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.

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.

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.

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 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.

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。

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.

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.

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。

NCEP/NOAA全球预报产品在江苏近岸及长江口外的精度评估

利用2021年1—7月江苏近岸和长江口外13个测风站、3个波浪浮标的观测数据,与美国国家环境预报中心/美国国家海洋和大气管理局(NCEP/NOAA)全球预报系统的风场、波浪预报数据进行对比。结果表明:与上一代预报产品相比,目前全球业务预报产品在风场预报方面的准确度明显提高,江苏近岸地区的风速预报误差明显小于长江口外地区,24 h风速和风向预报的均方根误差分别为2 m/s和45°。对大风天、大浪天环境下全球预报产品精度的评估表明:大风天风速预报精度在长江口外降低,在江苏近岸无明显变化,风向预报精度在长江口外无明显变化,在江苏近岸提高;大浪天波高、浪向的预报精度分别降低、提高。在台风极端天气条件下,全球预报产品对长江口的风场仍有一定的预报能力,但预报的最大风速的出现时间滞后6~9 h,且无法预报出风速剧烈变化的情况。尝试基于长短期记忆网络方法利用NCEP/NOAA预报及观测改进业务预报,可以改善短期单站预报水平。

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。

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。

浙江沿海基于浮标的有效波高分析和数值预报订正

基于2010年10月―2022年12月浙江沿海5个浮标站观测资料和2020—2022年欧洲中期天气预报中心细网格模式海浪和海面10 m风预报资料,对浮标站的风、浪相关性进行分析,对有效波高预报进行评估和订正方法研究。0~240 h预报偏差和均方根误差表明:模式对远岸浮标的预报比实况稍偏大,对近岸浮标预报则略偏小,预报不稳定性随预报时效的延长而增大。远离海岸的浮标站24 h预报与实况的相关性高于近岸站,两者的相关系数分别约为0.94和0.85。有效波高预报存在一定系统偏差,且是预报误差的主要来源。近岸浮标有效波高预报值小于观测值,远岸浮标的预报值偏差则随着有效波高的增大由正转负,负偏差的绝对值逐渐增大。对于远岸浮标,仅针对有效波高进行预报和实况的一元一次回归就有很好的订正效果,但近岸浮标受地形影响大,海浪预报的误差更大,同时引入有效波高和10 m风速作为预报因子,进行二元一次回归的订正效果更好。订正方程应用到同类型的周边海区浮标站仍然有很好的订正效果,可推广到浙江沿海同类型海区。

Relationship between wind-stress coefficient and wave height entropy

1 Wind-stress relation THE wind-stress coefficient of sea surface, C_D, is defined

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.

太湖北部风浪波高计算模式观测分析

通过用无量纲分析和线性回归方法对2002-2003年太湖4测点1000多组波浪资料的分析,给出了太湖不同时段风浪平均波高(H)与风区长度(F)、水深(d)、风速(v)6个关系模式.在此基础上,开展了模式的误差分析及与前人模式对比.结果表明,太湖北部不同区域风浪平均波高的计算应选用不同计算模式,但是可用如下形式表示:其中,a1-a8为和地形及水生植物覆盖度等相关的参数.误差分析结果显示:离岸距离大于1km区域的参数a1-a8的取值分别为0.217456、1、0.15、0.6、0.09、0.6、1.0、0.0052,模式估算平均波高的误差小于24％;近岸区参数a7大于1,a8取0,a4取值介于0.6-0.72,a5介于0.00131-0.00168,模式估算平均波高的误差较大,表明近岸区波浪还需进行进一步的观测研究.

广东阳西近岸海域波浪的分布特征

通过对广东阳西近岸测站1a实测波浪资料及岸边同期风资料的整理与分析,探讨了该海域的波浪特性,得出研究海域不分方向H1/10年平均值为1.00 m,常浪向为SE向,出现的频率为38.35%,强浪向为SE向,观测期间的最大波高出现在0814号"黑格比"台风期间,Hmax值为8.31 m.用已有的理论分布函数对实测统计数据进行拟合,筛选出研究海域的波高分布、周期分布及波高与周期联合分布的特征,结果表明双参数威布尔理论波高分布、杨正己威布尔周期分布、朗格-赫金斯83模式或者孙孚模式较为适用于本海区的波高分布、周期分布、波高周期联合分布;结合相应的风速风向资料,运用回归分析方法,建立了该地区的波高与风速之间、波高与波周期之间的关系.

OSMAR2000探测海面风浪场原理与实现

从 Barrick反演无向浪高谱的公式出发 ,在高频地波雷达 OSMAR2 0 0 0工作频率条件下 ,对反演均方浪高、浪周期的公式进行了修正 ,并将其应用于高频地波雷达 OSMAR2 0 0 0的风浪场的反演 ,将反演结果与同时进行现场工作的传统海洋探测设备输出结果比较 。

亚帆赛间便携式高频地波雷达的海态观测

2010年汕尾亚运会帆船赛期间,便携式高频地波雷达OSMAR-S作为一种重要的海态监测手段在汕尾海域进行观测,为保障亚帆赛顺利举行提供海洋气象服务。雷达获取了汕尾海域近1个月连续的流速、流向、浪高、浪周期、风向和风速等数据,并与海监船搭载的海流计与测风仪以及现场布放浮标实测的数据进行了对比。对比结果表明:雷达与现场海洋仪器的观测数据较为吻合,初步验证了OSMAR-S探测近海海态特别是风浪参数的能力。