Method and system for determining a historical similar typhoon based on large-scale environmental field similarity
By using Bayesian network models and multiple physical constraints, the problem of inaccurate characterization of the subtropical high's position and shape was solved, thus improving the accuracy and reliability of typhoon track forecasts.
CN122335893APending Publication Date: 2026-07-03上海亚太台风研究中心 +2
View PDF 0 Cites 0 Cited by
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- 上海亚太台风研究中心
- Filing Date
- 2026-04-08
- Publication Date
- 2026-07-03
AI Technical Summary
Technical Problem
Existing technologies are insufficient to accurately characterize key physical features such as the position, intensity, and shape of the subtropical high, resulting in inaccurate typhoon track forecasts.
Method used
A Bayesian network model was used to generate binarized images of the subtropical high and calculate their similarity. By combining spatial, temporal, and directional constraints, similar historical subtropical high images were selected to determine historical typhoon information and subsequent paths.
Benefits of technology
It improves the accuracy and reliability of typhoon path forecasts, provides similar historical cases with clear meteorological significance, and enhances the business reference value of search results.
✦ Generated by Eureka AI based on patent content.
Smart Images
Figure CN122335893A_ABST
Abstract
This invention discloses a method and system for determining historical similar typhoons based on large-scale environmental field similarity. The method includes: acquiring the state information of the current target typhoon and the corresponding large-scale environmental field data; processing and generating a binarized image of the target subtropical high centered on the typhoon; constructing a database of historical subtropical high binarized images; using a Bayesian network model, with subtropical high image pixel blocks as nodes, and learning their conditional probability dependencies, calculating the effective area, overlapping effective area, and similarity coefficient between the target and historical subtropical high images; then, applying spatial, temporal, and directional physical constraints to the similarity results for joint screening to obtain an optimal list of similar historical subtropical highs; finally, determining the corresponding historical typhoons and their subsequent paths based on this list as a forecast reference for the current typhoon. This method makes the similarity judgment more consistent with meteorological mechanisms and significantly improves the accuracy and operational reference value of historical similar typhoon retrieval.
Need to check novelty before this filing date? Find Prior Art