Estimation of mean and extreme waves in the East China Seas

Accurately estimating the mean and extreme wave statistics and better understanding their directional and seasonal variations are of great importance in the planning and designing of ocean and coastal engineering works. Due to the lack of long-term wave measurement data, the analysis of extreme waves is often based on the numerical wave hind-casting results. In this study, the wave climate in the East China Seas (including the Bohai Sea, the Yellow Sea and the East China Sea) for the past 35 years (1979–2013) is hind-casted using a third generation wave model – WAMC4 (Cycle 4 version of WAM model). Two sets of reanalysis wind data from NCEP (National Centers for Environmental Prediction, USA) and ECMWF (European Centre for Medium-range Weather Forecasts) are used to drive the wave model to generate the long-term wave climate. The hind-casted waves are then analysed to study the mean and extreme wave statistics in the study area. The results show that the mean wave heights decrease from south to north and from sea to land in general. The extreme wave heights with return periods of 50 and 100 years in the summer and autumn seasons are significantly higher than those in the other two seasons, mainly due to the effect of typhoon events. The mean wave heights in the winter season have the highest values, mainly due to the effect of winter monsoon winds. The comparison of extreme wave statistics from both wind fields with the field measurements at several nearshore wave observation stations shows that the extreme waves generated by the ECMWF winds are better than those generated by the NCEP winds. The comparison also shows the extreme waves in deep waters are better reproduced than those in shallow waters, which is partly attributed to the limitations of the wave model used. The results presented in this paper provide useful insight into the wave climate in the area of the East China Seas, as well as the effect of wind data resolution on the simulation of long-term waves.     

Oil dispersal modelling: reanalysis of the Rena oil spill using open-source modelling tools

ABSTRACT

Oil spill forecast modelling is typically used immediately after a spill to predict oil dispersal and promote mobilisation of more effective response operations. The aim of this work was to map oil dispersal after the grounding of the MV Rena on Astrolabe Reef and to verify the results against observations. Model predictions were broadly consistent with observed distribution of oil contamination. However, some hot spots of oil accumulation, likely due to surf-zone and rip current circulation, were not well represented. Additionally, the model was run with 81 differing wind conditions to show that the events occurring during the grounding represented the typical likely behaviour of an oil spill on Astrolabe Reef. Oil dispersal was highly dependent on prevailing wind patterns; more accurate prediction would require better observations of local wind patterns. However, comparison of predictions with observations indicated that the GNOME model was an effective low-cost approach.     

2001年秋季风对坦帕湾盐度平衡的影响

利用三维高分辨率有限体积的近海海域模型FVCOM来分析2001年秋季期间风作用对坦帕湾区域盐度平衡的影响。为了区分风的影响,分别设计了两个实验：一个由潮汐和河流作为驱动,另一个由潮汐、河流以及风场共同驱动。结论如下：首先,风作用会使盐度产生变化,能够明显地使坦帕湾内的盐度增加,并导致水平和垂直方向上盐度梯度的减少;随后,本文分析了坦帕湾区域内的盐度平衡,主要的盐度平衡来自于全部（水平和垂直方向上）平流的盐度流量分歧以及除去海峡底部的垂直方向上盐度流量分歧;最后,对由风引起的盐度变化进一步进行分析,结果表明风作用不能改变盐度平衡地位的相对重要性,由风引起的盐度平衡改变高度依靠于特殊的地形,除此之外,全部平流盐度流量分歧和垂直散布盐度通量分歧能够抵消,并且两者都远大于水平散步盐度流量分歧。     

星载SAR对雨团催生海面风场的观测研究

雨团或对流雨是热带与亚热带地区的主要降雨形式,较易被高分辨率星载合成孔径雷达（SAR）探测到。SAR图像上的雨团足印是由大气中雨滴的散射与吸收、下沉气流等共同导致形成的。本文以RADARSAT-2卫星100 m分辨率的SAR图像上雨团引起的海面风场及其结构反演与解译作为实例进行分析。使用CMOD4地球物理模式函数,分别以NCEP再分析数据、欧洲MetOp-A卫星先进散射计（ASCAT）和中国HY-2卫星微波散射计的风向为外部风向,进行了SAR图像的海面风场反演。反演的海面风速相对于NCEP、ASCAT和HY-2的均方根误差（RMSE）分别为1.48 m/s,1.64 m/s和2.14 m/s。SAR图像上一侧明亮另一侧昏暗的圆形信号图斑被解译为雨团携带的下沉气流对海面风场（海面粗糙度）的改变所致。平行于海面背景风场其通过雨团圆形足印中心的剖面上的风速变化可拟合为正弦或余弦曲线,其拟合线性相关系数均不低于0.80。背景风场的风速大小、雨团引起的风速大小以及雨团足印的直径可利用拟合曲线获得,雨团足印的直径大小一般为数千米或数十千米,本文的8例个例解译与分析均验证了该结论。     

Geological control factors of micro oil distribution in tight reservoirs

Understanding the oil distribution characteristics in unconventional tight reservoirs is crucial for hydrocarbon evaluation and oil/gas extraction from such reservoirs. Previous studies on tight oil distribution characteristics are mostly concerned with the basin scale. Based on Lucaogou core samples, geochemical approaches including Soxhlet extraction, total organic carbon (TOC), and Rock-Eval are combined with reservoir physical approaches including mercury injection capillary pressure (MICP) and porosity-permeability analysis, to quantitatively evaluate oil distribution of tight reservoirs on micro scale. The emphasis is to identify the key geological control factors of micro oil distribution in such tight reservoirs. Dolomicrites and non-detrital mudstones have excellent hydrocarbon generation capacity while detritus-containing dolomites, siltstones, and silty mudstones have higher porosity and oil content, and coarser pore throat radius. Oil content is mainly controlled by porosity, pore throat radius, and hydrocarbon generation capacity. Porosity is positively correlated with oil content in almost all samples including various lithologies, indicating that it is a primary constraint for providing storage space. Pore throat radius is also an important factor, as oil migration is inhibited by the capillary pressure which must be overcome. If the reservoir rock with suitable porosity has no hydrocarbon generation capacity, pore throat radius will be decisive. As tight reservoirs are generally characterized by widely distributed nanoscale pore throats and high capillary pressure, hydrocarbon generation capacity plays an important role in reservoir rocks with suitable porosity and fine pore throats. Because such reservoir rocks cannot be charged completely. The positive correlation between hydrocarbon generation capacity and oil content in three types of high porosity lithologies (detritus-containing dolomites, siltstones, and silty mudstones) supports this assertion.     

基于船位监控系统的拖网捕捞努力量提取方法研究

为了基于船位监控系统提取拖网捕捞努力量,通过统计航速获得3个峰值,拖网作业在第2个峰值,即1~2.1 m/s,拖网作业航向差一般在–50°~50°。利用航速、航向差阈值设定,把拖网船状态划分为慢速、作业、航行,然后提取出捕捞作业状态点,1 423艘拖网船共提取到处于捕捞状态的点318 433个,合计拖网捕捞时间15 921 h,利用反距离加权插值法生成捕捞强度分布变化趋势图。捕捞努力量在渔业资源研究中是重要的参考值之一,与传统的捕捞努力量计算方法相比,该方法具有实时、大范围、快速、分辨率高的特点,能够用于辅助渔业资源保护。     

178Hz正弦波对刺参行为、呼吸及免疫应答的影响

根据山东荣成沿岸风电机组产生的声波范围选取其中178Hz的峰值声音,声压级控制于(85±5)d B,在实验室水槽中,采用实验生态学方法研究了178Hz声波影响下的刺参(Apostichopus japonicus)幼参的行为反应、耗氧率以及体腔液抗氧化酶(CAT、SOD)浓度的变化。通过平均聚集率的变化比较,发现刺参对178Hz的声波胁迫环境的行为反应敏感;利用空瓶法测得幼参耗氧率显著低于对照组(P0.05);通过测定刺参体腔液免疫活性发现在该频率声波干扰下的刺参CAT活性显著高于对照组(P0.05),而SOD活性于对照组差异不明显(P0.05)。研究结果说明声波对刺参幼参的呼吸和免疫会产生明显影响,可为我国近海刺参养殖和风电发展策略提供参考。     

基于同步风场的机载SAR海浪参数反演方法

针对机载合成孔径雷达(SAR)对海探测特点,采用多入射角法从SAR数据本身得到与海浪参数反演区域时空匹配的同步海面风速和风向,并结合线性变换关系,计算得到海浪初猜谱对应的仿真SAR图像谱,将仿真SAR图像谱和观测SAR图像谱输入代价函数中进行迭代运算,通过非线性方程的解算得到最适海浪谱;采用交叉谱法去除海浪传播180°方向模糊,最终得到海浪参数。论文提出的基于同步风场的机载SAR海浪参数反演方法,充分利用了机载SAR海洋环境探测的优势,解决了传统SAR海浪参数反演中初猜谱构造依赖外部风场的问题,机载同步飞行试验的海浪参数反演结果与浮标观测值的有效波高、波向的均方根误差分别为0.23 m和13.23°,验证了该方法的有效性,可为机载SAR海浪参数反演业务化提供支持。     

Discussion on applying an analytical method to optimize the anti-freeze design parameters for underground water pipelines in seasonally frozen areas

Adopting the quasi-three-dimensional (Quasi-3D) numerical method to optimize the anti-freeze design parameters of an underground pipeline usually involves heavy numerical calculations. Here, the fitting formulae between the safe conveyance distance (SCD) of a water pipeline and six influencing factors are established based on the lowest water temperature (LWT) along the pipeline axis direction. With reference to the current widely used anti-freeze design approaches for underground pipelines in seasonally frozen areas, this paper first analyzes the feasibility of applying the maximum frozen penetration (MFP) instead of the mean annual ground surface temperature (MAGST) and soil water content (SWC) to calculate the SCD. The results show that the SCD depends on the buried depth if the MFP is fixed and the variation of the MAGST and SWC combination does not significantly change the SCD. A comprehensive formula for the SCD is established based on the relationships between the SCD and several primary influencing factors and the interaction among them. This formula involves five easy-to-access parameters: the MFP, buried depth, pipeline diameter, flow velocity, and inlet water temperature. A comparison between the analytical method and the numerical results based on the Quasi-3D method indicates that the two methods are in good agreement overall. The analytic method can be used to optimize the anti-freeze design parameters of underground water pipelines in seasonally frozen areas under the condition of a 1.5 safety coefficient.     

Interactive discovery of sequential patterns in time series of wind data

Wind speed and direction vary over space and time due to the interactions between different pressures and temperature gradients within the atmospheric layers. Near the earth’s surface, these interactions are modulated by topography and artificial structures. Hence, characterizing wind behaviour over large areas and long periods is a complex but essential task for various energy-related applications. In this study, we present a novel approach to discover wind patterns by integrating sequential pattern mining and interactive visualization techniques. The approach relies on the use of the Linear time Closed pattern Miner sequence algorithm in conjunction with a time sliding window that allows the discovery of all sequential patterns present in the data. These patterns are then visualized using integrated 2D and 3D coordinated multiple views and visually explored to gain insight into the characteristics of the wind from a spatial, temporal and attribute (type of wind pattern) point of view. This proposed approach is used to analyse 10 years of hourly wind speed and direction data for 29 weather stations in the Netherlands. The results show that there are 15 main sequential patterns in the data. The spatial task shows that weather stations located in the same region do not necessarily experience similar wind pattern. For within the selected time interval, similar wind patterns can be observed in different stations and in the same station at different times of occurrence. The attribute task discovered that the repetitive occurrences of chosen pattern indicate as regular wind behaviour at different weather stations that persisted continuously over time. The results of these tasks show that the proposed interactive discovery facilitates the understanding of wind dynamics in space and time.