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- Title
Binary dataset for machine learning applications to tropical cyclone formation prediction.
- Authors
Kieu, Chanh; Nguyen, Quan
- Abstract
Applications of machine learning (ML) in atmospheric science have been rapidly growing. To facilitate the development of ML models for tropical cyclone (TC) research, this binary dataset contains a specific customization of the National Center for Environmental Prediction (NCEP)/final analysis (FNL) data, in which key environmental conditions relevant to TC formation are extracted for a range of lead times (0–72 hours) during 1999–2023. The dataset is designed as multi-channel images centered on TC formation locations, with a positive and negative directory structure that can be readily read from any ML applications or common data interface. With its standard structure, this dataset provides users with a unique opportunity to conduct ML application research on TC formation as well as related predictability at different forecast lead times.
- Subjects
CYCLONE forecasting; TROPICAL cyclones; ATMOSPHERIC sciences; LEAD time (Supply chain management); MACHINE learning
- Publication
Scientific Data, 2024, Vol 11, Issue 1, p1
- ISSN
2052-4463
- Publication type
Article
- DOI
10.1038/s41597-024-03281-5