Investigation of cloud characteristics over a high-altitude region, Mt. Abu, using ground-based Lidar and satellite observations
Source
Theoretical and Applied Climatology
ISSN
0177-798X
Date Issued
2026-01
Author(s)
Kamat, Dharmendra
Sharma, Som Kumar
Kumar, Prashant
Kumar, Kondapalli Niranjan
Saha, Sourita
Aniket
Abstract
Clouds are critical in shaping local weather patterns, particularly in mountainous regions where complex environmental factors influence their behavior. This study provides a comprehensive analysis of cloud properties over Mt. Abu (24.59° N, 72.71° E, ~ 1219 m a.m.s.l), a high-altitude region in the Aravalli Range of Western India, utilizing ground-based Lidar and satellite datasets. The study found an annual cloud occurrence of approximately 23% from January to December 2023. The seasonal mean cloud occurrence was highest during the monsoon (42.88%), followed by pre-monsoon (19.25%), post-monsoon (7.28%), and winter (4.1%) seasons. The cloud frequency peaked in the afternoon (13:00–15:00 LT) during the monsoon, exceeding 60% in July and August. In contrast, the pre- and post-monsoon periods showed moderate midday peaks (~ 25%), while winter months exhibited minimal diurnal variation with cloud occurrence generally below 10%. The seasonal mean cloud base height (CBH) was lowest during the monsoon (780 ± 1370 m) and highest in winter (4620 ± 2390 m). Shallow boundary layer clouds, confined below 2 km, were commonly observed in the pre-monsoon and monsoon seasons. Low-visibility events (vertical visibility < 100 m), primarily mist, were most frequent during July (21.5%) and August (36.8%), while winter fog events were less frequent and driven by radiative cooling under stable boundary layer conditions. MODIS observations indicated a predominance of cirrostratus clouds (~ 30%) during satellite passes, and notable discrepancies were observed between MODIS-derived CBH and Ceilometer observations. This study highlights the complex cloud dynamics in mountainous environments and underscores the need for continuous, high-resolution observations to improve cloud representation in weather and climate models.
