Author

Jonathan Giezendanner

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#artificial intelligence Preprint Sep 2026

Benchmarking Generative Models for Near-Surface Data Assimilation on Real Station Observations

Weather reanalysis products rely on computationally intensive numerical weather predictions followed by data assimilation that corrects the forecast toward observations. Recent advances in deep generative models offer a cheaper alternative that shifts much of this cost from inference to offline training. However, exist...

Rui-Zhe Huang, Qi-Dong Yang, Jonathan Giezendanner et al. · 0 citations

#machine learning Preprint Sep 2026

SolarBench: A global solar energy nowcasting benchmark

As the share of solar power grows, nowcasting weather-driven solar variability becomes critical for reliable energy system operation. State-of-the-art approaches increasingly apply deep learning to sky camera and geostationary satellite observations, but fragmented datasets and inconsistent evaluation make it difficult...

Yuhao Nie, Stephen Campbell, Quentin Paletta et al. · 0 citations