Typhoon Landfall Prediction Method

Abstract

The invention provides a typhoon landing prediction method. The method comprises the first step of obtaining typhoon activity records in a specific region, the second step of screening out landing typhoons and non-landing typhoons from the typhoon activity records, the third step of screening out the regions where the landing typhoons are located during a preset time period before the landing typhoons land the specific region and dividing the regions into multiple sub-regions through a clustering algorithm, the fourth step of screening out all landing typhoon observation points and all non-landing typhoon observation points in each region with respect to each region in the multiple sub-regions, and obtaining characteristic factors of the landing typhoon observation points and characteristic factors of the non-landing typhoon observation points respectively, the fifth step of generating a typhoon landing judgment standard for each region through a sorting algorithm according to the obtained characteristic factors of the landing typhoon observation points and the obtained characteristic factors of the non-landing typhoon observation points in each region, and the sixth step of verifying the typhoon landing judgment standard for each region according to the obtained landing typhoon observation points and the obtained non-landing typhoon observation points in each region so as to obtain the probability of typhoon landing prediction. The method is high in accuracy and good in real-time performance.

Description

technical field [0001] The invention relates to the technical field of typhoon early warning, in particular to a typhoon landing prediction method. Background technique [0002] Typhoon forecasting and evaluation work has been widely concerned at home and abroad. Due to the characteristics of strong randomness, wide range of influence, and huge burst energy of typhoons, previous research has mainly focused on typhoon intensity and track prediction. The National Hurricane Center of the United States, the Tokyo Typhoon Center of Japan, and the Central Meteorological Observatory of China have been conducting statistical analysis, summary, and improvement of tropical cyclone forecasts in different regions. [0003] At present, the main methods of typhoon prediction are: variable dimension fractal model prediction, spatial analysis prediction based on geographic information system (GIS), climate persistence (CLIPER) model prediction, artificial neural network prediction based on ...

AI Technical Summary

Problems solved by technology

It can be seen that although the shortcomings of large typhoon track forecast errors have been improved, it still cannot meet the needs of various industries for typhoon forecast accuracy.

Moreover, the previous typhoon prediction methods could not judge whether the typhoon landed, but could only predict the typhoon path and corresponding characteristic factors.

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