• Journal of Environmental Science International
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• v.19 no.11
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• pp.1423-1436
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• 2010

The effects of meteorological and reclaiming conditions on the reduction of suspended particles are investigated using a computational fluid dynamics (CFD) model with the k-$\varepsilon$ turbulence closure scheme based on the renormalization group (RNG) theory. Twelve numerical experiments with different meteorological and reclaiming conditions are performed. For identifying the meteorological characteristics of the target area and providing the inflow conditions of the CFD model, the observed data from the automatic weather station (AWS) near the target area is analyzed. Complicated flow patterns such as flow distortion, horse-shoe vortex, recirculation zone, and channeling flow appeared due to the topography and buildings in the domain. Specially, the flow characteristics around the reclamation area are affected by the reclaiming height, reclaiming size and windbreak height. Reclaiming height affected the wind speed above the reclaiming area. Windbreak induces more complicated flow patterns around the reclaiming area as well as within the reclaiming area. In front of the windbreak, flow is distorted as it impinges on the windbreak. As a result, upward flow is generated there. Behind the windbreak, a secondary circulation, so called, a recirculation zone is generated and flow is reattached at the end of the recirculation zone (reattachment point). At the lower part of the recirculation zone, there is a reverse flow toward the windbreak. Flow passing to the reattachment point starts to be recovered. Total amounts of suspended particles are calculated using the frictional and threshold frictional velocities, erosion potential function, and the number of surface disturbance. In the case of a 10 m-reclaiming and northerly wind, the amount of suspended particles is largest. In the presence of 5 m windbreak, the friction velocity above the reclaiming area is largely reduced. As a result, the total amount of the suspended particles largely decreases, compared to the case with the same reclaiming and meteorological conditions except for the windbreak The calculated suspended particle amounts are used as the emission rate of the dispersion model simulations and the dispersion characteristics of the suspended particles are analyzed.

• Journal of Korean Society of Transportation
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• v.27 no.6
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• pp.139-146
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• 2009

While air pollutants emission caused by the traffic is one of the major sources, few researches have done. This study investigated the extent to which traffic and road related characteristics such as traffic volumes, speeds and road weather data including wind speed, temperature and humidity, as well as the road geometry affect the air pollutant emission. We collected the real time air pollutant emission data from Seoul automatic stations and real time traffic volume counts as well as the road geometry. The regression air pollutant emission models were estimated. The results show followings. First, the more traffic volume increase, the more pollutant emission increase. The more vehicle speed increase, the more measurement quantity of pollutant decrease. Secondly, as the wind speed, temperature, and humidity increase, the amount of air pollutant is likely to decrease. Thirdly, the figure of intersections affects air pollutant emission. To verify the estimated models, we compared the estimates of the air pollutant emission with the real emission data. The result show the estimated results of Chunggae 4 station has the most reliable data compared with the others. This study is differentiated in the way the model used the real time air pollutant emission data and real time traffic data as well as the road geometry to explain the effects of the traffic and road characteristics on air quality.

• The Journal of Engineering Geology
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• v.26 no.2
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• pp.197-205
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• 2016

Rainfall-induced landslide disaster case histories are typically required to establish critical lines based on the decrease coefficient for judging the likelihood of slope collapse or failure; however, reliably setting critical lines is difficult because the number of nationwide disaster case histories is insufficient and not well distributed across the region. In this study, we propose a method for setting the critical area to judge the risk of slope collapse without disaster case history information. Past 10 years rainfall data based on decrease coefficient are plotted as points, and a reference line is established by connecting the outermost points. When realtime working rainfall cross the reference line, warning system is operating and this system can be utilized nationwide through setting of reference line for each AWS (Automatic Weather Station). Warnings were effectively predicted at 10 of the sites, and warnings could have been issued 30 min prior to the landslide movement at eight of the sites. These results indicate a reliability of about 67%. To more fully utilize this model, it is necessary to establish nationwide rainfall databases and conduct further studies to develop regional critical areas for landslide disaster prevention.

• Journal of Korea Water Resources Association
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• v.31 no.5
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• pp.621-635
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• 1998

The feasibility of cloud seeding in Korea is presented from analyses of precipitation, cloud amount, satellite data, and upper air data. The daily mean precipitation over Dae-Kwan-Ryong is the largest(~4.5 mm/day), while the intensity of precipitation (amount of yearly rainfall divided by the frequency of rain days) over Southern area is above 14 mm/day, which shows the largest in Korea. Both the daily mean and the intensity of precipitation over Andong area are the smallest with values of ~2.7 mm/day and ~11 mm/day, respectively. In the meanwhile, the occurrence frequency of appropriate cloud top temperature (-10'~-30') for cloud seeding over the region has a large value (~130 days/year). The precipitation patterns of the region vary with wind direction and intensity calculated from 43 AWSs(Automatic Weather Station) and the additional 7 rain guages which were installed along Northern and Southern part of the Sobaek mountain. The Sc(Stratocumulus) cloud type over Andong is frequently observed, and Cirrus and Altostratus next. From the results, it is estimated that the feasibility of cloud seeding over the area would be high if a proper strategy of cloud seeding is set up. LCL (Lifting Condensation Level) and CCL (Convective Condensation Level) have the most frequency in 1000-950 hPa being occupied 4/9 of total analysis period and in 400-500 hPa, respectively, with both small variations from season to season. The correlation between vapor mixing ratio and CCL is the highest in Summer and the lowest in Winter. It means that the height of cumulus in Summer is high with an abundant water vapor but vice versa in Winter, and that the strategy of cloud seeding should be different with seasons.

• Journal of the Korean earth science society
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• v.24 no.4
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• pp.303-314
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• 2003

Ocean-air observation using an Automatic Weather Station (AWS) and Conductivity Temperature Depth (CTD) was conducted in the Mid-Yellow Sea off Korea during 8-10 July 2002. A water mass lower than 17$^{\circ}C$ around the Taean peninsula and a tidal front between 36$^{\circ}$20'N and 36$^{\circ}$30'N were observed. The horizontal distribution of air temperature was similar to that of sea surface temperature (SST). Hourly observation around Dukjuk island showed the cold and saline southwesterly and the warm and fresh northeasterly in phase with tidal current. Sea fogs two times formed at 2300 LST 8-0130 LST 9, and 0300-0600 LST 9 July 2002 during the observation period, respectively. During the initial stage of fogs, winds became northeasterly at the speed of 2-4m/s$^{-1}$, and air temperature dropped to 18$^{\circ}C$, as the North Pacific High weakened. The satellite image indicated that sea fogs formed over warm water in the western Yellow Sea and moved eastward toward the observation site, which could be called a steam fog. The fogs dissipated when wind speed and air temperature increased.

• Korean Journal of Remote Sensing
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• v.17 no.1
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• pp.15-31
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• 2001

The relationship between GMS-5 IR1 brightness temperature (CTT:cloud top temperature) and AWS (automatic weather station) rainfall is investigated on a heavy rain event over the mid-western part of Korea for August 5-6, 1998. It is found that a temporal variability of the heavy rain can be described in detail y the time series of rain area and rain rates over the study area that are calculated from AWS accumulated rainfalls for 15 minutes. A time period of 0030-0430 LST 6 August 1998 is chosen in the time series as a heavy rain period which has relatively small rain area (20~25%) and very strong rain rates(6~9 mm/15 min.) with a good time continuity. In the heavy rain period, CTT of a point and AWS 15-minute rainfall beneath that point are compared. From the comparison, AWS rainfalls are shown to be not closely correlated with CTT. In the range of CTT lower than -5$0^{\circ}C$ where most AWS with rain are distributed, the probability of rain is at most about 30%. However, when the satellite images are shifted by 2~3 pixels southward and 3 pixels westward for the geometric correction of images, AWS rainfalls are shown to be statistically correlated with CTT (correlation coefficient:-0.46). Most AWS with rain are distributed in the much lower CTT range(lower than -58$^{\circ}C$), but there is still not much change in the rain probability. Even though a temporal change of CTT is taken into account, the rain probability amount to at most 50~55% in the same range.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.6
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• pp.701-707
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• 2021

In this study, we examined the sea surface temperature (SST), air temperature (AT), and their time lag in response to an extreme cold wave in 2018 and a weak cold wave in 2019, cross-correlating these to the northern wind direction frequency. The data used in this study include SST observations of seven ocean buoys Real-time Information System for Aquaculture Environment provided by the National Institute of Fisheries Science and automatic weather station AT near them recorded every hour; null data was interpolated. A finite impulse response filter was used to identify the appropriate data period. In the extreme cold wave in 2018, the seven locations indicated low SST caused by moving cold air through the northern wind direction. A warm cold wave in 2019, the locations showed that the AT data was similar to the normal AT data, but the SST data did not change notably. During the extreme cold wave of 2018, data showed a high correlation coefficient of about 0.7 and a time lag of about 14 hours between AT and SST; during the weak cold wave of 2019, the correlation coefficient was 0.44-0.67 and time lag about 20 hours between AT and SST. This research will contribute to rapid response to such climate phenomena while minimizing aquaculture damage.

• Journal of the Korean earth science society
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• v.39 no.6
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• pp.533-544
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• 2018

Rainfall is one of the most important meteorological variables in meteorology, agriculture, hydrology, natural disaster, construction, and architecture. Recently, satellite remote sensing is essential to the accurate detection, estimation, and prediction of rainfall. In this study, the accuracy of Integrated Multi-satellite Retrievals for GPM (IMERG) product, a composite rainfall information based on Global Precipitation Measurement (GPM) satellite was evaluated with ground observation data in the inland of Korea. The Automatic Weather Station (AWS)-based rainfall measurement data were used for validation. The IMERG and AWS rainfall data were collocated and compared during one year from January 1, 2016 to December 31, 2016. The coastal regions and islands were also evaluated irrespective of the well-known uncertainty of satellite-based rainfall data. Consequently, the IMERG data showed a high correlation (0.95) and low error statistics of Bias (15.08 mm/mon) and RMSE (30.32 mm/mon) in comparison to AWS observations. In coastal regions and islands, the IMERG data have a high correlation more than 0.7 as well as inland regions, and the reliability of IMERG data was verified as rainfall data.

• Journal of Environmental Impact Assessment
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• v.33 no.1
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• pp.9-17
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• 2024

The purpose of this study is to select and predict optimal heatwave indices for describing and predicting heat-related illnesses. Regression analysis was conducted using Heat-related illness surveillance system data for a number of heat-related illnesses and meteorological data from the Korea Meteorological Administration's Automatic Weather Station (AWS) for the period from 2021 to 2023. Daily average temperature, daily maximum temperature, daily average Wet Bulb Globe Temperature (WBGT), and daily maximum WBGT values were calculated and analyzed. The results indicated that among the four indicators, the daily maximum WBGT showed the highest suitability with an R² value of 0.81 and RMSE of 0.98, with a threshold of 29.94 Celsius. During the entire analysis period, there were a total of 91 days exceeding this threshold, resulting in 339 cases of heat-related illnesses. Predictions of heat-related illness cases from 2021 to 2023 using the regression equation for daily maximum WBGT showed an accuracy with less than 10 cases of error annually, demonstrating a high level of precision. Through continuous research and refinement of data and analysis methods, it is anticipated that this approach could contribute to predicting and mitigating the impact of heatwaves.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.3
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• pp.132-146
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• 2014

The effects of the cold air generated from large cold water mass at the coastal area on observed air temperature in Busan were investigated using AWS(Automatic Weather Station) data at the Busan area operated by Korea Meterological Administration and SST(Sea Surface Temperature) data at the Gijang and Busan area operated by Korean National Fisheries Research Development Institute. First, the temperature difference between the coastal area and the city area was about $1^{\circ}C$ during cold water mass day while it was about $0.5^{\circ}C$ if cold water mass was not appeared. Second, for day time, the temperature at the coastal area was about $1^{\circ}C$ lower than that at the city area during cold water mass day, but the difference was only about $0.4^{\circ}C$ without cold water mass. On the other hand, for night time, the temperature at the coastal area was about $1.2^{\circ}C$ lower than that at the city area during cold water mass day and the difference was about $0.9^{\circ}C$ without cold water mass. As a result, temperature differences at night time were higher than those at day time whether or not cold water mass appeared. The reason for higher temperature at night time might be the urban heat island phenomenon.