• Journal of Korean Society of Coastal and Ocean Engineers
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• v.23 no.4
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• pp.313-325
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• 2011

Finite element grid system using h-refinement on the Yellow Sea was constructed based on previous study (Suh, 1999b) from 14 K to 210 K and special attention was concentrated on refining the coastal zone. In grid generation, depth change between adjacent points and non-dimensional tidal wave length ratio were considered. As a result approximately a quarter of the total nodes are located nearby 5 m of shallow area. Accurate bathymetry data using 30's and ETOPO1 with open boundary conditions of 8 major tidal constituents extracted automatically from FES2004 have been applied. In tidal simulation a 3-dimensional nonlinear harmonic model was setup and tidal amplification due to changes in vertical turbulent and bottom friction were simulated. In this study not only 8 major tidal constituents but also nonlinear shallow tides $M_4,$, $MS_4$ and long period $M_f,$, $M_{sf}$ were reproduced. It is found that implication of spatial variation of friction coefficient plays a very important role in reproduction of astronomical and shallow tides which are computed by iterative computation of nonlinear terms. Also it should be considered differently with respect to tidal periods. To understand the distribution of tidal asymmetry, amplitude ratio of $M_4/M_2$ and phase differences $2g(M_2)-g(M_4)$ were calculated. Tidal distortion ratio marks up to 0.2 on the west coast showing shallow coastal characteristics and somewhat wide range of ebb-dominances in front of Mokpo area are reproduced.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.6 no.1
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• pp.1-12
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• 2001

Tidal computations of $M_2,\;S_2,\; K_1$ and $O_1$ constituents in the northeast Asian sea are presented by blending the Topex/Poseidon (T/P) altimeter data into a hydrodynamic model with $5'{\times}5'$ resolution. A series of sensitivity experiments on a weighting factor, which is the control parameter in the blending method, are carried out using $M_2$ constituent. The weighting factor is set to be in inverse proportion to the square root of water depth to reduce noises which could occur in data-assimilative model by blending T/P data. Model results obtained by blending the T/P-derived $M_2,\;S_2,\; K_1$ and $O_1$ constituents simultaneously are compared with all T/P-track tidal data; Average values of amplitude and phase errors are close to zero. Standard deviations of amplitude and phase errors are approximately 2 cm and less than 10 degrees respectively. The data-assimilative model results show a quite good agreement with T/P-derived tidal data, particularly in shallow water region (h<250m). In deep water regions, T/P-derived tidal data show unreasonable spatial variations in amplitude and phase. The data-assimilative model results differ from T/P-derived data, but are improved to show reasonable spatial variations in amplitude and phase. In addition, the T/P-blended model results are in good agreement with coastal tide gauge data which are not blended into the model.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.26 no.1
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• pp.11-36
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• 2021

The solar annual (Sa) and semiannual (Ssa) tides account for much of the non-uniform annual and seasonal variability observed in sea levels. These non-equilibrium tides depend on atmospheric variations, forced by changes in the Sun's distance and declination, as well as on hydrographic conditions. Here we employ tidal harmonic analyses to calculate Sa and Ssa harmonic constants for 21 Korean coastal tidal stations (TS), operated by the Korea Hydrographic and Oceanographic Agency. We used 19 year-long (1999 to 2017) 1 hr-interval sea level records from each site, and used two conventional harmonic analysis (HA) programs (Task2K and UTide). The stability of Sa harmonic constants was estimated with respect to starting date and record length of the data, and we examined the spatial distribution of the calculated Sa and Ssa harmonic constants. HA was performed on Incheon TS (ITS) records using 369-day subsets; the first start date was January 1, 1999, the subsequent data subset starting 24 hours later, and so on up until the final start date was December 27, 2017. Variations in the Sa constants produced by the two HA packages had similar magnitudes and start date sensitivity. Results from the two HA packages had a large difference in phase lag (about 78°) but relatively small amplitude (<1 cm) difference. The phase lag difference occurred in large part since Task2K excludes the perihelion astronomical variable. Sensitivity of the ITS Sa constants to data record length (i.e., 1, 2, 3, 5, 9, and 19 years) was also tested to determine the data length needed to yield stable Sa results. HA results revealed that 5 to 9 year sea level records could estimate Sa harmonic constants with relatively small error, while the best results are produced using 19 year-long records. As noted earlier, Sa amplitudes vary with regional hydrographic and atmospheric conditions. Sa amplitudes at the twenty one TS ranged from 15.0 to 18.6 cm, 10.7 to 17.5 cm, and 10.5 to 13.0 cm, along the west coast, south coast including Jejudo, and east coast including Ulleungdo, respectively. Except at Ulleungdo, it was found that the Ssa constituent contributes to produce asymmetric seasonal sea level variation and it delays (hastens) the highest (lowest) sea levels. Comparisons between monthly mean, air-pressure adjusted, and steric sea level variations revealed that year-to-year and asymmetric seasonal variations in sea levels were largely produced by steric sea level variation and inverted barometer effect.