• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.1074-1081
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• 2021

Nitrous oxide (N₂O) is one of the six major greenhouse gases and is known to produce a greenhouse ef ect by absorbing infrared radiation in the atmosphere. In particular, its global warming potential (GWP) is 310 times higher than that of CO₂, making N₂O a global concern. Accordingly, strong environmental regulations are being proposed. N₂O reduction technology can be classified into concentration recovery, catalytic decomposition, and pyrolysis according to physical methods. This study intends to provide information on temperature conditions and reaction time required to reduce nitrogen oxides with cost. The high-temperature ranges selected for pyrolysis conditions were calculated at intervals of 100 K from 1073 K to 1373 K. Under temperatures of 1073 K and 1173 K, the N₂O reduction rate and nitrogen monoxide concentration were observed to be proportional to the residence time, and for 1273 K, the N₂O reduction rate decreased due to generation of the reverse reaction as the residence time increased. Particularly for 1373 K, the positive and reverse reactions for all residence times reached chemical equilibrium, resulting in a rather reduced reaction progression to N₂O reduction.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3B
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• pp.279-289
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• 2006

The reconstruction of low dimension nonlinear behavior from the hydrologic time series has been an active area of research in the last decade. In this study, we present the applications of a powerful state space reconstruction methodology using the method of Support Vector Machines (SVM) to the Great Salt Lake (GSL) volume. SVMs are machine learning systems that use a hypothesis space of linear functions in a Kernel induced higher dimensional feature space. SVMs are optimized by minimizing a bound on a generalized error (risk) measure, rather than just the mean square error over a training set. The utility of this SVM regression approach is demonstrated through applications to the short term forecasts of the biweekly GSL volume. The SVM based reconstruction is used to develop time series forecasts for multiple lead times ranging from the period of two weeks to several months. The reliability of the algorithm in learning and forecasting the dynamics is tested using split sample sensitivity analyses, with a particular interest in forecasting extreme states. Unlike previously reported methodologies, SVMs are able to extract the dynamics using only a few past observed data points (Support Vectors, SV) out of the training examples. Considering statistical measures, the prediction model based on SVM demonstrated encouraging and promising results in a short-term prediction. Thus, the SVM method presented in this study suggests a competitive methodology for the forecast of hydrologic time series.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.29 no.1
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• pp.1-13
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• 2024

The southwestern part of the East Sea is known to have a high primary productivity compared to those in the northern and eastern parts, which is attributed to nutrients supplies either by Tsushima Warm Current or by coastal upwelling. However, research on the biological pump in this area is limited. We developed machine learning models to estimate net community production (NCP), a measure of biological pump, with high spatial and time scales of 4 km and 8 days, respectively. The models were fed with the input parameters of sea surface temperature, chlorophyll-a, mixed layer depths, and photosynthetically active radiation and trained with observed NCP derived from high resolution measurements of surface O₂/Ar. The root mean square error between the predicted values by the best performing machine model and the observed NCP was 6 mmol O₂ m^-2 d^-1, corresponding to 15% of the average of observed NCP. The NCP in the central part of the Ulleung Basin was highest in March at 49 mmol O₂ m^-2 d^-1 and lowest in June and July at 18 mmol O₂ m^-2 d^-1. These seasonal variations were similar to the vertical nitrate flux based on the ³He gas exchange rate and to the particulate organic carbon flux estimated by the ²³⁴Th disequilibrium method. To expand this method, which produces NCP estimate for spring and summer, to autumn and winter, it is necessary to devise a way to correct bias in NCP by the entrainment of subsurface waters during the seasons.

• Korean Journal of Agricultural and Forest Meteorology
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• v.26 no.3
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• pp.209-218
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• 2024

The National Institute of Agricultural Sciences (NAS) operates in-house long-range climate forecasting system to support the agricultural use of climate forecast data. This system, developed through collaborative research with Pusan National University, is based on the PNU/RDA Coupled General Circulation Model (CGCM) and includes the regional climate model WRF (Weather Research and Forecasting). It generates detailed climate forecast data for periods ranging from 1 to 6 months, covering 20 key variables such as daily maximum, minimum, and average temperatures, precipitation, and agricultural meteorological elements like solar radiation, soil moisture, and ground temperature-factors essential for agricultural forecasting. The data are provided at a daily temporal resolution with a spatial resolution of a 5km grid, which can be used in point form (interpolated) or averaged across administrative regions. The system's seasonal temperature and precipitation forecasts align closely with observed climatological data, accurately reflecting spatial and topographical influences, confirming its reliability. These long-range forecasts from NAS are expected to offer valuable insights for agricultural planning and decision-making. The detailed forecast data can be accessed through the Climate Change Assessment Division of NAS.

• Journal of the Korean earth science society
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• v.33 no.2
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• pp.148-161
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• 2012

The intensive observation (ProbeX-2010) with 6-hour launches of radiosonde was performed over Seoul metropolitan area (Dongducheon, Incheon Airport, and Yangpyeong) from 13 Aug. to 3 Sep. 2010. Five typical heavy rainfall patterns occurred consecutively which are squall line, stationary front, remote tropical cyclone (TC), tropical depression, and typhoon patterns. On 15 Aug. 03 KST, when squall line developed over Seoul metropolitan area, dry mid-level air was drawn over warm and moist low-level air, inducing strong convective instability. From 23 to 26 Aug and from 27 to 29 Aug. Rainfall event occurred influenced by stationary front and remote TC, respectively. During the stationary frontal rainy period, thermal instability was dominant in the beginning stage, but dynamic instability became strong in the latter stage. Especially, heavy rainfall occurred on 25 Aug. when southerly low level jet formed over the Yellow Sea. During the rainy period by the remote TC, thermal and dynamic instability sustained together. Especially, heavy rainfall event occurred on 29 Aug. when the tropical air with high equivalent potential temperature (>345 K) occupied the deep low-middle level. On 27 Aug. and 2 Sep. tropical depression and typhoon Kompasu affected Seoul metropolitan area, respectively. During these events, dynamic instability was very strong.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.307-319
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• 2016

A Land-Atmosphere Modeling Package (LAMP) for supporting agricultural and forest management was developed at the National Center for AgroMeteorology (NCAM). The package is comprised of two components; one is the Weather Research and Forecasting modeling system (WRF) coupled with Noah-Multiparameterization options (Noah-MP) Land Surface Model (LSM) and the other is an offline one-dimensional LSM. The objective of this paper is to briefly describe the two components of the NCAM-LAMP and to evaluate their initial performance. The coupled WRF/Noah-MP system is configured with a parent domain over East Asia and three nested domains with a finest horizontal grid size of 810 m. The innermost domain covers two Gwangneung deciduous and coniferous KoFlux sites (GDK and GCK). The model is integrated for about 8 days with the initial and boundary conditions taken from the National Centers for Environmental Prediction (NCEP) Final Analysis (FNL) data. The verification variables are 2-m air temperature, 10-m wind, 2-m humidity, and surface precipitation for the WRF/Noah-MP coupled system. Skill scores are calculated for each domain and two dynamic vegetation options using the difference between the observed data from the Korea Meteorological Administration (KMA) and the simulated data from the WRF/Noah-MP coupled system. The accuracy of precipitation simulation is examined using a contingency table that is made up of the Probability of Detection (POD) and the Equitable Threat Score (ETS). The standalone LSM simulation is conducted for one year with the original settings and is compared with the KoFlux site observation for net radiation, sensible heat flux, latent heat flux, and soil moisture variables. According to results, the innermost domain (810 m resolution) among all domains showed the minimum root mean square error for 2-m air temperature, 10-m wind, and 2-m humidity. Turning on the dynamic vegetation had a tendency of reducing 10-m wind simulation errors in all domains. The first nested domain (7,290 m resolution) showed the highest precipitation score, but showed little advantage compared with using the dynamic vegetation. On the other hand, the offline one-dimensional Noah-MP LSM simulation captured the site observed pattern and magnitude of radiative fluxes and soil moisture, and it left room for further improvement through supplementing the model input of leaf area index and finding a proper combination of model physics.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1779-1790
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• 2023

Satellite-based fog detection algorithms are being developed to detect fog in real-time over a wide area, with a focus on the Korean Peninsula (KorPen). The GEO-KOMPSAT-2A/Advanced Meteorological Imager (GK2A/AMI, GK2A) satellite offers an excellent temporal resolution (10 min) and a spatial resolution (500 m), while GEO-KOMPSAT-2B/Geostationary Ocean Color Imager-II (GK2B/GOCI-II, GK2B) provides an excellent spatial resolution (250 m) but poor temporal resolution (1 h) with only visible channels. To enhance the fog detection level (10 min, 250 m), we developed a fused GK2AB fog detection algorithm (FDA) of GK2A and GK2B. The GK2AB FDA comprises three main steps. First, the Korea Meteorological Satellite Center's GK2A daytime fog detection algorithm is utilized to detect fog, considering various optical and physical characteristics. In the second step, GK2B data is extrapolated to 10-min intervals by matching GK2A pixels based on the closest time and location when GK2B observes the KorPen. For reflectance, GK2B normalized visible (NVIS) is corrected using GK2A NVIS of the same time, considering the difference in wavelength range and observation geometry. GK2B NVIS is extrapolated at 10-min intervals using the 10-min changes in GK2A NVIS. In the final step, the extrapolated GK2B NVIS, solar zenith angle, and outputs of GK2A FDA are utilized as input data for machine learning (decision tree) to develop the GK2AB FDA, which detects fog at a resolution of 250 m and a 10-min interval based on geographical locations. Six and four cases were used for the training and validation of GK2AB FDA, respectively. Quantitative verification of GK2AB FDA utilized ground observation data on visibility, wind speed, and relative humidity. Compared to GK2A FDA, GK2AB FDA exhibited a fourfold increase in spatial resolution, resulting in more detailed discrimination between fog and non-fog pixels. In general, irrespective of the validation method, the probability of detection (POD) and the Hanssen-Kuiper Skill score (KSS) are high or similar, indicating that it better detects previously undetected fog pixels. However, GK2AB FDA, compared to GK2A FDA, tends to over-detect fog with a higher false alarm ratio and bias.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.12C
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• pp.1192-1199
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• 2003

In this paper, we investigate the effect of pulse repetition frequency (PRF) and slot interval on the throughput performance of the ultra wide band (UWB) wireless communication system in multi-path channels, and based on these observations, a data throughput control using PRF and slot interval is proposed for maximizing the effective throughput. Recently, due to many desirable features of the UWB system, it has drawn much attention especially for short-range high-speed data transmission. The UWB system has two parameters to determine its data throughput; pulse repetition frequency and slot interval. In the multi-path channel with additive white Gaussian noise, the UWB system suffers from the inter-pulse interference (IPI) and noise, which result in degradation of system performance. The UWB system can vary the two parameters to maintain and/or improve the system performance. In this paper, we demonstrate the effects of the two parameters on the data throughput of the UWB system in various multi-path indoor channels through computer simulation, and show that the variable data rate approach designed based on the observations is superior to the fixed data rate one in terms of effective throughput performance.

• The Journal of Engineering Geology
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• v.3 no.2
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• pp.177-190
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• 1993

When soft soils are effected by unsymmetrical surcharge due to embankement and abutements of a bridge, large plastic sheraring deformations such as settlements, lateral displacements, upheavals and sliding shearing failure in the soils occurred and they have often damaged considerabily to the soils and structure. This study examines the existing theoretical background for the behavior of the displacement of soils by unsymmetrical surcharge on the soft soils and compares the analytical results to the actual measurements performed through the model test. The procedures of model test are that a model stock device is made and soft soils are filled in a container which fixes the soils. Then the displacements observed when surcharge load increa ses by regular interval at undrainage condition. It analyzes the relation of soil characteristics to displacement, critical surcharge and ultimate bearing capadty, condition of plastic flow and lateral flow pressure, comparing them with the existing theories. Understanding the causes of lateral displacement in soft soils due to unsymmetrical surchages will prevent a damage in advance.

• The Journal of Engineering Geology
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• v.12 no.1
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• pp.75-88
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• 2002

When unsymmetrical surcharge is worked on polluted soft soils, large plastic shearing deformation such as settlements, lateral displacement, upheavals and shearing failure occured in the soils and they have often done considerable damages to the soils and structures. Accordingly, this study conducts laboratory pilots test to investigate the determination method of lateral flow pressure of polluted soft soils by comparing it to existing equations. The model test is performed that a model stock device is made and polluted soils are filled in a container which fires the soils. Then the displacement is observed as surcharge load is increased by regular intervals at untrained condition. The result shows that test the lateral flow pressure is adequately calculated by the equation (P=K$_{0}$YH) and the maximum value of lateral flow pressure Is found near 0.3H of layer thickness(H) and is higher to ground surface than synthesis pattern, Poulos distribution pattern and soft clay soils(CL, CH) which is not polluted.