# Cloud Seeding Evidenced by Coherent Doppler Wind Lidar
## 4 Application in an Artificial Precipitation Operation
As altitude descends with temperature gradually increasing, the ice crystals generate liquid cloud droplets by melting. Subsequently, a mixed layer is formed, which makes the lidar signal difficult to penetrate, as shown in Figure 6a. In particular, the cloud spectrum width and skewness after seeding have a two-layer structure, and this continues for several hours, as shown in Figure 6b,c. The skewness of the lower layer (cloud base) is close to 0, with little spectrum width broadening, indicating that the lower layer is comprised of liquid cloud droplets. However, the skewness of the upper layer deviates from 0, with obvious spectrum width broadening, indicating that multiple components are mixed in this layer. This mixed layer might contain big cloud droplets, raindrops, melting ice particles, graupels, and small hail [59; 61]. In order to investigate specific components of the mixed layer, these multi-component spectra including mixed cloud spectra and precipitation spectra are identified by skewness. Then Doppler velocity and spectrum width are separated from these spectra by two-peak fitting, as demonstrated in Section 3. For the precipitation spectrum, the left peak with smaller Doppler velocity is grouped as cluster A (aerosol component), and the corresponding right peak with larger Doppler velocity is grouped as cluster B (raindrop component) [47; 51]. For the mixed cloud spectrum, the left and right peaks are grouped as cluster C and cluster D. Then, velocity components are retrieved from Doppler velocity, using the filtered sine wave fitting (FSWF) method [64], as shown in Figure 7. The horizontal speed and direction of spectrum components are close because of the drag effect, as shown in Figure 7b,c,f,g. The spectrum width and vertical velocity of cluster C are different from these of cluster D, but close to these of cloud base, as shown in Figure 7a,d. It indicates that cluster C is comprised of liquid cloud droplets as well. To analyse the differences of these clusters, the density distribution of the spectrum width and vertical velocity are shown in Figure 8. These four clusters can be clearly distinguished from Figure 8. Distributions of the aerosol and raindrops are consistent with the result in [51]. There is a slight decrease in speed (0.9 m/s) and spectrum broadening (5.2 MHz) in aerosol in the precipitation condition. The spectrum width and vertical velocity of cluster C (cloud droplet) are concentrated at 0 m/s and 4.0 MHz. The characteristics of cluster D are significantly different from raindrops below the cloud base. The spectrum width of cluster D is concentrated at 11.2 MHz, which is larger than that of the raindrops (8.4 MHz). The vertical velocity of cluster D is concentrated at 1-2 m/s, while that of raindrop is concentrated at 3-4 m/s. It is consistent with results of cloud ice and liquid precipitation observed in [30; 65]. Cluster D falls faster than cluster C, which is similar to the general mixed-phase cloud results observed by aircraft [66] and remote sensors [65; 67]. Thus, cluster D is likely to be cloud ice (crystal, graupel or small hail) [59]. Another possible explanation is that ice particles melt gradually when they fall through layers warmer than 0 \({}^{\circ}\)C. The ice particle is wrapped in water, which has a larger vertical velocity and wider particle spectrum distribution than cluster C. But these melting ice particles fall more slowly than raindrops with the same mass [68]. Similar to the relation between aerosol and rain, the vertical velocity of the cluster D is larger than that of small cloud droplets [69].