海南东方近岸海域海浪观测特征研究

利用海南东方近岸海域2014年至2015年间一整年的海浪观测资料, 分析了海浪的时间变化特征。观测时间段内, 有效波高最大值为4.03m, 平均值0.79m; 平均周期最大值为6.32s, 平均值为3.58s。该海域冬季波高较大, 秋季最小, 常浪向为SSW方向, 强浪向为WSW向。基于该长期观测数据, 文章亦研究了平均周期、有效波高之间的关系, 同时还确立了该海域波高与平均持续时间之间的关系。最后讨论了观测时间段内波浪能流密度的变化特征, 发现一年中能流密度大于2kW·m^-1的频率为26%, 且从全年的计算结果来看, 观测位置处12月的波浪能较适宜开发, 但总体波浪能资源不够丰富。文章对于认识海南东方近岸海域波浪特征以及工程设计都具有重要的意义。     

Stochastic simulations of ocean waves: An uncertainty quantification study

The primary objective of this study is to introduce a stochastic framework based on generalized polynomial chaos (gPC) for uncertainty quantification in numerical ocean wave simulations. The techniques we present can be easily extended to other numerical ocean simulation applications. We perform stochastic simulations using a relatively new numerical method to simulate the HISWA (Hindcasting Shallow Water Waves) laboratory experiment for directional near-shore wave propagation and induced currents in a shallow-water wave basin. We solve the phased-averaged equation with hybrid discretization based on discontinuous Galerkin projections, spectral elements, and Fourier expansions. We first validate the deterministic solver by comparing our simulation results against the HISWA experimental data as well as against the numerical model SWAN (Simulating Waves Nearshore). We then perform sensitivity analysis to assess the effects of the parametrized source terms, current field, and boundary conditions. We employ an efficient sparse-grid stochastic collocation method that can treat many uncertain parameters simultaneously. We find that the depth-induced wave-breaking coefficient is the most important parameter compared to other tunable parameters in the source terms. The current field is modeled as random process with large variation but it does not seem to have a significant effect. Uncertainty in the source terms does not influence significantly the region before the submerged breaker whereas uncertainty in the incoming boundary conditions does. Considering simultaneously the uncertainties from the source terms and boundary conditions, we obtain numerical error bars that contain almost all experimental data, hence identifying the proper range of parameters in the action balance equation.     

Subinertial and seasonal variations in the Soya Warm Current revealed by HF ocean radars,coastal tide gauges,and bottom-mounted ADCP

Subinertial and seasonal variations in the Soya Warm Current (SWC) are investigated using data obtained by high frequency (HF) ocean radars, coastal tide gauges, and a bottom-mounted acoustic Doppler current profiler (ADCP). The HF radars clearly captured the seasonal variations in the surface current fields of the SWC. Almost the same seasonal cycle was repeated in the period from August 2003 to March 2007, although interannual variations were also discernible. In addition to the annual and interannual variations, the SWC exhibited subinertial variations with a period of 5–20 days. The surface transport by the SWC was significantly correlated with the sea level difference between the Sea of Japan and Sea of Okhotsk for both the seasonal and subinertial variations, indicating that the SWC is driven by the sea level difference between the two seas. The generation mechanism of the subinertial variation is discussed using wind data from the European Centre for Medium-range Weather Forecasts (ECMWF) analyses. The subinertial variations in the SWC were significantly correlated with the meridional wind stress component over the region. The subinertial variations in the sea level difference and surface current delay from the meridional wind stress variations by one or two days. Sea level difference through the strait caused by wind-generated coastally trapped waves (CTWs) along the east coast of Sakhalin and west coast of Hokkaido is considered to be a possible mechanism causing the subinertial variations in the SWC.