Analysis of Hurricane Activity and Global Warming Based on Time Prediction Model

Yilun Wu, Peichen Ye

2ND INTERNATIONAL CONFERENCE ON APPLIED MATHEMATICS, MODELLING, AND INTELLIGENT COMPUTING (CAMMIC 2022)(2022)

引用 0|浏览0
暂无评分
摘要
This paper focuses on the research of hurricanes and global warming, and establishes a time series prediction model and an improved analytic hierarchy process model. The Pearson correlation analysis and entropy weight method were used to alleviate the warming problem and the intensity of hurricane activity. By exploring the extent of global warming,the improved AHP model based on entropy weight method is established, and the Mean-Kendall mutation test of the global mean temperature difference data is conducted to establish the Holt - Winters seasonless exponential smoothing model. After analyzing the intensity of the global hurricane activity, the trajectory of the hurricanes of the four oceans over the years, and get the distribution rules of the life cycle of each latitude and longitude. The horizontal distribution of storm helix, convective potential energy and wind speed in different regions is compared. The velocity field and vorticity of the eddy are basically in accordance with the Gauss model. It is concluded that the activity intensity of hurricanes is: when the vertical wind shear is strong, it helps to maintain and enhance the warm heart of the hurricane; the area with high latitudes is short; The small convective monomers increase the vertical vorticity of the Hurricane Center, which eventually leads to the intensities of the hurricane.
更多
查看译文
关键词
Entropy weight method, Improved correlation analysis, Mean-Kendall mutation test
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要