Supraglacial lakes in Antarctica are key indicators of surface meltwater processes and play a significant role in ice shelf stability and ice sheet dynamics. Despite their importance, the understanding of their spatiotemporal dynamics remains limited due to their high variability and the lack of consistent, large-scale monitoring approaches. To date, no bi-weekly, pan-Antarctic dataset exists that captures supraglacial lake extent over recent years. To address this gap, we introduce the PolarLakes dataset, generated using a deep learning-based workflow that automates the detection and mapping of supraglacial lakes across Antarctic ice shelves. This method integrates Sentinel-1 synthetic aperture radar (SAR) and Sentinel-2 optical imagery to enhance spatial and temporal coverage while improving detection accuracy under challenging conditions such as cloud cover and surface refreezing. The resulting open-access dataset provides bi-weekly records of supraglacial lake extents at 10 meter spatial resolution from 2015 through 2024. It reveals extensive ponding in East Antarctica until a pan-Antarctic peak in lake area in 2020, followed by higher melt extents on the Antarctic Peninsula, culminating in a secondary peak on the Antarctic Peninsula in 2023. The PolarLakes dataset offers a valuable resource for investigating supraglacial hydrology and provides essential observational constraints for hydrological and ice sheet modeling. The PolarLakes dataset is available at DLR’s GeoService at <a href="https://geoservice.dlr.de/web/datasets/polarlakes" target="_blank" rel="noopener">https://geoservice.dlr.de/web/datasets/polarlakes</a>.