杭州湾地波雷达观测的海流数据取样率分析

根据杭州湾口区两台地波雷达5个半月观测的资料,对其中的3 189个有效观测时次的海流数据取样率(CSR)在空间和时间上的变化规律进行了分析,结果表明,在两台雷达波交叉观测的中心区域各测点的地波雷达观测的海流数据取样率高于外围区域,在中心区域海流数据取样率可达98%以上,向外围区域海流数据取样率逐渐平缓递减,到边缘区域海流数据取样率仅在20%以下;地波雷达观测的海流数据取样率有明显的日变化,白天海流数据取样率明显低于夜间;17时海流数据平均取样率达到最低值(约49%),然后很快上升,至02时达最高值(约74%),然后再缓慢下降至17时为止。同时在10时和20时地波雷达观测的海流数据取样率呈现两个相对低值点,可能与人们在这两个时段通讯繁忙所造成的干扰有一定的关系。海流流速对地波雷达观测的海流数据取样率也有较大影响,呈负相关,流速大时海流数据取样率比流速小时的要低,在海流数据取样率大于98%的中心区域,流速和海流数据取样率的相关系数小于-0.8,在海流数据取样率大于60%的区域,流速和海流数据取样率的相关系数小于-0.6,体现明显的相互关联。地波雷达观测的海流数据取样率和潮汐有着每日4次的良好相干,而似乎和风没有显著的关系。希望这些分析对地波雷达以后的推广使用能积累一些经验和参考意见。     

岸基高频地波雷达资料后处理技术研究

综述了国内外高频地波雷达发展和研究现状,系统介绍了岸基高频地波雷达资料接收、预处理、计算机自动质量控 制、可视化人机交互审核和标准化输出等后处理工作内容与流程,详细阐述并以示例验证了岸基高频地波雷达资料非法码检 验、常规范围检验、相关性检验、气候学检验、统计学检验等质量控制方法和通过实测矢量场图、网格化矢量场图进行资料 深入审核的原理与方法,最后较为具体的提出了岸基高频地波雷达资料后处理系统的逻辑、物理和功能架构设计及技术指标 和运行环境。研究成果紧密贴合我国海洋观测网建设运行实际需求,对于我国岸基高频地波雷达资料后处理技术水平和能力 提升,具有科学和重要的技术参考价值。     

地波雷达海流观测数据验证的软件实现及初步分析

利用Matlab语言及其图形交互界面编程技术,将OSMAR高频地波雷达观测数据与现场测流数据的比对验证方法集成在软件中。利用该软件输入OSMAR地波雷达、海流计、ADP和美国CODAR雷达的试验海流数据得到了误差统计特征值,初步分析了不同比测站点和不同比测仪器对雷达数据验证工作的影响。     

象山港牛鼻山水道潮流场的高频地波雷达观测与分析

作为LORCE计划中构建高频地波雷达观测网的试点,面向象山港牛鼻山水道,在六横岛郭巨山和白马礁各设置了1台OSMAR S50高频地波雷达。在2台雷达合成表面流场有效区域的中间地带,利用Valeport旋桨式海流仪和ADCP定点开展了周日连续观测,以验证高频地波雷达合成表面流场的精度。对比定点流场和高频地波雷达对应数据发现,两者变化相关性较好,高频地波雷达在该点获得的流场有较高精度。借助SCHISM建立的区域模型结果,检验了高频地波雷达数据大面上的可用性。比较发现,观测和模拟值在大的趋势上是一致的：牛鼻山水道为规则半日潮流海域,M2是主要分潮,分潮M2和K1以往复流为主;涨潮时外海海水先通过牛鼻山水道流向象山港内,一段时间后再流向佛渡水道;落潮时象山港内海水率先经牛鼻山水道流出至外海,随后佛渡水道海水再逐渐流入牛鼻山水道。     

南海及邻近海域大气-海浪-海洋耦合精细化数值预报系统研制

本文主要介绍了南海及邻近海域大气-海浪-海洋耦合精细化数值预报系统的研制概况。预报区域为99°E~135°E，15°S~45°N，包括渤海、黄海、东海和南海及其周边海域。为了给耦合预报模式提供较准确的预报初始场，在预报开始之前，分别进行了海浪模式和海洋模式的前24小时同化后报模拟。海浪模式和海洋模式都采用了集合调整Kalman滤波同化方法，海浪模式同化了Jason-2有效波高数据；海洋模式同化了SST数据、MADT数据和ARGO剖面数据。为了改进海洋温度和盐度的模拟，我们在海洋模式的垂向混合方案中引入波致混合和内波致混合的作用。预报系统的运行主要包括两个阶段，首先海浪模式和海洋模式进行了2014年1月至2015年10月底的同化后报模拟，强迫场源自欧洲气象中心的六小时的再分析数据产品。然后耦合预报系统将同化后报模拟的结果作为初始场进行了14个月的耦合预报。预报产品包括大气产品（气温、风速风向、气压等）、海浪产品（有效波高和波向等）、海流产品（温度、盐度和海流等）。一系列观测资料的检验比较表明该大气-海浪-海洋耦合精细化数值预报系统的预报结果较为可靠，可以为南海及周边海洋资源开发和安全保障提供数据和信息产品服务。     

山东半岛北部海洋动力环境的高频地波雷达观测

利用两台高频地波雷达(ground wave radar,WERA)站对山东半岛北部雷达覆盖海区的浪、流场进行了观测,并且利用海洋-大气-波浪耦合沉积输运模型(coupled-ocean-atmosphere-wave-sediment transport modeling system,COAWST)对该区域的一个强风暴过程进行了数值模拟,对雷达观测数据、现场声学多普勒流速剖面仪(acoustic Doppler current profilers,ADCP)调查数据和数值模拟结果进行比对分析发现,模型模拟的水位变化与ADCP测量结果一致,WERA所观测到的有效波高和ADCP结果比较吻合,模型模拟的ADCP站位的流速相位、大小与雷达观测结果比较接近,与ADCP的结果有一定偏差。雷达观测的海区流场结果与模型反映趋势基本一致,但是在近岸方向上变化较大,其原因可能与ADCP的投放位置、模型的分辨率设置等因素有关。高频地波雷达系统是海岸带动力环境观测的一个有效工具,在实际应用中有着广泛的前景。     

便携式高频地波雷达海流探测长周期工作性能试验

2013年1月29日至3月15日在台湾海峡西南部海域进行了OSMAR-S100便携式高频地波雷达与浮标观测海流数据的长周期对比试验,验证了雷达系统在探测海流方面的准确性、可靠性和稳定性.通过实测海流与雷达矢量流的复相关分析,选定3 m层的海流为对比代表层.试验期间实测流速为0.0~120.0 cm/s,雷达海流有效探测区内的矢量流流速、流向的观测误差较小,能够满足实时监测海洋表层流的需要,高精度区流速、流向的均方根误差分别为9.1 cm/s和24.8°,边缘区的均方根误差为13.3~24.8 cm/s和39.4°~39.6°,与国内外达到业务化运行要求的同类产品实际观测精度相当.     

阵列式高频地波雷达矢量流长周期适用性比测试验数据分析

基于高频地波雷达长周期适用性比测试验数据,主要从以下3个方面系统分析国产阵列式高频地波雷达矢量流控测效果:(1)时间有效采样率和覆盖率的空间分布;(2)与反演的流速匹配的现场观测深度;(3)不同区域的探测精度.长周期的海流验证表明,雷达海流可以有效地反映有效探测区内表层海流及其时空变化,高精度区流速流向的均方根误差(RMS)分别为7.5～19.3cm/s和15.5°～33.7°,尤其是高精度区核心区域的RMS仅为7.5～10.1 cm/s和15.5°～28.5°.边缘区流速流向的RMS为16.1～25.8 cm/s和39.5°～40.7°,与国内外达到业务化运行要求的同类产品实际观测精度相当.     

四维变分同化技术在风暴潮数值模拟中的应用

利用区域海洋模式ROMS(Regional Ocean Modelling System)及其四维变分同化模块,建立了具有资料同化能力的东中国海风暴潮数值模式,通过将海洋站水位观测资料同化到风暴潮模式中,提高了模式对风暴潮的模拟精度。四维变分同化技术能够在整个同化时间窗口保持动力协调,使模拟结果在该时间窗口内最大程度的靠近观测,同时,得到了最优预报初始场。利用该模式,对两次温带风暴潮过程进行了数值模拟,结果表明:在同化窗口内,同化对模拟精度有明显的提高;结束同化之后,得到的最优预报初始场对临近预报精度也有一定提高。     

OSMAR071G地波雷达对“莫兰蒂”台风风眼的观测

利用福建省海洋预报台业务化运行的OSMAR071G高频地波雷达海洋表面观测系统,对2016年9月14日-15日"莫兰蒂"台风穿越台湾海峡并登陆厦门岛的全过程进行了实时观测。根据地波雷达观测的风场数据,计算了海洋表面风场涡流特征,通过涡场结构确定了涡旋的中心,以此确定为台风海面风眼实时位置,通过连续观测,从而得到了台风海面风眼的轨迹。该风眼轨迹与国家卫星气象中心的发布的台风路径基本一致。本次观测表明了OSMAR071G高频地波雷达系统能够准确实时地对台风进行遥感探测。     

Assimilation of surface currents into a regionalmodel over Qingdao coastal waters of China

Surface currents measured by high frequency （HF） radar arrays are assimilated into a regional ocean model over Qingdao coastal waters based on Kalman filter method. A series of numerical experiments are per- formed to evaluate the performance of the data assimilation schemes. In order to optimize the analysis pro- cedure in the traditional ensemble Kalman filter （ENKF）, a different analysis scheme called quasiensemble Kaman filter （QENKF） is proposed. The comparisons between the ENKF and the QENKF suggest that both them can improve the simulated error and the spatial structure. The estimations of the background error covariance （BEC） are also assessed by comparing three different methods： Monte Carlo method; Canadian quick covariance （CQC） method and data uncertainty engine （DUE） method. A significant reduction of the root-mean-square （RMS） errors between model results and the observations shows that the CQC method is able to better reproduce the error statistics for this coastal ocean model and the corresponding external forcing. In addition, the sensibility of the data assimilation system to the ensemble size is also analyzed by means of different scales of the ensemble size used in the experiments. It is found that given the balance of the computational cost and the forecasting accuracy, the ensemble size of 50 will be an appropriate choice in the Qingdao coastal waters.     

集合资料同化方法的理论框架及其在海洋资料同化的研究展望

在海洋动力系统的数值模拟中,海洋资料同化是一种能够有效融合多源海洋观测资料和数值模式的方法。它不仅可以显著地提高数值模拟的效果,构造海洋再分析资料场,还能有效减少海洋和气候预报时模式初始条件的不确定性。因此,海洋资料同化对于海洋研究和业务化应用具有非常重要的意义。资料同化方法的研究一直是大气、海洋科学的热门课题之一。其中,集合卡尔曼滤波器(EnKF)是一种有效的资料同化方法,自提出以来经过了20多年的发展和改进,已经在海洋资料同化中得到了广泛的研究和应用。近年来,随着动力模式的不断发展和计算能力的提高,粒子滤波器由于不受模型线性和误差高斯分布假设的约束,也逐渐成为了当前资料同化方法研究的热点。本文分析和总结了目前关于集合卡尔曼滤波器和粒子滤波器的一些最新理论研究结果,在贝叶斯滤波理论的框架下讨论了这两类算法的关联和区别,以及各自在资料同化实践中的优势和不足。在此基础上,我们探讨了粒子滤波器应用于海洋模式资料同化的主要困难和目前可行的一些解决方法,展望了集合资料同化方法研究的新趋势,为集合资料同化方法的进一步发展和应用提供理论基础。     

基于集合同化方法的南海北部最优观测实验

根据集合同化理论及最优观测方法,应用基于ROMS模式的南海北部区域模拟结果作为集合样本,对该区域的最优观测廓线以及最优观测航次进行了评估和选择.最优观测方法是一种不需要直接同化观测,而通过最小化分析场误差方差理论值来选择最优观测点的方法.最优观测方法根据卡曼滤波理论中协方差矩阵的更新方程,使用一组模式或观测得到的历史样...     

中国近海现场海洋观测系统设计评估

中国科学院正在发展一个在中国近海(包括黄海、东海和南海)现场海洋观测系统。观测系统包括3个沿岸观测站点、4个近海离岸浮标和由观测船只按固定航线做的船舶观测断面。观测站点、浮标和断面的位置已经预先确定,这个计划在2008-2011实施。利用基于卡尔曼理论的样本集合方法对这样一个能够监测大尺度的季节和年季变率的观测系统设计进行了评估。根据卡尔曼滤波理论,用集合样本的方法能够给出经过同化这个观测系统位置的观测资料后能够减少多少分析误差和分析场的不确定性。用2个来自不同模式、不同分辨率的模式的结果作为集合样本来计算静态的背景误差协方差,这2套样本分别是来自分辨率是0.5°×0.5°的模式同化结果和高分辨0.125°×0.125°的模式结果。由这2个不同资料得到的结果是一致的。发现来自3个近岸和4个离岸浮标得到的观测能够有效地减少SST在渤海、黄海、东海和南海中部的分析误差。然而在越南东部和台湾东部海域,分析误差减少的百分比相对要小。最后,给出了中国近海最优的观测位置序列设计。     

Numerical study of current fields near the Changjiang Estuary and impact of Quick-EnKF assimilation

A 30-d current numerical simulation is running for the Yangshan Port, the Changjiang Estuary, the Hangzhou Bay and their adjacent seas using a finite volume coastal ocean model (FVCOM), with Changjiang River runoff and wind effect being considered. At the open boundary, this model is driven by the water level obtained from prediction including eight main partial tides. After the harmonic analysis, the cotidal chart and the iso-amplitude line as well as the current ellipse distribution map are displayed to illustrate the propagation property of a tidal wave. Horizontal velocity of both the U and V components coincides with the actual measurement, which shows that the model result is credible to describe the hydrodynamic pattern in this sea area. On this basis, real-time current data from high-frequency radar is assimilated with the implementation of quick ensemble Kalman filter, which takes the variation tendency of the state vector to compute the analysis field, instead of integrating the field for N (the number of ensemble) times as it used to in the standard EnKF, aiming at raising the efficiency of computation, reducing the error of prediction and at the same time, improving the forecast effect.     

X-波段船用雷达观测海洋动力环境要素仿真研究

为了评估X-波段船载雷达观测海浪和海流参数的能力.基于随机海浪理论和雷达几何成像原理模拟了不同调制影响的X-波段船用雷达图像序列,介绍了估算海浪参数和海流参数的算法,对影响雷达观测海流和海浪有关因素进行了分析.同时在雷达图像中加入了随机高斯白噪声,并通过数值方法验证了雷达图像的信噪比开方和有效波高之间的线性关系.数值模拟结果说明X-波段船用雷达能够有效地估算海浪和海流参数,且带有不同噪声水平的雷达系统应具有不同的定标系数.     

Comparison of EnOI and EnKF regional ocean reanalysis systems

This study compares two regional eddy resolving ocean reanalysis systems, based on the ensemble Kalman filter (EnKF) and ensemble optimal interpolation (EnOI), focusing on data assimilation aspects. Both systems are configured for the Tasman Sea using the same ocean model with 0.1° resolution and commonly available observations of satellite altimetry, sea surface temperature and subsurface temperature and salinity. The primary goals are to quantify the difference in performance of the EnKF and EnOI and investigate how important this difference might be from an oceanographic perspective. We find that both systems generally constrain mesoscale circulation in the region, with some exceptions for the East Australian Current separation region, the most energetic and chaotic part of the domain. Overall, the EnKF is found to consistently outperform the EnOI, producing on average 9–21% smaller innovations. The EnKF also has better forecast skill relative to the persisted analysis than the EnOI. For SST the EnKF forecast outperforms persisted analysis by about 17%, which indicates that the surface circulation is mainly constrained. The EnKF and EnOI are shown to produce qualitatively different increments of unobserved or sparsely observed variables; however, we find only moderate improvements of the EnKF over EnOI in subsurface temperature fields when compared against withheld XBT observations. We attribute this lack of a major improvement in subsurface reconstruction to the inability of the EnKF to linearly constrain the system due to initialisation shock, model error caused by open boundaries, and possibly insufficient observations.     

A singular evolutive extended Kalman filter to assimilate ocean color data in a coupled physical–biochemical model of the North Atlantic ocean

Within the European DIADEM project, a data assimilation system for coupled ocean circulation and marine ecosystem models has been implemented for the North Atlantic and the Nordic Seas. One objective of this project is to demonstrate the relevance of sophisticated methods to assimilate satellite data such as altimetry, surface temperature and ocean color, into realistic ocean models. In this paper, the singular evolutive extended Kalman (SEEK) filter, which is an advanced assimilation scheme where three-dimensional, multivariate error statistics are taken into account, is used to assimilate ocean color data into the biological component of the coupled system. The marine ecosystem model, derived from the FDM model [J. Mar. Res. 48 (1990) 591], includes 11 nitrogen and carbon compartments and describes the synthesis of organic matter in the euphotic zone, its consumption by animals of upper trophic levels, and the recycling of detritic material in the deep ocean. The circulation model coupled to the ecosystem is the Miami isopycnic coordinate ocean model (MICOM), which covers the Atlantic and the Arctic Oceans with an enhanced resolution in the North Atlantic basin. The model is forced with realistic ECMWF ocean/atmosphere fluxes, which permits to resolve the seasonal variability of the circulation and mixed layer properties. In the twin assimimation experiments reported here, the predictions of the coupled model are corrected every 10 days using pseudo-measurements of surface phytoplankton as a substitute to chlorophyll concentrations measured from space. The diagnostics of these experiments indicate that the assimilation is feasible with a reduced-order Kalman filter of small rank (of order 10) as long as a sufficiently good identification of the error structure is available. In addition, the control of non-observed quantities such as zooplankton and nitrate concentrations is made possible, owing to the multivariate nature of the analysis scheme. However, a too severe truncation of the error sub-space downgrades the propagation of surface information below the mixed layer. The reduction of the actual state vector to the surface layers is therefore investigated to improve the estimation process in the perspective of sea-viewing wide field-of-view sensor (SeaWiFS) data assimilation experiments.     

OSTIA数据在中国近海业务化环流模型中的同化应用

The prediction of sea surface temperature(SST) is an essential task for an operational ocean circulation model. A sea surface heat flux, an initial temperature field, and boundary conditions directly affect the accuracy of a SST simulation. Here two quick and convenient data assimilation methods are employed to improve the SST simulation in the domain of the Bohai Sea, the Yellow Sea and the East China Sea(BYECS). One is based on a surface net heat flux correction, named as Qcorrection(QC), which nudges the flux correction to the model equation; the other is ensemble optimal interpolation(En OI), which optimizes the model initial field. Based on such two methods, the SST data obtained from the operational SST and sea ice analysis(OSTIA) system are assimilated into an operational circulation model for the coastal seas of China. The results of the simulated SST based on four experiments, in 2011, have been analyzed. By comparing with the OSTIA SST, the domain averaged root mean square error(RMSE) of the four experiments is 1.74, 1.16, 1.30 and 0.91°C, respectively; the improvements of assimilation experiments Exps 2, 3 and 4 are about 33.3%, 25.3%, and 47.7%, respectively.Although both two methods are effective in assimilating the SST, the En OI shows more advantages than the QC,and the best result is achieved when the two methods are combined. Comparing with the observational data from coastal buoy stations, show that assimilating the high-resolution satellite SST products can effectively improve the SST prediction skill in coastal regions.     

The impact of open boundary forcing on forecasting the East Australian Current using ensemble data assimilation

We investigate the performance of an eddy resolving regional ocean forecasting system of the East Australian Current (EAC) for both ensemble optimal interpolation (EnOI) and ensemble Kalman filter (EnKF) with a focus on open boundary model nesting solutions. The performance of nesting into a global re-analysis; nesting into the system’s own analysis; and nesting into a free model is quantified in terms of forecast innovation error. Nesting in the global reanalysis is found to yield the best results. This is closely followed by the system that nests inside its own analysis, which seems to represent a viable practical option in the absence of a suitable analysis to nest within. Nesting into a global reanalysis without data assimilation and nesting into an unconstrained model were both found to be unable to constrain the mesoscale circulation at all times. We also find that for a specific interior area of the domain where the EAC separation takes place, there is a mixture of results for all the systems investigated here and that, whilst the application of EnKF generates the best results overall, there are still times when not even this method is able to constrain the circulation in this region with the available observations.