• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.29 no.2
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• pp.101-115
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• 2024

The ocean heatwave is emerging as a major issue due to global warming, posing a direct threat to marine ecosystems and humanity through decreased food resources and reduced carbon absorption capacity of the oceans. Consequently, the prediction of ocean heatwaves in the vicinity of the Korean Peninsula is becoming increasingly important for marine environmental monitoring and management. In this study, an LSTM model was developed to improve the underestimated prediction of ocean heatwaves caused by the coarse vertical grid system of the Korean Peninsula Ocean Prediction System. Based on the results of ocean heatwave predictions for the Korean Peninsula conducted in 2023, as well as those generated by the LSTM model, the performance of heatwave predictions in the East Sea, Yellow Sea, and South Sea areas surrounding the Korean Peninsula was evaluated. The LSTM model developed in this study significantly improved the prediction performance of sea surface temperatures during periods of temperature increase in all three regions. However, its effectiveness in improving prediction performance during periods of temperature decrease or before temperature rise initiation was limited. This demonstrates the potential of the LSTM model to address the underestimated prediction of ocean heatwaves caused by the coarse vertical grid system during periods of enhanced stratification. It is anticipated that the utility of data-driven artificial intelligence models will expand in the future to improve the prediction performance of dynamical models or even replace them.

• Geophysics and Geophysical Exploration
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• v.27 no.2
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• pp.91-107
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• 2024

Single-channel seismic exploration has proven effective in delineating subsurface geological structures using small-scale survey systems. The seismic data acquired through zero- or near-offset methods directly capture subsurface features along the vertical axis, facilitating the construction of corresponding seismic sections. However, substantial noise in single-channel seismic data hampers precise interpretation because of the low signal-to-noise ratio. This study introduces a novel approach that integrate noise reduction and signal enhancement via matrix rank optimization to address this issue. Unlike conventional rank-reduction methods, which retain selected singular values to mitigate random noise, our method optimizes the entire singular value spectrum, thus effectively tackling both random and erratic noises commonly found in environments with low signal-to-noise ratio. Additionally, to enhance the horizontal continuity of seismic events and mitigate signal loss during noise reduction, we introduced an adaptive weighting factor computed from the eigenimage of the seismic section. To access the robustness of the proposed method, we conducted numerical experiments using single-channel Sparker seismic data from the Chukchi Plateau in the Arctic Ocean. The results demonstrated that the seismic sections had significantly improved signal-to-noise ratios and minimal signal loss. These advancements hold promise for enhancing single-channel and high-resolution seismic surveys and aiding in the identification of marine development and submarine geological hazards in domestic coastal areas.

• Korean Journal of Remote Sensing
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• v.30 no.4
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• pp.481-491
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• 2014

Blue-ice area is a glacial ice field in ice sheet, ice shelf and glaciers where snow ablation and sublimation is larger than snowfall. As the blue-ice area has large influences on the meteorite concentration mechanism and ice mass balance, it is required to quantify the concentration of blue-ice. We analyzed spectral reflectance characteristics of blue-ice, snow and cloud by using MODIS images obtained over blue-ice areas in McMurdo Dry Valleys, East Antarctica, from 2007 to 2012. We then developed Normalized Difference Blue-ice Index (NDBI) algorithm which quantifies the concentration of blue-ice. Snow and cloud have a high reflectance in visible and near-infrared (NIR) bands. Reflectance of blue-ice is high in blue band, while that lowers in the NIR band. NDBI is calculated by dividing the difference of reflectance in the blue and NIR bands by the sum of reflectances in the two bands so that NDBI = (Blue-NIR)/(Blue + NIR). NDBI calculated from the MODIS images showed that the blue-ice areas have values ranging from 0.2 to 0.5, depending on the exposure and concentration of blue-ice. It is obviously different from that of snow and cloud that has values less than 0.2 or rocks with negative values. The change of NDBI values in the blue-ice area has higher correlation with snow depth ($R^2=0.699$) than wind speed ($R^2=0.012$) or air temperature ($R^2=0.278$), all measured at a meteorological station installed in McMurdo Dry Valleys. As the snow depth increased, the NDBI value decreased, which suggests that snow depth can be estimated from NDBI values over blue-ice areas. The NDBI algorithm developed in this study will be useful for various polar research fields such as meteorite exploration, analysis of ice mass balance as well as the snow depth estimation.

• Korean Journal of Remote Sensing
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• v.29 no.4
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• pp.375-387
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• 2013

Accuracy assessment of tide models in polar ocean has to be performed to accurately analyze tidal response of glaciers by using Double-Differential Interferometric SAR (DDInSAR) technique. In this study, we used 120 DDInSAR images generated from 16 one-day tandem COSMO-SkyMed DInSAR pairs obtained for 2 years and in situ tide height for 11 days measured by a pressure type wave recorder to assess the accuracy of tide models such as TPXO7.1, FES2004, CATS2008a and Ross_Inv in Terra Nova Bay, East Antarctica. Firstly, we compared the double-differential tide height (${\Delta}\dot{T}$) for Campbell Glacier Tongue extracted from the DDInSAR images with that predicted by the tide models. Tide height (T) from in situ measurement was compared to that of the tide models. We also compared 24-hours difference of tide height ($\dot{T}$) from in situ tide height with that from the tide models. The root mean square error (RMSE) of ${\Delta}\dot{T}$, T and $\dot{T}$ decreased after the inverse barometer effect (IBE)-correction of the tide models, from which we confirmed that the IBE of tide models should be corrected requisitely. The RMSE of $\dot{T}$ and ${\Delta}\dot{T}$ were smaller than that of T. This was because $\dot{T}$ is the difference of tide height during temporal baseline of the DInSAR pairs (24 hours), in which the errors from mean sea level of the tide models and in situ tide, and the tide constituents of $S_2$, $K_2$, $K_1$ and $P_1$ used in the tide models were canceled. This confirmed that $\dot{T}$ and ${\Delta}\dot{T}$ predicted by the IBE-corrected tide models can be used in DDInSAR technique. It was difficult to select an optimum tide model for DDInSAR in Terra Nova Bay by using in situ tide height measured in a short period. However, we could confirm that Ross_Inv is the optimum tide model as it showed the smallest RMSE of 4.1 cm by accuracy assessment using the DDInSAR images.

• Korean Journal of Environmental Biology
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• v.23 no.3 s.59
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• pp.257-268
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• 2005

Meiofauna community was surveyed in the Arctic Ocean. Sediment samples were collected from six stations in the east Barents Sea and from five stations in Kongsfjorden, Svalbard during summer 2002. Eight taxa of meiofauna were identified in the Barents Sea. Meiofauna abundance ranged from 245 to 906 indiv.10 $cm^{-2}$ (mean 580 indiv.10 $cm^{-2}$) and total biomass varied from 23 and 404 ${\mu}gC10cm^{-2}$ (mean 184 ${\mug}C10cm^{-2}$) in the Barent Sea. Nematode predominated in meiofauna comprising $95.2\%$ of total abundance and $66.4\%$ of biomass. Copepods, polycheats and sarcomastigophonans were also dominant in the study area. Nine taxa of meiofauna were identified in Kongsfiorden. Meiofauna abundance ranged from 103 to 513 indiv.10 $cm^{-2}$ (mean 292 indiv.10 $cm^{-2}$) and biomass varied from 13 and 196{\mu}gC10\;cm^{-2}$ (mean 94{\mu}gC10\;cm^{-2}$) in the Kongsfiorden. Nematodes predominated in meiofauna, comprising $64.1\%$ of abundance and $64.3\%$ biomass. Copepods, polychaets, and kinorhyncha were also dominant in the study area. The meiofauna abundances from both the study areas well match with the previous reports from the various regions including the temperate areas. However the occurred taxa in the present study are only a half comparing with the reports from temperate zone. Meiofauna abundance, biomass, diversity index and species richness were much higher than in the coastal which were strongly affected by fresh water run off in the Barents Sea. The stations affected by chlorophyll had high abundance and biomass, but low diversity index and spices richness in Kongsfiorden.

• Journal of Life Science
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• v.30 no.11
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• pp.931-938
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• 2020

Translationally controlled tumor protein (TCTP) is one of the most abundant proteins in various eukaryotic organisms. TCTPs play important roles in cell physiological processes in cancer, cell proliferation, gene regulation, and heat shock response. TCTP is also considered an important factor in the resistance to oxidative stress induced by dithiothreitol or hydrogen peroxide (H₂O₂). Arctic calanoid copepods have a variety of antioxidant defense systems to regulate the levels of potentially harmful reactive oxygen species generated by ultraviolet radiation in the Arctic marine ecosystem. However, information on the antioxidant activity of TCTP in the Arctic Calanus glacialis is still scarce. To understand the putative antioxidant function of the Arctic copepod C. glacialis TCTP (Cg-TCTP), its gene was cloned and sequenced. The Cg-TCTP comprised 522 bp and encoded a 174-amino acid putative protein with a calculated molecular weight of ~23 kDa. The recombinant Cg-TCTP (Cg-r TCTP) gene was overexpressed in Escherichia coli (BL21), and Cg-rTCTP-transformed cells were grown in the presence or absence of H₂O₂. Cg-rTCTP-transformed E. coli showed increased tolerance to high H₂O₂ concentrations. Therefore, TCTP may be an important antioxidant protein related to tolerance of the Arctic copepod C. glacialis to oxidative stress in the harsh environment of the Arctic Ocean.

• Journal of the Korean earth science society
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• v.23 no.4
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• pp.357-368
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• 2002

In this study we have tried to explain the barrel-shaped morphology for young supernova remnants considering the dynamical effects of the ejecta. We consider the magnetic field amplification resulting from the Rayleigh-Taylor instability near the contact discontinuity. We can generate the synthetic radio image assuming the cosmic-ray pressure and calculate the azimuthal intensity ratio (A) to enable a quantitative comparison with observations. The postshock magnetic field are amplified by shearing, stretching, and compressing at the R-T finger boundary. The evolution of the instability strongly depends on the deceleration of the ejecta and the evolutionary stage of the remnant. the strength of the magnetic field increases in the initial phase and decreases after the reverse shock passes the constant density region of the ejecta. However, some memory of the earlier phases of amplification is retained in the interior even when the outer regions turn into a blast wave. The ratio of the averaged magnetic field strength at the equator to the one at the pole in the turbulent region can amount to 7.5 at the peak. The magnetic field amplification can make the large azimuthal intensity ratio (A=15). The magnitude of the amplification is sensitive to numerical resolution. This mens the magnetic field amplification can explain the barrel-shaped morphology of young supernova remnant without the dependence of the efficiency of the cosmic-ray acceleration on the magnetic field configuration. In order for this mechanism to be effective, the surrounding magnetic field must be well-ordered. The small number of barrel-shaped remnants may indicate that this condition rarely occurs.

• Journal of the Korean Electrochemical Society
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• v.10 no.4
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• pp.283-287
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• 2007

KIER has been developing the anode-supported flat tubular solid oxide fuel cell unit bundle for the intermediate temperature($700{\sim}800^{\circ}C$) operation. Anode-supported flat tubular cells have Ni/YSZ cermet anode support, 8 moi.% $Y_2O_3$ stabilized $ZrO_2(YSZ)$ thin electrolyte, and cathode multi-layer composed of Sr-doped $LaSrMnO_3(LSM)$, LSM-YSZ composite, and $LaSrCoFeO_3(LSCF)$. The prepared anode-supported flat tubular cell was joined with ferritic stainless steel cap by induction brazing process. Current collection for the cathode was achieved by winding Ag wire and $La_{0.6}Sr_{0.4}CoO_3(LSCo)$ paste, while current collection for the anode was achieved by using Ni wire and felt. For making stack, the prepared anode-supported flat tubular cells with effective electrode area of $90\;cm^2$ connected in series with 12 unit bundles, in which unit bundle consists of two cells connected in parallel. The performance of unit bundle in 3% humidified $H_2$ and air at $800^{\circ}C$ shows maximum power density of $0.39\;W/cm^2$ (@ 0.7V). Through these experiments, we obtained basic technology of the anode-supported flat tubular cell and established the proprietary concept of the anode-supported flat tubular cell unit bundle.

• Korean Journal of Remote Sensing
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• v.23 no.6
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• pp.507-520
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• 2007

Satellite passive microwave(PM) sensors have been observing polar sea ice concentration(SIC), ice temperature, and snow depth since 1970s. Among them SIC is playing an important role in the various studies as it is considered the first factor for the monitoring of global climate and environment changes. Verification and correction of PM SIC is essential for this purpose. In this study, we calculated SIC from KOMPSAT-1 EOC images obtained from Arctic sea ice edges from July to August 2005 and compared with SSM/I SIC calculated from NASA Team(NT) algorithm. When we have no consideration of sea ice types, EOC and SSM/I NT SIC showed low correlation coefficient of 0.574. This is because there are differences in spatial resolution and observing time between two sensors, and the temporal and spatial variation of sea ice was high in summer Arctic ice edge. For the verification of SSM/I NT SIC according to sea ice types, we divided sea ice into land-fast ice, pack ice, and drift ice from EOC images, and compared them with SSM/I NT SIC corresponding to each ice type. The concentration of land-fast ice between EOC and SSM/I SIC were calculated very similarly to each other with the mean difference of 0.38%. This is because the temporal and spatial variation of land-fast ice is small, and the snow condition on the ice surface is relatively dry. In case of pack ice, there were lots of ice ridge and new ice that are known to be underestimated by NT algorithm. SSM/I NT SIC were lower than EOC SIC by 19.63% in average. In drift ice, SSM/I NT SIC showed 20.17% higher than EOC SIC in average. The sea ice with high concentration could be included inside the wide IFOV of SSM/I because the drift ice was located near the edge of pack ice. It is also suggested that SSM/I NT SIC overestimated the drift ice covered by wet snow.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1177-1186
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• 2021

As the Arctic melt ponds play an important role in determining the interannual variation of the sea ice extent and changes in the Arctic environment, it is crucial to monitor the Arctic melt ponds with high accuracy. Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2), which is the NASA's latest altimeter satellite based on the green laser (532 nm), observes the global surface elevation. When compared to the CryoSat-2 altimetry satellite whose along-track resolution is 250 m, ICESat-2 is highly expected to provide much more detailed information about Arctic melt ponds thanks to its high along-track resolution of 70 cm. The basic products of ICESat-2 are the surface height and the number of reflected photons. To aggregate the neighboring information of a specific ICESat-2 photon, the segments of photons with 10 m length were used. The standard deviation of the height and the total number of photons were calculated for each segment. As the melt ponds have the smoother surface than the sea ice, the lower variation of the height over melt ponds can make the melt ponds distinguished from the sea ice. When the melt ponds were extracted, the number of photons per segment was used to classify the melt ponds covered with open-water and specular ice. As photons are much more absorbed in the water-covered melt pondsthan the melt ponds with the specular ice, the number of photons persegment can distinguish the water- and ice-covered ponds. As a result, the suggested melt pond detection method was able to classify the sea ice, water-covered melt ponds, and ice-covered melt ponds. A qualitative analysis was conducted using the Sentinel-2 optical imagery. The suggested method successfully classified the water- and ice-covered ponds which were difficult to distinguish with Sentinel-2 optical images. Lastly, the pros and cons of the melt pond detection using satellite altimetry and optical images were discussed.