AviaSafe: A Physics-Informed Data-Driven Model for Aviation Safety-Critical Cloud Forecasts

Researchers developed AviaSafe, a physics-informed AI model that forecasts aviation-critical cloud species up to 7 days ahead, addressing safety concerns around engine icing. The model outperforms operational weather models by predicting specific hydrometeor species rather than general atmospheric variables, enabling better aviation route optimization.

• →AviaSafe is the first AI weather model to predict individual cloud microphysical species critical for aviation safety rather than just general atmospheric variables.
• →The model uses physics-informed neural networks with hierarchical architecture to handle extreme sparsity and discontinuous distributions in cloud data.
• →Integration of the Icing Condition index helps identify regions where supercooled water creates explosive ice crystal growth hazards.
• →The system achieves lower RMSE for cloud species prediction compared to baselines and outperforms operational models at 7-day forecasts.
• →Applications include aviation route optimization where distinguishing ice from liquid water is crucial for preventing engine icing risks.