Based on wavelet analysis of the direct economic loss of the typhoon storm surge in China cycle analysis and prediction

Liu Xu; Dong Jianxi; Jiang Shan; Zhao Dajun; Fu Xiang; Wang Zheng; Liang Yingqi

doi:10.12284/hyxb2023109

Volume 45 Issue 7

Jul. 2023

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Article Navigation > Haiyang Xuebao > 2023 > 45(7): 137-146

Liu Xu，Dong Jianxi，Jiang Shan, et al. Based on wavelet analysis of the direct economic loss of the typhoon storm surge in China cycle analysis and prediction[J]. Haiyang Xuebao，2023, 45(7)：137–146 doi: 10.12284/hyxb2023109

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Based on wavelet analysis of the direct economic loss of the typhoon storm surge in China cycle analysis and prediction

doi: 10.12284/hyxb2023109

1.
National Marine Environmental Forecasting Center, Beijing 100081, China
2.
School of Economics & Management, Beijing Forestry University, Beijing 100083, China
3.
College of Economics and Management, Xinjiang Agricultural University, Urumqi 830052, China

Received Date: 2022-08-31
Rev Recd Date: 2023-01-02

Available Online: 2023-08-08

Publish Date: 2023-07-01

Abstract

Abstract

Based on the statistical data of direct economic losses of typhoon storm surge in China from 1989 to 2021, the economic losses of storm surge disasters in China during 32 years showed a significant downward trend, showing a thick-tailed distribution as a whole, and a normal distribution after logarithmic processing. The periodic changes of the direct economic losses of typhoon storm surge in China were analyzed by Morlet wavelet analysis method. According to the t-test, there were two quasi-high-frequency oscillations in the whole region, 1−2 years and 7−8 years oscillation , but the annual cycle gradually shortened to 3−5 years with the change of time. It indicated that the economic loss sequence of storm surge had high-frequency oscillation and multi-period nested low-frequency oscillation. On this basis, Daubechies wavelet decomposition was used to separate high frequency signal and low frequency signal. According to the results of root mean square error (RMSE) and signal-to-noise ratio, Daubechies wavelet base was set the vanishing moment is 7 and the number of decomposition layers is 2 for the direct economic loss time series of typhoon storm surges in China from 1989 to 2021, which had the optimal decomposition and reconstruction effect. Based on the results of stationarity test and white noise test of wavelet coefficients of each decomposition layer, the combined wavelet decomposed−ARMA model was established. The simulation accuracy and prediction accuracy were both better than that of single Autoregressive Integrated Moving Average model and Fourier series expansion model, which verified the reliability and superiority of wavelet decomposition method for rapid assessment of economic loss of typhoon storm surge in China.

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