An effective tropical cyclone intensity estimation model using Convolutional Neural Networks
In one sentence. A simple CNN estimates tropical cyclone intensity for Indian-basin storms, claimed to beat state-of-the-art methods with lower computation, with few quantitative details in the abstract.
Abstract
The tropical cyclones in India is a common natural disaster happening every year.As per the statistics, about three cyclones hit India's east coast in the Bay of Bengal, which damaged human lives, crops and property.It is essential to predict the cyclones in advance to prevent and reduce huge damage.The techniques used are based on numerical models that require vast expertise and higher skill sets to achieve better prediction accuracy.The usage of Convolutional Neural Networks shall overcome various issues like domain knowledge, the scope for human errors.Hence, in this paper, we attempted to predict cyclone intensity using Convolutional Neural Networks by proposing a simple and robust architecture for Tropical Cyclone intensity estimation.The results yielded better performance than the state-of-the-art techniques with reduced computation time.
Labels
- Topic
- Extremes & hazards
- Type
- New model or method
- Method
- CNN / U-Net
- Domain
- Regional
- Data
- Satellite
- Status
- Research
- Identifiers
- DOI:10.54302/mausam.v72i2.616 OpenAlex:W3182360148
- Added
- 2026-10-22
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