Intelligent early warning method for severe convective weather based on phased array weather radar cooperative networking
By combining multiple phased array weather radars in a coordinated network with the ViT-Large neural network model, the problems of blind spots and data uniformity in traditional radars have been solved, achieving high spatiotemporal resolution and high precision in severe convective weather warnings, thus improving the warning effect.
Patent Information
- Application Number
- CN202511802910.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-03
- Publication Date
- 2026-07-24
- Estimated Expiration
- 2045-12-03
AI Technical Summary
Traditional single-weather radar detection methods in existing technologies suffer from limited data types, low temporal resolution, and blind spots in the boundary layer at medium and long distances, making it difficult to fully capture the formation, development, and evolution characteristics of severe convective weather. Furthermore, existing deep learning models suffer from limited training sample data, poor global feature capture capabilities, uneven feature representation, and low computational efficiency, resulting in poor intelligent early warning effects for severe convective weather.
Multiple phased array (dual polarization) weather radars are networked collaboratively to acquire high spatiotemporal resolution observation data. Through data quality control, data fusion, and feature sample extraction, a smart early warning model for severe convective weather is constructed using the ViT-Large neural network architecture. The model is trained using a multi-channel input-single-channel output mechanism to output early warning results.
It significantly improves the timeliness and accuracy of early warnings for severe convective weather under complex climate and terrain conditions, reduces the rate of missed and false reports, provides more comprehensive information on the characteristics of severe convective weather, and enhances the effectiveness of early warnings.