Cloud vertical structure (CVS) strongly affects atmospheric circulation and radiative transfer. Yet, long-term, ground-based observations are scarce over the Tibetan Plateau (TP) despite its vital role in global climate. This study utilizes ground-based lidar and Ka-band cloud profiling radar (KaCR) measurements at Yangbajain (YBJ), TP, from October 2021 to September 2022 to characterize cloud properties. A satisfactorily performing novel anomaly detection algorithm (LevelShiftAD) is proposed for lidar and KaCR profiles to identify cloud boundaries. Cloud base heights (CBH) retrieved from KaCR and lidar observations show good consistency, with a correlation coefficient of 0.78 and a mean difference of –0.06 km. Cloud top heights (CTH) derived from KaCR match the FengYun-4A and Himawari-8 products well. Thus, KaCR measurements serve as the primary dataset for investigating CVSs over the TP. Different diurnal cycles occur in summer and winter. The diurnal cycle is characterized by a pronounced increase in cloud occurrence frequency in the afternoon with an early-morning decrease in winter, while cloud amounts remain high all day, with scattered nocturnal increases in summer. Summer features more frequent clouds with larger geometrical thicknesses, a higher multi-layer ratio, and greater inter-cloud spacing. Around 26% of the cloud bases occur below 0.5 km. Winter exhibits a bimodal distribution of cloud base heights with peaks at 0–0.5 km and 2–2.5 km. Single-layer and geometrically thin clouds prevail at YBJ. This study enriches long-term measurements of CVSs over the TP, and the robust anomaly detection method helps quantify cloud macro-physical properties via synergistic lidar and radar observations.
 

Ka-band cloud profiling radar, lidar, anomaly detection, cloud base heights, cloud top heights, Tibetan Plateau

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