• Atmosphere
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• v.29 no.1
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• pp.87-103
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• 2019

This study introduces the overall characteristics of LOVECLIM version 1.3, the earth system model of intermediate complexity (EMIC), including the installation and operation processes by conducting two kinds of past climate simulation. First climate simulation is the equilibrium experiment during the mid-Holocene (6,000 BP), when orbital parameters were different compared to those at present. The overall accuracy of simulated global atmospheric fields by LOVECLIM is relatively lower than that in Coupled Model Intercomparison Project phase 5 (CMIP5) and Paleoclimate modelling Intercomparison Project phase 3 (PMIP3) simulations. However, surface temperature over the globe, the 800 hPa meridional wind over the mid-latitude coastal region, and the 200 hPa zonal wind from LOVECLIM show similar spatial distribution to those multi-model mean of CMIP5/PMIP3 climate models. Second one is the transient climate experiment from mid-Holocene to present. LOVECLIM well captures the major differences in surface temperature between preindustrial and mid-Holocene simulations by CMIP5/PMIP3 multi-model mean, even though it was performed with short integration time (i.e., about four days in a single CPU environment). In this way, although the earth system model of intermediate complexity has a limit due to its relatively low accuracy, it can be a very useful tool in the specific research area such as paleoclimate.

• Economic and Environmental Geology
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• v.56 no.1
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• pp.65-73
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• 2023

As one of the most vulnerable countries to floods, there should be an increased necessity for accurate and reliable flood forecasting in Indonesia. Therefore, a new prediction model using a machine learning algorithm is proposed to provide daily flood prediction in Indonesia. Data crawling was conducted to obtain daily rainfall, streamflow, land cover, and flood data from 2008 to 2021. The model was built using a Random Forest (RF) algorithm for classification to predict future floods by inputting three days of rainfall rate, forest ratio, and stream flow. The accuracy, specificity, precision, recall, and F1-score on the test dataset using the RF algorithm are approximately 94.93%, 68.24%, 94.34%, 99.97%, and 97.08%, respectively. Moreover, the AUC (Area Under the Curve) of the ROC (Receiver Operating Characteristics) curve results in 71%. The objective of this research is providing a model that predicts flood events accurately in Indonesian regions 3 months prior the day of flood. As a trial, we used the month of June 2022 and the model predicted the flood events accurately. The result of prediction is then published to the website as a warning system as a form of flood mitigation.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.719-722
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• 2003

This paper presents the development of reservoir characterization model equipped with parallelized genetic algorithm, and its application for a heterogeneous reservoir system with integration of the well data and multi-phase production data. A parallel processing method performed by PC-cluster was applied to the developed model in order to reduce time for an inverse calculation. By utilizing the developed model, we performed the inverse calculation with the production data obtained from three layered reservoir system to estimate porosity and permeability distribution. As a result, the pressures observed at well almost identical to those calculated by the developed model. Also, it was confirmed that parallel processing could be applied for reservoir characterization study efficiently.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.16 no.11
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• pp.1092-1100
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• 2004

This paper presents the effect of opening configuration on the thermal behavior and air pattern of earth tube system. The earth tube system is a fresh air load reduction system by using underground double floor space for air-conditioning. In order to analyze the effect of opening configuration on thermal performance of this system and air pattern in underground double floor space quantitatively, we used a model dealing with tree-dimensional profile of wind velocity and temperature in underground double floor space. In conclusion, it is confirmed that heat exchange of a fresh air is mainly performed with upper and lower wall in underground double floor space, and that heat exchange area increased by installing the opening near the wall.

• Journal of Environmental Science International
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• v.23 no.9
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• pp.1551-1562
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• 2014

To clarify the characteristics of TKE (Turbulence Kinetic Energy) variation for offshore wind power development, several numerical experiments using WRF were carried out in three different coastal area of the Korean Peninsula. Buoyancy, mechanical and shear production term of the TKE budget are fundamental elements in the production or dissipation of turbulence. Turbulent kinetic energy of the south coast region was higher than in other sea areas due to the higher sea surface temperature and strong wind speed. In south coast region, strong wind passing through the Korea Strait is caused by channelling effect of the terrain of the Geoje Island. Although wind speed is weak in east coast, because of large difference in wind speed between the upper and lower layer, the development of mechanical turbulence tend to be predominant. Since lower sea surface temperature and smaller wind shear were detected in west coastal region, the possibility of turbulence production not so great in comparison with other regions. The understanding of the characteristics of turbulence in three different coastal region can be reduced the uncertainty of offshore wind construction.

• Journal of Soil and Groundwater Environment
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• v.18 no.3
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• pp.119-133
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• 2013

In the present study, several groundwater vulnerability assessment methods were applied to an agricultural area of Gumma in Korea. For the groundwater intrinsic vulnerability assessment, the performance of DRASTIC, SINTACS and GOD models was compared and an ensemble approach was suggested. M-DRASTIC and multi-linear regression (MLR) models were applied for the groundwater specific vulnerability assessment to nitrate of the study site. The correlation coefficient between the nitrate concentration and M-DRASTIC index was as low as 0.24. The result of the MLR model showed that the correlation coefficient is 0.62 and the areal extents of livestock farming and upland field are most influential factors for the nitrate contamination of groundwater in the study site.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1A
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• pp.163-171
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• 2006

The behaviors and design procedures of building excavation plane in innovative prestressed support (IPS) system are presented in this paper. Determination procedure for initial pretension in IPS wale subjected to design earth pressure is derived. The computer analysis model under uniform and non-uniform earth pressure is constructed using beam element for the IPS wale, tension-only element for cable, and compression-only element for soil. Axial forces and bending moments of IPS wale under initial pretension and design earth pressure are calculated. The combined stresses due to these axial force and bending moment are calculated and safety condition of building excavation plane is investigated.

• 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.

• Atmosphere
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• v.27 no.1
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• pp.105-118
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• 2017

This study assesses the performance of the Weather Research and Forecasting (WRF) model in reproducing regional climate over CORDEX-East Asia Phase 2 domain with different cumulus parameterization schemes [Kain-Fritch (KF), Betts-Miller-Janjic (BM), and Grell-Devenyi-Ensemble (GD)]. The model is integrated for 27 months from January 1979 to March 1981 and the initial and boundary conditions are derived from European Centre for Medium-Range Weather Forecast Interim Reanalysis (ERA-Interim). The WRF model reasonably reproduces the temperature and precipitation characteristics over East Asia, but the regional scale responses are very sensitive to cumulus parameterization schemes. In terms of mean bias, WRF model with BM scheme shows the best performance in terms of summer/winter mean precipitation as well as summer mean temperature throughout the North East Asia. In contrast, the seasonal mean precipitation is generally overestimated (underestimated) by KF (GD) scheme. In addition, the seasonal variation of the temperature and precipitation is well simulated by WRF model, but with an overestimation in summer precipitation derived from KF experiment and with an underestimation in wet season precipitation from BM and GD schemes. Also, the frequency distribution of daily precipitation derived from KF and BM experiments (GD experiment) is well reproduced, except for the overestimation (underestimation) in the intensity range above (less) then $2.5mm\;d^{-1}$. In the case of the amount of daily precipitation, all experiments tend to underestimate (overestimate) the amount of daily precipitation in the low-intensity range < $4mm\;d^{-1}$ (high-intensity range > $12mm\;d^{-1}$). This type of error is largest in the KF experiment.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.1
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• pp.33-40
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• 2023

With the development of supercomputing technology and hardware technology, numerical computation methods are also being advanced. Accordingly, improved weather prediction becomes possible. In this paper, we propose to apply the LAPACK(Linear Algebra PACKage) BLAS(Basic Linear Algebra Subprograms) library to the linear algebraic numerical computation part within the source code to improve the performance of the cumulative parametric code, Unicon(A Unified Convection Scheme), which is included in SCAM(Single-Columns Atmospheric Model, simplified version of CESM(Community Earth System Model)) and performs standby operations. In order to analyze this, an overall execution structure diagram of SCAM was presented and a test was conducted in the relevant execution environment. Compared to the existing source code, the SCOPY function achieved 0.4053% performance improvement, the DSCAL function 0.7812%, and the DDOT function 0.0469%, and all of them showed a 0.8537% performance improvement. This means that the LAPACK BLAS application method, a library for high-density linear algebra operations proposed in this paper, can improve performance without additional hardware intervention in the same CPU environment.