• Journal of Environmental Science International
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• v.25 no.6
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• pp.853-864
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• 2016

Meteo-tsunamis are tsunamis that are typically caused by strong atmospheric instability (e.g., pressure jumps) in low pressure systems, but some meteo-tsunamis in winter can be caused by local atmospheric instability in high pressure systems (e.g., the Siberian High). In this study, we investigated a meteo-tsunami event related to a high pressure system that occurred during winter on the Yellow Sea in 2005. Sea level data from tidal stations were analyed with a high-pass filter, and we also performed synoptic weather analyses by using various synoptic weather data (e.g., surface weather charts) collected during the winter season(DJF) of 2005. A numerical weather model (WRF) was used to analyze the atmospheric instability on the day of the selected event (21 Dec. 2005). On the basis of the results, we suggest that the meteo-tsunami triggered by the high pressure system occurred because of dynamic atmospheric instability induced by the expansion and contraction of the Siberian High.

• Journal of Environmental Science International
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• v.18 no.2
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• pp.129-139
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• 2009

Development of an artificial neural network model was presented to predict the daily maximum $SO_2$ concentration in the urban-industrial area of Ulsan. The network model was trained during April through September for 2000-2005 using $SO_2$ potential parameters estimated from meteorological and air quality data which are closely related to daily maximum $SO_2$ concentrations. Meteorological data were obtained from regional modeling results, upper air soundings and surface field measurements and were then used to create the $SO_2$ potential parameters such as synoptic conditions, mixing heights, atmospheric stabilities, and surface conditions. In particular, two-stage clustering techniques were used to identify potential index representing major synoptic conditions associated with high $SO_2$ concentration. Two neural network models were developed and tested in different conditions for prediction: the first model was set up to predict daily maximum $SO_2$ at 5 PM on the previous day, and the second was 10 AM for a given forecast day using an additional potential factors related with urban emissions in the early morning. The results showed that the developed models can predict the daily maximum $SO_2$ concentrations with good simulation accuracy of 87% and 96% for the first and second model. respectively, but the limitation of predictive capability was found at a higher or lower concentrations. The increased accuracy for the second model demonstrates that improvements can be made by utilizing more recent air quality data for initialization of the model.

• Journal of Environmental Science International
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• v.5 no.2
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• pp.131-140
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• 1996

Analysis of hourly variations of sulfur dioxide ($SO_2$) concentrations affected by regional climates for the period of yellow sandy dusts was carried out from March 31 through April 9, 1993. The concentration of 50, at a coastal city, Kangnung city, was much higher than that at an inland city Wonju in the west, but the hourly distrbutions of $SO_2$ concentrations show a similar tendency at both cities. Under the prevailing synoptic-scale westerly winds blowing over a high Mt. Taegualyang in the west toward Kangnung city in the eastern coastal region, the $SO_2$ at Kangnung is trapped by an easterly sea-breeze during the day and under prevailing easterly winds, it is also isolated by the high wall of Mt. Taegualyang, with its high concentration from 14 to 16 LST. Furthermore, when the westerly winds were dominent all day long the high $SO_2$ concentrations at Kangnung were produced by its intrusion from a urban city, Wonju or China in the west into a mountainous coastal city, Kangnung, to some extent, and when the air becomes rapidly cooled down at the clear daytime or the nighttime, their concentrations are also increased by a great amount of heating fuel combustion. Especilly, its maximum concentrations were shown in Wonju and Kangnung from 08 LST through 10 LST, due to the increase of auto vehicles near the beginning time of office hour and were detected again after sunset due to both increases of vehicles at the end of office hour and heating fuel combustion. During the period of Yellow Sandy Dusts which are transported from China into Korea, the $SO_2$ concentrations on rainy days at Wonju and Kangnung were much lower than the monthly mean values of $SO_2$, and their low concentrations could be caused by the scavenging process of rain.

• Atmosphere
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• v.31 no.4
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• pp.421-431
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• 2021

The Yeongdong region is frequently vulnerable to heavy snowfall in winter in terms of societal and economical damages. By virtue of a lot of previous efforts, snowfall forecast has been significantly improved, but the performance of light snowfall forecast is still poor since it is very conducive to synoptic and mesoscale interactions, largely attributable to Taeback mountains and East Sea effects. An intensive observation has been made in cooperation with Gangwon Regional Meteorological Office and National Institute of Meteorological Studies in winter seasons since 2019. Two distinctive Cold Air Damming (CAD) events (14 February 2019 and 6 February 2020) were observed for two years when the snowfall forecast was wrong specifically in its location and timing. For two CAD events, lower-level temperature below 2 km ranged to lowest limit in comparisons to those of the previous 6-years (2014~2019) rawinsonde soundings, along with the stronger inversion strength (> 2.0℃) and thicker inversion depth (> 700 m). Further, the northwesterly was predominant within the CAD layer, whereas the weak easterly wind was exhibited above the CAD layer. For the CAD events, strong cold air accumulation along the east side of Taeback Mountains appeared to prevent snow cloud and convergence zone from penetrating into the Yeongdong region. We need to investigate the influence of CAD on snowfall in the Yeongdong region using continuous intensive observation and modeling studies altogether. In addition, the effect of synoptic and mesoscale interactions on snowfall, such as nighttime drainage wind and land breeze, should be also examined.

• Journal of Astronomy and Space Sciences
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• v.27 no.2
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• pp.75-80
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• 2010

Several survey observations have produced light curves of more than five thousand eclipsing binaries for last 15 years. Future missions such as the Large Synoptic Survey Telescope (LSST), the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS) and Gaia are expected to yield hundreds thousands of new variable stars and eclipsing binaries. Current methods require a week to analyze the light curves of an eclipsing binary for its physical and orbital parameters. The current methods of analyzing the light curves will be inadequate to treat the overwhelming influx of new data. Therefore we developed a new method to treat large numbers of light curves of eclipsing binaries. We tested the new method by analyzing more than one hundred light curves of the detached and semi-detached eclipsing binaries discovered in the Small Magellan Cloud and present their fitted light curves with observations.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.25 no.1
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• pp.1-10
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• 2017

A heavy foggy event accompanying with complex coastal fog was investigated in this study. This heavy foggy event occurred on FEB 11, 2015. Due to reduced visibility with this foggy event induced more than 100times serial traffic accidents over the Young-jong highway, and Flights from 04:30 AM to 10:00 AM were cancelled on Inchon International Airport. This heavy foggy event was occurred in synoptic and mesoscale environments but dense coastal fog were combined with a combination of sea fog, steam fog, and radiation fog. This kind of coastal fog can predicted by accurate analysis of the direction of the air flow, sea surface temperature(SST), and 925hPa isotherms from numerical weather prediction charts and real time analysis charts.

• Journal of the Korean Data and Information Science Society
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• v.17 no.1
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• pp.131-139
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• 2006

Statistical analyses for spatial data are important features for various types of fields. Spatial data are taken at specific locations or within specific regions and their relative positions are recorded. Lattice data are synoptic observation covering an entire spatial region, like cancer rates corresponding to each county in a state. The main purpose of this paper is to detect hotspots for the region with significantly high or low rates. Kulldorff(1997) detected hotspots based on circular spatial scan statistics. We propose a new method to find any shapes of hotspots by use of echelon analysis with spatial scan statistics.

• Journal of the Korean Solar Energy Society
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• v.32 no.5
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• pp.94-101
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• 2012

A Dokdo wind resource map has been drawn up for the Green Island Energy Master Plan according to Korea's national vision for 'Low Carbon Green Growth'. The micro-siting software WindSim v5.1,which is based on Computational Flow Analysis, is used with MERRA reanalysis data as synoptic climatology input data, and sensitivity analysis on turbulence model is accompanied. A wind resource assessment has been conducted for the Dokdo wind power dissemination plan, which consists of two 10kW wind turbines to be installed at the Dongdo dock and Dokdo guard building. It is evaluated that the capacity factors at Dongdo dock and Dokdo guard building are about 20% and 30% respectively, and annual and hourly variations of wind power generation have been analyzed, but summertime energy production is predicted to be only 40% of wintertime energy production.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.4
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• pp.199-205
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• 2001

This study was conducted to figure out temperature profiles of a partially developed paddy rice canopy, which are necessary to run plant disease forecasting models. Air temperature over and within the developing rice canopy was monitored from one month after transplanting (June 29) to just before heading (August 24) in 1999 and 2001. During the study period, the temporal march of the within-canopy profile was analyzed and an empirical formula was developed for simulating the profile. A partially developed rice canopy temperature seemed to be controlled mainly by the ambient temperature above the canopy and the water temperature beneath the canopy, and to some extent by the solar altitude, resulting in alternating isothermal and inversion structures. On sunny days, air temperature at the height of maximum leafages was increased at the same rate as the ambient temperature above the canopy after sunrise. Below the height, the temperature increase was delayed until the solar noon. Air temperature near the water surface varied much less than those of the outer- and the upper-canopy, which kept increasing by the time of daily maximum temperature observed at the nearby synoptic station. After sunset, cooling rate is much less at the lower canopy, resulting in an isothermal profile at around the midnight. A fairly consistent drop in temperature at rice paddies compared with the nearby synoptic weather stations across geographic areas and time of day was found. According to this result, a cooling by 0.6 to 1.2$^{\circ}C$ is expected over paddy rice fields compared with the officially reported temperature during the summer months. An empirical equation for simulating the temperature profile was formulated from the field observations. Given the temperature estimates at 150 cm above the canopy and the maximum deviation at the lowest layer, air temperature at any height within the canopy can be predicted by this equation. As an application, temperature surfaces at several heights within rice fields were produced over the southwestern plains in Korea at a 1 km by 1km grid spacing, where rice paddies were identified by a satellite image analysis. The outer canopy temperature was prepared by a lapse rate corrected spatial interpolation of the synoptic temperature observations combined with the hourly cooling rate over the rice paddies.

• Journal of Environmental Science International
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• v.24 no.1
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• pp.81-96
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• 2015

The characteristics of atmospheric dispersion of radioactive material (i.e. $^{137}Cs$) related to local wind patterns around the Kori nuclear power plant (KNPP) were studied using WRF/HYSPLIT model. The cluster analysis using observed winds from 28 weather stations during a year (2012) was performed in order to obtain representative local wind patterns. The cluster analysis identified eight local wind patterns (P1, P2, P3, P4-1, P4-2, P4-3, P4-4, P4-5) over the KNPP region. P1, P2 and P3 accounted for 14.5%, 27.0% and 14.5%, respectively. Both P1 and P2 are related to westerly/northwesterly synoptic flows in winter and P3 includes the Changma or typhoons days. The simulations of P1, P2 and P3 with high wind velocities and constant wind directions show that $^{137}Cs$ emitted from the KNPP during 0900~1400 LST (Local Standard Time) are dispersed to the east sea, southeast sea and southwestern inland, respectively. On the other hands, 5 sub-category of P4 have various local wind distributions under weak synoptic forcing and accounted for less than 10% of all. While the simulated $^{137}Cs$ for P4-2 is dispersed to southwest inland due to northeasterly flows, $^{137}Cs$ dispersed northward for the other patterns. The simulated average 137Cs concentrations of each local wind pattern are $564.1{\sim}1076.3Bqm^{-3}$. The highest average concentration appeared P4-4 due to dispersion in a narrow zone and weak wind environment. On the other hands, the lowest average concentration appeared P1 and P2 due to rapid dispersion to the sea. The simulated $^{137}Cs$ concentrations and dispersion locations of each local wind pattern are different according to the local wind conditions.