Understanding the seasonal lake dynamics is critical for water resource management and climate adaptation, yet intra-annual variability of Tibetan Plateau (TP) lakes remains poorly characterized. Here we present a monthly lake-surface area dataset covering 23,623 lakes (2000-2021), and propose a two-tiered classification framework identifying six distinct seasonal patterns. It reveals that semi-annual-cycle lakes predominate in endorheic regions while annual-cycle lakes concentrate in exorheic basins. Annual-cycle lakes are governed by single dominant factors and exhibit remarkable stability. In contrast, semi-annual-cycle lakes reflect coupled spring snowmelt and late-summer precipitation dynamics, showing high vulnerability to transitions. The Spring Peak (SP) pattern, whose shifts are attributable to intensified glacial melt and permafrost thaw, serves as a sensitive indicator of environmental changes. Seasonal complexity scales non-linearly with lake size. The post-2015 lake expansion coincided with rapid intensification of seasonal amplitude, indicating a fundamental hydrological transition that could threaten pastoral systems and water security across vulnerable endorheic regions. Semi-annual-cycle lakes occur mainly in endorheic regions and annual-cycle lakes in exorheic basins, with the former showing high vulnerability to seasonal transitions, according to analysis of monthly lake-surface area for 23,623 Tibetan lakes from 2000 to 2021.
Yao et al. (Wed,) studied this question.