• 제목/요약/키워드: Sea ice model

검색결과 101건 처리시간 0.02초

원격 탐사 기반 해양 표면 온도의 미세 분포 차이에 따른 강설량 예측성 연구 (A Study on Predictability of Snowfall Amount due to Fine Difference of Spatial Distribution of Remote Sensing based Sea Surface Temperature)

  • 이순환;유정우
    • 한국환경과학회지
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    • 제23권8호
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    • pp.1481-1493
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    • 2014
  • In order to understand the relation between the distribution of sea surface temperature and heavy snowfall over western coast of the Korean peninsula, several numerical assessments were carried out. Numerical model used in this study is WRF, and sea surface temperature data were FNL(National Center for Environment Prediction-Final operational global analysis), RTG(Real Time Global analysis), and OSTIA(Operational Sea Surface Temperature and Sea Ice Analysis). There were produced on the basis of remote sensing data, such as a variety of satellite and in situ observation. The analysis focused on the heavy snowfall over Honam districts for 2 days from 29 December 2010. In comparison with RTG and OSTIA SST data, sensible and latent heat fluexes estimated by numerical simulation with FNL data were higher than those with RTG and OSTIA SST data, due to higher sea surface temperature of FNL. General distribution of RTG and OSTIA SST showed similar, however, fine spatial differences appear in near western coast of the peninsula. Estimated snow fall amount with OSTIA SST was occurred far from the western coast because of higher SST over sea far from coast than that near coast. On the other hand, snowfall amount near coast is larger than that over distance sea in simulation with RTG SST. The difference of snowfall amount between numerical assessment with RTG and OSTIA is induced from the fine difference of SST spatial distributions over the Yellow sea. So, the prediction accuracy of snowfall amount is strongly associated with the SST distribution not only over near coast but also over far from the western coast of the Korean peninsula.

지표 특성 변화에 대한 평형온도의 반응 연구 : EBM 연구 (On response of Surface Equilibrium Temperature for Change of Surface Characteristics : An EBM Study)

  • 서예원;추정은;하경자
    • 한국제4기학회지
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    • 제24권2호
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    • pp.1-11
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    • 2010
  • 지표 특성 차이에 따라 외부강제력에 대한 차별적인 반응을 보이는 지표 평형온도 분포를 실험하기 위해 에너지 균형 모형(Energy Balance Model, EBM)이 사용되었다. EBM은 입사되는 복사에너지가 각 위도별로 수송되는 에너지와 방출되는 복사에너지의 합과 균형을 이루었을 때의 온도를 산출한다. 지구의 에너지 원천인 태양복사에너지를 전지구 에너지 균형에 있어 중요하게 취급하기 위하여 위도별 알베도 변화뿐만 아니라 해륙의 분포 차이에 따른 에너지 균형을 고려한 지구 평형온도 분포에 관한 실험이 수행되었으며, 입사되는 태양복사에너지량을 강제력으로 하여 위도별 알베도의 선형적인 증감, 극지역 알베도의 5%, 10%, 15% 증감에 대한 반응, 극과 중위도 지역에서의 상반된 증감에 대한 반응을 실험하였다. 그리고 얼음-알베도 피드백의 유무에 대한 실험도 수행되었다. 극지역의 알베도를 증가시키면 입사되는 태양에너지를 차단시켜 위도별 열수송을 감소시키는데 이는 극지역을 저에너지 상태로 유지시킴으로써 저위도에서부터의 에너지 수송을 강화시킨다. 이러한 수송량의 차이로 인해 중위도 지역의 온도 변화는 극지역에 비해 크게 나타난다. 육지는 해양에 비해 열용량이 작기 때문에 평형온도에 도달하는 시간이 짧으며 알베도에 따른 온도변화에 민감하여 해양과의 온도차이를 유발시킨다. 따라서 평형온도는 지표가 가지는 특성인 알베도와 열용량의 차이에 따라 다르게 나타나며 알베도가 증가함에 따라 감소하고 열용량이 작을수록 변화율이 큰 특징이 있다. 얼음-알베도 피드백은 알베도의 선형적인 증가에 따른 지구 평형온도의 감소를 가속화시키지만 국지적으로는 비선형적인 감소를 보인다.

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A New Application of Unsupervised Learning to Nighttime Sea Fog Detection

  • Shin, Daegeun;Kim, Jae-Hwan
    • Asia-Pacific Journal of Atmospheric Sciences
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    • 제54권4호
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    • pp.527-544
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    • 2018
  • This paper presents a nighttime sea fog detection algorithm incorporating unsupervised learning technique. The algorithm is based on data sets that combine brightness temperatures from the $3.7{\mu}m$ and $10.8{\mu}m$ channels of the meteorological imager (MI) onboard the Communication, Ocean and Meteorological Satellite (COMS), with sea surface temperature from the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA). Previous algorithms generally employed threshold values including the brightness temperature difference between the near infrared and infrared. The threshold values were previously determined from climatological analysis or model simulation. Although this method using predetermined thresholds is very simple and effective in detecting low cloud, it has difficulty in distinguishing fog from stratus because they share similar characteristics of particle size and altitude. In order to improve this, the unsupervised learning approach, which allows a more effective interpretation from the insufficient information, has been utilized. The unsupervised learning method employed in this paper is the expectation-maximization (EM) algorithm that is widely used in incomplete data problems. It identifies distinguishing features of the data by organizing and optimizing the data. This allows for the application of optimal threshold values for fog detection by considering the characteristics of a specific domain. The algorithm has been evaluated using the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) vertical profile products, which showed promising results within a local domain with probability of detection (POD) of 0.753 and critical success index (CSI) of 0.477, respectively.

Variation of the Relationship Between Arctic Oscillation and East Asian Winter Monsoon in CCSM3 Simulation

  • Wie, Jieun;Moon, Byung-Kwon;Lee, Hyomee
    • 한국지구과학회지
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    • 제40권1호
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    • pp.1-8
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    • 2019
  • Although recent reports suggest that the negative correlation between the Arctic Oscillation (AO) and the East Asian winter monsoon (EAWM) has been strengthened, it is not clear whether this intermittent relationship is an intrinsic oscillation in the climate system. We investigate the oscillating behavior of the AO-EAWM relationship at decadal time scales using the long-term (500-yr) climate model simulation. The results show that ice cover over the East Siberian Seas is responsible for the change in the coupling strength between AO and EAWM. We found that increased ice cover over these seas strengthens the AO-EAWM linkage, subsequently enhancing cold advection over the East Asia due to anomalous northerly flow via a weakened jet stream. Thus, this strengthened relationship favors more frequent occurrences of cold surges in the EAWM region. Results also indicate that the oscillating relationship between AO and EAWM is a natural variability without anthropogenic drivers, which may help us understand the AO-EAWM linkage under climate change.

마지막 최대 빙하기의 온도 및 물수지 변화 수치모델연구 (Numerical Model study of Surface Temperature and Hydrological Budget Change for the Last Glacial Maximum)

  • 김성중;이방용;윤호일
    • 지구물리
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    • 제9권2호
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    • pp.135-145
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    • 2006
  • 미국 해양대기청의 CCM3 기후모델을 이용하여 마지막최대빙하기 (Last Glacial Maximum(LGM)의 기온 및 물. 이용된 수치모델의 수평해상도는 약 75 km로 비교적 상세한 기후 기작들이 표현된다. LGM 실험은 CLIMAP 프로젝트에서 복원된 표층해수가 경계조건으로 이용되었으며 , LGM에 낮았던 대기 이산화탄소농도(200 pm) 이 적용되었고, 대륙빙하를 포함한 LGM 지표지형이 표현되었다 . LGM 경계조건하에서 전구온도는 겨울철 6.1도 여름철 5.6도 그리고 연평균 6도정도 감소한 것으로 시뮬레이션 된다 . 표층 기온의 감소는 14% 감소하고 여름에 17% 그리고 연간 13% 감소한다. 하지만, 미국, 남부유럽, 동아프리카, 남아메리카 등은 겨울에 현재보다 더 습하게 나타나며 , 캐나다 와 중동 지방은 여름철에 습윤하게 시뮬레이션 된다 . 이런 결과들은 호수면 변화기록으로부터 복원한 고기후 프락시 물수지 자료들과도 대체로 잘 일치한다 . 전체적으로 고해상도 기후모델은 지상에서 나타나는 세부적인 특징들을 잘 재현해내고 있다 .

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위성관측(MSU)과 모델 재분석 자료에서 조사된 대기물현상과 표면 방출율의 분포 (Distribution of Hydrometeors and Surface Emissivity Derived from Microwave Satellite Observations and Model Reanalyses)

  • 김태연;유정문
    • 한국지구과학회지
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    • 제23권7호
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    • pp.552-564
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    • 2002
  • 하부 대류권의 대기물현상과 마이크로파 표면 방출율를 전구적으로 조사하기 위하여 1981-93년 기간의 MSU 채널1 밝기온도와 대기대순환 모델(GCM) 재분석 월평균 자료를 사용하였다. 모델재분석 채널1 자료의 평균값이 MSU 채널1 가중함수를 기초로 하여 세 종류의 모델(NCEP ECMWF, GEOS) 재분석에서 온도장을 이용하여 재구성되었다. 모델재분석 채널1 온도는 하부 대류권의 열적 상태를 주로 반영하기 때문에, 해양과 육지에서 계절에 관계없이 각 반구 여름철에 최대값을 나타내었다. MSU 채널1 밝기온도는 해양에서 대기물현상으로 인해 열대 및 남태평양 수렴대들 에서 극대값을 보였다. 또한 이 밝기온도는 빙하/눈 방출율 효과로 인하여 고위도 해양에서 증가하는 반면에, 고위도육지에서는 감소하였다. 열대 및 남태평양 수렴대들의 계절적 이동은 GCM과 MSU 사이의 채널1 온도 차의 분포에서 체계적으로 나타났다. 이러한 온도차의 극소값 위치에서 추정할 때, 열대 수렴대는 가을에 9N까지 북상하였고, 남태평양 수렴대는 북반구 가을과 겨울에 12S까지 남하하였다. 고위도 경우에는 해빙이 각 반구의 겨울에 북반구에서 53N까지 남하하고, 남반구에서는 58S까지 북상하였다 복사전달 결과를 이용하여 MSU 채널1 밝기온도에 대한 대기물현상과 표면 방출율의 부분적인 기여도를 분리하여 조사하였다. ITCZ지역에서 4-6K의 밝기온도 상승은 1-1.5mm/day의 대기물현상 증가에, 그리고 고위도 해양에서의 10-30K의 상승은 0.6-0.9값의 해빙 방출율의 기여에 해당하였다.

Biochemical Adaptation to the Freezing Environment - the Biology of Fish Antifreeze Proteins

  • Li, Zhengjun;Li, n Qingsong;Low Woon-Kai;Miao Megan;Hew Choy L.
    • Ocean and Polar Research
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    • 제25권4호
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    • pp.607-615
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    • 2003
  • Many organisms are known to survive in icy environments. These include both over wintering terrestrial insects and plants as well the marine fish inhabiting high latitudes. The adaptation of these organisms is both a fascinating and important topic in biology. Marine teleosts in particular, can encounter ice-laden seawater that is approximately $1^{\circ}C$ colder than the colligative freezing point of their body fluids. These animals produce a unique group of proteins, the antifreeze proteins (AFPs) or antifreeze glycoproteins (AFGPs) that absorb the ice nuclei and prevent ice crystal growth. Presently, there are at least four different AFP types and one AFGP type that are isolated from a wide variety of fish. Despite their functional similarity, there is no apparent common protein homology or ice-binding motifs among these proteins, except that the surface-surface complementarity between the protein and ice are important for binding. The remarkable diversity of these proteins and their odd phylogenetic distribution would suggest that these proteins might have evolved recently in response to sea level glaciations just 1-2 million years ago in the northern hemisphere and 10-30 million years ago around Antarctica. Winter flounder, Pleuronectes americanus, has been used as a popular model to study the regulation of AFP gene expression. It has a built-in annual cycle of AFP expression controlled negatively by the growth hormone. The signal transduction pathways, transcription factors and promoter elements involved in this process have been studied in our laboratory and these studies will be presented.

고해상도 장기예측시스템의 주별 앙상블 예측자료 성능 평가 (Performance Assessment of Weekly Ensemble Prediction Data at Seasonal Forecast System with High Resolution)

  • 함현준;원덕진;이예숙
    • 대기
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    • 제27권3호
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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.

남극 장보고기지 주변 강풍사례 모의 연구 (A Numerical Simulation Study of Strong Wind Events at Jangbogo Station, Antarctica)

  • 권하택;김신우;이솔지;박상종;최태진;정지훈;김성중;김백민
    • 대기
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    • 제26권4호
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    • pp.617-633
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    • 2016
  • Jangbogo station is located in Terra Nova Bay over the East Antarctica, which is often affected by individual storms moving along nearby storm tracks and a katabatic flow from the continental interior towards the coast. A numerical simulation for two strong wind events of maximum instantaneous wind speed ($41.17m\;s^{-1}$) and daily mean wind speed ($23.92m\;s^{-1}$) at Jangbogo station are conducted using the polar-optimized version of Weather Research and Forecasting model (Polar WRF). Verifying model results from 3 km grid resolution simulation against AWS observation at Jangbogo station, the case of maximum instantaneous wind speed is relatively simulated well with high skill in wind with a bias of $-3.3m\;s^{-1}$ and standard deviation of $5.4m\;s^{-1}$. The case of maximum daily mean wind speed showed comparatively lower accuracy for the simulation of wind speed with a bias of -7.0 m/s and standard deviation of $8.6m\;s^{-1}$. From the analysis, it is revealed that the each case has different origins for strong wind. The highest maximum instantaneous wind case is caused by the approach of the strong synoptic low pressure system moving toward Terra Nova Bay from North and the other daily wind maximum speed case is mainly caused by the katabatic flow from the interiors of Terra Nova Bay towards the coast. Our evaluation suggests that the Polar WRF can be used as a useful dynamic downscaling tool for the simulation and investigation of high wind events at Jangbogo station. However, additional efforts in utilizing the high resolution terrain is required to reduce the simulation error of high wind mainly caused by katabatic flow, which is received a lot of influence of the surrounding terrain.

극지운항용 빙해선박의 밸러스트 수 결빙방지 기법 연구 (A Study on Anti-Icing Technique for Ballast Water of Icebreaking Vessels Operating in Ice-Covered Water)

  • 정성엽;이춘주;조성락
    • 대한조선학회논문집
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    • 제48권1호
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    • pp.93-97
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    • 2011
  • When freezing is present on ballast water, it can impose additional loads on the hull and effect on stabilization of ship. The anti-icing techniques of ballast water, therefore, are key criteria for ship safety. The existing anti-icing techniques of ballast tank are hull heating, water circulation and air bubble system etc. In this research, anti-icing performance tests for the ballast water using micro-bubble system and sea water circulation system have been carried out at two temperature conditions($-10^{\circ}C$ and $-25^{\circ}C$). Ambient temperature, sea water temperature and temperature of the inner parts of the ballast tank are measured and also ballast water conditions are checked during the model test. The applied anti-icing techniques of ballast water, such as micro-bubble system and sea water circulation system show good performance in the low temperature conditions.