IMPMCT: a dataset of Integrated Multi-source Polar Meso-Cyclone Tracks

Abstract. Polar Mesoscale Cyclones (PMCs), particularly their intense subset known as Polar Lows (PLs), characterized by short lifespans of 3-36 hours and horizontal scales below 1,000 km, pose significant hazards to polar maritime activities due to extreme winds exceeding 15 m s⁻¹ and wave heights surpassing 11 meters. These intense weather systems play a critical role in modulating sea-ice dynamics and ocean-atmosphere heat exchange. However, current understanding remains constrained by sparse observational records and overdependence on singular data sources (e.g., remote sensing or reanalysis). To address these gaps, this study presents the Integrated Multi-source Polar Meso-Cyclone Tracks (IMPMCT) dataset, a comprehensive 24-year (2001-2024) wintertime PMCs record for the Nordic Seas. IMPMCT combines vortices tracking algorithms from ERA5 reanalysis with deep learning-based detection of cyclonic cloud features in Advanced Very High-Resolution Radiometer (AVHRR) infrared imagery, while incorporating near-surface wind matching by Advanced Scatterometry (ASCAT) and Quick Scatterometry (QUIKSCAT) measurements. The dataset contains 1,184 vortex tracks, 16,630 cyclonic cloud features, and 4,373 wind speed records, with multi-dimensional attributes such as cloud morphology, core wind speed, and environmental advection wind speed. Validation demonstrates a 70–90 % match rate with existing PLs track datasets while providing more complete cyclone life cycle trajectories, more intuitive cloud imagery visualization, and a richer set of parameters compared to previous datasets. As the most comprehensive PMCs archive for the Nordic Seas, the IMPMCT dataset provides fundamental data for advancing our understanding of the genesis and intensification mechanisms, enables the development of enhanced monitoring and early warning systems, supports the validation and refinement of polar numerical weather prediction models, and facilitates improved risk assessment and safety protocols for maritime operations. The dataset is available at https://doi.org/10.5281/zenodo.15355602 (Fang et al., 2025).