Statistics of nonlinear wave crests and groups

Groups of large nonlinear waves with sharper higher crests can pose hazards to ships, induce harbor resonance and cause wave-overtopping of fixed and floating structures. Past interest in wave groups has mostly been focused on the statistics and modeling of linear wave groups. Studies on nonlinear wave groups are surprisingly few, and address deep water waves only. Here, statistics of nonlinear wave crests and wave-crest groups in deep and transitional water depths are considered, using an appropriate second-order representation for crest heights and the continuous wave-envelope approach. In particular, theoretical expressions describing the statistics of nonlinear wave crests and their groups are posed in the form of a simple second-order transformation of well-known results on linear waves. Predictions from the transformation so posed compare well with nonlinear wave data gathered in the North Sea, and demonstrate that nonlinearities do affect the statistics of large wave crests and their groups significantly.     

The effect of tidal inlets on open coast storm surge hydrographs

Bridge scour modeling requires storm surge hydrographs as open ocean boundary conditions for coastal waters surrounding tidal inlets. These open coast storm surge hydrographs are used to accurately determine both horizontal and vertical circulation patterns, and thus scour, within the inlet and bay for an extreme event. At present, very little information is available on the effect that tidal inlets have on these open coast storm surge hydrographs. Furthermore, current modeling practice enforces a single design hydrograph along the open coast boundary for bridge scour models. This study expands on these concepts and provides a more fundamental understanding on both of these modeling areas.     

The Huelva (Spain) Tsunami-Ready Station and Its Interaction with Storm Emma (March 2018)

Abstract

The sea level station operating since 1996 at Mazagón (Huelva, Spain) has been progressively upgraded to fit tsunami warning requirements, due to its location in one of the main regions at risk. Its radar water level sensor was complemented in 2017, with the addition of a pressure sensor. The performance of both sea level sensors and their response to sea level oscillations, at different frequencies, is assessed. Particular emphasis is put on the effect of extreme events, such as Storm Emma, when alternative methods to obtain 1-min data are tested, in contrast to the one based on arithmetic means. The overall differences are small, for the whole period of study (centered-root-mean-square-error below 1?cm, for 5-min, and hourly data; similar tidal parameters and sea level oscillations with periods between 30?s and 5?min). However, during Storm Emma, the pressure sensor presents sensibly lower readings than the radar, with the centered-root-mean-square-error rising to 80?mm on the March 2^nd 2018. A new method to compute 1-min data, based on medians, reduced this value to 10?mm for the same day.     

近40a来海南岛南岸的相对海平面变化

根据海南岛榆林验潮站１９５４～１９９２年连续３９ａ潮位观测资料，经过统一基准面校正后，运用多种统计分析方法研究，得出近４０ａ来海南岛南岸的相对海平面变化呈上升趋势，相应的平均上升速率为０．６４ｍｍ／ａ，这一数值较近百年来１～２ｍｍ／ａ的全球海平面上升速率明显偏小，反映出同期海南岛南岸的地面是微弱抬升的。     

Neural network for wave forecasting among multi-stations

Unlike in the open sea, the use of wind information for forecasting waves may encounter more ambiguous uncertainties in the coastal or harbor area due to the influence of complicated geometric configurations. Thus this paper attempts to forecast the waves based on learning the characteristics of observed waves, rather than the use of the wind information. This is reported in this paper by the application of the artificial neural network (ANN), in which the back-propagation algorithm is employed in the learning process for obtaining the desired results. This model evaluated the interconnection weights among multi-stations based on the previous short-term data, from which a time series of waves at a station can be generated for forecasting or data supplement based on using the neighbor stations data. Field data are used for testing the applicability of the ANN model. The results show that the ANN model performs well for both wave forecasting and data supplement when using a short-term observed wave data.     

A novel technique in analyzing non-linear wave-wave interaction

During wave growth non-linear wave–wave interactions cause transfer of some wave energy from lower to higher wave periods as the spectrum grows. Wavelet bicoherence, which is a new technique in the analysis of wind–wave and wave–wave interactions, is used to analyze non-linear wave–wave interactions. A selected record of wind wave that contains the maximum wave height observed during 6 h of wave generation is divided into five segments and wavelet bicoherence is computed for the whole record, and for all divided segments. The study shows that the non-linear wave–wave interaction occurs at different bicoherence levels and these levels are different from one segment to another due to the non-stationarity feature of the examined data set.     

粘土矿物去除赤潮生物的动力学研究

于１９９２年４－９月进行粘土矿的絮凝赤潮生物（微型原甲藻）的动力学研究；考察粘土种类、浓度、第二组分（ＰＡＣＳ）和ＰＨ等因素对絮凝速率的影响，建立粘土矿物絮凝赤潮生物的动力学模型，从理论上分析和讨论各种因素的影响，并提出提高絮凝速率的方法和途径。结果表明，高岭土体系絮凝速率大于蒙脱土体系，其速率方程可用双分子反应来描述。其中，速率常数随絮凝过程发生变化；粒子间的相互作用能和作用半径是控制和影响絮凝     

浙江南部海域富营养化和赤潮的探讨

本文探讨了浙江南部海域1990年春季发生赤潮期间的水化学特征和富营养化状况,及与赤潮生物的线性回归关系。分析结果表明,该海域出现高营养盐以至形成富营养化乃是江浙沿岸流和瓯江等河流径流及远岸区盐度锋辐聚的综合影响的结果。根据回归分析,NO_3-N,SiO_3-Si与浮游植物细胞密度之间存在着较为显著的负相关。亦即N,Si和高N/P比(35:1左右)可能是导致浮游植物(夜光藻)异常增殖的重要因素。     

Are Global Tide Gauge Data Stationary in Variance?

Tide gauges distributed all over the world provide valuable information for monitoring mean sea level changes. The statistical models used in estimating sea level change from the tide gauge data assume implicitly that the random model components are stationary in variance. We show that for a large number of global tide gauge data this is not the case for the seasonal part using a variate-differencing algorithm. This finding is important for assessing the reliability of the present estimates of mean sea level changes because nonstationarity of the data may have marked impact on the sea level rate estimates, especially, for the data from short records.     

两种涡鞭毛藻的周日垂直迁移特性研究

Ａｌｅｘａｎｄｒｉｕｍ ｌｕｓｉｔａｎｉｃｕｍ于１９８７年采自葡萄牙沿海，Ｙ－１００于１９８９年采自德国湾。在暗室中用一根柱长１５０ｃｍ，内径３．４ｃｍ的玻璃柱对两种涡鞭毛藻的垂直行特性进行研究。结果表明，两种藻均进行有规律的周日垂直迁移，且均在始前２ｈ开始向上迁移，光照结束前３ｈ开始向移速度约为２８０μｍ／ｓ，向下约为１４０μｍ／ｓ向下约为８５０μｍ／ｓ；Ｙ－１００向上迁移速度约为２８０μｍ／ｓ