A Physical-Based Semi-Automatic Algorithm for Post-Tropical Cyclone Identification and Tracking in Australia - Difei Deng (Remote Sensing)
Of all meteorological events, Tropical Cyclones (TCs) are by far the costliest of natural hazards around the globe. They typically lose their strength quite rapidly once making landfall. Recent studies have revealed that TCs, even degrading below TC strength after landfall, can survive for prolonged periods and still exert a significant impact as Post-Tropical Cyclones (PTCs). However, the widely used TC best track datasets, including the International Best Track Archive for Climate Stewardship, do not consistently track TCs for long enough following landfall to include complete PTC tracks. The absence of tracking limits our understanding of the overall TC-related impacts. In this study, we developed a semi-automatic tracking algorithm using satellite imagery and reanalysis data to extend TC tracks beyond the best track dataset until dissipation overland. Based on all landfalling TCs for the period 1990–2020 in Australia, these TCs can be further tracked overland for an additional 1.6 days on average, with a maximum of 15 days, since the last record in best track datasets. Although the intensity of Australian landfalling TCs has declined over the 30 years, they continue to linger over land for similar durations before dissipation, suggesting an increasing likelihood of favorable land conditions for TCs and PTCs.