• Geophysics and Geophysical Exploration
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• v.19 no.2
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• pp.67-75
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• 2016

To investigate spatial and temporal variations of low-frequency (${\leq}5Hz$) ambient seismic noise, we analyzed the noise data recorded for one whole year of 2014 at surface accelerometer stations in South Korea. After decomposed into low-frequency (LF; < 1 Hz) and high-frequency (HF; ${\geq}1Hz$) components, the root-mean-squared (RMS) amplitudes and power spectral densities (PSD) of the noise data were computed. The RMS amplitudes were larger on islands and near-shore stations, but also large RMS amplitudes were observed at inland stations in large cities only for HF components. The RMS amplitudes of HF components were larger in the daytime than at nighttime and during weekdays than on Sunday and holidays. This indicates the HF components are closely related to human activities. On the contrary, daily and weekly variations were not clear in the LF components while they showed seasonal variations with its maximum during the winter and a good correlation with significant wave height. Therefore, we interpret the mechanism of LF components is closely related to natural phenomena such as sea. The amplitude of LF components decreased as an exponential function of the distance to the center of typhoons. The exponential index of -0.76 suggested that ambient seismic noise included both surface and body waves. Peak frequencies of the PSD curves were near 0.34 Hz indicating the double frequency. No temporal variation in the peak frequency was clearly noticed.

• Journal of Environmental Science International
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• v.29 no.3
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• pp.257-272
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• 2020

This study investigates the temporal and spatial variations of marine meterological elements (air temperature (Temp), Sea Surface Temperature (SST), and Significant Wave Height (SWH)) in seven coastal waters of South Korea, using hourly data observed at marine meteorological buoys (10 sites), Automatic Weather System on lighthouse (lighthouse AWS) (9 sites), and AWS (20 sites) during 2013-2017. We also compared the characteristics of Temp, SST, and air-sea temperature difference (Temp-SST) between sea fog and non-sea-fog events. In general, annual mean values of Temp and SST in most of the coastal waters were highest (especially in the southern part of Jeju Island) in 2016, due to heat waves, and lowest (especially in the middle of the West Sea) in 2013 or 2014. The SWH did not vary significantly by year. Wind patterns varied according to coastal waters, but their yearly variations for each coastal water were similar. The maximum monthly/seasonal mean values of Temp and SST occurred in summer (especially in August), and the minimum values in winter (January for Temp and February for SST). Monthly/seasonal mean SWH was highest in winter (especially in December) and lowest in summer (June), while the monthly/seasonal variations in wind speed over most of the coastal waters (except for the southern part of Jeju Island) were similar to those of SWH. In addition, sea fog during spring and summer was likely to be in the form of advection fog, possibly because of the high Temp and low SST (especially clear SST cooling in the eastern part of South Sea in summer), while autumn sea fog varied between different coastal waters (either advection fog or steam fog). The SST (and Temp-SST) during sea fog events in all coastal waters was lower (and more variable) than during non-sea-fog events, and was up to -5.7℃ for SST (up to 5.8℃ for Temp-SST).

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.24 no.5
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• pp.305-318
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• 2012

Although the existing performance-based design method for the vertical breakwater evaluates an average sliding distance during an arbitrary time, it does not calculate the probability of the first occurrence of an event exceeding an allowable sliding distance(i.e. the first-passage probability). Designers need information about the probability that the structure is damaged for the first time for not only design but also maintenance and operation of the structure. Therefore, in this study, a time-dependent reliability design method based on a stochastic process is developed to evaluate the first-passage probability of caisson sliding. Caisson sliding can be formulated by the Poisson spike process because both occurrence time and intensity of severe waves causing caisson sliding are random processes. The occurrence rate of severe waves is expressed as a function of the distribution function of sliding distance and mean occurrence rate of severe waves. These values simulated by a performance-based design method are expressed as multivariate regression functions of design variables. As a result, because the distribution function of sliding distance and the mean occurrence rate of severe waves are expressed as functions of significant wave height, caisson width, and water depth, the first-passage probability of caisson sliding can be easily evaluated.

• Journal of the Korean Institute of Landscape Architecture
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• v.45 no.6
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• pp.115-125
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• 2017

This study was to investigate the user's thermal environments under the pergola($L\;7,200{\times}W\;4,200{\times}H\;2,700mn$) covered with Wisteria floribunda(Willd.) DC. according to the variation of leaf area index(LAI). We carried out detailed measurements with two human-biometeorological stations on a popular square Jinju, Korea($N35^{\circ}10^{\prime}59.8^{{\prime}{\prime}}$, $E\;128^{\circ}05^{\prime}32.0^{{\prime}{\prime}}$, elevation: 38m). One of the stations stood under a pergola, while the other in the sun. The measurement spots were instrumented with microclimate monitoring stations to continuously measure air temperature and relative humidity, wind speed, shortwave and longwave radiation from the six cardinal directions at the height of 0.6m so as to calculate the Universal Thermal Climate Index(UTCI) from $9^{th}$ April to $27^{th}$ September 2017. The LAI was measured using the LAI-2200C Plant Canopy Analyzer. The analysis results of 18 day's 1 minute term human-biometeorological data absorbed by a man in sitting position from 10am to 4pm showed the following. During the whole observation period, daily average air temperatures under the pergola were respectively $0.7{\sim}2.3^{\circ}C$ lower compared with those in the sun, daily average wind speed and relative humidity under the pergola were respectively 0.17~0.38m/s and 0.4~3.1% higher compared with those in the sun. There was significant relationship in LAI, Julian day number and were expressed in the equation $y=-0.0004x^2+0.1719x-11.765(R^2=0.9897)$. The average $T_{mrt}$ under the pergola were $11.9{\sim}25.4^{\circ}C$ lower and maximum ${\Delta}T_{mrt}$ under the pergola were $24.1{\sim}30.2^{\circ}C$ when compared with those in the sun. There was significant relationship in LAI, reduction ratio(%) of daily average $T_{mrt}$ compared with those in the sun and was expressed in the equation $y=0.0678{\ln}(x)+0.3036(R^2=0.9454)$. The average UTCI under the pergola were $4.1{\sim}8.3^{\circ}C$ lower and maximum ${\Delta}UTCI$ under the pergola were $7.8{\sim}10.2^{\circ}C$ when compared with those in the sun. There was significant relationship in LAI, reduction ratio(%) of daily average UTCI compared with those in the sun and were expressed in the equation $y=0.0322{\ln}(x)+0.1538(R^2=0.8946)$. The shading by the pergola covered with vines was very effective for reducing daytime UTCI absorbed by a man in sitting position at summer largely through a reduction in mean radiant temperature from sun protection, lowering thermal stress from very strong(UTCI >$38^{\circ}C$) and strong(UTCI >$32^{\circ}C$) down to strong(UTCI >$32^{\circ}C$) and moderate(UTCI >$26^{\circ}C$). Therefore the pergola covered with vines used for shading outdoor spaces is essential to mitigate heat stress and can create better human thermal comfort especially in cities during summer. But the thermal environments under the pergola covered with vines during the heat wave supposed to user "very strong heat stress(UTCI>$38^{\circ}C$)". Therefore users must restrain themselves from outdoor activities during the heat waves.