• 제목/요약/키워드: Double gyre

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바람의 회전응력, 지형, 그리고 성층화가 성층 호수의 물 순환에 미치는 영향 (Effects of Wind Stress Curl, Topography, and Stratification on the Basin-scale Circulations in a Stratified Lake)

  • 정세웅
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2015년도 학술발표회
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    • pp.53-53
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    • 2015
  • Basin-scale motions in a stratified lake rely on interactions of spatially and temporally varying wind force, bathymetry, density variation, and earth's rotation. These motions provide a major driving force for vertical and horizontal mixing of inorganic and organic materials, dissolved oxygen, storm water and floating debris in stratified lakes. In Lake Tahoe, located between California and Nevada, USA, basin-scale circulations are obviously important because they are directly associated with the fate of the suspended particulate materials that degrade the clarity of the lake. A three-dimensional hydrodynamic model, ELCOM, was applied to Lake Tahoe to investigate the underlying mechanisms that determine the characteristics of basin-scale circulations. Numerical experiments were designed to examine the relative effects of various mechanisms responsible for the horizontal circulations for two different seasons, summer and winter. The unique double gyre, a cyclonic northern gyre and an anti-cyclonic southern gyre, occurred during the winter cooling season when wind stress curl, stratification, and Coriolis effect were all incorporated. The horizontal structure of the upwelling and downwelling formed due to basin-scale internal waves found to be closely related to the rotating direction of each gyre. In the summer, the spatially varying wind field and the Coriolis effect caused a dominant anti-cyclonic gyre to develop in the center of the lake. In the winter, a significant wind event excited internal waves, and a persistent (2 week long) cyclonic gyre formed near the upwelling zone. Mechanism of the persistent cyclonic gyre is explained as a geostrophic circulation ensued by balancing of the baroclinc pressure gradient (or baroclinic instability) and Coriolis effect. Topographic effect, examined by simulating a flat bathymetry with constant depth of 300m, was found to be significant during the winter cooling season but not as significant as the wind curl and baroclinic effects.

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Double Gyre 모형 해양에서 앙상블 칼만필터를 이용한 자료동화와 쌍둥이 실험들을 통한 민감도 시험 (Implementation of the Ensemble Kalman Filter to a Double Gyre Ocean and Sensitivity Test using Twin Experiments)

  • 김영호;유상진;최병주;조양기;김영규
    • Ocean and Polar Research
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    • 제30권2호
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    • pp.129-140
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    • 2008
  • As a preliminary effort to establish a data assimilative ocean forecasting system, we reviewed the theory of the Ensemble Kamlan Filter (EnKF) and developed practical techniques to apply the EnKF algorithm in a real ocean circulation modeling system. To verify the performance of the developed EnKF algorithm, a wind-driven double gyre was established in a rectangular ocean using the Regional Ocean Modeling System (ROMS) and the EnKF algorithm was implemented. In the ideal ocean, sea surface temperature and sea surface height were assimilated. The results showed that the multivariate background error covariance is useful in the EnKF system. We also tested the sensitivity of the EnKF algorithm to the localization and inflation of the background error covariance and the number of ensemble members. In the sensitivity tests, the ensemble spread as well as the root-mean square (RMS) error of the ensemble mean was assessed. The EnKF produces the optimal solution as the ensemble spread approaches the RMS error of the ensemble mean because the ensembles are well distributed so that they may include the true state. The localization and inflation of the background error covariance increased the ensemble spread while building up well-distributed ensembles. Without the localization of the background error covariance, the ensemble spread tended to decrease continuously over time. In addition, the ensemble spread is proportional to the number of ensemble members. However, it is difficult to increase the ensemble members because of the computational cost.