Characteristics of Warm Clouds and Precipitation in South China during the Pre-Flood Season Using Datasets from a Cloud Radar, a Ceilometer, and a Disdrometer

Abstract

The millimeter-wave cloud radar, ceilometer, and disdrometer have been widely used to observe clouds and precipitation. However, there are some drawbacks when those three instruments are solely employed due to their own limitations, such as the fact that radars usually suffer from signal attenuation and ceilometers/disdrometers cannot provide measurements of the hydrometeors of aloft clouds and precipitation. Thus, in this paper, we developed an integrated technology by combining and utilizing the advantages of three instruments together to investigate the vertical structure and diurnal variation of warm clouds and precipitation, and the raindrop size distribution. Specifically, the technology consists of appropriate data processing, quality control, and retrieval methods. It was implemented to study the warm clouds and precipitation in South China during the pre-flood season of 2016. The results showed that the hydrometeors of warm clouds and precipitation were mainly distributed below 2.5 km and most of the rainfall events were very light with a rain rate less than 1 mm h−1, however, the stronger precipitation primarily contributed the accumulated rain amount. Furthermore, a rising trend of cloud base height from 1000 to 1900 BJT was found. The cloud top height and cloud thickness gradually increased from 1200 BJT to reach a maximum at 1600 BJT (Beijing Standard Time, UTC+8), and then decreased until 2000 BJT. Also, three periods of the apparent rainfall on the ground of the day, namely, 0400–0700 BJT, 1400–1800 BJT, and 2300–2400 BJT were observed. During three periods, the raindrops had wider size spectra, higher number concentrations, larger rain rates, and higher water contents than at other times. The hydrometeor type, size, and concentration were gradually changed in the vertical orientation. The raindrop size distributions of warm precipitation in the air and on the ground were different, which can be expressed by γ distributions N(D) = 1.49 × 104D−0.9484exp(−6.79D) in the air and N(D) = 1.875 × 103D0.862exp(−2.444D) on the ground, where D and N(D) denote the diameter and number concentration of the raindrops, respectively.

Characteristics of Clouds and Raindrop Size Distribution in Xinjiang, Using Cloud Radar Datasets and a Disdrometer

“…The Ka-band MMCR has a temporal resolution and spatial resolution of 1 min and 30 m, respectively, and the detection height ranges from 0.06 to 20 km. In addition to the attenuation of electromagnetic waves passing through clouds, radar noise level calculation, cloud-precipitation signal extraction, signal attenuation correction, non-meteorological echo removal, retrieval of the cloud-precipitation macrophysical quantity and other processing may also cause some uncertainty in the data [20,21].…”

“…On this basis, information such as rainfall intensity (R), radar reflectivity (Z), and DSD can also be obtained. Previous studies indicated that the impossibility of PARSIVEL disdrometer to detect raindrops with diameters smaller than 0.2 mm may produce unreasonable results [21].…”

“…Data quality has a certain impact on the application of the MMCR and the disdrometer results, and, therefore, it is necessary to carry out data processing and quality control [21,57].…”

“…Liu et al [20] proposed that numerous clouds are distributed below 3 km and are most prominent at sunrise, noon, and sunset. Zheng et al [21] investigated warm clouds by MMCR in South China during the pre-flood season and found that warm clouds are mainly distributed at altitudes below 2.5 km, and the height of the cloud base, height of the cloud top, and cloud thickness have the characteristics of a diurnal variation. However, research on cloud characteristics and diurnal changes in arid areas using radar is limited.…”

Statistical Characteristics of Cloud Occurrence and Vertical Structure Observed by a Ground-Based Ka-Band Cloud Radar in South Korea

“…They are frequently observed at higher altitudes than the top of the convective boundary layer in the morning, making it challenging to distinguish between insects and low-level clouds [4,5]. They were removed by using parameters such as their altitude, average moving speed, linear depolarization ratio (LDR), and spectral characteristics [6][7][8][9].…”