Method for eyed typhoon two-dimensional surface wind field inversion on basis of SVM and PDE

Abstract

To solve the problem that errors generated in solving an infrared cloud image eyed typhoon two-dimensional surface wind field through ordinarily used algorithms are large, the invention provides a method for performing inversion on an eyed typhoon two-dimensional surface wind field by combination with novel algorithms of an SVM and a PDE. The method comprises the steps of first performing typhoon eye wall extraction on an infrared cloud image provided by a weather bureau by combination with the PDE algorithm, obtaining coordinate values and gray levels of every point of an eye wall, utilizing the SVM to perform modeling of the average gray level and the maximum wind speed of a typhoon close to the center, finally performing eye wall segmentation on the randomly given infrared cloud image, extracting reference point gray levels to serve as a model to perform input to obtain the reference point wind speed, and utilizing a linear interpolation to perform inversion of the whole two-dimensional surface wind field. According to experiments, the average error obtained through the method is 2.9m / s, the performance is better that that of a linear regression method and a radial basis neural network method, and a powerful basis is provided for typhoon intensity forecast.

Description

technical field [0001] The invention belongs to the application field of typhoon intensity forecasting. In particular, it relates to a two-dimensional surface wind field inversion method for eye-catching typhoon based on SVM and PDE. Background technique [0002] The information of the typhoon wind field is very important. First, it reflects the intensity of the typhoon. For example, the maximum wind speed near the center can generally be expressed as the intensity of the typhoon; secondly, it can also reflect the structural information of the typhoon, which is also one of the factors that determine the intensity of the typhoon; therefore , the key to improving the level of intensity forecasting lies in how to select appropriate techniques to extract wind field information from known information, and combine appropriate numerical forecasting for intensity forecasting. Generally speaking, typhoon intensity is mainly determined by the maximum wind speed near the eyewall near ...

AI Technical Summary

Problems solved by technology

[0004] Although there are many sources of typhoon peripheral wind field information, the typhoon core wind field information can only be obtained through low-altitude aircraft detection, such as WP-3D of the National Oceanic and Atmospheric Administration (NOAA), WC-130 of the US Air Force, etc.

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