Omni-Weather: Unified Weather Model
Published:Dec 25, 2025 12:08
•1 min read
•ArXiv
Analysis
This paper introduces Omni-Weather, a novel multimodal foundation model that merges weather generation and understanding into a single architecture. This is significant because it addresses the limitations of existing methods that treat these aspects separately. The integration of a radar encoder and a shared self-attention mechanism, along with a Chain-of-Thought dataset for causal reasoning, allows for interpretable outputs and improved performance in both generation and understanding tasks. The paper's contribution lies in demonstrating the feasibility and benefits of unifying these traditionally separate areas, potentially leading to more robust and insightful weather modeling.
Key Takeaways
- •Omni-Weather is a unified multimodal foundation model for weather.
- •It integrates generation and understanding within a single architecture.
- •It uses a radar encoder and shared self-attention.
- •It utilizes a Chain-of-Thought dataset for causal reasoning.
- •It achieves state-of-the-art performance in both generation and understanding.
Reference
“Omni-Weather achieves state-of-the-art performance in both weather generation and understanding. Generative and understanding tasks in the weather domain can mutually enhance each other.”