Numerical simulation and preliminary analysis on ocean waves during Typhoon Nesat in South China Sea and adjacent areas

Using the wave model WAVEWATCH III(WW3), we simulated the generation and propagation of typhoon waves in the South China Sea and adjacent areas during the passage of typhoon Nesat(2011). In the domain 100°–145°E and 0°–35°N, the model was forced by the cross-calibrated multi-platform(CCMP) wind fi elds of September 15 to October 5, 2011. We then validated the simulation results against wave radar data observed from an oil platform and altimeter data from the Jason-2 satellite. The simulated waves were characterized by fi ve points along track using the Spectrum Integration Method(SIM) and the Spectrum Partitioning Method(SPM), by which wind sea and swell components of the 1D and 2D wave spectra are separated. There was reasonable agreement between the model results and observations, although the WW3 wave model may underestimate swell wave height. Signifi cant wave heights are large along the typhoon track and are noticeably greater on the right of the track than on the left. Swells from the east are largely unable to enter the South China Sea because of the obstruction due to the Philippine Islands. During the initial stage and later period of the typhoon, swells at the fi ve points were generated by the propagation of waves that were created by typhoons Haitang and Nalgae. Of the two methods, the 2D SPM method is more accurate than the 1D SIM which overestimates the separation frequency under low winds, but the SIM method is more convenient because it does not require wind speed and wave direction. When the typhoon left the area, the wind sea fractions decreased rapidly. Under similar wind conditions, the points located in the South China Sea are affected less than those points situated in the open sea because of the infl uence of the complex internal topography of the South China Sea. The results reveal the characteristic wind sea and swell features of the South China Sea and adjacent areas in response to typhoon Nesat, and provide a reference for swell forecasting and offshore structural designs.     

Underwater topography detection of Taiwan Shoal with SAR images

Under suitable conditions of tidal current and wind, underwater topography can be detected by synthetic aperture radar (SAR) indirectly. Underwater topography SAR imaging includes three physical processes: radar ocean surface backscattering, the modulation of sea surface short wave spectrum by the variations in sea surface currents, and the modulation of sea surface currents by the underwater topography. The first process is described usually by Bragg scattering theory because the incident angle of SAR is always between 20°-70°. The second process is described by the action balance equation. The third process is described by an ocean hydrodynamic model. Based on the SAR imaging mechanism for underwater topography, an underwater topography SAR detection model and a simplified method for its calculation are introduced. In the detection model, a two-dimensional hydrodynamic model – the shallow water model is used to describe the motion of tidal current. Due to the difficulty of determining the expression of SAR backscattering cross section in which some terms can not be determined, the backscattering cross section of SAR image used in the underwater topography SAR detection is pro-processed by the simulated SAR image of the coarse-grid water depth to simplify the calculation. Taiwan Shoal, located at the southwest outlet of Taiwan Strait, is selected as an evaluation area for this technique due to the occurrence of hundreds of sand waves. The underwater topography of Taiwan Shoal was detected by two scenes of ERS-2 SAR images which were acquired on 9 January 2000 and 6 June 2004. The detection results are compared with in situ measured water depths for three profiles. The average absolute and relative errors of the best detection result are 2.23 m and 7.5 %, respectively. These show that the detection model and the simplified method introduced in the paper is feasible.     

基于再分析数据的南海三维温盐结构特征分析

掌握南海三维温盐场特征对于研究南海海洋动力环境及其对海洋气候变化的影响具有重要意义。基于海洋再分析数据GLORYS12V1和AVHRR OISST数据,开展了南海温盐空间分布及季节变化分析,以及海表温度对台风过程的响应特征分析。分析结果表明：南海海表温度一般为25～32℃,最高温度出现在8月的黄岩岛附近海域,海表盐度一般为32～35 psu,最高盐度出现在7月的东海附近海域;温盐垂向结构表现为表层高温低盐,随着深度增加温盐季节性变化越小。南海地区温跃层深度存在明显季节变化特征,秋冬季节温跃层深度大于春夏两季。根据“威马逊”台风期间海表温度变化特征分析海表温度对台风过程的响应,台风期间南海水体垂向混合作用增强,海表温度降温明显。     

基于现场和卫星有效波高数据评估WAVEWATCH III的输入/耗散项

基于WAVEWATCH III,在输入相同的风场条件下,评估了三个输入耗散项WAM3,WAM4以及TC96在是否考虑大气稳定性时的模拟能力。通过5组实验,用南海的测波雷达数据以及研究区域内HY-2高度计的有效波高数据对不同源项的模拟结果进行了比较分析,研究区域为100-135°E,0-35°N。对TC96中的风速校正参数进行了敏感性分析。结果表明,这几种源项在涌浪占主导时的模拟效果都不太理想;考虑大气不稳定性的TC96源项模拟的效果最好;大气不稳定性的影响是以一种所谓的“高效风速”的策略来反映的,其中最重要的一个参数为风速转换参数,这个参数非常敏感,在对特定区域进行模拟之前,应先分析出这个参数的最优值。     

联合多代卫星测高资料反演中国南海重力异常

联合HY-2A、Geosat、ERS1/2、Envisat、T/P、Jason1/2等多颗测高卫星,通过共线处理和交叉点平差削弱海面时变效应和径向轨道误差等影响,以Jason-1测高卫星作为参考,对多代测高卫星进行基准统一,消除测高数据的不一致性,基于全球EGM2008重力场模型,采用移去恢复技术和逆Vening-Meinesz公式反演中国南海(0°~23°N,103°~120°E)2'×2'重力异常,与船测重力数据比较,均方根误差为4.9m Gal。     

基于遥感的海洋三维温盐场智能探测研究进展

海洋三维温盐场信息是描述海洋物理属性特征和掌握海洋物理运动过程的重要参数,获取准确的海洋三维温度和盐度信息对于认识海洋、开发利用海洋和海洋科学研究等具有重要意义。随着人工智能与深度学习方法的发展,采用深度学习方法的海洋次表层三维温盐场智能探测研究成为热点之一。从海洋温盐观测数据集、传统机器学习方法三维温盐智能探测、一般神经网络三维温盐智能探测和深度学习三维温盐智能探测等方面展开,对与海洋三维温盐场智能探测相关的研究进展进行综述,最后针对三维温盐场智能探测存在的问题和未来的发展趋势进行了总结和展望。     

基于ROMS模式的南海SST与SSH四维变分同化研究

卫星遥感观测获得了大量高分辨率的海面实时信息,包括海面温度（SST）和海面高度（SSH）等,同化进入数值模式可有效提升模拟精度。本文基于ROMS模式与四维变分同化方法（4DVAR）,使用AVHRR SST和AVISO SSH数据,开展了南海区域同化实验。为检验同化的效果,分别利用HYCOM再分析资料和Argo温盐实测数据分析了同化结果的海面高度、流场及温盐剖面的精度。对比结果表明,SST和SSH的同化能够改善ROMS的模拟结果:同化后海面高度场能够更为准确地捕捉海洋的中尺度特征,与HYCOM海面高度再分析资料相比,平均绝对偏差和均方根误差分别为0.054 m和0.066 m;与HYCOM 10 m层流场相比,东向与北向流速平均绝对偏差分别为0.12 m/s和0.11 m/s,相比未同化均提升约0.01 m/s;温盐同化结果与Argo温盐实测具有较高的一致性,温度和盐度平均绝对偏差为0.45℃、0.077,均方根误差为0.91℃、0.11,单个的温盐廓线对比说明,同化结果与HYCOM再分析资料精度相当。     

基于卫星测高与卫星测温的表层流产品生成方法应用评估

提高海洋表层流的精度与分辨率对于相关应用领域至关重要.研究引入海表面温度(sea surface temperature,SST)信息对高度计导出流场的改进效果,计算了 2018年每日无间隔的全球海洋表层流速度.通过增加热量守恒方程约束,引入卫星测温产品,在地转流基础上生成表层流产品,并与现场漂流浮标速度比较,评估了使...     

基于ASCAT 散射计数据的2013 年南极周边海面风速特征分析

利用2013年1月1日~2013年12月31日的ASCAT散射计风速数据,从海面风速季平均分布特征、平均海面风速特征、海面风速大于10 m/s发生比例统计等方面,对55°S以南的南极周边海域开展了风速空间分布特性统计,得到以下结果:7月平均风速最大,为12 m/s,1月平均风速最小,为8 m/s。对于南极周边海域,区域平均风速主要在9~12 m/s,全年出现的时间大于280 d,约占全年的77%。风速大于10 m/s所占比例4~9月大于1~3月和10~12月。从全年来看,南极周边海域在4~9月风速普遍较大,且0°~60°W海域内风速明显比其他海域要小。在此基础上将2013年每日的区域平均风速与月平均风速与2012年做了对比,变化趋势与2012年基本一致。通过本项长期工作,可以了解南极风场环境基本情况,建立与更新基础资料和图件,得到南极地区风场要素时空分布、变化规律,服务于南极科学考察、全球变化等多学科研究应用。