paper
2024
Extremes & hazards
Observations & remote sensing New model or method
CNN / U-Net6 h–3 daysChina Meteorological Administration (CMA)Fudan University (FuXi)Nanjing University of Information Science & Technology (NUIST) Journal
2024-01-01
047
Jan 2024
Wei Tian, Yuanyuan Chen, Ping Song et al.
IEEE Transactions on Geoscience and Remote Sensing
China Meteorological Administration (CMA), Fudan University (FuXi), Nanjing University of Information Science & Technology (NUIST)
TCIP-Net predicts tropical cyclone intensity from infrared satellite imagery using radial structure evolution, with interpretable contributions and without reanalysis inputs.
TCIP-Net: Quantifying Radial Structure Evolution for Tropical Cyclone Intensity Prediction
In one sentence. TCIP-Net predicts tropical cyclone intensity from infrared satellite imagery using radial structure evolution, with interpretable contributions and without reanalysis inputs.
Labels
- Topic
- Extremes & hazards, Observations & remote sensing
- Type
- New model or method
- Method
- CNN / U-Net
- Time scale
- 6 h–3 days
- Domain
- Regional
- Data
- Satellite
- Status
- Research
- Identifiers
- DOI:10.1109/tgrs.2024.3450711 OpenAlex:W4402302416
- Added
- 2026-10-22
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