Dynamical Characteristics in Time Series Between PM10 and Wind Speed | Zendy

Deok Du Kang | Zendy; Dong In Lee | Zendy; Jaewon Jung | Zendy; Kyungsk Kim | Zendy

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Dynamical Characteristics in Time Series Between PM10 and Wind Speed

Author(s) -

Deok Du Kang,

Dong In Lee,

Jaewon Jung,

Kyungsk Kim

Publication year - 2021

Publication title -

international journal of mathematical models and methods in applied sciences

Language(s) - English

Resource type - Journals

ISSN - 1998-0140

DOI - 10.46300/9101.2021.15.5

Subject(s) - wind speed , series (stratigraphy) , statistics , time series , detrended fluctuation analysis , meteorology , correlation coefficient , correlation , mathematics , variation (astronomy) , environmental science , atmospheric sciences , climatology , geography , geology , physics , geometry , paleontology , scaling , astrophysics

We study the temporal variation characteristics of PM10 and wind velocity in eight South Korean cities. We employ the detrended cross-correlation analysis (DCCA) method to extract the overall tendency of the hourly variation. We ascertain from three-daily and one-weekly intervals that Busan has the negative largest, while Donghae has the positive largest in the DCCA cross-correlation coefficient between PM10 and wind velocity. As a result of Asian dust events, the cross-correlation is statistically significant for the hourly time series data less than two days. Particularly, we discuss whether a cross-correlation is statistically significant or not from random number surrogation and shuffled time series surrogation

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