Diffusion reduction in an arbitrary scale third generation wind wave model

The numerical schemes for the geographic propagation of random, short-crested, wind-generated waves in third-generation wave models are either unconditionally stable or only conditionally stable. Having an unconditionally stable scheme gives greater freedom in choosing the time step (for given space steps). The third-generation wave model SWAN (“Simulated WAves Nearshore”, Booij et al., 1999) has been implemented with this type of scheme. This model uses a first order, upwind, implicit numerical scheme for geographic propagation. The scheme can be employed for both stationary (typically small scale) and nonstationary (i.e. time-stepping) computations. Though robust, this first order scheme is very diffusive. This degrades the accuracy of the model in a number of situations, including most model applications at larger scales. The authors reduce the diffusiveness of the model by replacing the existing numerical scheme with two alternative higher order schemes, a scheme that is intended for stationary, small-scale computations, and a scheme that is most appropriate for nonstationary computations. Examples representative of both large-scale and small-scale applications are presented. The alternative schemes are shown to be much less diffusive than the original scheme while retaining the implicit character of the particular SWAN set-up. The additional computational burden of the stationary alternative scheme is negligible, and the expense of the nonstationary alternative scheme is comparable to those used by other third generation wave models. To further accommodate large-scale applications of SWAN, the model is reformulated in terms of spherical coordinates rather than the original Cartesian coordinates. Thus the modified model can calculate wave energy propagation accurately and efficiently at any scale varying from laboratory dimensions (spatial scale O(10 m) with resolution O(0.1 m)), to near-shore coastal dimension (spatial scale O(10 km) with resolution O(100 m)) to oceanic dimensions (spatial scale O(10 000 km) with resolution O(100 km).     

The SWAN model used to study wave evolution in a flume

The SWAN numerical model is used to model the evolution of JONSWAP wave spectra and hence the significant wave height of waves in a tank. Comparison with experiment has shown that modelling triad interactions in the numerical model leads to too low predictions of spectra and significant wave height and should therefore be excluded. The modelling of the breaking constant was also investigated, by looking at the use of a constant breaking constant, Nelson formula, and Goda formula (added into SWAN for this study). Using a constant value of 0.78 within SWAN gave the best comparison between theory and experiment.     

Nonlinear saturation-based whitecapping dissipation in SWAN for deep and shallow water

This study investigates the effectiveness of a revised whitecapping source term in the spectral wind wave model SWAN (Simulating WAves Nearshore) that is local in frequency space, nonlinear with respect to the variance density and weakly dependent on the wave age. It is investigated whether this alternative whitecapping expression is able to correct the tendency towards underprediction of period measures that has been identified in the default SWAN model. This whitecapping expression is combined with an alternative wind input source term that is more accurate for young waves than the default expression. The shallow water source terms of bottom friction, depth-induced breaking and triad interaction are left unaltered. It is demonstrated that this alternative source term combination yields improved agreement with fetch- and depth-limited growth curves. Moreover, it is shown, by means of a field case over a shelf sea, that the investigated model corrects the erroneous overprediction of wind-sea energy displayed by the default model under combined swell-sea conditions. For a selection of field cases recorded at two shallow lakes, the investigated model generally improves the agreement with observed spectra and integral parameters. The improvement is most notable in the prediction of period measures.     

Numerical Study of Wave Diffraction Effect Introduced in the SWAN Model

New version of SWAN model includes the wave diffraction effect which is the main improvement compared with the previous versions.Experimental data collected in the wave basin of the University of Delaware were used to test its performance.Wave heights were compared in the four cases(with different wave energies and directional spreading spectra).The results agreed well with the measurements,especially for the broad directional spectra cases.The effect of wave diffraction was analyzed by switching on/off the corresponding term.By introducing the diffraction term,the distributions of wave height and wave direction were smoothed,especially obvious for the narrow spectrum cases.Compared with the calculations without diffraction,the model with diffraction effect gave better results.     

高分辨率风场对长江口海域波浪场模拟能力的影响研究——以台风“灿都”为例

长江口海域岛屿众多, 地形复杂多变, 对灾害性海浪模拟和预报能力的提升有迫切需求。本研究基于长江口高分辨率非结构网格海浪模式SWAN(Simulating WAve Nearshore), 结合“两洋一海”区域耦合预报系统模拟风场, 以2021年第14号台风“灿都”为例, 研究了台风轨迹、台风移速和台风风场分辨率等对长江口及邻近海域海浪模拟和预报的影响。结果表明: 风场模型水平分辨率增加有利于台风细结构和台风悬臂状结构的模拟。分辨率增加, 风速整体呈减弱趋势, 但在台风中心(小于两倍最大风速半径)和外围悬臂区域风速增加显著。风场分辨率从27 km提升至9 km和3 km, 波浪模拟精度增加显著, 3 km风场驱动的波浪模拟精度最高, 继续提升风场分辨率至1 km对波浪模拟无明显提升。改变风场模型分辨率同时会影响台风路径和移动速度。波浪场的差异反映了台风结构、路径和移动速度的共同影响, 由于波浪的波动传播属性, 台风浪的差异一般比风场差异的范围更大。     

浙江近海波浪能资源的初步研究

以2000年为例,采用SWAN波浪数值模型对浙江近海海域的波浪进行了全年模拟计算,并计算获得年、月平均波功率密度分布。研究表明,浙江近岸海域年平均波功率密度约为2~6 kW·m^-1,往外海逐渐增大;同时季节变化明显,秋、冬季节波功率密度较大,春、夏季节较小。另外,通过对浙北、浙中和浙南3个近海海区的波浪出现频率和波功率密度随波高和周期变化的分析可知,浙北海域波功率密度比较高的波高及周期范围和波浪出现频率较高范围较为接近,而其对应平均波功率密度相对较低;浙南海域波功率密度比较高的范围所对应的平均波功率密度较高,而与波浪出现频率较高的范围则略有差异;浙中海域居两者之间。总体而言,浙江近海波浪能资源丰富,且全年中可开发与利用的波浪能出现频率较高。     

A coupled tide-wave model for the NW European shelf seas

Understanding the interaction of tides and waves is essential in many studies, including marine renewable energy, sediment transport, long-term seabed morphodynamics, storm surges and the impacts of climate change. In the present research, a COAWST model of the NW European shelf seas has been developed and applied to a number of physical processes. Although many aspects of wave–current interaction can be investigated by this model, our focus is on the interaction of barotropic tides and waves at shelf scale. While the COWAST model was about five times more computationally expensive than running decoupled ROMS (ocean model) and SWAN (wave model), it provided an integrated modelling system which could incorporate many wave–tide interaction processes, and produce the tide and wave parameters in a unified file system with a convenient post-processing capacity. Some applications of the model such as the effect of tides on quantifying the wave energy resource, which exceeded 10% in parts of the region, and the effect of waves on the calculation of the bottom stress, which was dominant in parts of the North Sea and Scotland, during an energetic wave period are presented, and some challenges are discussed. It was also shown that the model performance in the prediction of the wave parameters can improve by 25% in some places where the wave-tide interaction is significant.     

SWAN模型模拟风浪场侧边界失真范围研究

鉴于SWAN模型存在着不能有效地模拟固壁边界附近风浪场的缺点,即在边界附近所模拟的波要素存在失真的现象,研究了在不同水深、风速和风向情况下模型侧边界附近波要素的失真范围,并对计算结果进行了详细的分析。结果表明水深、风速和风向对于侧边界附近波要素的失真范围具有不同的影响,即在风速一定的情况下,失真范围随着水深的增大而增大;水深一定的情况下,失真范围随着风速的增大而减小、随着风向的增大而增大。在利用SWAN模型模拟计算近岸或内陆湖泊风浪场时,必须采取适当的措施以减少实际计算域侧边界附近计算结果的失真范围。     

一组雷达预警指标在2013年短时强降水中的应用分析

利用一组雷达阈值指标,对2013年四川盆地发生的5次区域性暴雨过程中的短时强降雨进行检验和订正,结果表明,(1)无论针对具体的站点,还是区域面上的短时强降水,预警指标对预警短时强降水是可行的,且预警时效在0~2h内效果较佳。(2)SWAN产品中分析显示,要产生20mm/h以上的短时强降水,满足预警指标的回波需要监测到3个6min以上,通常强回波持续越长,对应的雨量也越大。(3)针对降水面上的预警准确率除2013年7月04日15时的成功预警率在57.1%左右,其余过程中预警指标对未来1h短时强降雨的预警成功率基本在80%以上,误报率基本在20%以下,在误报的站点中,SWAN拼图中回波与单站雷达探测的回波,尤其是在低仰角度上存在较大误差。     

基于SWAN模式的南海台风浪推算的影响因素分析

基于南海实际地形和真实的台风过程,对影响SWAN模式在南海台风浪推算中的准确性的因素进行了较系统的研究。首先对不同的模型风场进行了对比分析,结果表明一个准确的风场是正确推算台风浪的关键。同时对SWAN模式中的白冠耗散作用、风能输入与白冠耗散不同的组合方式和折射项作用等因素对台风浪推算的影响进行分析,并对模式中的各影响因素给出了合理建议。使得SWAN模式在南海台风浪推算中具有更好的适用性。