Data Science and Machine Learning for hurricane forecasting
In one sentence. Argues that data science approaches can improve hurricane forecasting beyond traditional statistical methods; methods and results are only vaguely described.
Abstract
This paper demonstrates the importance of Data Science techniques within the Natural Sciences sector, more specifically, within the area of climate research such as global warming and hurricane development. During times of a continued increase in global temperatures, it more important than ever to further improve today's forecasting and prediction methods. Two possible Data Science approaches are being demonstrated and proveen to add value to the traditional statistics based forecasting methods.
Labels
- Topic
- Extremes & hazards
- Type
- Position or perspective paper
- Method
- Classical ML (trees, GP, linear, kernels)
- Domain
- Global
- Data
- Other
- Status
- Research
- Identifiers
- DOI:10.5281/zenodo.5932783 OpenAlex:W4226167585
- Added
- 2026-10-22
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