• Title/Summary/Keyword: Sea Ice

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Dynamic-Thermodynamic Sea Ice Model: Application to Climate Study and Navigation

  • Makshtas, Alexander;Shoutilin, Serger V.;Marchenko, Alexey V.;Bekryaev, Roman V.
    • Journal of Ship and Ocean Technology
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    • v.8 no.2
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    • pp.20-28
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    • 2004
  • A dynamic-thermodynamic sea ice model with 50-km spatial and 24-hour temporal resolution is used to investigate the spatial and long-term temporal variability of the sea ice cover the Arctic Basin. The model satisfactorily reproduces the averaged main characteristics of the sea ice and the sea ice extent in the Arctic Basin and its decrease in early 1990th. At times model allows to suppose partial recovery of sea ice cover in the last years of twenty century. The employment of explicit form for description of ridging gives opportunity to assume that the observed thinning is the result of reduction the intensity of ridging processes and to estimate long-term variability of probability the ridge free navigation in the different parts of the Arctic Ocean including the North Sea Route area.

Status of Korean Research Activity on Arctic Sea Ice Monitoring using KOMPSAT-series Satellite

  • Kim, Hyun-cheol;Chae, Tae-Byeong
    • Journal of the Korean earth science society
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    • v.40 no.4
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    • pp.329-339
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    • 2019
  • Arctic warming is a global issue. The sea ice in the Arctic plays a crucial role in the climate system. We thought that a recent abnormality in many countries in the northern hemisphere could be related to the effects of shrinking sea ice in the Arctic. Many research groups monitor sea ice in the Arctic for climate research. Satellite remote sensing is an integral part of Arctic sea ice research due to the Arctic's large size, making it difficult to observe with general research equipment, and its extreme environment that is difficult for humans to access. Along with monitoring recent weather changes, Korea scientists are conducting polar remote sensing using a Korean satellite series to actively cope with environmental changes in the Arctic. The Korean satellite series is known as KOMPSAT (Korea Multi-Purpose Satellite, Korean name is Arirang) series, and it carries optical and imaging radar. Since the organization of the Satellite Remote Sensing and Cryosphere Information Center in Korea in 2016, Korean research on and monitoring of Arctic sea ice has accelerated rapidly. Moreover, a community of researchers studying Arctic sea ice by satellite remote sensing increased in Korea. In this article, we review advances in Korea's remote sensing research for the polar cryosphere over the last several years. In addition to satellite remote sensing, interdisciplinary studies are needed to resolve the current limitations on research on climate change.

Seasonal and Inter-annual Variations of Sea Ice Distribution in the Arctic Using AMSR-E Data: July 2002 to May 2009 (AMSR-E 위성 데이터를 이용한 북극해빙분포의 계절 변동 및 연 변동 조사: 2002년 7월 ~ 2009년 5월)

  • Yang, Chan-Su;Na, Jae-Ho
    • Korean Journal of Remote Sensing
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    • v.25 no.5
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    • pp.423-434
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    • 2009
  • The Arctic environment is sensitive to change of sea-ice distribution. The increase and decrease of sea ice work to an index of globe warming progress. In order to predict the progress of hereafter earth global warming, continuous monitoring regarding a change of the sea ice area in the Arctic should be performed. The remote sensing based on an artificial satellite is most effective on the North Pole. The sea ice observation using a passive microwave sensor has been continued from 1970's. The determination of sea ice extent and ice type is one of the great successes of the passive microwave imagers. In this paper, to investigate the seasonal and inter-annual variation of sea-ice distribution we used here the sea ice data from July 2002 to May 2009 around the Arctic within $60^{\circ}N$ for the AMSR-E 12.5km sea-ice concentration, a passive microwave sensor. From an early analysis of these data, the arctic sea-ice extent has been steadily decreasing at a rate of about 3.1%, accounting for about $2{\times}10^5\;km^2$, which was calculated for the sea-ice cover reaching its minimum extent at the end of each summer. It is also revealed that this trend corresponds to a decline in the multi-year ice that is affected mainly by summer sea surface and air temperature increases. The extent of younger and thinner (first-year) ice decreased to the 2007 minimum, but rapidly recovered in 2008 and 2009 due to the dramatic loss in 2007. Seasonal variations of the sea-ice extent show significant year-to-year variation in the seasons of January-March in the Barents and Labrador seas and August-October in the region from the East Siberian and Chukchi seas to the North Pole. The spatial distribution of multi-year ice (7-year old) indicates that the perennial ice fraction has rapidly shrunk recently out of the East Siberian, Laptev, and Kara seas to the high region of the Arctic within the last seven years and the Northeast Passage could become open year-round in near future.

Distribution of Antarctic Sea Ice from Satellite Altimetry in the Weddell Sea: Preliminary Results

  • Kim, Jeong-Woo;Hong, Sung-Min;Hwang, Jong-Sun;Yoon, Ho-Il;Lee, Bang-Yong;Kim, Yea-Dong
    • Ocean and Polar Research
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    • v.24 no.3
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    • pp.255-261
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    • 2002
  • We investigated the distribution of sea ice using Topex/Poseidon (T/P) and ERS-1 .ada. altimeter data in the northwest Weddell Sea, Antarctica, between the area $45-75^{\circ}W\;and\;55-66^{\circ}S$. Using the Geo_Bad_1 flag of the Merged GDR of the T/P, we classified the surface into ocean, land, and sea. Total 257 cycles of altimeter measurements between Oct. 1992 and Sep. 1999 (for nearly 2570 days) were used to analyze the distribution of the Antarctic sea ice. We then calculated the surface area of ice coverage using SUTM20 map projection to monitor the periodic variations. Each year, the maximum and minimum coverage of the sea ice were found in late August and February in the study area, respectively. We also studied the sea ice distribution using ERS-1 altimeter data between $45-75^{\circ}W\;and\;55-81.5^{\circ}S$ to compare with the T/P Using the Valid/Invalid flag of the Ocean Product, we analyzed the sea ice distribution between March and August of 1995, which showed very good coherence with the T/P measurements. Our preliminary results showed that the altimeter measurements can be effectively used to monitor the distribution of the sea ice in the polar region. However, the size of radar footprint, typically 2-6km depending on the roughness of the sea surface, may be too big to monitor the sharp boundary between ice and water/land. If more other altimeter mission data with dense coverage such as Geosat GM are analyzed together, this limitation can be significantly improved. If we also combine other microwave remote sensing data such as radiometer, and SSM/I, the result will be significantly enhanced.

Study on icebreaking performance of the Korea icebreaker ARAON in the arctic sea

  • Kim, Hyun-Soo;Lee, Chun-Ju;Choi, Kyung-Sik;Kim, Moon-Chan
    • 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.

Analyzing the Characteristics of Sea Ice Initial Conditions for a Global Ocean and Sea Ice Prediction System, the NEMO-CICE/NEMOVAR over the Arctic Region (전지구 해양·해빙예측시스템 NEMO-CICE/NEMOVAR의 북극 영역 해빙초기조건 특성 분석)

  • Ahn, Joong-Bae;Lee, Su-Bong
    • Journal of the Korean earth science society
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    • v.36 no.1
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    • pp.82-89
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    • 2015
  • In this study, the characteristics of sea ice initial conditions generated from a global ocean and sea ice prediction system, the Nucleus for European Modeling of the Ocean (NEMO) - Los Alamos Sea Ice Model (CICE)/NEMOVAR were analyzed for the period June 2013 to May 2014 over the Arctic region. For the purpose, the observed and reanalyzed data were used to compare with the sea ice initial conditions. Results indicated that the variability of the monthly sea ice extent and thickness in model initial conditions were well represented as compared to the observation, while it was found that the extent and thickness of Arctic sea ice in initial data were narrower and thinner than those in reanalysis and observation for the period. The reason for the narrower sea ice extent in model initial conditions seems to be due to the fact that the initial sea ice concentration at the boundary area of sea ice was about 20 percent less than the reanalysis data. Also, the reason for the thinner sea-ice thickness in the Arctic region is due to the underestimation of Arctic sea ice thickness (about 60 cm) of the model initial conditions in the Arctic Ocean area adjacent to Greenland and Arctic archipelago where thick sea ice appears all the year round.

Performance Assessment of Two-stream Convolutional Long- and Short-term Memory Model for September Arctic Sea Ice Prediction from 2001 to 2021 (Two-stream Convolutional Long- and Short-term Memory 모델의 2001-2021년 9월 북극 해빙 예측 성능 평가)

  • Chi, Junhwa
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.1047-1056
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    • 2022
  • Sea ice, frozen sea water, in the Artic is a primary indicator of global warming. Due to its importance to the climate system, shipping-route navigation, and fisheries, Arctic sea ice prediction has gained increased attention in various disciplines. Recent advances in artificial intelligence (AI), motivated by a desire to develop more autonomous and efficient future predictions, have led to the development of new sea ice prediction models as alternatives to conventional numerical and statistical prediction models. This study aims to evaluate the performance of the two-stream convolutional long-and short-term memory (TS-ConvLSTM) AI model, which is designed for learning both global and local characteristics of the Arctic sea ice changes, for the minimum September Arctic sea ice from 2001 to 2021, and to show the possibility for an operational prediction system. Although the TS-ConvLSTM model generally increased the prediction performance as training data increased, predictability for the marginal ice zone, 5-50% concentration, showed a negative trend due to increasing first-year sea ice and warming. Additionally, a comparison of sea ice extent predicted by the TS-ConvLSTM with the median Sea Ice Outlooks (SIOs) submitted to the Sea Ice Prediction Network has been carried out. Unlike the TS-ConvLSTM, the median SIOs did not show notable improvements as time passed (i.e., the amount of training data increased). Although the TS-ConvLSTM model has shown the potential for the operational sea ice prediction system, learning more spatio-temporal patterns in the difficult-to-predict natural environment for the robust prediction system should be considered in future work.

Prediction of Design Ice Load on Icebreaking Vessels under Normal Operating Conditions (정상운항 상태에서 쇄빙선박에 작용하는 설계 빙하중 추정)

  • Choi, Kyung-Sik;Jeong, Seong-Yeob;Nam, Jong-Ho
    • Journal of the Society of Naval Architects of Korea
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    • v.46 no.6
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    • pp.603-610
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    • 2009
  • Ice load is one of the important design parameters for the construction of icebreaking vessels. In this paper, the design ice load prediction for the icebreaking vessels under normal operating condition in ice-covered sea is discussed. The ice loads under normal operating condition are expected from sea trials in moderate ice conditions. In this sense the extreme ice loads during heavy ramming or accidental collision are not considered. Current study describes the global ice load on the hull of the icebreaking vessels. Available ice load data from full-scale sea trials are collected and analyzed according to various ship-ice interaction parameters including displacement, stem angle, speed of a ship and flexural strength and thickness of sea ice. The ice load prediction formula is compared with the collected full-scale sea trials data and it shows a good agreement.

Correction Methods and Validation for Environmental Conditions in the Ice Field Trials (빙해역 시운전 해석을 위한 환경조건 보정 방법 및 검증)

  • Kim, Hyun Soo
    • Journal of the Society of Naval Architects of Korea
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    • v.56 no.2
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    • pp.117-127
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    • 2019
  • Vessel's ice speed performances will be verified in ice sea trial but environmental conditions of ice fields are changeable according to the weather condition of ice trial area. Speed performance has to correct in the no wind, wave and current etc. after sea trial. Especially finding ice fields which is exact the same as owner's ice thickness and strength requirements is not easy. Therefore speed correction according to environment condition has to be done after sea trial measurements. Correction methods for ice thickness, ice strength, wave, wind and ship draft, trim, ice drift etc. are checked in ice sea trial based on literature review such as ISO standard, ITTC recommendation, journal papers and proceedings of conferences. Possibility of application for current and ice drift correction in ice field are discussed and measuring schemes and procedures of correction methods are described in this paper. All of correction schemes are calculated for 'Araon' which is ice breaking research vessel with Arctic and Antarctic ice field test results. Analyzed results shows that Araon is satisfied with her official ice speed performance of 3 knots with 10MW power at 1m ice thickness, 570kPa ice flexural strength.

Study on effective band of advanced microwave scanning radiometer (AMSR) for observing first year sea ice in the Okhotsk Sea by airborne microwave radiometer (AMR)

  • Nakayama, Masashige;Nishio, Fumihiko;Tanikawa, Tomonori;Cho, Kohei;Shimoda, Haruhisa
    • Proceedings of the KSRS Conference
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    • 1999.11a
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    • pp.456-461
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    • 1999
  • It is very important for monitoring the interannual variability of sea ice extents in the Okhotsk Sea because the global warming has firstly appeared around the Okhotsk Sea, locating around the southernmost region of sea ice cover in the Northern Hemisphere. In order to develop the sea ice concentration algorithm by microwave sensors onboard satellite, electromagnetic properties of sea ice in the Okhotsk Sea, therefore, were observed by airborne microwave radiometer (AMR), which has the same frequencies as AMSR (Advanced Microwave Scanning Radiometer), ADEOS-II, launching on November, 2000. On this study, it is discussed how to make the image of AMR-EFOV and the video image with nadir angle under flight at the same time, and superimpose the brightness temperature data by AMR-EFOV on the video mosaiced images. For comparing SPOT image, it is clearly that the variation of brightness temperature is small in 89GHz V-pol without the sea ice types and increase at the lower frequency-band.

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