Distributional autoencoders trained on climate model simulations model full conditional distributions of European temperature fields to enable probabilistic storyline attribution, illustrated by higher intensities and probability ratios for a 2003-like heatwave in 2028 and 2053.
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Diffusion model improves GFS/GEFS ensemble CAPE forecasts and incorporates aerosol optical depths for additional gains.
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Probabilistic storyline attribution using machine learning
Distributional autoencoders trained on climate model simulations model full conditional distributions of European temperature fields to enable probabilistic storyline attribution, illustrated by higher intensities and probability ratios for a 2003-like heatwave in 2028 and 2053.
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Improving Ensemble CAPE Forecasts with a Diffusion Model Incorporating Aerosol Information
Diffusion model improves GFS/GEFS ensemble CAPE forecasts and incorporates aerosol optical depths for additional gains.