paper
2023
Nowcasting
Extremes & hazards New model or method
RNN / LSTM / ConvLSTMGAN or VAE0–6 h Journal
2023-04-24
016
Apr 2023
Philippe Baron, Kohei Kawashima, Dongkyun Kim et al.
Journal of Atmospheric and Oceanic Technology
Adversarially trained 3D LSTM nowcasts sudden localized heavy rain from MP-PAWR radar with 10-min lead, outperforming an advection model and JMA's operational system at onset.
Nowcasting Multiparameter Phased-Array Weather Radar (MP-PAWR) Echoes of Localized Heavy Precipitation Using a 3D Recurrent Neural Network Trained with an Adversarial Technique
In one sentence. Adversarially trained 3D LSTM nowcasts sudden localized heavy rain from MP-PAWR radar with 10-min lead, outperforming an advection model and JMA's operational system at onset.
Labels
- Topic
- Nowcasting, Extremes & hazards
- Type
- New model or method
- Method
- RNN / LSTM / ConvLSTM, GAN or VAE
- Time scale
- 0–6 h
- Domain
- Local / station
- Data
- Radar
- Status
- Pre-operational / experimental
- Identifiers
- DOI:10.1175/jtech-d-22-0109.1 OpenAlex:W4366830053
- Added
- 2026-10-22
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