Correlation between atmospheric turbulence and cloud microphysical parameters detected by a novel variable dual field of view multiple scattering Raman lidar

Abstract

As a crucial component of atmospheric dynamics, atmospheric turbulence significantly influences the interactions between aerosols, clouds, and precipitation and is closely linked to the formation and development of clouds and precipitation. Investigating the impact mechanisms of varying turbulence intensities on cloud microphysical parameters and the interactions among aerosols, clouds, and precipitation has become an essential research topic. In this study, a novel variable dual-field-of-view multiple scattering Raman lidar system capable of synchronously detecting atmospheric turbulence and cloud microphysical parameters was developed. Using this lidar system, long-term continuous observations of atmospheric turbulence and low-level clouds in the Yinchuan region of China were conducted under diverse weather conditions, including sunny, cloudy, and precipitative scenarios. The data were analyzed, and comprehensive assessments of atmospheric turbulence and cloud microphysical parameters were performed. The atmospheric refractive index structure constant, the distribution of cloud droplet effective radius (CDER), and liquid water content (LWC) in lower atmosphere clouds were successfully obtained. By combining these findings with inversion results, we investigated the correlation between atmospheric turbulence and cloud microphysical parameters under specific weather conditions. The experimental results indicate that LWC is relatively low during clear days, ranging from 20 to 72 mg/m3 within clouds located at altitudes of 2.5–4 km. Under transitions from sunny-to-cloudy conditions, LWC decreases over time at altitudes of 3–4 km while increasing at altitudes of 2.5–3 km. During the progression from cloudy to precipitation weather, LWC reaches a maximum value of 480 mg/m3 at an altitude of 3 km. Furthermore, under clear weather conditions, CDER remains relatively stable. However, during transitions from sunny-to-cloudy conditions, CDER decreases. Notably, prior to precipitation, turbulence intensity within the cloud increases rapidly, leading to significant changes in both CDER and LWC. The research holds significant value for further studying clouds and precipitation, enhancing the accuracy of precipitation forecasting, and efficiently utilizing atmospheric water resources.