• Journal of Ocean Engineering and Technology
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• v.38 no.2
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• pp.64-73
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• 2024

Oil spills pose significant threats to marine ecosystems, human health, socioeconomic aspects, and coastal communities. Accurate real-time predictions of oil slick transport along coastlines are paramount for quick preparedness and response efforts. This study used an open-source OpenOil numerical model to simulate the fate and trajectories of oil slicks released during the 2007 Hebei Spirit accident along the Korean coasts. Six combinations of input parameters, derived from a five-day met-ocean dataset incorporating various hydrodynamic, meteorological, and wave models, were investigated to determine the input variables that lead to the most reasonable results. The predictive performance of each combination was evaluated quantitatively by comparing the dimensions and matching rates between the simulated and observed oil slicks extracted from synthetic aperture radar (SAR) data on the ocean surface. The results show that the combination incorporating the Hybrid Coordinate Ocean Model (HYCOM) for hydrodynamic parameters exhibited more substantial agreement with the observed spill areas than Copernicus Marine Environment Monitoring Service (CMEMS), yielding up to 88% and 53% similarity, respectively, during a more than four-day oil transportation near Taean coasts. This study underscores the importance of integrating high-resolution met-ocean models into oil spill modeling efforts to enhance the predictive accuracy regarding oil spill dynamics and weathering processes.

• Atmosphere
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• v.34 no.2
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• pp.187-202
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• 2024

We analyzed the observed characteristics of monoterpene and developed an empirical formula for monoterpene concentration in the pine-dominated mixed forest of the National Center for Forest Therapy. Monoterpene was measured at 0800, 1200 and 1700 LST once a month using sorbent tube sampling coupled with thermal desorption gas chromatography and mass spectrometry. Monoterpene concentration is low in winter and shows a maximum in June and July. The major components of monoterpene are alpha-pinene, camphene and beta-pinene. During the warm period from May to November, monoterpene concentration is higher at 0800 and 1700 LST than at 1200 LST. The empirical formula takes into account the vegetation variables, temperature-controlled emission, oxidation processes and dilution by wind. The vegetation variable accounts for the difference in observed monoterpene concentration between two sites. The observed monoterpene concentration normalized by the vegetation variable increases exponentially with air temperature. The oxidation process explains the lower monoterpene concentration at 1200 LST than at 0800 and 1700 LST during the warm period. The monoterpene estimates using the empirical formula shows a correlation of 0.52 with the observation for the development period (2018~2020), while it shows a correlation of 0.72 for the validation year (2021). Such higher correlation for the validation year than for the development period is due to the fact that variability of monoterpene concentration is better explained by air temperature in 2021 than in the development period. However, the developed formula underestimates the monoterpene concentration in May and June, showing the limitation in accurately capturing the monthly variation of monoterpene.

• Journal of the Korean earth science society
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• v.22 no.3
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• pp.223-236
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• 2001

The concentration of gaseous mercury (Hg) was measured at hourly intervals along with relevant environmental parameters from two monitoring stations (Hannam and Kwachun) in Seoul metropolitan city during September 1999 to July 2000. Irrespective of the environmental and areal differences in the two locations, the concentrations of observed Hg levels were remarkably compatible each other. The results showed that the mean Hg level in Hannam was measured to be 5.34${\pm}$3.92 ngm$^{-3}$ (N = 2576), while that of Kwachun was 5.25${\pm}$2.53 ngm$^{-3}$ (N = 1992). Using these measurement data, we inspected Hg distribution and behavior at various time scale. When the data were analyzed at 24 hr scale, the distribution patterns for the two areas were distinguished by enrichment in either night(Hannam) or day (Kwachun). The patterns for seasonal distributions were also opposing each other such as the occurrences of peak during winter (Hannam) or summer (Kwachun). In order to analyze the factors affecting Hg distributions between two sites over different time scale, we conducted both correlation and factor analysis on both all data sets and on seasonally divided data groups. Whereas Hg exhibits strong correlations with such parameters as PM (particulate matter), SO$_2$, and NO$_2$, its relationship with meteorological parameters was not significant enough in many cases. The results of factor analysis also indicated that the Hg levels are tightly associated with most pollutants, explaining the largest portions of statistical variance. According to our study, we conclude that patterns of Hg distributions can exhibit variable patterns depending on local source processes which we expect to be diverse among different areas.

• Journal of the Korean earth science society
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• v.22 no.6
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• pp.480-490
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• 2001

The soil-air exchange processes of Hg were investigated from the Hari area of Kang Hwa Island during the late March 2001. In the course of our study, we determined the concentration gradients of Hg and combined these gradient data with micrometeorological components to derive its fluxes. Results of our study indicate that the concentration levels of Hg in the study area are notably lower than those typically found in urbanized areas of Korea. However, the computed fluxes were seen to be significantly larger for relatively remote areas, reaching over 200 ng/m$^2$/hr. Comparison of environmental conditions shows that the concentrations of most pollutant species including NO$_X$ and PM were significantly higher during emission, while meteorological conditions were characterized by high temperature and low humidity. Results of correlation analysis also indicate that such pollutants as hydrocarbons, nitrogen oxides, and PM generally exhibit strong positive correlations with Hg-related parameters during emission events, while such relationships were reversed during dry deposition events. The results of our present study suggest the possibility that the concentrations and fluxes of total gaseous Hg observed during deposition events can be influenced by the processes that are also important for the fine, rather than coarse, size fraction of particles.

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.2
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• pp.88-99
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• 2007

Soil moisture is one of the essential components in determining surface hydrological processes such as infiltration, surface runoff as well as meteorological, ecological and water quality responses at watershed scale. This paper discusses soil moisture transfer processes measured at hillslope scale in the Gwangneung forest catchment to understand and provide the basis of stochastic structures of soil moisture variation. Measured soil moisture series were modelled based upon the developed univariate model platform. The modeling consists of a series of procedures: pre-treatment of data, model structure investigation, selection of candidate models, parameter estimation and diagnostic checking. The spatial distribution of model is associated with topographic characteristics of the hillslope. The upslope area computed by the multiple flow direction algorithm and the local slope are found to be effective parameters to explain the distribution of the model structure. This study enables us to identify the key factors affecting the soil moisture distribution and to ultimately construct a realistic soil moisture map in a complex landscape such as the Gwangneung Supersite.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.268-279
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• 2021

The geospatial schemes based on topo-climatology have been developed to produce digital climate maps at a site-specific scale. Their development processes are reviewed here to derive the needs for new schemes in the future. Agricultural and forestry villages in Korea are characterized by complexity and diversity in topography, which results in considerably large spatial variations in weather and climate over a small area. Hence, the data collected at a mesoscale through the Automated Synoptic Observing System (ASOS) operated by the Korea Meteorological Administration (KMA) are of limited use. The geospatial schemes have been developed to estimate climate conditions at a local scale, e.g., 30 m, lowering the barriers to deal with the processes associated with production in agricultural and forestry industries. Rapid enhancement of computing technologies allows for near real-time production of climate information at a high-resolution even in small catchment areas and the application to future climate change scenarios. Recent establishment of the early warning service for agricultural weather disasters can provide growth progress and disaster forecasts for cultivated crops on a farm basis. The early warning system is being expanded worldwide, requiring further advancement in geospatial schemes and digital climate mapping.

• Korean Journal of Soil Science and Fertilizer
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• v.25 no.3
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• pp.220-230
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• 1992

Soil temperature is one of the important environmental factors which control all the physical, chemical and biological processes in soil including germination and root growth of plants and other organisms living in the soil ecosystem. Soil water and nutrient availability and mobility are temperature dependent. Soil temperature change is depended primarily upon energy exchange in soil surface, meteorological variance and physical properties of the soils which are closely related to heat transfer mechanism. In this study physical properties including bulk density, soil texture and organic matter content were measured and thermal diffusivity on the soils was calculated. Soil samples from the 66 meteorological stations under the Korea Meteorology were collected and the physical parameters were measured. To obtain relationship between thermal diffusivity and soil water content a heat probe thermal diffusivity measurement apparatus was designed and used in this experiment. According to the survey on soil physicsal properties on the 66 meteorological stations, the 52% of the surface soil texture were sandy loam and laomy sand or sand, 38% were loam and silty loam, and 10% were clay loam and silty clay loam. The bulk density which was closely related with thermal properties showed average of $1.41g/cm^3$ for sandy soils, $1.33g/cm^3$ for loam and silty loam soils, and $1.21g/cm^3$ for clay loam and silty clay loam soils. The apparent thermal diffusivity of the upper layer from 0 to 30cm ranged from 1.16 to $8.40{\times}10^{-3}cm^3/sec$ with average of $3.53{\times}10^{-3}cm^3/sec$. The apparent thermal diffusivities of the Jeju soils of which organic matter contents were high and the bulk densities were low were near $2{\times}10^{-3}cm^3/sec$. The thermal diffusivity of snow measured in Chuncheon ranged from 0.822 to $2.237{\times}10^{-3}cm^3/sec$. The damping depth calculated from the thermal diffusivity ranged from 5.92 to 13.65cm for daily basis and 124 to 342cm for yearly basis. The significant regression equation to estimate thermal diffusivity with bulk density and soil water content was obtained by the heat probe in laboratory.

• Journal of Climate Change Research
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• v.2 no.4
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• pp.297-307
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• 2011

This study investigates relation of food safety incidents with climate. Therefore food safety incidents and climate data during 1999 to 2009 have been analyzed. In situ observations of monthly mean temperature, maximum temperature, minimum temperature, precipitation, and relative humidity in 60 observation stations of Korean Meteorological Administration (KMA) have been used in this study. Food safety incidents data have been constructed by searching media reports following Park's method (2009) during the same period. According to the Park's method, 729 events were collected. To analyze its relations, food safety incidents data have been classified into chemical, biological, and physical hazards. Pearson product-moment correlation coefficients have been applied to analyze the relations. The correlation of food safety incidents has negative one with precipitation (-0.48), and positive one with minimum temperature(0.45). Precipitation has been correlated with biological and physical hazards more than chemical hazard. Temperatures (mean temperature, maximum temperature, and minimum temperature) have been correlated closely with chemical hazard than others. Food safety incidents data has been interblended with human behavior factor through decision-making processes in food manufacturing, processing, and consumption phases of "farm-totable" food processing. Act in the preventing damage will be obvious if the hazard were apparent. Therefore abnormal condition could be more dangerous than that of apparent extreme events because apparent events or extreme events become one of alarm over hazards. Therefore, human behavior should be considered as one of the important factors for analysis of food safety incidents. The result of this study can be used as a better case study for food safety researches related to climate change.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.1
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• pp.29-41
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• 2019

Terrestrial Gross Primary Production (GPP) is the largest global carbon flux, and forest ecosystems are important because of the ability to store much more significant amounts of carbon than other terrestrial ecosystems. There have been several attempts to estimate GPP using mechanism-based models. However, mechanism-based models including biological, chemical, and physical processes are limited due to a lack of flexibility in predicting non-stationary ecological processes, which are caused by a local and global change. Instead mechanism-free methods are strongly recommended to estimate nonlinear dynamics that occur in nature like GPP. Therefore, we used the mechanism-free machine learning techniques to estimate the daily GPP. In this study, support vector machine (SVM), random forest (RF) and artificial neural network (ANN) were used and compared with the traditional multiple linear regression model (LM). MODIS products and meteorological parameters from eddy covariance data were employed to train the machine learning and LM models from 2006 to 2013. GPP prediction models were compared with daily GPP from eddy covariance measurement in a deciduous forest in South Korea in 2014 and 2015. Statistical analysis including correlation coefficient (R), root mean square error (RMSE) and mean squared error (MSE) were used to evaluate the performance of models. In general, the models from machine-learning algorithms (R = 0.85 - 0.93, MSE = 1.00 - 2.05, p < 0.001) showed better performance than linear regression model (R = 0.82 - 0.92, MSE = 1.24 - 2.45, p < 0.001). These results provide insight into high predictability and the possibility of expansion through the use of the mechanism-free machine-learning models and remote sensing for predicting non-stationary ecological processes such as seasonal GPP.

• Journal of the Korean earth science society
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• v.43 no.1
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• pp.60-76
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• 2022

This study presents a software full setup and the following test execution times in a Linux cluster for the United Kingdom Earth System Model (UKESM) and then compares the model results from control and experimental simulations of the UKESM relative to various observations. Despite its low resolution, the latest version of the UKESM can simulate tropospheric chemistry-aerosol processes and the stratospheric ozone chemistry using the United Kingdom Chemistry and Aerosol (UKCA) module. The UKESM with UKCA (UKESM-UKCA) can treat atmospheric chemistryaerosol-cloud-radiation interactions throughout the whole atmosphere. In addition to the control UKESM run with the default CMIP5 SO₂ emission dataset, an experimental run was conducted to evaluate the aerosol effects on meteorology by changing atmospheric SO₂ loading with the newest REAS data over East Asia. The simulation period of the two model runs was 28 years, from January 1, 1982 to December 31, 2009. Spatial distributions of monthly mean aerosol optical depth, 2-m temperature, and precipitation intensity from model simulations and observations over East Asia were compared. The spatial patterns of surface temperature and precipitation from the two model simulations were generally in reasonable agreement with the observations. The simulated ozone concentration and total column ozone also agreed reasonably with the ERA5 reanalyzed one. Comparisons of spatial patterns and linear trends led to the conclusion that the model simulation with the newest SO₂ emission dataset over East Asia showed better temporal changes in temperature and precipitation over the western Pacific and inland China. Our results are in line with previous finding that SO₂ emissions over East Asia are an important factor for the atmospheric environment and climate change. This study confirms that the UKESM can be installed and operated in a Linux cluster-computing environment. Thus, researchers in various fields would have better access to the UKESM, which can handle the carbon cycle and atmospheric environment on Earth with interactions between the atmosphere, ocean, sea ice, and land.