Global dominance of seasonality in shaping lake-surface-extent dynamics

Lakes are crucial for ecosystems1, greenhouse gas emissions2 and water resources3, yet their surface-extent dynamics, particularly seasonality, remain poorly understood at continental to global scales owing to limitations in satellite observations4,5. Although previous studies have focused on long-term changes6–8, comprehensive assessments of seasonality have been constrained by trade-offs between spatial resolution and temporal resolution in single-source satellite data. Here we show that seasonality is the dominant driver of lake-surface-extent variations globally. By leveraging a deep-learning-based spatiotemporal fusion of MODIS and Landsat-based datasets, combined with high-performance computing, we…