Integration of lidar and meteorological data for a comprehensive study of high-level clouds

Subject of study. The optical characteristics of high-level clouds (HLCs), which significantly affect the Earth’s radiation budget and climate due to their large spatial extent, are investigated. Aim of study. This study aims to develop an approach for the comprehensive study and assessment of HLC characteristics. In addition, the study seeks to determine the conditions and frequency of HLC occurrence by comparing satellite, lidar, and meteorological data, thereby broadening the geophysical applicability of the results. Method. Data from polarization lidar sensing, the MODIS satellite spectroradiometer, radiosonde observations, weather stations, and atmospheric reanalysis datasets ERA5 and MERRA-2 are used. These reanalysis datasets combine numerical atmospheric modeling with heterogeneous observations, providing temporally and spatially consistent datasets. Main results. A lidar dataset for 2009–2024 is described, together with the distributions of HLC characteristics derived from it. Atmospheric data sources suitable for predicting the formation of HLCs and their characteristics, including cirrus with a preferred horizontal orientation of ice crystals, are identified. Practical significance. The results can be used to refine parameters in climate models and short-term cloud forecasts, as well as for analyzing the distribution and dynamics of clouds in various regions. Integration of local lidar observations with large-scale meteorological information based on the analysis of optical characteristics of clouds significantly expands the geophysical applicability of the results.