Joint Return Value Estimation of Significant Wave Heights and Wind Speeds with Bivariate Copulas

The joint design criteria of significant wave heights and wind speeds are quite important for the structural reliability of fixed offshore platforms.However,the design method that regards different ocean environmental variables as independent is conservative.In the present study,we introduce a bivariate sample consisting of the maximum wave heights and concomitant wind speeds of the threshold by using the peak-over-threshold and declustering methods.After selecting the appropriate bivariate copulas and univariate distributions and blocking the sample into years,the bivariate compound distribution of annual extreme wave heights and concomitant wind speeds is constructed.Two joint design criteria,namely,the joint probability density method and the conditional probability method,are applied to obtain the joint return values of significant wave heights and wind speeds.Results show that(28.5±0.5)m s^(-1)is the frequently obtained wind speed based on the Atlantic dataset,and these joint design values are more appropriate than those calculated by univariate analysis in the fatigue design.

The seasonal variations in the significant wave height and sea surface wind speed of the China's seas

Long-term variations in a sea surface wind speed （WS） and a significant wave height （SWH） are associated with the global climate change, the prevention and mitigation of natural disasters, and an ocean resource exploitation, and other activities. The seasonal characteristics of the long-term trends in China＇s seas WS and SWH are determined based on 24 a （1988-2011） cross-calibrated, multi-platform （CCMP） wind data and 24 a hindcast wave data obtained with the WAVEWATCH-III （WW3） wave model forced by CCMP wind data. The results show the following. （1） For the past 24 a, the China＇s WS and SWH exhibit a significant increasing trend as a whole, of 3.38 cm/（s.a） in the WS, 1.3 cm/a in the SWH. （2） As a whole, the increasing trend of the China＇s seas WS and SWH is strongest in March-April-May （MAM） and December-January-February （DJF）, followed by June-July-August （JJA）, and smallest in September-October-November （SON）. （3） The areal extent of significant increases in the WS was largest in MAM, while the area decreased in JJA and DJF; the smallest area was apparent in SON. In contrast to the WS, almost all of China＇s seas exhibited a significant increase in SWH in MAM and DJF; the range was slightly smaller in JJA and SON. The WS and SWH in the Bohai Sea, the Yellow Sea, East China Sea, the Tsushima Strait, the Taiwan Strait, the northern South China Sea, the Beibu Gull and the Gulf of Thailand exhibited a significant increase in all seasons. （4） The variations in China＇s seas SWH and WS depended on the season. The areas with a strong increase usually appeared in DJF.

Long-Term Characterization of Sea Conditions in the East China Sea Using Significant Wave Height and Wind Speed

In this study, the statistical characterization of sea conditions in the East China Sea(ECS) is investigated by analyzing a significant wave height and wind speed data at a 6-hour interval for 30 years(1980–2009), which was simulated and computed using the WAVEWATCH Ⅲ(WW3) model. The monthly variations of these parameters showed that the significant wave height and wind speed have minimum values of 0.73 m and 5.15 ms^(-1) and 1.73 m and 8.24 ms^(-1) in the month of May and December, respectively. The annual, seasonal, and monthly mean sea state characterizations showed that the slight sea generally prevailed in the ECS and had nearly the highest occurrence in all seasons and months. Additionally, the moderate sea prevailed in the winter months of December and January, while the smooth(wavelets) sea prevailed in May. Furthermore, the spatial variation of sea states showed that the calm and smooth sea had the largest occurrences in the northern ECS. The slight sea occurred mostly(above 30%) in parts of the ECS and the surrounding locations, while higher occurrences of the rough and very rough seas were distributed in waters between the southwest ECS and the northeast South China Sea(SCS). The occurrences of the phenomenal sea conditions are insignificant and are distributed in the northwest Pacific and its upper region, which includes the Southern Kyushu-Palau Ridge and Ryukyu Trench.

Joint Occurrence Period of Wind Speed and Wave Height Based on Both Service Term and Risk Probability

Return periods calculated for different environmental conditions are key parameters for ocean platform design.Many codes for offshore structure design give no consideration about the correlativity among multi-loads and over-estimate design values.This frequently leads to not only higher investment but also distortion of structural reliability analysis.The definition of design return period in existing codes and industry criteria in China are summarized.Then joint return periods of different ocean environmental parameters are determined from the view of service term and danger risk.Based on a bivariate equivalent maximum entropy distribution,joint design parameters are estimated for the concomitant wave height and wind speed at a site in the Bohai Sea.The calculated results show that even if the return period of each environmental factor,such as wave height or wind speed,is small,their combinations can lead to larger joint return periods.Proper design criteria for joint return period associated with concomitant environmental conditions will reduce structural size and lead to lower investment of ocean platforms for the exploitation of marginal oil field.

Applicability evaluation of ERA5 wind and wave reanalysis data in the South China Sea

Wind and wave data are essential in climatological and engineering design applications.In this study,data from 15 buoys located throughout the South China Sea(SCS)were used to evaluate the ERA5 wind and wave data.Applicability assessment are beneficial for gaining insight into the reliability of the ERA5 data in the SCS.The bias range between the ERA5 and observed wind-speed data was-0.78-0.99 m/s.The result indicates that,while the ERA5 wind-speed data underestimation was dominate,the overestimation of such data existed as well.Additionally,the ERA5 data underestimated annual maximum wind-speed by up to 38%,with a correlation coefficient>0.87.The bias between the ERA5 and observed significant wave height(SWH)data varied from-0.24 to 0.28 m.And the ERA5 data showed positive SWH bias,which implied a general underestimation at all locations,except those in the Beibu Gulf and centralwestern SCS,where overestimation was observed.Under extreme conditions,annual maximum SWH in the ERA5 data was underestimated by up to 30%.The correlation coefficients between the ERA5 and observed SWH data at all locations were greater than 0.92,except in the central-western SCS(0.84).The bias between the ERA5 and observed mean wave period(MWP)data varied from-0.74 to 0.57 s.The ERA5 data showed negative MWP biases implying a general overestimation at all locations,except for B1(the Beibu Gulf)and B7(the northeastern SCS),where underestimation was observed.The correlation coefficient between the ERA5 and observed MWP data in the Beibu Gulf was the smallest(0.56),and those of other locations fluctuated within a narrow range from 0.82 to 0.90.The intercomparison indicates that during the analyzed time-span,the ERA5 data generally underestimated wind-speed and SWH,but overestimated MWP.Under non-extreme conditions,the ERA5 wind-speed and SWH data can be used with confidence in most regions of the SCS,except in the central-western SCS.

The comparison of altimeter retrieval algorithms of the wind speed and the wave period

With the launch of altimeter,much effort has been made to develop algorithms on the wind speed and the wave period.By using a large data set of collocated altimeter and buoy measurements,the typical wind speed and wave period algorithms are validated.Based on theoretical argument and the concept of wave age,a semi-empirical algorithm for the wave period is also proposed,which has the wave-period dimension,and explicitly demonstrates the relationships between the wave period and the other variables.It is found that Ku and C band data should be applied simultaneously in order to improve either wind speed or wave period algorithms.The dual-band algorithms proposed by Chen et al.(2002) for the wind speed and Quilfen et al.(2004) for the wave period perform best in terms of a root mean square error in the practical applications.

Analysis on monthly-averaged distribution of sea surface wind and wave over the seas southeast of Asia using ERS-2 scatterometer data

在亚洲(SSEA ) 的海东南上的风系在中国的气候变化起一个重要作用。在这篇论文， ERS scatterometer 弯屈从 2000 年 1 月盖住时期到 2000 年 12 月和 2-41 ° N 的区域， 105-130 ° E 与重量 adistance 插值方法和海面风速度的每月吝啬的分发被分析被给。在 SSEA 的风的季节的特征被分析。基于的 onWAVEWATCH Ⅲ模型，有效波高的分发被计算。

An evaluation of input/dissipation terms in WAVEWATCH Ⅲ using in situ and satellite significant wave height data in the South China Sea

A WAVEWATCH III version 3.14（WW3） wave model is used to evaluate input/dissipation source term packages WAM3, WAM4 and TC96 considering the effect of atmospheric instability. The comparisons of a significant wave height acquired from the model with different packages have been performed based on wave observation radar and HY-2 altimetry significant wave height data through five experiments in the South China Sea domain spanning latitudes of 0°–35°N and longitudes of 100°–135°E. The sensitivity of the wind speed correction parameter in the TC96 package also has been analyzed. From the results, the model is unable to dissipate the wave energy efficiently during a swell propagation with either source packages. It is found that TC96 formulation with the ＂effective wind speed＂ strategy performs better than WAM3 and WAM4 formulations. The wind speed correction parameter in the TC96 source package is very sensitive and needs to be calibrated and selected before the WW3 model can be applied to a specific region.

Development and validation of an ocean wave retrieval algorithm for VV-polarization Sentinel-1 SAR data

The purpose is to study the accuracy of ocean wave parameters retrieved from C-band VV-polarization Sentinel-1Synthetic Aperture Radar（SAR） images, including both significant wave height（SWH） and mean wave period（MWP）, which are both calculated from a SAR-derived wave spectrum. The wind direction from in situ buoys is used and then the wind speed is retrieved by using a new C-band geophysical model function（GMF） model,denoted as C-SARMOD. Continuously, an algorithm parameterized first-guess spectra method（PFSM） is employed to retrieve the SWH and the MWP by using the SAR-derived wind speed. Forty-five VV-polarization Sentinel-1 SAR images are collected, which cover the in situ buoys around US coastal waters. A total of 52 subscenes are selected from those images. The retrieval results are compared with the measurements from in situ buoys. The comparison performs good for a wind retrieval, showing a 1.6 m/s standard deviation（STD） of the wind speed, while a 0.54 m STD of the SWH and a 2.14 s STD of the MWP are exhibited with an acceptable error.Additional 50 images taken in China＇s seas were also implemented by using the algorithm PFSM, showing a 0.67 m STD of the SWH and a 2.21 s STD of the MWP compared with European Centre for Medium-range Weather Forecasts（ECMWF） reanalysis grids wave data. The results indicate that the algorithm PFSM works for the wave retrieval from VV-polarization Sentinel-1 SAR image through SAR-derived wind speed by using the new GMF C-SARMOD.

The temporal and spatial variations in the Pacific wind and wave fields for the period 2002–2011

The temporal and spatial variations in the wind and wave fields in the Pacific Ocean between 2002 and 2011 are analyzed using a third-generation wave model（WAVEWATCH III）. The model performance for a significant wave height is validated using in situ buoy data. The results show that the wave model effectively hindcasts the significant wave height in the Pacific Ocean, but the errors are relatively large in the mid- and low-latitude regions. The spatial distributions and temporal variations in a wind speed and the significant wave height in the Pacific Ocean are then considered after dividing the Pacific Ocean into five regions, which show meridional differences and seasonal cycles. Regional mean values are used to give yearly average time series for each separate zone. The high latitude region in the Southern Hemisphere had a stronger significant wave height trend in the model results than regions at other latitudes. The sources and sinks of wave energy are then investigated. Their regional mean values are used to quantify variations in surface waves. Finally, the spectral analyses of the daily mean wind speeds and the significant wave heights are obtained. The significant wave height and the wind speed spectra are found to be connected in some ways but also show certain differences.

SAR Azimuth Cut-off to Estimate Wind Speed under High Wind Regimes

In this study,the azimuth cut-off method,typically used for SAR moderate wind speed estimation purposes,is analyzed under high wind regimes.Firstly,the importance of the pixel spacing,the size of the boxes selected for Synthetic Aperture Radar(SAR)image partitioning and the image texture in terms of homogeneities are discussed by considering their influence on the azimuth cut-off(λc)estimation.Secondly,a quality control analysis of the reliability ofλc is carried out by evaluating the distance between the autocorrelation functions(ACF)and their correspondent fittings.This analysis points out the importance of filtering out the unreliable and unfeasibleλc values in order to improve the wind speed estimation.The quality control procedure is based on a x2 test,applied on a large Sentinel-1 A dataset.The soundness of the test is verified by an increment in terms of correlation betweenλc estimations and wind speed values.This approach is,then,applied under high wind regimes,i.e.,tropical cyclones.

Comparison of retrieving methods of ocean wave periods from satellite altimeter with buoy measurements

为验证检索吝啬的波浪时期的结果，以前建立的四个实验算法被介绍。把年基于超过五的数据为全部华东海的导出的 fromTOPEX 卫星高度表，海浪时期被计算，在他们之中的统计比较被执行。检索吝啬的波浪时期 < T > 与我们参数更好显示出的新分发获得了同意，波浪时期 T_B 比由另外的三个算法计算了由浮标测量了。平均值之间的差别 < T > 并且 T_B 的是 0.16 s 和 RMSE (根均方误差)< T > 是最低价值(0.48 ) 。

Observing seasonal variations of sea surface wind speed and significant wave height using TOPEX altimetry

One year of ocean topography experiment (TOPEX) altimeter data are used to study the seasonal variations of global sea surface wind speed and significant wave height. The major wind and wave zones of the world oceans are precisely identified, their seasonal variability and characteristics are quantitatively analyzed, and the diversity of global wind speed seasonality and the variability of significant wave height in response to sea surface wind speed are also revealed.

考虑时间相关性的风速和波浪高度短期预测

风与波浪高度是海洋工程设计的重要参数之一,其准确预测具有重要的工程意义。针对波浪高度复杂多变、难以预测的挑战,本文考虑时间相关性,利用长短时记忆(Long-Short-Term Memory,LSTM)神经网络方法建立风和波浪高度的短期预测模型。首先,对波浪高度和风速等海洋环境原始时间序列进行分析,并选取不同时间间隔对浪高和风速极值进行取值;其次,对风速与波浪高度开展相关性分析,并基于LSTM方法,构建风和波浪高度单步预测模型。在时间间隔为0.5 h时,波浪的预测误差为0.12 m;进而构建风和波浪联合预测模型,预测风速下的波高预测误差仅为0.12m,与实测风速下的波浪预测误差基本一致。

基于WAVEWATCH-Ⅲ模式的近10年南海波候统计分析

基于国际上较为先进的第三代海浪数值模式WAVEWATCH-Ⅲ,以QuikSCAT/NCEP混合风场为驱动场,得到南海1999年8月—2009年7月的海浪场,并据此对近10 a南海的波候特征进行分析。结果表明:(1)南海受季风影响显著,风场和浪场的对应关系在季风盛行季节明显好于季风过渡季节。(2)南海南部海域的浪场对海表风场的响应比南海北部海域更为显著,南海北部海域海表风场与浪场的相关系数月变化较明显。(3)1月南海5级以上大浪出现的频率较高,但没有出现8级以上的大浪;4月、7月、10月大浪基本只在南海北部、中部海域出现,7月和10月均有一定频数的8级以上大浪出现。(4)极值风速与极值波高的分布较为一致,大值区均集中在台湾以东、东沙群岛附近海域。

基于全球卫星导航系统的海洋环境监测方法研究综述

实时、准确、可靠地监测海洋环境信息,对于海洋灾害预警预报、防灾减灾、海洋资源开发、保障海洋安全等具有至关重要的作用。近年来,随着全球卫星导航系统(GNSS)不断发展与升级,基于GNSS导航信号进行大气和海洋环境信息探测发展成为新技术新方法,并成为海洋环境监测技术研究热点,已在海洋气象监测、数值预报、科学研究等领域得到了广泛应用。系统综述了GNSS技术在海面有效波高、风速、降雨强度、水汽及潮位监测等海洋环境监测领域的应用研究现状,对新技术新方法进行了系统总结,并对未来发展趋势进行了展望,以期对相关领域的研究提供参考。

Nonparametric estimations of the sea state bias for a radar altimeter

To estimate the sea state bias（SSB） for radar altimeter, two nonparametric models, including a Nadaraya-Watson（NW） kernel estimator and a local linear regression（LLR） estimator, are studied based on the Jason-2 altimeter data. Selecting from different combinations of the Gaussian kernel function, spherical Epanechnikov kernel function, a fixed bandwidth and a local adjustable bandwidth, it is observed that the LLR method with the spherical Epanechnikov kernel function and the local adjustable bandwidth is the optimal nonparametric model for the SSB estimation. The comparisons between the nonparametric and parametric models are conducted and the results show that the nonparametric model performs relatively better at high-latitudes of the Northern Hemisphere. This method has been applied to the HY-2A altimeter as well and the same conclusion can be obtained.

Sea State Bias Estimation with Least Absolute Shrinkage and Selection Operator(LASSO)

With the sea-level rising,the measurement of sea surface height(SSH) is attracting more and more attention in the area of oceanography.Satellite radar altimeter is usually used to measure the SSH.However,deviation between the measured value and the actual one always exists.Among others,the sea state bias(SSB) is a main reason to cause the deviation.In general,one needs to estimate SSB first to correct the measured SSH.Currently,existing SSB estimation methods more or less have shortcomings,such as with many parameters,high prediction error and long training time.In this paper,we introduce an effective and efficient linear model called LASSO to the SSB estimation.The LASSO algorithm minimizes the residual sum of squares under the condition that the sum of the absolute values of each coefficient is less than a certain constant.In the implementation of LASSO,we use the significant wave height and wind speed to fit the LASSO model.Hence,the applied model has only 3 parameters,corresponding to the two inputs and a bias.Experimental results on the data of JASON-2,JASON-3,T/P and HY-2 radar altimetry show that LASSO performs better than geophysical data records(GDR) and ordinary least squares(OLS) estimator.Moreover,from the running time,we can see that LASSO is very efficient.

Statistical Analyses of Sea State Conditions in South China Sea

The statistical characterization of sea conditions in the South China Sea(SCS) was investigated by analyzing a 30-year(1976–2005) numerically simulated daily wave height and wind speed data. The monthly variation of these parameters shows that wave height and wind speed have minimum values of 0.54 m and 4.15 ms^(-1), respectively in May and peak values of 2.04 m and 8.12 ms^(-1), respectively in December. Statistical analysis of the daily wave height and wind speed and the subsequent characterization of the annual, seasonal and monthly mean sea state based on these parameters were also done. Results showed that, in general, the slight sea state prevails in the SCS and has nearly the highest occurrence in all seasons and months. The moderate sea condition prevails in the winter months of December and January while the smooth(wavelets) sea state prevails in May. Furthermore, spatial variation of sea states showed that calm and smooth sea conditions have high occurrences(25%–80%) in the southern SCS. The slight sea condition shows the largest occurrence(25%–55%) over most parts of the SCS. High occurrences(8%–17%) of the rough and very rough seas distribute over some regions in the central SCS. Sea states from high to phenomenal conditions show rare occurrence(<12%) in the northern SCS. The calm(glassy) sea condition shows no occurrence in the SCS.

江苏滨海海域海上风电场的极值波高推算

为了给江苏滨海海域海上风电场的结构设计提供更为合理的设计参数,本文利用定量分析法对比分析了采用不同推算方法推算得到的工程海域极值波高,讨论了不同推算方法的差异及影响。结果表明:采用年极值法、条件极值法(包括风暴统计法、阈值上限法)和组合法推算出的工程海域极值波高受理论频率曲线、热带风暴年均频次、极端设计风速和特定水位的影响较大。其中,热带风暴年均频次主要影响风暴统计法推算的结果,当热带风暴年均频次不小于1时,推算的结果趋于稳定,相对偏差小于5%;极端设计风速和特定水位主要影响组合法推算的结果,极端设计风速的选择主要影响极值波高在各个方向上的分布,特定水位的叠加主要影响极值波高的幅值;对于非特定水位下的极值波高,利用条件极值法中的风暴统计法推算的结果最大,为6.55m;利用年极值法中P-Ⅲ型曲线推算的结果最小,为5.48m;两者相对偏差约20%;对于特定水位下的极值波高,利用组合法推算出的NW—SE方向极值波高与水位呈正相关,即叠加正水位时,极值波高增大,叠加负水位时,极值波高减小,幅值变化可达±15%;且极值波高的方向分布与所采用的极端设计风速的方向分布相同,利用极值波高对应的设计风速推算出的极值波高在各方向上的分布更符合实际海况。