• Title/Summary/Keyword: Mean sea surface model

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Estimation of Geostrophic Current Calculated from Sea Surface Topography in East Sea (동해의 해면지형 계산에 의한 지형류의 흐름 추정)

  • Yun Hong-Sic;Lee Dong-Ha
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.24 no.2
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    • pp.159-165
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    • 2006
  • This paper deals with the estimation of geostrophic current using the sea surface topography calculated from the geoidal height from EGM96 geopotential model and the mean sea surface height from CLS_SHOM mean sea surface model. The CLS_SHOM model was developed using the altimetry data set. The estimation of geostrophic current is available in the characteristic research of ocean in many country, while for East Sea a few studies were done. The goal of this study is basically to provide the characteristics of geostrophic current in East Sea. The results show that the mean sea surface topography (SST) in East Sea is about 0.37 m and the mean geostrophic velocity is -0.028 m/sec. The Pacific water enters into the East Sea through the Korea Strait and after passing the strait, this inflow splits into two branches: one flows northward along the Korean coast and another outflows into Pacific ocean through Tsugaru and Soya strait passing the east-northeastward along the Japanese outer shelf, and outflows into Okhotsk ocean.

Characteristics of the Monthly Mean Sea Surface Winds and Wind Waves near the Korean Marginal Seas in the 2002 Year Computed Using MM5/KMA and WAVEWATHC-III model (중규모 기상모델(MM5/KMA)과 3세대 파랑모델(WAVEWATCH-III)로 계산된 한반도 주변해역의 2002년 월평균 해상풍과 파랑 분포 특성)

  • 서장원;장유순
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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    • v.8 no.3
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    • pp.262-273
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    • 2003
  • We have analyzed the characteristics of the monthly mean sea surface winds and wind waves near the Korean marginal seas in the 2002 year on the basis of prediction results of the sea surface winds from MM5/KMA model, which is being used for the operation system at the Korea Meteorological Administration and the third generation wave model, WAVEWATCH-III. which takes the sea surface winds derived from MM5/KMA model as the initial data. Statistical comparisons have been applied with both the marine meteorological observation buoy and the TOPEX/POSEIDON satellite wave heights data to verify the model results. The correlation coefficients between the models and observation data reach up to about 60-80%, supporting that these models satisfactorily simulate the sea surface winds and wave heights even at the coastal regions except for Chilbal-Do located very close to the land. Based on these verification results, the distributions of monthly mean sea surface winds, significant wave heights, wave lengths and wave periods around the Korean marginal seas during 2002 year have been represented.

Marine Meteorological Characteristics in 2006-2007 : Sea Surface Wind (2006-2007년 해양기상 특성 : 해상풍)

  • You, Sung Hyup;Kwon, Ji Hye;Kim, Jeong-Sik
    • Atmosphere
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    • v.19 no.2
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    • pp.145-154
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    • 2009
  • This study compared the sea surface wind pattern between model results from KMA operational model (RDAPS) and retrieved results from QuickSCAT in the 2006-2007 year. The mean spatial distributions of sea surface wind of RDAPS and QuikSCAT show the prominent seasonal patterns of summer and winter season adjacent to Korean Peninsular. The magnitude of sea surface wind predicted by RDAPS is weaker than that of QuikSCAT in most north Pacific ocean. In summer of 2006 positive bias with the maximum of 1 m/s is appeared in broad region of north Pacific ocean, however. the positive bias region is decreased to small region in 2007. Even though the predicted sea wind by RDAPS is stronger(weaker) than observed one by QuikSCAT in summer (winter), the RDAPS model simulate well the sea surface wind adjacent to Korean peninsular.

Atmospheric and Oceanic Factors Affecting the Air-Sea Thermal Interactions in the East Sea (Japan Sea) (東海海面 熱交換에 影響을 미치는 大氣 및 海洋的 要因)

  • Kang, Yong Q
    • 한국해양학회지
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    • v.19 no.2
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    • pp.163-171
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    • 1984
  • The atmospheric and oceanic influences on the air-sea thermal interaction in the East Sea (Japan Sea) are studied by means of an analytic model which is based on the heat budget of the ocean. By means of the model, the model, the annual variations of heat fluxes and air temperatures in the East Sea are analytically simulated. The model shows that the back radiation, the latent heat and the sensible heat increase with the warn water advection. The latent heat increases with the sea surface temperature (SST) but the back radiation and the sensible heat dcrease as the SST increases. In the East Sea, an increase of mean SST by 1.0$^{\circ}C$ yields an increase of mean air temperature by 1.2$^{\circ}C$. The heat storage in the ocean plays an important role in the annual variations of heat flux across the sea surface.

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Transfer Function Model Forecasting of Sea Surface Temperature at Yeosu in Korean Coastal Waters (전이함수모형에 의한 여수연안 표면수온 예측)

  • Seong, Ki-Tack;Choi, Yang-Ho;Koo, Jun-Ho;Lee, Mi-Jin
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.20 no.5
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    • pp.526-534
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    • 2014
  • In this study, single-input transfer function model is applied to forecast monthly mean sea surface temperature(SST) in 2010 at Yeosu in Korean coastal waters. As input series, monthly mean air temperature series for ten years(2000-2009) at Yeosu in Korea is used, and Monthly mean SST at Yeosu station in Korean coastal waters is used as output series(the same period of input). To build transfer function model, first, input time series is prewhitened, and then cross-correlation functions between prewhitened input and output series are determined. The cross-correlation functions have just two significant values at time lag at 0 and 1. The lag between input and output series, the order of denominator and the order of numerator of transfer function, (b, r, s) are identified as (0, 1, 0). The selected transfer function model shows that there does not exist the lag between monthly mean air temperature and monthly mean SST, and that transfer function has a first-order autoregressive component for monthly mean SST, and that noise model was identified as $ARIMA(1,0,1)(2,0,0)_{12}$. The forecasted values by the selected transfer function model are generally $0.3-1.3^{\circ}C$ higher than actual SST in 2010 and have 6.4 % mean absolute percentage error(MAPE). The error is 2 % lower than MAPE by ARIMA model. This implies that transfer function model could be more available than ARIMA model in terms of forecasting performance of SST.

Computation of the Sea Surface Topography over the East China Sea (동지나해의 해면변위산정)

  • 최병호
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.4 no.1
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    • pp.1-12
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    • 1986
  • An attempt to obtain equipotential surface over the East China Sea along the three SEASAT ground tracks are described. Total correction of sea surface heights above the reference ellipsoid provided by SEASAT GDR Altimeter data consists of ocean tides and surges, body tides, sea level pressure inverse barometer effect corrections for the present study. It was shown that three equipotential surface derived from the corrections were qualitatively in agreement with GEM l0B Model and SS3 Mean Sea Surface Model.

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Evaluation of Upper Ocean Temperature and Mixed Layer Depth in an Eddy-permitting Global Ocean General Circulation Model (중해상도 전지구 해양대순환 모형의 상층 수온과 혼합층 깊이 모사 성능 평가)

  • Jang, Chan-Joo;Min, Hong-Sik;Kim, Cheol-Ho;Kang, Sok-Kuh;Lie, Heung-Jae
    • Ocean and Polar Research
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    • v.28 no.3
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    • pp.245-258
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    • 2006
  • We investigated seasonal variations of the upper ocean temperature and the mixed layer depth (MLD) in an eddy-permitting global ocean general circulation model (OGCM) to assess the OGCM perfermance. The OGCM is based on the GFDL MOM3 which has a horizontal resolution of 0.5 degree and 30 vertical levels. The OGCM was integrated for 68 years using a monthly-mean climatological wind stress forcing. The model sea surface temperature (SST) and sea surface salinity were restored to the Levitus climatology with a time scale of 30 days. Annual-mean model SST shows a cold bias $(<\;-2^{\circ}C)$ in the summer hemisphere and a warm bias $(>\;1^{\circ}C)$ in the winter hemisphere mainly due to the restoring boundary condition of temperature. The model MLD captures well the observed features in most areas, with a slightly deep bias. However, in the Ross Sea and Weddell Sea, the model shows significantly deeper MLD than the climatology-mainly due to weak salinity stratifications in the model. For amplitude of seasonal variation, the model SST is smaller $(1{\sim}3^{\circ}C)$ than the observation largely due to the restoring surface boundary condition while the model MLD has larger seasonal variation $({\sim}50m)$. It is suggested that for more realistic simulation of the upper ocean structure in the present eddy-permitting ocean model, more refinements in the surface boundary condition for the thermohaline forcing and parameterization for vertical mixing are required, together with the incorporation of a sea-ice model.

Comparison of Topex/Poseidon sea surface heights and Tide Gauge sea levels in the South Indian Ocean

  • Yoon, Hong-Joo
    • Proceedings of the KSRS Conference
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    • 1998.09a
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    • pp.70-75
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    • 1998
  • The comparison of Topex/Poseidon sea surface heights and Tide Gauge sea levels was studied in the South Indian Ocean after Topex/Poseidon mission of about 3 years (11- 121 cycles) from January 1993 through December 1995. The user's handbook (AVISO) for sea surface height data process was used in this study Topex/Poseidon sea suface heights ($\zeta$$^{T/P}$), satellite data at the point which is very closed to Tide Gauge station, were chosen in the same latitude of Tide Gauge station. These data were re-sampled by a linear interpolation with the interval of about 10 days, and were filtered by the gaussian filter with a 60 day-window. Tide Gauge sea levels ($\zeta$$^{Argos}$, $\zeta$$^{In-situ}$ and $\zeta$$^{Model}$), were also treated with the same method as satellite data. The main conclusions obtained from the root-mean-square and correlation coefficient were as follows: 1) to Produce Tide Gauge sea levels from bottom pressure, in-situ data of METEO-FRANCE showed very good values against to the model data of ECMWF and 2) to compare Topex/Poseidon sea surface heights of Tide Gauge sea levels, the results of the open sea areas were better than those of the coast and island areas.

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Monthly-mean sea surface winds over the adjacent seas of the Korea Peninsular (한국근해의 월평균 해상풍)

  • 나정열;서장원
    • 한국해양학회지
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    • v.27 no.1
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    • pp.1-10
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    • 1992
  • The sea surface winds are computed over the adjacent seas of Korea from the twice-dayily weather maps for the ten-year period 1978-1987 by using the Cardone model. Monthly mean wind-stress and wind0stress curl are also calculated and given as maps. the computed surface winds are compared with observed one at the JMA (Japan Meteorological Agency) Buoy. and the results show a good consistency in speed and direction. In particular, the magnitude of mean wind-stress is turned out to be twice bigger than the previous results over the sea of Japan. Monthly distributions of wind-stress curl reveal that over the yellow sea by the longitudinal boundary of $120^{\circ}{\;}~{\;}125^{\circ}{\;}E$, the area of negative cur exists over the western part of the sea except summer season, while the positive sign of the curl prevails over the eastern part of the Yellow Sea. However, over the Sea of Japan, with two positive maxima at the northern part and near the Wonsan Bay, the positive curl in the northern half and the negative curl in the southern of the sea characterize the monthly mean distribution of the wind-stress curl.

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Comparison of KMA Operational Model RDAPS with QuikSCAT Sea Surface Wind Data (기상청 현업 모델 RDAPS와 QuikSCAT 해상풍 자료의 비교)

  • You, Sung-Hyup;Cho, Jae-Gab;Seo, Jang-Won
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.19 no.5
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    • pp.467-475
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    • 2007
  • This study compared the sea surface wind pattern between model results from KMA operational model (RDAPS) and observational results from QuikSCAT in the 2005-2006 year. The mean spatial distributions of sea surface wind show the prominent seasonal patterns of summer and winter season adjacent to Korean Peninsular. The statistical analysis also shows well seasonal variation of sea surface wind patterns between model and observation results. The BIAS value represents less than -0.5 m/s and -1 m/s in summer and winter seasons, respectively. The spatially averaged correlation coefficient shows larger than 0.7 and 0.8 in summer and winter seasons, respectively. The correlation coefficient of winter season shows higher value than that of summer season in the comparison between model and observation. This results show that the RDAPS model simulate well strong sea surface wind in winter season rather than weak sea surface wind in summer season.