波向对变风向响应理论模式的检验

基于文圣常等提出的风浪成长标准曲线和普遍采用的无因次方法,将理论导出的波向对变风向响应模式表达成在资料处理中常采用的无因次形式,分别用Holthuijsen等的观测结果和Gao等用WAM模式数值计算的结果进行检验和比较.结果表明,所提出的理论结果较其他计算结果更与实测值相吻合.     

非匀质波场波向响应模式

本文基于波能平衡方程,通过考虑波浪传播项,即Δ↓「Ｃｓ（ｆ,θ）Ｅ（ｆ,θ）」≠０,理论上导出了非均质波场波向对变风向的响应模式,研究了波场非匀质性对波向响应的影响;导出了有限风区波浪产生的非均质情形下平均波向与无因次风区的关系;同时还进行了某些讨论。     

波场非匀质性对波向对变风向响应的影响

本文基于波能平衡方程，通过考虑波的传播项，即，研究波场非匀质性对波向对变风向的响应的影响。导出的结果表明，响应的时间尺度可由３部分表示：１．匀质情形响应的贡献；２．波能分布非匀质性的影响；３．平均波向分布非匀质性的影响。在理论上，它暗示波场的非匀质性在波向响应中起着实质性的作用；在实际情况下，对匀质和平稳风场，波场的非匀质性总是使响应时间尺度减少这一事实进行了讨论。     

波场非匀质性对波向对变风向响应的影响

本文基于波能平衡方程，通过考虑波的传播项，即△↓［（Ｃｇ（ｆ，０）Ｅ（ｆ，０）］≠０，研究波场非匀质性对波向对变风向的响应的影响。导出的结果表明，响应的时间尺度可由３部分表示：１．匀质情形响应的贡献；２．波能分布非匀质性的影响；３．平均波向分布非匀质性的影响。在理论上，它暗示波场的非匀质性在波向响应中起着实质性的作用；在实际情况下，对匀匀和平稳风场，波场的非匀质性总是使响应时间尺度减少这一事实进行     

非匀质波场波向响应模式

本文基于波能平衡方程,通过考虑波浪传播项,即［Ｃｇ（ｆ,θ）Ｅ（ｆ,θ）］ ≠０ ,理论上导出了非匀质波场波向对变风向的响应模式;研究了波场非匀质性对波向响应的影响;导出了有限风区波浪产生的非匀质情形下平均波向与无因次风区的关系;同时还进行了某些讨论。     

非匀质波场波向对变风向响应现场观测设计

理论导出的非匀质波场波向对变风向响应的模式表明,单点波浪观测资料不足以提供非匀质情况下波向对变风向响应的信息。基于理论模式,提出了采用仪器阵列进行波浪观测研究波向响应的观测设计方案。     

非匀质波场波向对变风向响应现场观测设计

理论导出的非匀质波场波向对变风向响应的模式表明,单点波浪观测资料不足以提供非匀质情况下波向对变风向响应的信息。基于理论模式,提出了采用仪器阵列进行波浪观测研究波向响应的观测设计方案。     

向岸风作用下海浪方向谱的某些统计特征

本文基于956 pitch-roll wave track buoy 测得的资料,研究由风暴引起的向岸风作用下的海浪方向谱的某些统计特征。结果表明:海浪方向谱相对频率和方向的分布多为双峰谱;中频段组成波平均波向对局地变风速和变风向产生响应,使其平均波向与风向趋于一致,高频段和低频段组成波平均波向对变风速和变风向基本不产生影响;谱峰频率对应的特征波平均波向频率分布与风向频率分布符合良好;在风浪消衰过程中,由于远离测点外海波场的影响,使海浪有效波高衰减缓慢。     

第5章 耦合混合(型)模式

5.1 风浪谱 由经验可知,处于成长状态的风浪谱,在各种风浪生成条件下,往往有着大致一样的谱形。此一事实可促使对风浪谱进行参数描述。谱的分布只是随频率及能量的尺度不同而异,若用g和局部风速U或者摩擦速度u_*进行无因次化处理,还可进一步发现频率及能量两个尺度参数间的近似关系。因此,成长风浪谱在一阶近似下便可由一个无因次变量来表征,如无因次能量E~*=Eg~2u_*~(-4),所有其它无因次变量,诸如无因次峰频f_p~*=u_*f_p/g及Phillips“常数”α,便可随之确定。E~*与充分成长能量E_∞~*之比,则提供了风浪“年令”的唯一量度。     

深水风浪的风区指数律

对已有根据观测提出的幂函数形式风浪成长关系进行了分析。发现这些风浪成长关系在消去无因次风区后一致地与3／2指数律相协调，尽管它们原来存在较大的不协调性。发现Jeffreys，Sverdrup和Munk以及Platit的风能输入源函数在谱积分意义下具有相似性，而Tsikunov，Hasselmann和Phillips的破波耗散源函数在谱积分意义下也具有相似性，尽管这些源函数的原始形式和物理背景显著地不同。利用有效波能量平衡方程，将3／2指数律和发现的风能输入及破波耗散源函数相似性相结合，提出了深水风浪随风区成长的分式指数律，以得到的分式指数律拟合已有基于观测提出的风浪成长关系提出了半经验的风浪成长关系，与已有观测数据符合。     

A model for the response of wave directions in slowly turning wind fields

On the basis of the wave energy balance equation, the response model of mean directions of locally wind-generated waves in slowly turning wind fields has been derived. The results show that in a homogeneous field, the time scale of the response is not only related to the rate of wave growth, but also to the directional energy distribution and the angle between the wind direction and the mean wave direction. Furthermore, the law of change in the mean wave direction has been derived. The numerical computations show that the response of wave directions to slowly turning wind directions can be treated as the superposition of the responses of wave directions to a series of sudden small-angle changes of wind directions and the turning rate of the mean wave direction depends on the turning rate and the total turning angles of the wind direction. The response of wave directions is in agreement with the response for a sudden change of wind directions if the change in wind directions is very fast. Based on the no     

两类典型台风路径影响下的黄、渤海海浪场特征研究

台风引起的海浪灾害对我国黄、渤海沿岸影响巨大,严重威胁相关区域人民群众生命财产安全.本文主要利用ERA5(the fifth generation European Center for Medium-Range Weather forecasts atmospheric reanalysis of the globa...     

风浪成长关系的分析及其对3/2指数律的支持

系统地分析比较了迄今根据观测已提出的一些风浪成长关系。通过研究发现 :这些风浪成长关系式存在较大的不协调性。然而 ,当消去无因次风区后 ,由这些关系式得到的无因次波高与无因次周期关系却与 3/ 2指数律有着非常好的协调一致性。还分析 Wen etal构造出的代表平均状况的风浪成长关系。发现由这一风浪成长关系得到的无因次波高与无因次周期关系是与平均状况的 3/ 2指数律完全一致的。上述风浪成长关系构成对 3/ 2指数律的观测支持 ,从而说明了 3/ 2指数律的普遍性。并提出这些风浪成长关系间不协调性的一个可能解释     

Wave Energy Estimation by Using A Statistical Analysis and Wave Buoy Data near the Southern Caspian Sea

Statistical analysis was done on simultaneous wave and wind using data recorded by discus-shape wave buoy. The area is located in the southern Caspian Sea near the Anzali Port. Recorded wave data were obtained through directional spectrum wave analysis. Recorded wind direction and wind speed were obtained through the related time series as well. For 12-month measurements(May 25 2007-2008), statistical calculations were done to specify the value of nonlinear auto-correlation of wave and wind using the probability distribution function of wave characteristics and statistical analysis in various time periods. The paper also presents and analyzes the amount of wave energy for the area mentioned on the basis of available database. Analyses showed a suitable comparison between the amounts of wave energy in different seasons. As a result, the best period for the largest amount of wave energy was known. Results showed that in the research period, the mean wave and wind auto correlation were about three hours. Among the probability distribution functions, i.e Weibull, Normal, Lognormal and Rayleigh, "Weibull" had the best consistency with experimental distribution function shown in different diagrams for each season. Results also showed that the mean wave energy in the research period was about 49.88 k W/m and the maximum density of wave energy was found in February and March, 2010.     

南麂海域大浪与大风的分布关系

本文根据南麂海洋站１９８３～１９８９年实测风和浪的资料，分析了大风和大浪的关系。结果表明：大浪日、大风日各月出现次数不匀。风浪大浪日及涌浪大浪日出现比率分别占５６％和４４％。各向大浪波高均值变化幅度不大。各向大浪波高极值却有较大差异。风浪Ｈ１／１０波高为１．５～２．０ｍ、当风速为１１～１３ｍ／ｓ时，大浪出现频率最高。本文还给出了波龄较大的风浪大浪波高与大风风速的经验关系。基于不同类型的台风路径，得到了本区从Ｈ１／１０波高为１．５ｍ以上时台风中心的位置。利用此结果可以预报本区大浪出现的时间。     

An evaluation of model estimates of ocean wave directions

The potential accuracy of local models is investigated to determine the mean direction of waves from the time history of locally observed significant wave height (or peak frequency) and locally observed wind. This is done by comparing results of such models with observations at a location in the southern North Sea for a period of six weeks. The model results are also compared with results of two synoptic models which require large scale wind information to estimate the local mean wave direction.For significant wave heights larger than 1.5 m the rms-error of the estimated mean wave direction was about 30° for the best performing local model and about 15° for the best performing synoptic model.     

Wind- and wave-field measurements using marine X-band radar-image sequences

This paper describes two algorithms for the retrieval of high-resolution wind and wave fields from radar-image sequences acquired by a marine X-band radar. The wind-field retrieval algorithm consists of two parts. In the first part, wind directions are extracted from wind-induced streaks, which are approximately in line with the mean surface wind direction. The methodology is based on the retrieval of local gradients from the mean radar backscatter image and assumes the surface wind direction to be oriented normal to the local gradient. In the second part, wind speeds are derived from the mean radar cross section. Therefore, the dependence of the radar backscatter on the wind vector and imaging geometry has to be determined. Such a relationship is developed by using neural networks (NNs). For the verification of the algorithm, wind directions and speeds from nearly 3300 radar-image sequences are compared to in situ data from a colocated wind sensor. The wave retrieval algorithm is based on a methodology that, for the first time, enables the inversion of marine radar-image sequences to an elevation-map time series of the ocean surface without prior calibration of the acquisition system, and therefore, independent of external sensors. The retrieved ocean-surface elevation maps are validated by comparison of the resulting radar-derived significant wave heights, with the significant wave heights acquired from three colocated in situ sensors. It is shown that the accuracy of the radar-retrieved significant wave height is consistent with the accuracy of the in situ sensors.     

Local balance in the air-sea boundary processes

A new growth equation for wind waves of simple spectrum is presented upon three basic concepts. The period and the wave height of significant waves in dimensionless forms, which are considered to correspond to the peak frequency and the energy level, respectively, are used as representative quantities of wind waves. One of the three basic concepts is the concept of local balance, and the other two concern the acquisition of wave energy and the dissipation of wave energy, respectively. It is shown from some actual data that the equation, together with two universal constants concerning the acquisition and the dissipation of wave energy (B=6.2×10^?2 andK=2.16×10^?5, respectively), is applied universally to wide ranges of wind waves from those in a wind-wave tunnel to fully developed sea in the open ocean. “The three-second power law for wind waves of simple spectrum”, and a few relations as the lemmas, are derived, such that the mean surface transport due to the orbital motion of wind waves is always proportional to the friction velocity in wind, and that the steepness is inversely proportional to the root of the wave age. It is also derived that the portion of wind stress which directly enters the wind waves decreases exponentially with increasing wave age and is 7.5 % of the total wind stress for very young waves. Also, equations are presented as to the increase of momentum of drift current, and as to the supply of turbulent energy by wind waves into the upper ocean.     

The energy cycle of wind waves on the sea surface

The problems of wind-induced waves on the sea surface are considered. To this end, the empirical fetch laws that determine variations in the basic periods and heights of waves in relation to their fetch are used. The relation between the fetch and the physical time is found, as are the dependences of the basic characteristics of waves on the time of wind forcing. It is found that about 5% of wind energy dissipated in the near-water air layer contributes to the growth of wave heights, i.e. wave energy, although this quantity depends on the age of waves and the exponent in the fetch laws. With consideration for estimates of the probability distribution functions for the wind over the world ocean [11], it is found that the rate of wind-energy dissipation in the near-water air layer is on the order of 1 W/m². The calculations of wind waves [19] for the world ocean for 2007 have made it possible to assess the mean characteristics of the cycle of wave development and their seasonal variations. An analysis of these calculations [19] shows that about 20% of wind energy is transferred to the water surface. The remaining amount (80%) of wind energy is spent on the generation of turbulence in the near-water air layer. About 2%, i.e., one tenth of the energy transferred to water, is spent on turbulence generation due to the instability of the vertical velocity profile of the Stokes drift current and on energy dissipation in the surf zones. Of the remaining 18%, 5% is spent directly on wave growth and 13% is spent on the generation of turbulence during wave breaking and on a small-scale spectral region. These annually and globally mean estimates have a seasonal cycle with an amplitude on the order of 20% in absolute values but with a smaller amplitude in relative values. According to [19] and to the results of this study, the annually mean height of waves is estimated as 2.7 m and their age is estimated as 1.17.