• Atmosphere
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• v.29 no.4
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• pp.367-380
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• 2019

Global warming causes various problems such as the increase of the sea surface temperature, the change of coastlines, ocean acidification and sea level rise. Sea level rise is an especially critical threat to coastal regions where massive population and infrastructure reside. Sea level change is affected by thermal expansion and mass increase. This study projected future sea level changes in the 21st century using the HadGEM2-AO with RCP8.5 scenario. In particular, sea level change due to water mass input from ice-sheets and glaciers melting is studied. Sea level based on surface mass balance of Greenland ice-sheet and Antarctica ice-sheet rose 0.045 m and -0.053 m over the period 1986~2005 to 2081~2100. During the same period, sea level owing to dynamical change on Greenland ice-sheet and Antarctica ice-sheet rose 0.055 m and 0.03 m, respectively. Additionally, glaciers melting results in 0.145 m sea level rise. Although most of the projected sea level changes from HadGEM2-AO are slightly smaller than those from 21 ensemble data of CMIP5, both results are significantly consistent each other within 90% uncertainty range of CMIP5.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.633-633
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• 2002

We investigated the distributions of sea ice using various microwave remote sensing techniques in the part of Drake passage, Antarctica, between the area 45-75$^{\circ}$W and 55-66$^{\circ}$S. We used Topex/Poseidon(T/P) radar altimeter, ERS-1 altimeter, ERS-2 scatterometer, Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR), and DMSP Special Sensor Microwave/Imager(SSM/I) data. The sea ice distributions were estimated between May and Jun., 1995 and Oct. and Nov., 1998. The two altimeter measurements (T/P and ERS-1) showed good coherence with the results from the radiometer data in the given period when the ice concentration of 20% and greater was selected. The scatterometer data also showed good correlation with altimetry-implied sea ice surface. The maximum and minimum values of sea ice distribution were appeared in Aug. and Feb., respectively. In general, the sea ice distributions estimated from radar altimeter, radioneter, and scatterometer are well correlated.

• Ocean and Polar Research
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• v.40 no.4
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• pp.281-288
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• 2018

The transmission of solar light according to the distribution of chromophoric dissolved organic matter (CDOM) was measured in the Pacific Arctic Ocean. The Research Vessel Araon visited the ice-covered East Siberian and Chukchi Seas in August 2016. In the Arctic, solar [ultraviolet-A (UV-A), ultraviolet-B (UV-B), and photosynthetically active radiation (PAR)] radiation reaching the surface of the ocean is primarily protected by the distribution of sea ice. The transmission of solar light in the ocean is controlled by sea ice and dissolved organic matter, such as CDOM. The concentration of CDOM is the major factor controlling the penetration depth of UV radiation into the ocean. The relative CDOM concentration of surface sea water was higher in the East Siberian Sea than in the Chukchi Sea. Due to the distribution of CDOM, the penetration depth of solar light in the East Siberian Sea (UV-B, $9{\pm}2m$; UV-A, $13{\pm}2m$; PAR, $36{\pm}4m$) was lower than in the Chukchi Sea (UV-B, $15{\pm}3m$; UV-A, $22{\pm}3m$; PAR, $49{\pm}3m$). Accelerated global warming and the rapid decrease of sea ice in the Arctic have resulted in marine organisms being exposed to increased harmful UV radiation. With changes in sea ice covered areas and concentrations of dissolved organic matter in the Arctic Ocean, marine ecosystems that consist of a variety of species from primary producers to high-trophic-level organisms will be directly or indirectly affected by solar UV radiation.

• Journal of Ocean Engineering and Technology
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• v.35 no.5
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• pp.369-381
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• 2021

The International Ice Patrol (IIP) was established after the Titanic collided with an iceberg off the eastern coast of Canada in 1912 and sank, killing more than 1,500 people. Recently, the IIP has analyzed satellite images and provided safe operation information to vessels by tracking the occurrence and movement of icebergs. A large number of recent arctic studies mainly deal with sea ice formed by freezing seawater related to sea routes and resource development. The iceberg that collided with the Titanic was land-based ice that dislodged from a glacier and fell into the sea. The properties of these two types of ice are different. In addition, vessels operating in ice-covered waters such as the Arctic sea have an ice-breaking function or minimum ice-strengthened functions. Ships operating on transatlantic routes including the eastern coast of Canada do not necessarily require ice-strengthened functions. Hundreds to thousands of icebergs are discovered each year near the area where the Titanic sank. In this study, the status of ship-iceberg collision accidents was investigated to provide useful information to researchers, and the physical and mechanical characteristics of icebergs were investigated and summarized.

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.999-1009
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• 2019

The importance of high-resolution sea ice maps of the Arctic Ocean is increasing due to the possibility of pioneering North Pole Routes and the necessity of precise climate prediction models. In this study,sea ice classification algorithms for two deep learning models were examined using Sentinel-1 A/B SAR data to generate high-resolution sea ice classification maps. Based on current ice charts, three classes (Open Water, First Year Ice, Multi Year Ice) of training data sets were generated by Arctic sea ice and remote sensing experts. Ten sea ice classification algorithms were generated by combing two deep learning models (i.e. Simple CNN and Resnet50) and five cases of input bands including incident angles and thermal noise corrected HV bands. For the ten algorithms, analyses were performed by comparing classification results with ground truth points. A confusion matrix and Cohen's kappa coefficient were produced for the case that showed best result. Furthermore, the classification result with the Maximum Likelihood Classifier that has been traditionally employed to classify sea ice. In conclusion, the Convolutional Neural Network case, which has two convolution layers and two max pooling layers, with HV and incident angle input bands shows classification accuracy of 96.66%, and Cohen's kappa coefficient of 0.9499. All deep learning cases shows better classification accuracy than the classification result of the Maximum Likelihood Classifier.

• Journal of the Society of Naval Architects of Korea
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• v.51 no.6
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• pp.489-494
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• 2014

Estimation of correct ice load under various operating conditions is important during the design and the operation stages of an icebreaker. Normal operating conditions are expected from the official field ice trials and also from general ice transit action. In this paper ice load for the Korean icebreaking research vessel, ARAON, under normal operating condition, is discussed. Published ice load data from full-scale sea trials of six icebreakers were analysed to derive an empirical ice load prediction formula. The IBRV ARAON had sea ice trials during 2010 and 2012 summer season. Strain gauge signal were recorded during her icebreaking voyage and the measured strain data were converted to the equivalent hull stress values. The effect of ARAON's speed in ice and the hull stresses are investigated. By comparing the empirical formula and ice load calculation based von measured data, it is recommended to use the empirical ice load estimation formula for the initial design stage.

• Journal of Advanced Research in Ocean Engineering
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• v.1 no.1
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• pp.25-35
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• 2015

This study presents the analysis of relationship between ship speed and local ice load on the Korean Icebreaker ARAON. The relationship curves were made from the data obtained at two areas: the Arctic and the Antarctic; and for two operation condition: the icebreaking condition in sea ice trial and general operation in ice covered sea. The strain data were converted to the equivalent stress value, and the influence of ship speed on the local ice load was analyzed and compared each other. These analysis results are useful in working on a statistically valid hull design approach.

• Journal of the Korean Institute of Navigation
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• v.11 no.1
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• pp.107-144
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• 1987

In cold season, ice accretion on ship, drift ice, NW winter monsoon, developed extratropical cyclones and associated cold fronts, in warm season, tropical cyclones and dense sea fogs, are encountered very frequently in the North Pacific, especially in the northwest part of it. The two areas, namely, the northwest part of the North Pacific and Burmuda Triangle in the North Atlantic are generally known as most dangerous areas in the world because its high incidence of sea cascualities. In recent years, the small fisherboats operating in the northern seas were frequently sunk in a group as they encountered ice accretion or drift ice. And ocean going vessels were also sunk frequently due to strong winds and very high seas in winter monsoon or developed cyclones and cold fronts. The purpose of this paper is to analyze the real state of heavy weather conditions such as ice accretion on ship drift, ice, typhoons and sea fogs, and also to analyse the effect of these heavy weather phenomena on the vessels at sea, thus helping mariners operate in such heavy weather conditions.

• Journal of applied mathematics & informatics
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• v.26 no.3_4
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• pp.519-530
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• 2008

This paper studies the multi-domain coupled system of one dimensional Arctic temperature field and establishes identification model about the thermodynamic parameters of sea ice (heat storage capacity, density and conductivity) by the so-called output least-square estimate according to the temperature data acquired by a monitor buoy installed in the Arctic ocean. By the optimal control theory, the existence and dependability of weak solution and the identifiability of identification model have been given. Moreover, necessary optimality condition is proposed. Furthermore, the optimal algorithm for the identification model is constructed. By using the optimal thermodynamic parameters of Arctic sea ice, the numerical simulation is implemented, and the numerical results of temperature distribution of Arctic sea ice are demonstrated.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1215-1227
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• 2018

Sea ice motion is an important factor for assessing change of sea ice because the motion affects to not only regional distribution of sea ice but also new ice growth and thickness of ice. This study presents an application of multi-temporal high-resolution optical satellites images obtained from Korea Multi-Purpose Satellite-2 (KOMPSAT-2) and Korea Multi-Purpose Satellite-3 (KOMPSAT-3) to measure sea ice motion using SIFT (Scale-Invariant Feature Transform), SURF (Speeded Up Robust Features) and ORB (Oriented FAST and Rotated BRIEF) feature tracking techniques. In order to use satellite images from two different sensors, spatial and radiometric resolution were adjusted during pre-processing steps, and then the feature tracking techniques were applied to the pre-processed images. The matched features extracted from the SIFT showed even distribution across whole image, however the matched features extracted from the SURF showed condensed distribution of features around boundary between ice and ocean, and this regionally biased distribution became more prominent in the matched features extracted from the ORB. The processing time of the feature tracking was decreased in order of SIFT, SURF and ORB techniques. Although number of the matched features from the ORB was decreased as 59.8% compared with the result from the SIFT, the processing time was decreased as 8.7% compared with the result from the SIFT, therefore the ORB technique is more suitable for fast measurement of sea ice motion.