• Journal of the Earthquake Engineering Society of Korea
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• v.21 no.1
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• pp.1-9
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• 2017

The scale of disaster and damage witnessed in the 2004 Indian Ocean Tsunami and the 2011 Great East Japan Tsunami has motivated researchers in developing foolproof disaster mitigation techniques for safety of coastal communities. This study focuses on developing tsunami hazard map by numerical modeling at Imwon Port to minimize losses of human beings and property damage when a real tsunami event occurs. A hazard map is developed based on inundation maps obtained by numerical modeling of 3 past and 11 virtual tsunami cases. The linear shallow-water equations with manipulation of frequency dispersion and the non-linear shallow-water equations are employed to obtain inundation maps. The inundation map gives the maximum extent of expected flooded area and corresponding inundation depths which helps in identifying vulnerable areas for unexpected tsunami attacks. The information can be used for planning and developing safety zones and evacuation structures to minimize damage in case of real tsunami events.

• Atmosphere
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• v.20 no.3
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• pp.333-341
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• 2010

The stratiform rain fraction is investigated in the tropical boreal winter Madden-Julian oscillation (MJO) and summer intraseasonal oscillation (ISO) using Tropical Rainfall Measuring Mission (TRMM) Precipitation Rader data for the 11-yr period from 1998 to 2008. Composite analysis shows that the MJO/ISO produces larger stratiform rain rate than convective rain rate for nearly all phases following the propagating MJO/ISO deep clouds, with the greatest stratiform rainfall amount when the MJO/ISO center is located over the central-eastern Indian Ocean and the western Pacific. The fraction of the intraseasonally filtered stratiform rainfall compared to total rainfall (i.e., convective plus stratiform rainfall) amounts to 53~56%, which is 13~16% larger than the stratiform rain fraction estimated for the same data on seasonal-to-annual time scales by Schumacher and Houze. This indicates that the MJO/ISO exhibits the organized rainfall process which is characterized by the shallow convection/heating at the incipient phase and the subsequent flare-up of strong deep convection, followed by the development of stratiform clouds at the upper troposphere.

• Atmosphere
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• v.21 no.2
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• pp.143-149
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• 2011

A new multi-timescale analysis method, Ensemble Empirical Mode Decomposition (EEMD), is used to diagnose the variation of the MJO activity determined by 850hPa and 200hPa zonal winds from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) Reanalysis data for the 56-yr period from 1950 to 2005. The results show that MJO activity can be decomposed into 9 quasi-periodic oscillations and a trend. With each level of contribution of the quasi-periodic oscillation discussed, the bi-seasonal oscillation, the interannual oscillation and the trend of the MJO activity are the most prominent features. The trend increases almost linearly, so that prior to around 1978 the activity of the MJO is lower than that during the latter part. This may be related to the tropical sea surface temperature(SST). It is speculated that the interdecadal change in the MJO activity appeared in around 1978 is related to the warmer SST in the equatorial warm pool, especially over the Indian Ocean.

• Advances in Computational Design
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• v.1 no.3
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• pp.235-251
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• 2016

We have performed a design optimization of a stiffened panel with curvilinear stiffeners using an artificial neural network (ANN) residual kriging based surrogate modeling approach. The ANN residual kriging based surrogate modeling involves two steps. In the first step, we approximate the objective function using ANN. In the next step we use kriging to model the residue. We optimize the panel in an iterative way. Each iteration involves two steps-shape optimization and size optimization. For both shape and size optimization, we use ANN residual kriging based surrogate model. At each optimization step, we do an initial sampling and fit an ANN residual kriging model for the objective function. Then we keep updating this surrogate model using an adaptive sampling algorithm until the minimum value of the objective function converges. The comparison of the design obtained using our optimization scheme with that obtained using a traditional genetic algorithm (GA) based optimization scheme shows satisfactory agreement. However, with this surrogate model based approach we reach optimum design with less computation effort as compared to the GA based approach which does not use any surrogate model.

• Environmental Engineering Research
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• v.23 no.4
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• pp.462-473
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• 2018

The uranium ore residues from the legacies of past uranium mining and milling activities that resulted from the less stringent environmental standards along with the uranium residues from the existing nuclear power plants continue to be a cause of concern as the final uranium residues are not made safe from radiological and general safety point of view. The deposition of uranium in ponds increases the risk of groundwater getting contaminated as these residues essentially leach through the upper unsaturated geological formation. In this context, a numerical model has been developed in order to forecast the $^{238}U$ and its progenies concentration in an unsaturated soil. The developed numerical model is implemented in a hypothetical uranium tailing pond consisting of sandy soil and silty soil types. The numerical results show that the $^{238}U$ and its progenies are migrating up to the depth of 90 m and 800 m after 10 y in silty and sandy soil, respectively. Essentially, silt may reduce the risk of contamination in the groundwater for longer time span and at the deeper depths. In general, a coupled effect of sorption and hydro-geological parameters (soil type, moisture context and hydraulic conductivity) decides the resultant uranium transport in subsurface environment.

• Journal of Species Research
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• v.12 no.2
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• pp.122-149
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• 2023

Two known species of the family Comesomatidae Filipjev, 1918 were collected from marine sediments of the sublittoral zone in the East Sea, Korea and described and illustrated. Dorylaimopsis variabilis Muthumbi, Soetaert and Vincx, 1997, which was originally described from the Kenyan coast in the Indian Ocean, is recorded from the East Sea, Korea for the first time; there are only slight differences in amphidial fovea turns, body length, body width and relative length of tail. Setosabatieria hilarula (De Man, 1922), Platt, 1985, which was originally described from the North Sea, is recorded from the East Sea, Korea for the first time; there are only slight differences in the number of precloacal supplements, the relative length of tail and the posterior portion of tail. We provide pictorial keys for determination of valid species in the genera Dorylaimopsis Ditlevsen, 1918 and Setosabatieria Platt, 1985. This is the first description of the genus Dorylaimopsis and Setosabatieria from Korean waters.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.21 no.2
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• pp.49-57
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• 2016

Even if an external forcing that will drive a climate change is given uniformly over the globe, the corresponding climate change and the feedbacks by the climate system differ by region. Thus the detection of global warming signal has been made on a regional scale as well as on a global average against the internal variabilities and other noises involved in the climate change. The purpose of this study is to estimate a timing of unprecedented climate due to global warming and to analyze the regional differences in the estimated results. For this purpose, unlike previous studies that used climate simulation data, we used an observational dataset to estimate a magnitude of internal variability and a future temperature change. We calculated a linear trend in surface temperature using a historical temperature record from 1880 to 2014 and a magnitude of internal variability as the largest temperature displacement from the linear trend. A timing of unprecedented climate was defined as the first year when a predicted minimum temperature exceeds the maximum temperature record in a historical data and remains as such since then. Presumed that the linear trend and the maximum displacement will be maintained in the future, an unprecedented climate over the land would come within 200 years from now in the western area of Africa, the low latitudes including India and the southern part of Arabian Peninsula in Eurasia, the high latitudes including Greenland and the mid-western part of Canada in North America, the low latitudes including Amazon in South America, the areas surrounding the Ross Sea in Antarctica, and parts of East Asia including Korean Peninsula. On the other hand, an unprecedented climate would come later after 400 years in the high latitudes of Eurasia including the northern Europe, the middle and southern parts of North America including the U.S.A. and Mexico. For the ocean, an unprecedented climate would come within 200 years over the Indian Ocean, the middle latitudes of the North Atlantic and the South Atlantic, parts of the Southern Ocean, the Antarctic Ross Sea, and parts of the Arctic Sea. In the meantime, an unprecedented climate would come even after thousands of years over some other regions of ocean including the eastern tropical Pacific and the North Pacific middle latitudes where an internal variability is large. In summary, spatial pattern in timing of unprecedented climate are different for each continent. For the ocean, it is highly affected by large internal variability except for the high-latitude regions with a significant warming trend. As such, a timing of an unprecedented climate would not be uniform over the globe but considerably different by region. Our results suggest that it is necessary to consider an internal variability as well as a regional warming rate when planning a climate change mitigation and adaption policy.

• Journal of the Mineralogical Society of Korea
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• v.30 no.4
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• pp.219-227
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• 2017

Manganese (Mn) nodules in the Arctic Sea have been founded in the Kara Sea and Barents Sea, but mineral and chemical compositions have been rarely investigated. In this study, mineralogical and geochemical characteristics of Mn nodules obtained during the Arctic Expedition ARA07C in northern East Siberian Sea were identified, and then genesis of Mn nodules were estimated by using these characteristics. Main manganese oxide minerals constituting the manganese nodule were buserite, birnessite, and vernadite. The Mn nodules generally represent radiated and massive texture, and the layered texture was developed restrictively. The radiated texture, main feature of the manganese nodule in the East Siberian Sea, is mainly composed of cuspate-globular microstructure. Compared with the Mn nodules in Pacific and Indian Oceans, Mn nodules of the East Siberian Sea are abundant in Mn, but Fe is too scarce. There was no difference in the chemical composition and microstructures between outer and inner part of nodule. Therefore, nodules are most likely to have only one genesis during their growth, and all of nodules indicate the diagenetic in $Mn-Fe-(Cu+Ni+Co){\times}10$ ternary diagram. It is considered that the manganese nodules in the East Siberian Sea are characterized by high Mn contents because manganese contents in the Arctic Ocean were mainly resulted from river or coastal erosion and most of them are trapped in the Arctic Ocean.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.27 no.4
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• pp.225-231
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• 1991

In order to suggest the useful information on the fishing ground of the bigeye tuna Thunnus obesus(LOWE), a data base system was formed with catch data of the Korean tuna long liners during from 1975 to 1987 by using a set of 16 bits personal computer. This data base was constructed of the handling program and 4 types of data file processed from the monthly and yearly catch data of the whole tunas and the bigeye tuna. And when the system was started, the map of one among various Oceans such as the Pacific, the Atlantic and the Indian Ocean. is drawn on the monitor. And then the catch rates of the whole tunas or the catch ratios of bigeye tunas are indicated by the figured symbols and the colors on the sea divisions of 5$^{\circ}$ space of longitude and latitude respectively at the same time. Also this system has the preestimating program on the catch rates of the whole tunas and the bigeye tuna in the desired month and sea divisions. In the results than this data base system was handled and tested, very useful informations were obtained for the detection of tunas, especially bigeye tuna, and the preestimation was possible in a desired level.

• Korean Journal of Remote Sensing
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• v.21 no.3
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• pp.189-211
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• 2005

This paper makes an effort to compare the recently evolved soft classification method based on Linear Spectral Mixture Modeling (LSMM) with the traditional hard classification methods based on Iterative Self-Organizing Data Analysis (ISODATA) and Maximum Likelihood Classification (MLC) algorithms in order to achieve appropriate results for mapping, monitoring and preserving valuable coastal wetland ecosystems of southern India using Indian Remote Sensing Satellite (IRS) 1C/1D LISS-III and Landsat-5 Thematic Mapper image data. ISODATA and MLC methods were attempted on these satellite image data to produce maps of 5, 10, 15 and 20 wetland classes for each of three contrast coastal wetland sites, Pitchavaram, Vedaranniyam and Rameswaram. The accuracy of the derived classes was assessed with the simplest descriptive statistic technique called overall accuracy and a discrete multivariate technique called KAPPA accuracy. ISODATA classification resulted in maps with poor accuracy compared to MLC classification that produced maps with improved accuracy. However, there was a systematic decrease in overall accuracy and KAPPA accuracy, when more number of classes was derived from IRS-1C/1D and Landsat-5 TM imagery by ISODATA and MLC. There were two principal factors for the decreased classification accuracy, namely spectral overlapping/confusion and inadequate spatial resolution of the sensors. Compared to the former, the limited instantaneous field of view (IFOV) of these sensors caused occurrence of number of mixture pixels (mixels) in the image and its effect on the classification process was a major problem to deriving accurate wetland cover types, in spite of the increasing spatial resolution of new generation Earth Observation Sensors (EOS). In order to improve the classification accuracy, a soft classification method based on Linear Spectral Mixture Modeling (LSMM) was described to calculate the spectral mixture and classify IRS-1C/1D LISS-III and Landsat-5 TM Imagery. This method considered number of reflectance end-members that form the scene spectra, followed by the determination of their nature and finally the decomposition of the spectra into their endmembers. To evaluate the LSMM areal estimates, resulted fractional end-members were compared with normalized difference vegetation index (NDVI), ground truth data, as well as those estimates derived from the traditional hard classifier (MLC). The findings revealed that NDVI values and vegetation fractions were positively correlated ($r^2$= 0.96, 0.95 and 0.92 for Rameswaram, Vedaranniyam and Pitchavaram respectively) and NDVI and soil fraction values were negatively correlated ($r^2$ =0.53, 0.39 and 0.13), indicating the reliability of the sub-pixel classification. Comparing with ground truth data, the precision of LSMM for deriving moisture fraction was 92% and 96% for soil fraction. The LSMM in general would seem well suited to locating small wetland habitats which occurred as sub-pixel inclusions, and to representing continuous gradations between different habitat types.