• Title/Summary/Keyword: Multi-year ice

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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.

Relationship between Spring Bloom and Sea Ice in the Northern East Sea

  • Park, Kyung-Ae;Choi, Hwa-Jeong
    • 한국지구과학회:학술대회논문집
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    • 2010.04a
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    • pp.134-134
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    • 2010
  • Sea ices at the Tatarskiy Straitin the East/Japan Sea appear from November to April. Cold and fresh water, melted from the sea ices, may contain nutrients which are indispensable to spring bloom of phytoplankton and may provide a preferable condition to the spring bloom through changes in vertical structure of water column and stratification. Relation between the spring bloom along the Primorye coast and sea ices in the Tatarskiy Strait were investigated using multi-satellite multi-sensor data; ten-year SeaWiFS chlorophyll-a concentration data and PAR data, sea surface temperatures from NOAA/AVHRR, sea ice concentration and near-surface wind speed data from DMSP/SSMI, near-surface wind vectors from QuikSCAT, and others. We provided evidences of southwestward flowing cold water masses from sea ice and its relation of chlorophyll-a concentration. This study showed that year-to-year variations of chlorophyll-a concentration in spring were positively correlated with those of sea ice concentrations at the Tatarskiy Strait.

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A Measurement of Sea Ice Properties at Chukchi Borderland During the Summer (여름철 Chukchi Borderland 부근 해빙 재료특성 계측)

  • Jeong, Seong-Yeob;Choi, Gul-Gi
    • Journal of the Society of Naval Architects of Korea
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    • v.49 no.1
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    • pp.45-51
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    • 2012
  • Sea ice properties have been considered a key indicator in the structural design criteria of icebreaking vessels and arctic offshore platforms to estimate design ice load and resistance for their safety management in Arctic Ocean. A measurement study of sea ice properties was conducted during July to August of 2011 with the Korean icebreaking research vessel "Araon" around Chukchi Borderland. The sea ice concentration appears to be rapidly decreasing during this cruise. Ice condition seems to be thick second-year ice and multi-year ice and then, a lot of melt ponds were observed in the surface of ice floe. Calculated flexural strength of sea ice was about 250~550kPa, ice thickness was roughly 1.3~3.0m. In this research we performed field experiment to measure ice temperature along the depth, thickness, density, salinity, brine volume ratio and crystal structure. Apparent conductivities derived with the electromagnetic induction instrument were compared to drill hole measurement results and accuracy of sea ice thickness estimation formula was discussed.

A Study on Classifying Sea Ice of the Summer Arctic Ocean Using Sentinel-1 A/B SAR Data and Deep Learning Models (Sentinel-1 A/B 위성 SAR 자료와 딥러닝 모델을 이용한 여름철 북극해 해빙 분류 연구)

  • Jeon, Hyungyun;Kim, Junwoo;Vadivel, Suresh Krishnan Palanisamy;Kim, Duk-jin
    • 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.

Classification for Landfast Ice Types in the Greenland of the Arctic by Using Multifrequency SAR Images (다중주파수 SAR 영상을 이용한 북극해 그린란드 정착빙 분류)

  • Hwang, Do-Hyun;Hwang, Byongjun;Yoon, Hong-Joo
    • Korean Journal of Remote Sensing
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    • v.29 no.1
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    • pp.1-9
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    • 2013
  • To classify the landfast ice in the north of the Greenland, observation data, multifrequency Synthetic Aperture Radar (SAR) images and texture images were used. The total four types of sea ice are first year ice, highly deformed ice, ridge and moderately deformed ice. The texture images that were processed by K-means algorithm showed higher accuracy than the ones that were processed by SAR images; however, overall accuracy of maximum likelihood algorithm using texture images did not show the highest accuracy all the time. It turned out that when using K-means algorithm, the accuracy of the multi SAR images were higher than the single SAR image. When using the maximum likelihood algorithm, the results of single and multi SAR images are differ from each other, therefore, maximum likelihood algorithm method should be used properly.

EFFECTS OF ATMOSPHERIC WATER AND SURFACE WIND ON PASSIVE MICROWAVE RETRIEVALS OF SEA ICE CONCENTRATION: A SIMULATION STUDY

  • Shin, Dong-Bin;Chiu, Long S.;Clemente-Colon, Pablo
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.892-895
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    • 2006
  • The atmospheric effects on the retrieval of sea ice concentration from passive microwave sensors are examined using simulated data typical for the Arctic summer. The simulation includes atmospheric contributions of cloud liquid water and water vapor and surface wind on surface emissivity on the microwave signatures. A plane parallel radiative transfer model is used to compute brightness temperatures at SSM/I frequencies over surfaces that contain open water, first-year (FY) ice and multi-year (MY) ice and their combinations. Synthetic retrievals in this study use the NASA Team (NT) algorithm for the estimation of sea ice concentrations. This study shows that if the satellite sensor’s field of view is filled with only FY ice the retrieval is not much affected by the atmospheric conditions due to the high contrast between emission signals from FY ice surface and the signals from the atmosphere. Pure MY ice concentration is generally underestimated due to the low MY ice surface emissivity that results in the enhancement of emission signals from the atmospheric parameters. Simulation results in marginal ice areas also show that the atmospheric and surface effects tend to degrade the accuracy at low sea ice concentration. FY ice concentration is overestimated and MY ice concentration is underestimated in the presence of atmospheric water and surface wind at low ice concentration. In particular, our results suggest that strong surface wind is more important than atmospheric water in contributing to the retrieval errors of total ice concentrations over marginal ice zones.

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Comparison of SSM/I Sea Ice Concentration with Kompsat-1 EOC Images of the Arctic and Antarctic (북극과 남극의 SSM/I Sea Ice Concentration과 Kompsat-1 EOC 영상의 비교)

  • Han Hyang-Sun;Lee Hoon-Yol
    • Proceedings of the KSRS Conference
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    • 2006.03a
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    • pp.153-156
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    • 2006
  • 북극과 남극의 해빙을 촬영한 Kompsat-1 EOC 영상을 SSM/I Sea Ice Concentration(SIC)과 비교하였다. EOC 영상은 2005년 $7{\sim}8$월 북극 해빙지역의 가장자리를 지나는 10개 궤도(624 영상)와 $9{\sim}11$월 남극대륙의 가장자리를 지나는 11개 궤도(676 영상)에서 얻어졌다. 그 중 구름의 영향이 없는 약 12%의 영상으로부터 감독분류와 육안분류를 통해 Multi-year ice와 First-year ice(M+F), Young ice(Y), New ice(N)로 해빙의 유형을 구분하여 SIC를 계산하였으며, 이를 NASA Team Algorithm(NTA)으로 계산된 SSM/I SIC와 비교하였다. 북극의 여름철에는 해빙의 시공간적 변화가 매우 크기 때문에 EOC SIC(M+F+Y+N)와 SSM/I SIC의 상관계수는 0.671로 잘 일치하지 않았다. 남극의 봄철에 N을 제외한 EOC SIC(M+F+Y)의 경우 SSM/I SIC와 0.873의 높은 상관계수를 가졌다. 이로부터 NTA로 계산된 남극의 SSM/I SIC가 M과 F를 비롯하여 Y도 포함하는 것을 알 수 있었다.

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Rediscovery of the Arctic: A New Arena of Competition for Natural Resources in the 21st Century? (북극의 재발견: 국제 자원경쟁의 새로운 각축장?)

  • Lee, Seo-Hang
    • Strategy21
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    • s.30
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    • pp.200-235
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    • 2012
  • Over the past few years, due to the climate change of the earth, the Arctic's sea ice cover is undergoing a historic transformation - thinning, extent reduction in all seasons, and mitigation in the area of multi-year ice in the central Arctic Ocean. These changes allow for increases in maritime access throughout the Arctic Ocean and for potential longer seasons of navigation and possibly transarctic voyage in the summer. These changes also allow more exploration for oil, gas, and other minerals. The Arctic is now an archetype of the complex, multi-dimensional global problems of the twenty-first century. Military security, environmental security, and economic security interact. The potentially enormous economic stakes, sufficient to change the strategic balance among the states of the region, set off competitive pressures for national advantage. Korea, which is heavily dependent upon the sea lane in terms of transportation of its exports and imports, is very much interested in the Arctic sea routes. Korea believes that the Artic sea route, particularly the Northern Sea Route (NSR), could serve as a new useful sea lane, which will enable shorter times between East Asia and Europe, thus resulting in substantial cost saving for ship operators. In addition to shipping, Korea is interested in other Arctic-related maritime industries. Korea, as a leading shipbuilder in the global market, is interested in building ice breakers, drill ships, and other vessels which can contribute to safe operation in Arctic resource development and exploration. Korea, as one of the future stakeholders in Arctic maritime activities, should be ready to foster international cooperation in the region.

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Recent Ultrasonic Guided Wave Inspection Development Efforts

  • Rose, Joseph L.;Tittmann, Bernhard R.
    • Journal of the Korean Society for Nondestructive Testing
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    • v.21 no.4
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    • pp.371-382
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    • 2001
  • The recognition of such natural wave guides as plates, rods, hollow cylinders, multi-layer structures or simply an interface between two materials combined with an increased understanding of the physics and wave mechanics of guided wave propagation has led to a significant increase in the number of guided wave inspection applications being developed each year. Of primary attention Is the ability to inspect partially hidden structures, hard to access areas, and teated or insulated structures. An introduction to some physical consideration of guided waves followed by some sample problem descriptions in pipe, ice detection, fouling detection in the foods industry, aircraft, tar coated structures and acoustic microscopy is presented in this paper. A sample problem in Boundary Element Modeling is also presented to illustrate the move in guided wave analysis beyond detection and location analysis to quantification.

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Simulation of Past 6000-Year Climate by Using the Earth System Model of Intermediate Complexity LOVECLIM (중간복잡도 지구시스템모델 LOVECLIM을 이용한 과거 6천년 기후 변화 모의)

  • Jun, Sang-Yoon
    • Atmosphere
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    • v.29 no.1
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    • pp.87-103
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    • 2019
  • This study introduces the overall characteristics of LOVECLIM version 1.3, the earth system model of intermediate complexity (EMIC), including the installation and operation processes by conducting two kinds of past climate simulation. First climate simulation is the equilibrium experiment during the mid-Holocene (6,000 BP), when orbital parameters were different compared to those at present. The overall accuracy of simulated global atmospheric fields by LOVECLIM is relatively lower than that in Coupled Model Intercomparison Project phase 5 (CMIP5) and Paleoclimate modelling Intercomparison Project phase 3 (PMIP3) simulations. However, surface temperature over the globe, the 800 hPa meridional wind over the mid-latitude coastal region, and the 200 hPa zonal wind from LOVECLIM show similar spatial distribution to those multi-model mean of CMIP5/PMIP3 climate models. Second one is the transient climate experiment from mid-Holocene to present. LOVECLIM well captures the major differences in surface temperature between preindustrial and mid-Holocene simulations by CMIP5/PMIP3 multi-model mean, even though it was performed with short integration time (i.e., about four days in a single CPU environment). In this way, although the earth system model of intermediate complexity has a limit due to its relatively low accuracy, it can be a very useful tool in the specific research area such as paleoclimate.