• Journal of the Society of Naval Architects of Korea
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• v.55 no.3
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• pp.236-242
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• 2018

Damage due to ice collision is the most serious threat for the structural safety of ships operating in arctic region. Since such hull damages are usually caused by the collision of floating ice at excessive voyage speed of ships, the authorities responsible for the shipping at arctic sea are required to provide the speed limit for safe voyage, so-called safe speed. In countries near arctic ocean, such as Canada and Russia, empirical methods to determine the safe speed of ships based on their long experience of arctic voyage have been established and applied them in the real arctic navigation. However, in Korea, it is not easy to accumulate the arctic voyage experience and related technical database, so it seems to be a realistic approach to adopt a safe voyage speed estimating method in arctic sea based on the ice collision simulation technology using the nonlinear finite element analysis. The aim of this study is to develop a technique for estimating the safe voyage speed of vessels operating at arctic sea through the ice collision analysis, In order to achieve this goal, the standard procedure of the ice collision analysis is dealt with and example analysis was carried out and the results were considered. To investigate the validity of developed method, POLARIS system proposed by IMO was studied for comparison.

• Journal of the Korean Professional Engineers Association
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• v.46 no.1
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• pp.45-48
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• 2013

Arctic shipping via the Northern Sea Route could save about 40% of the sailing distance and shorten more than 10 days of the sailing time from Asia to Europe comparing to the existing Southern route through the Suez Canal. Since commercial voyage along the Northern Sea Route and resource development in the Arctic sea will be realized in the near future, Korea needs to challenge Arctic shipping and resource development in the strategic point of view.

• Journal of Ocean Engineering and Technology
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• v.28 no.6
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• pp.527-532
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• 2014

The thickness of Arctic sea ice is a particularly significant factor in Arctic shipping and other ice-related research areas such as scientific sea ice investigations and Arctic engineering. In this study, the relation between the measured sea ice thickness and freeboard on the Chukchi and Beaufort Seas during the 2010 and 2011 Arctic cruise of the icebreaking research vessel "Araon" were considered. An assumption of hydrostatic equilibrium was used to estimate the ice thickness as a function of the freeboard. Then, to examine the degree of error, a sensitivity analysis of the thickness estimation of the sea ice was conducted. The error in the density and depth of the snow and the error in the density of the seawater were subordinate parameters, but the density of the ice and the freeboard were the primary parameters in the error calculation. The presented relation formula showed fairly close agreement between the calculated and measured results at a freeboard of >0.24 m.

• Atmosphere
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• v.32 no.4
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• pp.297-306
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• 2022

We examined potential seasonal prediction of the Korean surface temperature using the relationships between the Arctic Sea Ice Area (SIA) in autumn and the temperature in the following July and February at 850 hPa in East Asia (EA). The Surface Air Temperature (SAT) over Korea shows a similar relationship to that for EA. Since 2007, reduction of autumn SIA has been followed by warming in Korea in July. The regional distribution shows strong correlations in the southern and eastern coastal areas of Korea. The correlations in the sea surface temperature shows the maximum values in July around the Korean Peninsula, consistent with the coastal regions in which the maximum correlations in the Korean SAT are seen. In February, the response of the SAT to the SIA is the opposite of that for the July temperature. The autumn sea ice reduction is followed by cooling over Korea in February, although the magnitude is small. Cooling in the Korean Peninsula in February may be related to planetary wave-like features. Examining the autumn Arctic sea ice variation would be helpful for seasonal prediction of the Korean surface temperature, mostly in July and somewhat in February. Particularly in July, the regression line would be useful as supplementary information for seasonal temperature prediction.

• Korea Trade Review
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• v.44 no.4
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• pp.115-128
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• 2019

This article analyzes issues regarding the economic development of the arctic area with the aim of finding ways to help solve the problems and to support sustainable economic development of the arctic area. Some proposals are introduced for establishing a sound legal infrastructure of the Korea-Russia economic development of the arctic area. As Russia develops the Arctic area and the route through the Arctic area, Korea will gain the possibility of transportation efficiency, vitalization of international transaction, and finding new markets. Resource development in the North Pole is ongoing, with matching international transaction and economic benefits. To reflect the Korea-Russia interests and to sustain the effect, the legal infrastructure is inevitable. For example, it would be reinforced by pushing forward the Korea-Russia FTA. The legal infrastructure for economic cooperation of Korea and Russia has to reflect that 'the development of the Arctic area and making the route through the Arctic area' should increase the sustainability and vitality of international transaction. The legal infrastructure for economic benefits can also help mitigating non-economic arguments of international community such as the security risk in the Korean-peninsula and around the world.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1273-1282
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• 2018

Recently, active research on the Arctic Ocean has been conducted due to the influence of global warming and new Arctic ship route. Although previous studies already calculated quantitative extent of sea ice using passive microwave radiometers, melting at the edge of sea ice and surface roughness were hardly considered due to low spatial resolution. Since Sentienl-1A/B data in Extended Wide (EW) mode are being distributed as free of charge and bulk data for Arctic sea can be generated during a short period, the entire Arctic sea ice data can be covered in high spatial resolution by mosaicking bulk data. However, Sentinel-1A/B data in EW mode, especially in HV polarization, needs significant radiometric correction for further classification. Thus, in this study, we developed algorithms that can correct thermal noise and scalloping effects, and confirmed that Arctic sea ice and open-water were well classified using the corrected dual-polarization SAR data.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1261-1272
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• 2018

It is important to measure the Arctic surface air temperature because it plays a key-role in the exchange of energy between the ocean, sea ice, and the atmosphere. Although in-situ observations provide accurate measurements of air temperature, they are spatially limited to show the distribution of Arctic surface air temperature. In this study, we proposed machine learning-based models to estimate the Arctic surface air temperature in summer based on buoy data and Advanced Microwave Scanning Radiometer 2 (AMSR2)satellite data. Two machine learning approaches-random forest (RF) and support vector machine (SVM)-were used to estimate the air temperature twice a day according to AMSR2 observation time. Both RF and SVM showed $R^2$ of 0.84-0.88 and RMSE of $1.31-1.53^{\circ}C$. The results were compared to the surface air temperature and spatial distribution of the ERA-Interim reanalysis data from the European Center for Medium-Range Weather Forecasts (ECMWF). They tended to underestimate the Barents Sea, the Kara Sea, and the Baffin Bay region where no IABP buoy observations exist. This study showed both possibility and limitations of the empirical estimation of Arctic surface temperature using AMSR2 data.

• Ocean and Polar Research
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• v.32 no.4
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• pp.379-386
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• 2010

This study examines changes in the Arctic sea ice associated with global warming by analyzing the climate coupled general circulation models (CGCMs) provided in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. We selected nine models for better performance under 20th century climate conditions based on two different criteria, and then estimated the changes in sea ice extent under global warming conditions. Under projected 21st century climate conditions, all models, with the exception of the GISS-AOM model, project a reduction in sea ice extent in all seasons. The mean reduction in summer (-63%) is almost four times larger than that in winter (-16%), resulting an enhancement of seasonal variations in sea ice extent. The difference between the models, however, becomes larger under the 21st century climate conditions than under 20th century conditions, thus limiting the reliability of sea-ice projections derived from the current CGCMs.

• Atmosphere
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• v.28 no.1
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• pp.15-24
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• 2018

Sea ice plays an important role in modulating surface conditions at high and mid-latitudes. It reacts rapidly to climate change, therefore, it is a good indicator for capturing these changes from the Arctic climate. While many models have been used to study the predictability of climate variables, their performance in predicting sea ice was not well assessed. This study examines the predictability of the Arctic sea ice extent from ensemble prediction systems. The analysis is focused on verification of predictability in each model compared to the observation and prediction in particular, on lead time in Sub-seasonal to Seasonal (S2S) scales. The S2S database now provides quasi-real time ensemble forecasts and hindcasts up to about 60 days from 11 centers: BoM, CMA, ECCC, ECMWF, HMCR, ISAC-CNR, JMA, KMA, Meteo France, NCEP and UKMO. For multi model comparison, only models coupled with sea ice model were selected. Predictability is quantified by the climatology, bias, trends and correlation skill score computed from hindcasts over the period 1999 to 2009. Most of models are able to reproduce characteristics of the sea ice, but they have bias with seasonal dependence and lead time. All models show decreasing sea ice extent trends with a maximum magnitude in warm season. The Arctic sea ice extent can be skillfully predicted up 6 weeks ahead in S2S scales. But trend-independent skill is small and statistically significant for lead time over 6 weeks only in summer.

• International Journal of Naval Architecture and Ocean Engineering
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• v.3 no.3
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• pp.208-215
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• 2011

A full-scale field trial in ice-covered sea is one of the most important tasks in the design of icebreaking ships. The first Korean icebreaking research vessel 'ARAON', after her delivery in late 2009, had a sea ice field trial in the Arctic Sea during July-August, 2010. This paper describes the test procedures and data analysis on the icebreaking performance of the IBRV ARAON. The data gathered from the icebreaking performance test in the Chukchi Sea and the Beaufort Sea during the Arctic voyage of ARAON includes the speed and engine power of the ship as well as sea ice thickness and strength data. The air temperature, wind speed and heading of the ship were also measured during each sea ice trial. The ARAON was designed to break 1 m thick level ice with a flexural strength of 630kPa at a continuous speed of 3knots. She is registered as a KR POLAR 10 class ship. The principal dimensions of ARAON are 110 m, 19 m and 6.8 m in length, breadth and draft respectively. She is equipped with four 3,500kW diesel-electric main engines and two Azipod type propulsion motors. Four sea ice trials were carried out to understand the relationship between the engine power and the ship speed, given the Arctic ice condition. The analysis shows that the ARAON was able to operate at 1.5knots in a 2.5m thick medium ice floe condition with the engine power of 5MW, and the speed reached 3.1 knots at the same ice floe condition when the power increased to 6.6MW. She showed a good performance of speed in medium ice floe compared to the speed performance in level ice. More detailed analysis is summarized in this paper.