1. Binary dataset for machine learning applications to tropical cyclone formation prediction.
- Author
-
Kieu, Chanh and Nguyen, Quan
- Subjects
CYCLONE forecasting ,TROPICAL cyclones ,ATMOSPHERIC sciences ,LEAD time (Supply chain management) ,MACHINE learning - 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. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF