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Wave measurement and modeling in Chesapeake bay

机译:切萨皮克湾的波浪测量和建模

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Three recently measured wind and wave data sets in the northern part of Chesapeake Bay (CB) are presented. Two of the three data sets were collected in late 1995. The third one was collected in July of 1998. The analyzed wind and wave data show that waves were dominated by locally generated, fetch limited young wind seas. Significant wave heights were highly correlated to the local driving wind speeds and the response time of the waves to the winds was about I h. We also tested two very different numerical wave models, Simulation of WAves Nearshore (SWAN) and Great Lakes Environmental Research Laboratory (GLERL), to hind-cast the wave conditions against the data sets. Time series model-data comparisons made using SWAN and GLERL showed that both models behaved well in response to a suddenly changing wind. In general, both SWAN and GLERL over-predicted significant wave height; SWAN over-predicted more than GLERL did. SWAN had a larger scatter index and a smaller correlation coefficient for wave height than GLERL had. In addition, both models slightly under-predicted the peak period with a fairly large scatter and low correlation coefficient. SWAN predicted mean wave direction better than GLERL did. Directional wave spectral comparisons between SWAN predictions and the data support these statistical comparisons. The GLERL model was much more computationally efficient for wind wave forecasts in CB. SWAN and GLERL predicted different wave height field distributions for the same winds in deeper water areas of the Bay where data were not available, however. These differences are as yet unresolved. (C) 2002 Elsevier Science Ltd. All rights reserved. [References: 29]
机译:介绍了切萨皮克湾(CB)北部最近测量的三个风浪数据集。这三个数据集中有两个是在1995年末收集的。第三个是在1998年7月收集的。分析的风浪数据显示,海浪主要由本地产生的,获取有限的年轻风海所主导。显着的波高与当地行驶风速高度相关,并且波对风的响应时间约为1 h。我们还测试了两个截然不同的数值波浪模型,即近岸波浪模拟(SWAN)和大湖区环境研究实验室(GLERL),以将波浪条件与数据集进行后向对比。使用SWAN和GLERL进行的时间序列模型数据比较显示,两种模型在响应突然变化的风时表现良好。一般而言,SWAN和GLERL都高估了重要的波高。 SWAN的预测超出了GLERL的预测。与GLERL相比,SWAN的散射指数更大,波高的相关系数更小。此外,这两个模型均以较高的散度和较低的相关系数略微预测了峰值时段。 SWAN预测的平均波向要比GLERL更好。 SWAN预测和数据之间的定向波谱比较支持这些统计比较。对于CB中的风浪预测,GLERL模型的计算效率更高。但是,SWAN和GLERL预测在没有数据的海湾较深水域中,相同风向的不同波高场分布。这些差异尚未解决。 (C)2002 Elsevier ScienceLtd。保留所有权利。 [参考:29]

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