Simultaneous retrieval algorithm of water cloud optical and microphysical properties by high-spectral-resolution lidar

Abstract

The uncertainty of water cloud feedback on radiative forcing is one of the largest obstacles to producing confident projections of the global climate. Sufficient measurements of water clouds are crucial to addressing this issue. However, existing techniques based on remote sensing or in situ instruments face limitations in data capacity attributed to the short lifetime, high temporal variability, and complex vertical structure of water clouds. In this study, taking advantage of a dual-field-of-view (dual-FOV) high-spectral-resolution lidar (HSRL), we developed a novel algorithm to obtain diurnal simultaneous profiles of water cloud optical and microphysical properties with high temporal-spatial resolution. This technique does not rely on the widely used subadiabatic assumption about the vertical structure of water clouds. The retrieval algorithm, validated by simulations and cloud radar measurements, was applied to field experiment data collected at the Beijing and Hangzhou sites in China. The relationship functions between water cloud properties are presented to enhance our understanding of the underlying processes. Furthermore, the vertical distributions of retrieved properties are compared to the subadiabatic assumption. The dual-FOV HSRL technique enables comprehensive observations, enhancing our understanding of water clouds and providing significant insights into the interactions among clouds, aerosols, precipitation, and radiation.