4 citations · 18 across the 5 of their papers we have counts for
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physics.ao-ph2024★ 4 cited
Ai4Fapar: How artificial intelligence can help to forecast the seasonal earth observation signal
Filip Sabo, Martin Claverie, Michele Meroni +1
This paper investigated the potential of a multivariate Transformer model to forecast the temporal trajectory of the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR…
physics.ao-ph2023★ 4 cited
Super-resolved rainfall prediction with physics-aware deep learning
S. Moran, B. Demir, F. Serva +1
Rainfall prediction at the kilometre-scale up to a few hours in the future is key for planning and safety. But it is challenging given the complex influence of climate change on cl…