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Spectral analysis of wind time series at a mountainous coastal region of the eastern Korean peninsula
Journal of the Korean Data & Information Science Society 2019;30:365-83
Published online March 31, 2019;  https://doi.org/10.7465/jkdi.2019.30.2.365
© 2019 Korean Data and Information Science Society.

Je-Won Kim1 · Song-Lak Kang2

12Atmospheric and Environmental Sciences, Gangneung-Wonju National University
Correspondence to: Professor, Department of Atmospheric and Environmental Sciences, Gangneung-Wonju National University, 7, Jukheon-gil, Gangneung-si, Gangwon-do, South Korea. Email: slkang@gwnu.ac.kr
This research was National Research Foundation of Korea (NRF) grant funded by the Korea government (MIST) (No.2018R1A2B6008631) and a research grant (A study mountainous coastal region of the eastern Korea peninsula) funded by the Gangwon regional office of meteorology.
Received December 12, 2018; Revised January 28, 2019; Accepted February 6, 2019.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
There have been multiple-year, 1-min time series measurements of surface meteorological variables at more than 600 surface stations in South Korea. As far as the authors know, there is few studies focusing on the spectral characteristics of wind speed time series. Being motivated by this absence, we perform a spectral analysis of 5-year, 1-min wind time series particularly collected at 13 surface stations within a mountainous coastal region of an area about 65 km by 35 km in the eastern Korean peninsula. Based on the composite spectra of the 5-year time series over the 13 stations, we found at least two interesting results. First, the wind spectrum shows significant aliasing, particularly in the frequency range higher than about a few tens of minutes, which seems to be caused by considerable turbulence energy. This indicates that the 1-min wind time series needs to be used as averaged values over a period of a few tens of minutes or longer. Second, the wind speed spectrum presents the most significant peak at the diurnal cycle, which is somewhat different from those of temperature and moisture in which the annual peak is the primary one.
Keywords : Aliasing, Fourier spectrum, mountainous coastal region, surface observation, wind time series.