Abstract:
Clouds are integral components of the hydrological cycle and exert significant influence on regional and global weather patterns. Understanding cloud height, layers, and fraction in the atmosphere is crucial for precipitation and regulating Earth’s energy balance. This study investigates the cloud characteristics such as the cloud base height (CBH), cloud top height (CTH), and the vertical visibility over Udaipur, an urban city situated in the Aravalli ranges of Western India, employing ground-based Lidar (Ceilometer), satellite (MODIS), and reanalysis datasets (ERA5). The analysis focuses on CBH observations from Ceilometer Lidar during 2021-22, evaluating reanalysis and satellite-derived CBH. Results reveal peak detection (cloud presence or fully obscured sky) during the southwest monsoon, with frequencies reaching approximately 44%, 79%, 71%, and 37% in June, July, August, and September, respectively. While single-layer clouds are prevalent throughout the observation period, multiple layers are primarily observed during the monsoon, peaking in July and August. CBH exhibits a seasonal pattern, remaining low during the monsoon and high during pre-monsoon periods. Cloud type quantification based on CTH properties from MODIS satellites shows cirrostratus clouds as the most prevalent (approximately 36%) during the study period. Although CBH derived from MODIS CTH aligns with Ceilometer observations, the overall correlation is weak. Additionally, a seasonal variation is observed in ERA5 reanalysis performance regarding cloud base height detection over Udaipur. Therefore, the findings could contribute to broader scientific knowledge on cloud formation over complex hilly regions and these insights are crucial for improving weather prediction models by offering detailed data on cloud behavior, essential for accurate local weather forecasts.