{"ID":2852420,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.19854","arxiv_id":"2510.19854","title":"Multi-Resolution Analysis of the Convective Structure of Tropical Cyclones for Short-Term Intensity Guidance","abstract":"Accurate tropical cyclone (TC) short-term intensity forecasting with a 24-hour lead time is essential for disaster mitigation in the Atlantic TC basin. Since most TCs evolve far from land-based observing networks, satellite imagery is critical to monitoring these storms; however, these complex and high-resolution spatial structures can be challenging to qualitatively interpret in real time by forecasters. Here we propose a concise, interpretable, and descriptive approach to quantify fine TC structures with a multi-resolution analysis (MRA) by the discrete wavelet transform, enabling data analysts to identify physically meaningful structural features that strongly correlate with rapid intensity change. Furthermore, deep-learning techniques can build on this MRA for short-term intensity guidance.","short_abstract":"Accurate tropical cyclone (TC) short-term intensity forecasting with a 24-hour lead time is essential for disaster mitigation in the Atlantic TC basin. Since most TCs evolve far from land-based observing networks, satellite imagery is critical to monitoring these storms; however, these complex and high-resolution spati...","url_abs":"https://arxiv.org/abs/2510.19854","url_pdf":"https://arxiv.org/pdf/2510.19854v1","authors":"[\"Elizabeth Cucuzzella\",\"Tria McNeely\",\"Kimberly Wood\",\"Ann B. Lee\"]","published":"2025-10-21T18:50:42Z","proceeding":"eess.IV","tasks":"[\"eess.IV\",\"cs.LG\"]","methods":"[]","has_code":false}