paper
2021
Extremes & hazards
Observations & remote sensing New model or method
CNN / U-Net6 h–3 daysNanjing University of Information Science & Technology (NUIST) Journal
2021-04-09
022
Apr 2021
Rui Zhang, Qingshan Liu, Renlong Hang et al.
IEEE Transactions on Geoscience and Remote Sensing
Nanjing University of Information Science & Technology (NUIST)
CNN-based fusion of satellite and ERA5 predictors detects 97.1% of developing tropical cyclones in the western North Pacific at a 20.3% false alarm rate.
Predicting Tropical Cyclogenesis Using a Deep Learning Method From Gridded Satellite and ERA5 Reanalysis Data in the Western North Pacific Basin
In one sentence. CNN-based fusion of satellite and ERA5 predictors detects 97.1% of developing tropical cyclones in the western North Pacific at a 20.3% false alarm rate.
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, ERA5 / reanalysis
- Status
- Research
- Identifiers
- DOI:10.1109/tgrs.2021.3069217 OpenAlex:W3155849328
- Added
- 2026-10-22
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