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.

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.

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.

Revisiting the seasonal wave height variability in the South China Sea with merged satellite altimetry observations

The seasonal variability of the significant wave height（SWH） in the South China Sea（SCS） is investigated using the most up-to-date gridded daily altimeter data for the period of September 2009 to August 2015. The results indicate that the SWH shows a uniform seasonal variation in the whole SCS, with its maxima occurring in December/January and minima in May. Throughout the year, the SWH in the SCS is the largest around Luzon Strait（LS） and then gradually decreases southward across the basin. The surface wind speed has a similar seasonal variation, but with different spatial distributions in most months of the year. Further analysis indicates that the observed SWH variations are dominated by swell. The wind sea height, however, is much smaller. It is the the largest in two regions southwest of Taiwan Island and southeast of Vietnam Coast during the northeasterly monsoon, while the largest in the central/southern SCS during the southwesterly monsoon. The extreme wave condition also experiences a significant seasonal variation. In most regions of the northern and central SCS, the maxima of the 99 th percentile SWH that are larger than the SWH theoretically calculated with the wind speed for the fully developed seas mainly appear in August–November, closely related to strong tropical cyclone activities.Compared with previous studies, it is also implied that the wave climate in the Pacific Ocean plays an important role in the wave climate variations in the SCS.

The difference between the joint probability distributions of apparent wave heights and periods and individual wave heights and periods

The joint distribution of wave heights and periods of individual waves is usually approximated by the joint distribution of apparent wave heights and periods. However there is difference between them. This difference is addressed and the theoretical joint distributions of apparent wave heights and periods due to Longuet-Higgins and Sun are modified to give more reasonable representations of the joint distribution of wave heights and periods of individual waves. The modification has overcome an inherent drawback of these joint PDFs that the mean wave period is infinite. A comparison is made between the modified formulae and the field data of Goda, which shows that the new formulae consist with the measurement better than their original counterparts.

Modified Joint Distribution of Wave Heights and Periods

The modified versions of the linear theoretical model of Longuet-Higgins （1983） are derived in this work and also compared with the laboratory experiments carried out in MAR1NTEK. The main feature of modifications is to replace the mean frequency in the formulation with the peak frequency of the wave spectrum. These two alternative forms of joint distributions are checked in three typical random sea states characterized by the initial wave steepness. In order to further explore the properties ＆these models, the associated marginal distributions of wave heights and wave periods are also researched with the observed statistics and some encouraging results are obtained.

WAVEWATCH Ⅲ模式在渤海海浪预报的应用与检验

大连黄海、渤海海浪数值预报系统采用WAVEWATCH III模式进行海浪预报,预报产品包括48 h内浪高、周期和浪向的逐3 h预报,并可对其进行检验。结果表明:WAVEWATCH III模式对渤海中部浪高模拟较好,浪高预报TS为71.7%,对近岸海区浪高模拟相对较差。个例检验表明,浪高最大值模拟较好,模拟浪高最大值出现的时间与实况基本吻合,浪高变化趋势预报也较好。WAVEWATCH III模式对两个周期个例进行检验,预报误差最低可达0.17 s,预报效果较好。

WAVEWATCH Ⅲ和SWAN模式在南海北部海域海浪模拟结果的对比分析

基于1987年9月到1988年8月期间南海北部的一个浮标资料,首先分析了美国环境预报中心(NCEP)和国家大气研究中心(NCAR)联合推出的再分析风场在南海北部海域的适用性,结果表明NCEP/NCAR再分析风场在一定程度上与浮标观测结果相一致。然后利用NCEP/NCAR再分析风场作为海浪模式输入场,评估了WAVEWATCHⅢ(WW3)和Simulating Waves Nearshore(SWAN)这2个海浪模式在南海北部海域模拟海浪的能力,结果表明在季风和季风转换期间,WW3模式和SWAN模式对有效波高的模拟能力几乎一致。在季风期间,WW3模式对平均波周期的模拟能力优于SWAN模式;而在季风转换时期,SWAN模式模拟平均波周期的能力较好。此外,还利用WW3模拟结果分析了南海北部海域海浪的空间分布特征,分析结果表明有效波高受季风影响呈显著的季节变化,平均波周期呈现相对显著的半年变化。

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。

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.

Effect of Changes in Sea-Surface State on Statistical Characteristics of Sea Clutter with X-Band Radar

We have made observations of X-band radar sea clutter from the sea surface and sea-surface state in the Uraga Suido Traffic Route, which is used by ships entering and leaving Tokyo Bay, and the nearby Daini Kaiho Sea Fortress. We estimated the distributions of reflected amplitudes due to sea clutter using models that assume Weibull, Log-Weibull, Log-normal, and K-distributions. We then compared the results of estimating these distributions with sea-surface state data to investigate the effects of changes in the sea-surface state on the statistical characteristics of sea clutter. As a result, we showed that observed sub-ranges not containing a target conformed better to the Weibull distribution regardless of Significant Wave Height (SWH). Further, sub-ranges conforming to the Log-Weibull or Log-normal distribution in areas contained a target when the SWH was large, and as SWH decreases, sub-ranges conforming to a Log-normal. We also showed that for observed sub-ranges not containing a target, the shape parameter, c, of both Weibull and Log-Weibull distribution correlated with SWH. The correlation between wave period and shape parameters of Weibull and Log-Weibull distribution showed a weak correlation.

The Characteristics of Storm Wave Behavior and Its Effect on Cage Culture Using the ADCIRC+SWAN Model in Houshui Bay, China

The current storm wave hazard assessment tends to rely on a statistical method using wave models and fewer historical data which do not consider the effects of tidal and storm surge.In this paper,the wave-current coupled model ADCIRC+SWAN was used to hindcast storm events in the last 30 years.We simulated storm wave on the basis of a large set of historical storms in the North-West Pacific Basin between 1985 and 2015 in Houshui Bay using the wave-current coupled model ADCIRC+SWAN to obtain the storm wave level maps.The results were used for the statistical analysis of the maximum significant wave heights in Houshui Bay and the behavior of wave associated with storm track.Comparisons made between observations and simulated results during typhoon Rammasun(2014)indicate agreement.In addition,results demonstrate that significant wave height in Houshui Bay is dominated by the storm wind velocity and the storm track.Two groups of synthetic storm tracks were designed to further investigate the worst case of typhoon scenarios.The storm wave analysis method developed for the Houshui Bay is significant in assisting government's decision-making in rational planning of deep sea net-cage culture.The method can be applied to other bays in the Hainan Island as well.

Simulation of Typhoon-Driven Waves in the Yangtze Estuary with Multiple-Nested Wave Models

Typhoon-generated waves are simulated with two numerical wave models, the SWAN model for the coastal and Yangtze Estuary domain, nested within the WAVEWATCHIII （WW3） for the basin-scale East China Sea domain. Typhoon No. 8114 is chosen because it was very strong, and generated high waves in the Estuary. WW3 was implemented for the East China Sea coarse-resolution computational domain, to simulate the waves over a large spatial scale and provide boundary conditions for SWAN model simulations, implemented on a fine-resolution nested domain for the Yangtze Estuary area. The Takahashi wind model is applied to the simulation of the East China Sea scale （3-hourly） and Yangtze Estuary scale （1-hourly） winds. Simulations of significant wave heights in the East China Sea show that the highest waves are on the right side of the storm track, and maxima tend to occur at the eastern deep-water open boundary of the Yangtze Estuary. In the Yangtze Estuary, incoming swell is dominant over locally generated waves before the typhoon approaches the Estuary. As the typhoon approaches the Estuary, wind waves and swell coexist, and the wave direction is mainly influenced by the swell direction and the complex topography.

预测有效波高的深度学习模型研究

研究基于RNN、LSTM、GRU深度学习模型,针对NOAA浮标数据集中的44013、44014、44017浮标的数据,通过斯皮尔曼相关性分析提高模型预测效果。实验结果表明,在进行相关性分析后,S-RNN、S-LSTM、S-GRU的预测效果均比原始RNN、LSTM、GRU模型预测效果好。此外,提出一种基于LSTM的LSTM-Attention波高预测模型,并进行相关实验,量化LSTM-Attention模型的预测效果,实验结果表明LSTM-Attention模型有更好的预测效果。为评估模型的泛化能力,研究还提出了一种采用邻近浮标数据进行学习,预测浮标缺失数据的方法。实验结果表明,该方法的预测精度可以达到97.93%。本研究为海浪预测提供了新的方法和思路,也为未来深度学习模型在海浪预测中的应用提供了参考。

基于深度神经网络的CALIOP透明云下海面风速反演

构建了一种适用于CALIOP透明云下数据的深度神经网络模型,用于反演海面风速。通过使用2017年1、4、7、10月的CALIOP夜间数据和准同步的AMSR-2风速数据对模型进行训练,然后将该模型应用于2018年1—9月的夜间云下数据,实现海面风速的反演。与无云数据对比,所得反演结果表明精度接近,标准偏差最大为0.89 m/s,最低相关系数为0.94。在引入ERA5有效波高数据后,反演精度进一步提升,标准偏差最大为0.68 m/s,相关系数达到0.96以上。研究结果表明,透明云下数据同样可用于风速反演,深度神经网络能够有效地从CALIOP数据中提取风速信息,并结合有效波高数据进一步提高反演精度。

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。

2023年冬季海洋天气评述

2023年冬季(2023年12月—2024年2月)大气环流特征为:北半球极涡呈偶极型分布,中高纬度西风带呈3波型分布,西风带槽脊较常年同期偏强。西北太平洋和南海共生成1个热带气旋,比常年平均(1.53个)偏少0.53个。全球其他海域共生成12个热带气旋,比常年平均(15.33个)偏少3.33个。我国近海有8次8级以上大风过程,其中5次由冷空气产生,1次由温带气旋产生,2次由冷空气和入海温带气旋共同产生。我国近海出现7次明显的海雾过程,出现13次2.0 m以上的大浪过程。近海海面温度逐渐下降,并且北部海域的降温幅度大于南部海域。

基于机器学习的海面风速和有效波高联合反演

海面风速和有效波高(significant wave height,SWH)是海洋环境中的关键参数,两者之间关系密切。全球导航卫星系统反射测量(global navigation satellite system reflectometry,GNSS-R)可有效反演海面风速和SWH,然而已有研究局限于单一参数的反演。为此,提出一种基于机器学习算法的海面风速和SWH联合反演方法。首先通过质量控制获取有效的气旋全球导航卫星系统(cyclone global navigation satellite system,CYGNSS)观测数据,进而分别采用随机森林、极端梯度提升、轻量梯度提升机、决策树和自适应增强算法建立联合反演模型,并对比分析其反演性能。经实验表明:极端梯度提升更适用于海面风速和SWH的联合反演,均方根误差分别为0.91 m/s和0.20 m,皮尔逊相关系数分别达到0.90和0.96。相对于传统的单一参数反演,本文方法能够实现对海面风速和SWH高效又准确的反演。

2022汤加海底火山活动的测高海面观测异常分析

2022年1月14日—2022年1月15日,汤加海底火山发生剧烈喷发并造成全球性海啸,引起了国际广泛关注。针对汤加火山喷发引起的海洋环境异常综合观测,本文提出了利用Jason-3测高卫星数据研究火山喷发对海洋环境的短期和长期影响。针对短期影响,利用距离火山最近的弧段186的重复轨道,对比不同时间观测值,分析火山喷发时期海平面变化、有效波高和电离层总电子含量(TEC)异常。结果表明:卫星测高可观测到火山喷发引起的海面异常。火山喷发期间:海平面产生短期变化,原因可能与火山活动引起的波浪、海洋环境变化和海底地形变化有关;火山喷发引起部分海域有效波高显著增加,弧段186区域电离层TEC明显降低。针对长期影响,构建了研究区域内2016年2月—2023年2月共7年区域平均海面观测时间序列,并采用小波变换、奇异谱分析方法探测时间序列中的异常扰动,分析其与火山活动的关系,从而推断火山喷发活动对海洋环境的长期影响。结果表明:火山喷发可能会对海平面变化产生长期影响,海平面变化分布与俯冲带位置相关,其影响还与EI Nino和La Nina事件产生的影响耦合,需要更多资料进一步分析;另外,汤加火山喷发对研究海域内的平均有效波高和电离层TEC分布长期影响较小。

2023年秋季海洋天气评述

2023年秋季(9—11月)北半球极涡为单极型分布,中高纬度地区呈5波型,欧亚大陆西风环流较为平直,西风带槽脊较弱。我国近海共出现16次8级以上大风过程,其中热带气旋大风过程3次,热带气旋与冷空气共同影响的大风过程3次,冷空气和温带气旋共同影响的大风过程3次,冷空气大风过程7次。西北太平洋和南海共生成4个热带气旋,热带气旋活动较常年偏少,全球其他海域生成热带气旋22个。近海出现2.0 m以上大浪过程17次,大浪日数占秋季总日数约71%。近海海面温度较常年平均偏高。