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AI weather model Aardvark goes probabilistic, attributing forecast uncertainty

By PulseAugur Editorial · [3 sources] ·

Researchers have developed a probabilistic version of the Aardvark Weather model, an end-to-end AI system for weather forecasting. By incorporating learned noise in the observation encoder and Monte Carlo Dropout in the processor, the model can now attribute forecast uncertainty to either observation errors (aleatoric) or model dynamics (epistemic). This probabilistic finetuning not only improves the mean forecast by an average of 4.2% but also provides a calibrated ensemble that rivals operational models in accuracy and offers greater transparency into forecast origins. AI

IMPACT Enhances transparency in AI weather models by attributing forecast uncertainty to specific sources.

RANK_REASON Research paper detailing a novel probabilistic approach to an AI weather model.

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 3 sources. How we write summaries →

AI weather model Aardvark goes probabilistic, attributing forecast uncertainty

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COVERAGE [3]

  1. arXiv cs.LG TIER_1 English(EN) · Julian F. Schmitt, Bertrand Delorme, Robert C. King, Yashica Patodia, Tapio Schneider, Aditi Sheshadri, Ravi Jain ·

    Improving precipitation forecasts in an AI weather model using observational data

    arXiv:2609.03210v1 Announce Type: cross Abstract: Artificial intelligence weather prediction (AIWP) systems now surpass state-of-the-art physical models for medium-range weather forecasting. Current global AIWP models are trained almost exclusively using one reanalysis dataset, E…

  2. arXiv cs.LG TIER_1 English(EN) · Rodrigo Almeida, Noelia Otero, Jost Arndt, Simon Baur, Wojciech Samek, Jackie Ma ·

    Uncertainty-Aware End-to-End AI Weather Forecasting: Disentangling Observation and Model Contributions

    arXiv:2608.30795v1 Announce Type: cross Abstract: End-to-end weather forecasting systems produce skillful global gridded and station forecasts directly from raw Earth observations, replacing the numerical weather prediction pipeline, including data assimilation, at a fraction of …

  3. Hugging Face Daily Papers TIER_1 English(EN) ·

    Uncertainty-Aware End-to-End AI Weather Forecasting: Disentangling Observation and Model Contributions

    The Aardvark Weather model is made probabilistic by adding learned observation noise and Monte Carlo dropout to its encoder and processor, yielding a calibrated nested ensemble that improves mean forecasts and separates aleatoric and epistemic uncertainty.

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