Analysis of hurricane activity and global warming based on time prediction model

Yilun Wu; Peichen Ye

doi:10.1117/12.2639888

17 May 2022 Analysis of hurricane activity and global warming based on time prediction model

Yilun Wu, Peichen Ye

Proceedings Volume 12259, 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2022); 122595C (2022) https://doi.org/10.1117/12.2639888
Event: 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing, 2022, Kunming, China

Abstract

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.

Citation Download Citation

Yilun Wu and Peichen Ye "Analysis of hurricane activity and global warming based on time prediction model", Proc. SPIE 12259, 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2022), 122595C (17 May 2022); https://doi.org/10.1117/12.2639888

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