• Journal of Soil and Groundwater Environment
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• v.19 no.4
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• pp.23-30
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• 2014

Coastal aquifer in Muan, Jeonnam, has experienced heavy seawater intrusion caused by the extraction of a substantial amount of groundwater for the agricultural purpose throughout the year. It was observed that groundwater level dropped below sea level due to heavy pumping during a dry season, which could accelerate seawater intrusion. Therefore, water level needs to be monitored and managed to prevent further seawater intrusion. The purpose of this study is to develop the autoregressive-cross-regressive (ARCR) models that can predict the present or future groundwater level using its own previous values and pumping events. The ARCR model with pumping and water level data of the proceeding five hours (i.e., the model order of five) predicted groundwater level better than that of the model orders of ten and twenty. This was contrary to expectation that higher orders do increase the coefficient of determination ($R^2$) as a measure of the model's goodness. It was found that the ARCR model with order five was found to make a good prediction of next 48 hour groundwater levels after the start of pumping with $R^2$ higher than 0.9.

• Atmosphere
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• v.28 no.1
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• pp.37-51
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• 2018

In this study, we investigate the performance of Global Seasonal Forecasting System version 5 (GloSea5) in Korea Meteorological Administration on the relationship between El $Ni{\tilde{n}}o$ and East Asian climate for the period of 1991~2010. It is found that the GloSea5 has a great prediction skill of El $Ni{\tilde{n}}o$ whose anomaly correlation coefficients of $Ni{\tilde{n}}o$ indices are over 0.96 during winter. The eastern Pacific (EP) El $Ni{\tilde{n}}o$ and the central Pacific (CP) El $Ni{\tilde{n}}o$ are considered and we analyze for EP El $Ni{\tilde{n}}o$, which is well simulated in GloSea5. The analysis period is divided into the developing phase of El $Ni{\tilde{n}}o$ summer (JJA(0)), mature phase of El $Ni{\tilde{n}}o$ winter (D(0)JF(1)), and decaying phase of El $Ni{\tilde{n}}o$ summer (JJA(1)). The GloSea5 simulates the relationship between precipitation and temperature in East Asia and the prediction skill for the East Asian precipitation and temperature varies depending on the El $Ni{\tilde{n}}o$ phase. While the precipitation and temperature are simulated well over the equatorial western Pacific region, there are biases in mid-latitude region during the JJA(0) and JJA(1). Because the low level pressure, wind, and vertical stream function are simulated weakly toward mid-latitude region, though they are similar with observation in low-latitude region. During the D(0)JF(1), the precipitation and temperature patterns analogize with observation in most regions, but there is temperature bias in inland over East Asia. The reason is that the GloSea5 poorly predicts the weakening of Siberian high, even though the shift of Aleutian low is predicted. Overall, the predictability of precipitation and temperature related to El $Ni{\tilde{n}}o$ in the GloSea5 is considered to be better in D(0)JF(1) than JJA(0) and JJA(1) and better in ocean than in inland region.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.6
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• pp.981-987
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• 2017

Jeju Island is a volcanic island which has a large permeability. Groundwater is a major water resources and its proper management is essential. Especially, there is a multilevel restriction due to the groundwater level decline during a drought period to protect sea water intrusion. Preliminary countermeasure using long-term groundwater level prediction is necessary to use agricultural groundwater properly. For this purpose, the monthly groundwater level prediction technique by Artificial Neural Network model was developed and applied to the representative monitoring wells. The monthly prediction model showed excellent results for training and test periods. The continuous groundwater level prediction model also developed, which used the monthly forecasted values adaptively as input data. The characteristics of groundwater declines were analyzed under extreme cases without precipitation for several months.

• The Journal of Korean Institute of Information Technology
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• v.17 no.9
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• pp.11-17
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• 2019

In recent years, damage and loss of life and property have been occurred frequently due to swelling waves in the East Sea. Swelling waves are not easy to predict because they are caused by various factors. In this research, we build a model for predicting the swelling waves occurrence in the East Coast of Korea using machine learning technique. We collect historical data of unloading interruption in the Pohang Port, and collect air pressure, wind speed, direction, water temperature data of the offshore Pohang Port. We select important variables for prediction, and test various machine learning prediction algorithms. As a result, tide level, water temperature, and air pressure were selected, and Random Forest model produced best performance. We confirm that Random Forest model shows best performance and it produces 88.86% of accuracy

• International Union of Geodesy and Geophysics Korean Journal of Geophysical Research
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• v.26 no.1
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• pp.15-29
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• 1998

The numerical simulation of heavy precipitation event occurred in the central Korean Peninsula on July 26-28, 1996 was performed using the fine mesh model. ARPS (Advanced Regional Prediction System) developed by the CAPS (Center for Analysis and Prediction of Storms). Usually, the heavy rainfalls occurred at late July in the Korean Peninsula were difficult to predict, and showed very strong rainfall intensity. As results, they caused a great loss of life and property. As it usual, this case was unsuccessful to predict the location of rain band and the precipitation intensity with the coarse-mesh model. The same case was, however, simulated well with fine-mesh storm-scale model, ARPS. Moisture band at 850 hPa appeared along the Changma Front in the area of China through central Korea passed Yellow Sea. Also the low-level jet at 700 hPa existed in the Yellow Sea through central Korea and they together offered favorable condition to induce heavy rainfall in that area. The convective activities developed to a meso-scale convective system were observed at near the Yangtze River and moved to the central Korean Peninsula. Furthermore, the intrusion of warm and moist air, origninated from typhoon, into the Asia Continent might result in heavy rainfall formation through redistribution of moisture and heat. In the vertical circulation, the heavy rainfall was formed between the upper- and low-level jets, especially, the entrance region of the upper-level jet above the exit the region of the low-level jet. The low level convergence, the upper level divergence and the strong vertical wind were organized to the very north of the low level jet and concentrated on tens to hundreds km horizontal distance. These result represent the upper- and low-level jets are one of the most important reasons on the formation of heavy precipitation.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.6
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• pp.106-112
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• 2001

Unfortunately, the area without economical efficiency, especially the far distance sea, is much lower than that of a urban area-built-up area. It should be promoted the equivalent level to a urban area in the light of future-oriented universal service. Actually, Because propagation environment of mobile communication in the sea is greatly different from that for inland focused on built-up area, a propagation prediction model in the sea should be distinguished from inland-based one. Accordingly, the purpose of this study is to suggest the propagation prediction model for the sea service as a method to minimize unnecessary facilities investment and maintenance caused by additional or new building of a base station. If mobile phone service for far distance sea is provided by expanding limited communication zone of narrow band CDMA mobile communication whose spread band FA is 1.2288MHz. Suggested propagation prediction model includes five parameters to minimize facilities investment of a base station and maximize channel capacity: equivalent line of sight, chip delay by PN code, antenna altitude, power of base station and gain of antennas. Finally, suggested propagation prediction model is simulated and, the results are examined for its utility by comparing with loss of free space.

• Atmosphere
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• v.24 no.2
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• pp.131-140
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• 2014

The "Barents Oscillation (BO)", first designated by Paul Skeie (2000), is an anomalous recurring atmospheric circulation pattern of high relevance for the climate of the Nordic Seas and Siberia, which is defined as the second Emperical Orthogonal Function (EOF) of monthly winter sea level pressure (SLP) anomalies, where the leading EOF is the Arctic Oscillation (AO). BO, however, did not attracted much interest. In recent two decades, variability of BO tends to increase. In this study, we analyzed the spatio-temporal structures of Atmospheric internal modes such as Arctic Oscillation (AO) and Barents Oscillation (BO) and examined how these are related with Arctic warming in recent decade. We identified various aspects of BO, not dealt in Skeie (2000), such as upper-level circulation and surface characteristics for extended period including recent decade and examined link with other surface variables such as sea-ice and sea surface temperature. From the results, it was shown that the BO showed more regionally confined spatial pattern compared to AO and has intensified during recent decade. The regional dipolelar structure centered at Barents sea and Siberia was revealed in both sea-level pressure and 500 hPa geopotential height. Also, BO showed a stronger link (correlation) with sea-ice and sea surface temperature especially over Barents-Kara seas suggesting it is playing an important role for recent Arctic amplification. BO also showed high correlation with Ural Blocking Index (UBI), which measures seasonal activity of Ural blocking. Since Ural blocking is known as a major component of Eurasian winter monsoon and can be linked to extreme weathers, we suggest deeper understanding of BO can provide a missing link between recent Arctic amplification and increase in extreme weathers in midlatitude in recent decades.

• Journal of KSNVE
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• v.9 no.6
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• pp.1187-1192
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• 1999

The purpose of this study is to determine the most appropriate experimental method of the measurement of "damping loss factors" (DLF) for the statistical energy analysis(SEA) calculation. The successful prediction of vibration levels from the structure is critically dependent on the accurate estimation of DLF's not only in conventional vibration analysis but especially in SEA. Unforunately, calculation of accurate DLF is not an easy matter. So experimental methods are made use of for the DLF values. Three kinds of experimental methods for estimating DLF, i.e. decay rate method, half-power bandwidth method and power balance method, are presented and tests are carried out for the plate and the cylindrical shell examples. Pro and con of each methods is reviewed. Finally, calculated DLF values are used for vibration level estimation using commercial SEA software and compared with measured vibration data.tion data.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.2
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• pp.111-122
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• 2010

As the Jamsu-bridge and the floodplains of the Han River can be flooded during the rainy season, the exact prediction of the peak flood time is very important for mitigation of flood hazard. This study analyzes the effect of outflow of Paldang Dam and tide of Yellow Sea on the Han River. A target area is from the Paldang dam to Jeonryu gauging station. Water level of Jeonryu as a downstream boundary condition was estimated through multi linear regression analysis with outflow of Paldang dam and tide level of Incheon, because it was influenced by both a tide of Yellow Sea and outflow of Paldang dam. In this study, Water Level Rising Travel Time of the Jamsu-bridge and some floodplains in the Han River are estimated. Also, The second order polynomial expressions for relationships of outflow of Paldang Dam and Water Level Rising Travel Time were developed considering the outflow of Paldang dam and tide of Yellow Sea.

• Atmosphere
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• v.31 no.3
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• pp.327-340
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• 2021

In this study, the impact of soil moisture initialization in GloSea5, the operational climate prediction system of the Korea Meteorological Administration (KMA), has been investigated for the period of 1991~2010. To overcome the large uncertainties of soil moisture in the reanalysis, JRA55 reanalysis and CMAP precipitation were used as input of JULES land surface model and produced soil moisture initial field. Overall, both mean and variability were initialized drier and smaller than before, and the changes in the surface temperature and pressure in boreal summer and winter were examined using ensemble prediction data. More realistic soil moisture had a significant impact, especially within 2 months. The decreasing (increasing) soil moisture induced increases (decreases) of temperature and decreases (increases) of sea-level pressure in boreal summer and its impacts were maintained for 3~4 months. During the boreal winter, its effect was less significant than in boreal summer and maintained for about 2 months. On the other hand, the changes of surface temperature were more noticeable in the southern hemisphere, and the relationship between temperature and soil moisture was the same as the boreal summer. It has been noted that the impact of land initialization is more evident in the summer hemispheres, and this is expected to improve the simulation of summer heat wave in the KMA's operational climate prediction system.