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Author

Jorge Guevara

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Open access Aug 2026

Enhancing operational wind downscaling capabilities over Canada: Application of a Conditional Wasserstein GAN methodology

Downscaling based on Artificial Intelligence (AI) has been demonstrated to be a powerful tool for improving the spatial resolution of weather forecasts. This study advances wind downscaling by extending the DownGAN framework introduced by Annau et al. to operational Canadian Numerical Weather Predictions (NWP), namel...

Jorge Guevara, Victor Nascimento, Johannes Schmude et al. · 0 citations
Preprint Aug 2026

Precipitation Downscaling Using Foundation Model-Conditioned Diffusion

Results indicate that cross-attention conditioning offers advantages over simple concatenation for probabilistic precipitation downscaling, and that pre-trained foundation model representations may offer benefits in data-limited settings.

Victor Nascimento Ribeiro, Jorge Guevara, J. Moraga et al. · 0 citations
Open access 2026

Frequency-Conditioned GAN for Remote Sensing Image Super-Resolution

FC-GAN is built, a frequency-conditioned model that adapts frequency separation techniques to remote sensing data and extends the standard frequency-domain evaluation framework from the meteorological downscaling literature to assess spectral fidelity using the radially averaged power spectral density and log-spectral...

Victor Nascimento Ribeiro, Jorge Guevara, D. Szwarcman et al. · 0 citations

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