• Atmosphere
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• v.24 no.4
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• pp.555-563
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• 2014

The impacts of dynamic and thermodynamic schemes used in the Community Ice CodE (CICE), the Los Alamos sea ice model, on sea ice concentration, extent and thickness over the Arctic and Antarctic regions are evaluated. Using the six dynamic and thermodynamic schemes such as sea ice strength scheme, conductivity scheme, albedo type, advection scheme, shortwave radiation method, and sea ice thickness distribution approximation, the sensitivity experiments are conducted. It is compared with a control experiment, which is based on the fixed atmospheric and oceanic forcing. For sea ice concentration and extent, it is found that there are remarkable differences between each sensitivity experiment and the control run over the Arctic and Antarctic especially in summer. In contrast, there are little seasonal variations between the experiments for sea ice thickness. In summer, the change of the albedo type has the biggest influence on the Arctic sea ice concentration, and the Antarctic sea ice concentration has a greater sensitivity to not only the albedo type but also advection scheme. The Arctic sea ice thickness is significantly affected by the albedo type and shortwave radiation method, while the Antarctic sea ice thickness is more sensitive to sea ice strength scheme and advection scheme.

• 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.

• Journal of Information Processing Systems
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• v.14 no.4
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• pp.1010-1032
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• 2018

Recent advances in medical science have made people live longer, which has affected many aspects of life, such as caregiver burden, increasing cost of healthcare, increasing number of disabled and depressive disorder persons, and so on. Researchers are now focused on elderly living assistance services in smart home environments. In recent years, assisted living technologies have rapidly grown due to a faster growing aging society. Many smart devices are now interconnected within the home network environment and such a home setup supports collaborations between those devices based on the Internet of Things (IoT). One of the major challenges in providing elderly living assistance services is to consider each individual's requirements of different needs. In order to solve this, the virtualization of physical things, as well as the collaboration and composition of services provided by these physical things should be considered. In order to meet these challenges, Web of Objects (WoO) focuses on the implementation aspects of IoT to bring the assorted real world objects with the web applications. We proposed a semantic modelling technique for manual and semi-automated service composition. The aim of this work is to propose a framework to enable RESTful web services composition using semantic ontology for elderly living assistance services creation in WoO based smart home environment.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.1
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• pp.127-132
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• 2018

One of the key issues in the Unmanned Aerial Vehicle (: UAV) technology is the collision avoidance. Specifically, the collision avoidance among multiple UAVs is critical to expand UAV applications to civil sector where large number of UAVs could be operated in the limited space. In this paper, we introduce a collision avoidance scheme based on Flying Ad Hoc Network (: FANET). The proposed scheme adopts collision avoidance mechanism used in wireless data communication networks. Using this scheme UAVs can not only communicate conventional user information, but also share flight information to avoid collision.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.236-236
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• 2016

현재 댐운영 계획 수립 시 매월 유지해야 하는 저수량의 범위를 나타낸 기준수위가 사용되고 있으며 매년 홍수기 말에 현재의 수문 상황과 장래의 전망을 통한 시기별 연간, 월간 댐운영 계획을 수립하고 있다. 물관리의 이수측면에서 댐수위 운영계획 수립과 홍수기 운영목표 수위를 결정하는데 활용하기 위해서는 계절단위, 연단위의 기상정보가 필요하다. 본 연구에서는 기상청에서 운영하고 제공하는 전지구 계절예측시스템 GloSea5(Global Seasonal forecasting system version 5)자료를 활용하여 금강유역에 적용하고자 하였다. GloSea5는 전지구계절예측시스템으로 대기(UM), 지면(JULES), 해양(NEMO), 해빙(CICE)모델이 서로 결합되어 하나의 시스템으로 구성되어 있으며 공간 수평해상도는 N216($0.83^{\circ}{\times}0.56^{\circ}$)으로 중위도에서 약60km이다. Hindcast자료는 유럽중기예보센터(ECMWF)에서 생산된 ERA-Interim 재분석장을 대기 모델의 초기장으로 사용하며 기간은 1996~2009년의 총 14년이다. 예보자료의 검증은 예보의 질을 결정하는 과정으로 Brier Skill Score (BSS), Reliability Diagrams, Relative Operating, Characteristics (ROC)등을 통해 정확성과 오차에 의한 예보의 성능을 검증하였다. 또한 Glosea5의 통계적 상세화를 수행하여 다양한 변수가 갖는 계통적인 지역 오차를 보정함으로써 자료의 신뢰도를 향상시키고자 하였으며 이는 이후 수문모델과의 연계 시 보다 정확하고 효율적인 댐운영에 활용할 수 있는 기후예측정보를 제공할 수 있을 것으로 판단된다.

• Atmosphere
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• v.27 no.3
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• pp.261-276
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• 2017

The main objectives of this study are to introduce Global Seasonal forecasting system version5 (GloSea5) of KMA and to evaluate the performance of ensemble prediction of system. KMA has performed an operational seasonal forecast system which is a joint system between KMA and UK Met office since 2014. GloSea5 is a fully coupled global climate model which consists of atmosphere (UM), ocean (NEMO), land surface (JULES) and sea ice (CICE) components through the coupler OASIS. The model resolution, used in GloSea5, is N216L85 (~60 km in mid-latitudes) in the atmosphere and ORCA0.25L75 ($0.25^{\circ}$ on a tri-polar grid) in the ocean. In this research, we evaluate the performance of this system using by RMSE, Correlation and MSSS for ensemble mean values. The forecast (FCST) and hindcast (HCST) are separately verified, and the operational data of GloSea5 are used from 2014 to 2015. The performance skills are similar to the past study. For example, the RMSE of h500 is increased from 22.30 gpm of 1 week forecast to 53.82 gpm of 7 week forecast but there is a similar error about 50~53 gpm after 3 week forecast. The Nino Index of SST shows a great correlation (higher than 0.9) up to 7 week forecast in Nino 3.4 area. It can be concluded that GloSea5 has a great performance for seasonal prediction.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.241-241
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• 2017

기후변화로 인하여 강우의 불확실성이 가중되고 홍수, 가뭄 등 물 관련 재해의 발생빈도 및 강도가 증가함에 따라 안정적인 용수공급 등 수자원 관리 및 운영에 어려움을 겪고 있어 예측기반의 수자원 계획 및 운영이 요구되고 있는 실정이다. 우리나라 기상청에서는 2010년 6월 영국기상청과 장기 계절예측시스템의 구축 및 운영에 관한 협정을 체결하였으며 2014년부터 전지구 계절예측시스템 GloSea5(Global seasonal forecasting system version 5)을 현업에 활용하고 있다. GloSea5 모델은 대기(UM), 지면(JULES), 해양(NEMO), 해빙(CICE) 모델이 커플러(OASIS)에 의해 결합된 통합 시스템으로 일단위 자료로 제공된다. 현재 수자원 분야에서는 장기예보자료가 제공되고 있음에도 불구하고 장기예보자료의 불확실성 및 수문 모형 입력자료로의 활용 어려움, 예측자료의 검증 미흡 등으로 기상청에서 제공하는 장기예보를 참고할 뿐 실제로는 과거 관측자료를 기반한 빈도해석 결과를 활용하여 댐 운영 계획을 수립하고 있는 실정이다. 따라서, 본 연구에서는 GloSea5모델에서 제공되는 일 단위 예측 강수량을 수자원 장기이수계획 및 관리에 활용하고자 GloSea5모델의 예측력을 평가하고 수치모델이 가지는 시스템 에러에 대하여 편의보정 및 지점 상세화를 수행하였다. 본 연구의 분석결과는 향후, 저수지 운영계획 및 증가하는 물수요와 불확실한 공급에 대한 의사결정 지원, 가뭄 대비를 위한 물 공급 제한 등에 활용 가능할 것으로 판단된다.