise. The interference signal is eliminated from the power spectrum of the MMCR by using SNRmin and the spectral point continuous threshold, and the quality control of the meteorological signal (echo reflectivity factor) obtained by the inversion is carried out, which improves the detection accuracy of the cloud signal. Based on the advantages and disadvantages of the two devices in detecting cloud boundaries under different conditions, cloud boundary statistical rules are established to analyze the characteristics of cloud boundary changes in Xi'an in 2021. The seasonal variation characteristics of clouds show that the frequency distribution of cloud boundaries in vertical height in spring and summer has a similar variation trend. The normalized cloud amount is the lowest in spring (0.65) and the highest in summer (2.46). The frequency distribution of high-level clouds (at 11~12 km) is the highest in autumn, and the clouds in winter are mainly distributed below 8 km. Furthermore, the cloud boundary frequency distribution results for the whole year of 2021 show that the cloud bottom boundary below 1.5 km is more than 10 %, the frequency within the height range of 3.06 km~3.6 km is approximately 3.24 %, and the frequency above 8 km is less than 2 %. The cloud top boundary frequency distribution has the characteristics of a bimodal distribution. The first narrow peak lies at approximately 1.5~3.1 km, and the second peak appears at 7.5~10.5 km.