paper
2020
Extremes & hazards
New model or method
CNN / U-Net6 h–3 days Other
2020-04-03
012
Apr 2020
Wenke Wang, Xin Wang
preprint
A 3D convolutional network using environmental fields and sea surface temperature predicts 24-hour tropical cyclone intensity change, with better strengthening/weakening classification accuracy.
The Prediction Method of Tropical Cyclone Intensity Change Based on Deep Learning
In one sentence. A 3D convolutional network using environmental fields and sea surface temperature predicts 24-hour tropical cyclone intensity change, with better strengthening/weakening classification accuracy.
Labels
- Topic
- Extremes & hazards
- Type
- New model or method
- Method
- CNN / U-Net
- Time scale
- 6 h–3 days
- Domain
- Global
- Data
- ERA5 / reanalysis, NWP analysis or forecasts (IFS, GFS, ...)
- Status
- Research
- Identifiers
- DOI:10.1002/essoar.10502649.1 OpenAlex:W3017623228
- Added
- 2026-10-22
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