一种考虑高风速下消亡过程的赤潮短期趋势预测方法
By constructing a stochastic diffusion model that considers the properties of algal clusters and a high-wind-speed decay algorithm, the problem of inaccurate simulation of the red tide decay process under high wind speeds in red tide migration prediction models has been solved. This has enabled accurate prediction of short-term red tide trends and accurate delineation of affected areas, providing technical support for the scientific management of red tides.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- BEIHAI FORECASTING CENT OF STATE OCEANIC ADMINISTRATION ((QINGDAO MARINE FORECASTING STATION OF STATE OCEANIC ADMINISTRATION) (QINGDAO MARINE ENVIRONMENT MONITORING CENT OF STATE OCEANIC ADMINISTRATION))
- Filing Date
- 2026-04-30
- Publication Date
- 2026-07-17
AI Technical Summary
Existing red tide migration prediction models cannot accurately simulate the dissipation process and spatial distribution of red tides under high wind speed conditions, resulting in high uncertainty in prediction results and failing to effectively guide the forecasting of red tide-affected areas.
By constructing a stochastic diffusion model that considers the properties of algal masses and combining it with a high-wind-speed decay algorithm, the migration and decay process of red tide algal masses under the action of ocean dynamics is simulated. Using ocean dynamics and meteorological model forecast data as driving fields, stochastic diffusion algorithms and high-wind-speed algal mass decay algorithms are developed to predict the range of red tide influence.
It enables accurate prediction of short-term red tide trends under high wind speed conditions, accurately simulates algal cluster distribution and the range of red tide influence, provides scientific decision-making assistance, and improves the accuracy and reliability of red tide forecasting.
Smart Images
Figure CN122132677B_ABST