Aurora 1.5: Fine-Tuning a Foundation Model for Medium-Range Ensemble Weather Prediction

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We present Aurora 1.5, a fine-tuned variant of the Aurora atmospheric foundation model [Bodnar
et al., 2025] optimized for skillful medium-range ensemble weather prediction. Building on Aurora’s
pretraining across diverse heterogeneous atmospheric data, we introduce a three-stage fine-tuning
pipeline that (i) expands the single-level variable set and randomizes lead-time embeddings to enable
a native one-hour temporal resolution, (ii) injects Gaussian noise into AdaptiveLayerNorm (AdaLN)
modules to generate stochastic forward passes and optimizes a Continuous Ranked Probability Score
(CRPS) objective in place of a deterministic loss, and (iii) performs auto-regressive fine-tuning on
operational ECMWF analyses with multi-step rollouts. Aurora 1.5 ENS outperforms the ECMWF
ENS operational ensemble on 88.9% of upper-air and single-level target variables in the medium range
(days 1–10). Reliability diagnostics including rank histograms indicate that Aurora 1.5 ENS achieves
this result with a slight over-dispersion, in contrast to the under-dispersion typical of dynamical
models. Compared to Aurora, Aurora 1.5 also better predicts extreme events, reducing tropical
cyclone track errors by 16% and the mean absolute error on top-5th percentile heat waves by 58%.
Aurora 1.5 demonstrates that foundation model fine-is a viable, cost-effective path toward
reliable probabilistic AI weather prediction.

Aurora 1.5 ensemble forecast example showing mean and ensemble uncertainty for total cloud cover and surface solar radiation (SSRD) over the Atlantic and Europe region at a 2–3 day forecast range. Four globe maps display the ensemble mean and standard deviation for each variable, illustrating Aurora's ability to predict both expected conditions and forecast uncertainty for cloud cover and solar radiation.
Figure 1: Illustration of the capabilities of Aurora 1.5 ensemble for predicting new impactful parameters such as total cloud cover and solar radiation. Ensemble mean and standard deviation are shown. 
detailed map showing Hurricane Helene track forecast
Figure 3. Hurricane Helene ensemble forecast from Aurora 1.5, showing multiple plausible storm tracks starting at 0 UTC on September 24, 2024. The probabilistic ensemble forecast envelops the verified track, effectively capturing uncertainty in the storm’s progression.