5 papers
A Checklist to assess the energy and carbon impacts of ML/AI applications in Earth System Modeling
Filippo Dainelli, Amirpasha Mozaffari, Marina Castaño +5
As machine learning and artificial intelligence find their way into nearly every aspect of climate, weather, and Earth system modeling, it is worth pausing to consider what our des…
Learning Climate Variability from Scarce Data with Diffusion Models: A Test Case for ENSO
Lluis Palma, Vincent Verjans, Amanda Duarte +2
Diffusion models are increasingly applied to climate emulation, but whether they capture the correct modes of variability remains unclear, a concern amplified by data scarcity at l…
Scalable Deep Learning Framework for Global High-Resolution Land Use Reconstruction
Amirpasha Mozaffari, Marina Castaño, Stefano Materia +7
Uncertainty in the terrestrial carbon cycle remains a major constraint in climate projections, partly driven by the uncertainties affecting the land surface representation and vari…
The Rise of AI in Weather and Climate Information and its Impact on Global Inequality
Amirpasha Mozaffari, Amanda Duarte, Lina Teckentrup +8
AI development's current trajectory risks automating and amplifying the North-South divide in the global climate information system. Frontier models are built almost exclusively in…
Data-driven Seasonal Climate Predictions via Variational Inference and Transformers
Lluís Palma, Alejandro Peraza, David Civantos +7
Most operational climate services providers base their seasonal predictions on initialised general circulation models (GCMs) or statistical techniques that fit past observations. G…