paper
2021
Climate emulation
Probabilistic & ensemble forecasting New model or method
GAN or VAECNN / U-NetMétéo-France (incl. CNRM) Journal
2021-01-01
047
Jan 2021
Camille Besombes, Olivier Pannekoucke, Corentin Lapeyre et al.
Nonlinear processes in geophysics
Météo-France (incl. CNRM)
Wasserstein GAN with a CNN generator learns a 64-dimensional latent space of synthetic PLASIM climate states, reproducing leading EOF statistics and geostrophic balance.
Producing realistic climate data with generative adversarial networks GANs
In one sentence. Wasserstein GAN with a CNN generator learns a 64-dimensional latent space of synthetic PLASIM climate states, reproducing leading EOF statistics and geostrophic balance.
Labels
- Topic
- Climate emulation, Probabilistic & ensemble forecasting
- Type
- New model or method
- Method
- GAN or VAE, CNN / U-Net
- Domain
- Global
- Data
- Other
- Status
- Research
- Identifiers
- DOI:10.5194/npg-2021-6 OpenAlex:W4205420528
- Added
- 2026-10-22
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