Numerical simulation and satellite observations of suspended matterin the North Sea

Two methods for the investigation of suspended particulate matter (SPM) transport in the North Sea are presented: numerical modeling and remote sensing by satellite. The principles and the main components of the two methods are outlined. The numerical model uses a particle tracer method for the simulation of advective transport. It takes into account the interaction with the sediment bed (deposition, erosion). Remote sensing uses data of the Coastal Zone Colour Scanner (CZCS). The physical background of remote sensing is outlined and an inverse modeling procedure for evaluation of the satellite images is described. Data obtained with the two methods are compared with each other and with ship measured data which shows the strong and the weak points of each method. The combined use of field measurements, satellite observations, numerical modeling and specific in situ process studies is recommended as the most effective way to investigate SPM transport     

Asynchronous data assimilation with the EnKF

This study revisits the problem of assimilation of asynchronous observations, or four-dimensional data assimilation, with the ensemble Kalman filter (EnKF). We show that for a system with perfect model and linear dynamics the ensemble Kalman smoother (EnKS) provides a simple and efficient solution for the problem: one just needs to use the ensemble observations (that is, the forecast observations for each ensemble member) from the time of observation during the update, for each assimilated observation. This recipe can be used for assimilating both past and future data; in the context of assimilating generic asynchronous observations we refer to it as the asynchronous EnKF. The asynchronous EnKF is essentially equivalent to the four-dimensional variational data assimilation (4D-Var). It requires only one forward integration of the system to obtain and store the data necessary for the analysis, and therefore is feasible for large-scale applications. Unlike 4D-Var, the asynchronous EnKF requires no tangent linear or adjoint model.     

Remotely sensed seasonality in the spatial distribution of sea-surface suspended particulate matter in the southern North Sea

An algorithm is presented for estimating near-surface SPM concentrations in the turbid Case 2 waters of the southern North Sea. The single band algorithm, named POWERS, was derived by parameterising Gordon's approximation of the radiative transfer model with measurements of Belgian and Dutch inherent optical properties. The algorithm was used to calculate near-surface SPM concentration from 491 SeaWiFS datasets for 2001. It was shown to be a robust algorithm for estimating SPM in the southern North Sea. Regression of annual geometric mean SPM concentration derived from remote sensing (SPM_rs), against in situ (SPM_is) data from 19 Dutch monitoring stations was highly significant with an r² of 0.87. Further comparison and statistical testing against independent datasets for 2000 confirmed the consistency of this relationship. Moreover, time series of SPM_rs concentrations derived from the POWERS algorithm, were shown to follow the same temporal trends as individual SPM_is data recorded during 2001. Composites of annual, winter and summer SPM_rs for 2001 highlight the three dominant water masses in the southern North Sea, as well as their winter–fall and spring–summer variability. The results indicate that wind induced wave action and mixing cause high surface SPM signals in winter in regions where the water column becomes well mixed, whereas in summer stratification leads to a lower SPM surface signal. The presented algorithm gives accurate near-surface SPM concentrations and could easily be adapted for other water masses and seas.     

基于适应性观测误差和温盐偏差控制的EnKF温盐廓线资料同化试验

通过开展2008年夏季南海北部开放航次CTD的温盐廓线数据资料同化试验,本文采取了观测误差适应的方法来防止EnKF滤波发散问题;同时,从背景误差协方差和温盐模式偏差关系入手,在同化中引入温盐控制来减小模式偏差对同化结果的影响。对于改进的同化方案进行了试验验证,并用卫星高度计观测数据,OSCAR流速数据,走航ADCP数据作为独立观测数据检验。结果证明新的EnKF同化策略能够有效地减小温盐均方根误差。同时整个同化系统能有效地改善高度场和流场的模拟。     

Assimilation of sea surface temperature in the Northwest Pacific Ocean and its marginal seas using the ensemble Kalman filter

Satellite-borne sea surface temperature (SST) data were assimilated with the ensemble Kalman filter (EnKF) in a Northwest Pacific Ocean circulation model to examine the effect of data assimilation. The model domain included the northwestern part of the Pacific Ocean and its marginal seas, such as the Yellow Sea and East/Japan Sea. The performance of the data assimilation was evaluated by comparing the simulated ocean state with that observed. Spatially averaged root-mean-squared errors in the SST and sea surface height (SSH) decreased by 0.44 °C and 4 cm, respectively, by the assimilation. The results of the numerical experiments substantiated the effectiveness of the SST assimilation via the EnKF for all marginal seas, as well as the Kuroshio region. The benefit of the data assimilation depended on the characteristics of each marginal sea. The variation of the SST in the East/Japan Sea and the Kuroshio extension (KE) region were improved 34% and those in the Yellow Sea 12.5%. The variation of the SSH was improved approximately 36% in the KE region. This large improvement was achieved in the deep-water regions because assimilation of SST data corrected the separation point of the western boundary currents, such as the Kuroshio and the East Korea Warm Current, and the associated horizontal surface currents. The SST assimilation via the EnKF also improved the subsurface temperature profiles. The effectiveness of SST assimilation was seasonally dependent, with the improvement being relatively larger in winter than in summer, which was related to the seasonal variation of the vertical mixing and stratification in the ocean surface layer.     

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.     

珠江口水体叶绿素荧光特性研究

利用2003年1月和2004年1月珠江口实测的遥感反射率和叶绿素浓度,建立了基于实测1nm带宽及其模拟MERIS遥感反射率数据的叶绿素荧光特征与叶绿素浓度之间的拟合关系。基于实测1nm带宽遥感反射率光谱,叶绿素荧光峰的位置和高度分别与叶绿素浓度之间存在良好的线性关系和指数关系;基于模拟MERIS遥感反射率数据,叶绿素荧光峰的高度与叶绿素浓度之间存在良好的线性关系,叶绿素荧光峰位置与叶绿素浓度之间不存在明显的相关关系,但可作为叶绿素浓度数量级的有效探针。利用2006年5月和8月的珠江口实测遥感反射率和叶绿素浓度对拟合结果进行了检验,结果表明其精度较高,说明叶绿素荧光特征在探测叶绿素浓度时效果良好且MERIS数据在近岸二类水体叶绿素浓度反演、水质监测等方面有着良好的应用前景。     

基于ROMS和4DVAR的沿轨与网格化SSH数据同化效果评价

Remote sensing products are significant in the data assimilation of an ocean model. Considering the resolution and space coverage of different remote sensing data, two types of sea surface height(SSH) product are employed in the assimilation, including the gridded products from AVISO and the original along-track observations used in the generation. To explore their impact on the assimilation results, an experiment focus on the South China Sea(SCS) is conducted based on the Regional Ocean Modeling System(ROMS) and the four-dimensional variational data assimilation(4 DVAR) technology. The comparison with EN4 data set and Argo profile indicates that, the along-track SSH assimilation result presents to be more accurate than the gridded SSH assimilation, because some noises may have been introduced in the merging process. Moreover, the mesoscale eddy detection capability of the assimilation results is analyzed by a vector geometry–based algorithm. It is verified that, the assimilation of the gridded SSH shows superiority in describing the eddy's characteristics, since the complete structure of the ocean surface has been reconstructed by the original data merging.     

FerryBox and MERIS – Assessment of coastal and shelf sea ecosystems by combining in situ and remotely sensed data

An automatic measuring system called “FerryBox” was installed in the North Sea on a ferry travelling between Germany (Cuxhaven) and Great Britain (Harwich), enabling online oceanographic and biological measurements such as salinity, temperature, fluorescence, turbidity, oxygen, pH, and nutrient concentrations. Observations made along the ferry transect reveal characteristic phenomena such as high salinity inflow through the Channel into the Southern Bight, algal bloom dynamics and related oxygen and pH changes. Combination of these online observations with remote sensing enhances the spatial resolution of the transect related measurements. Several examples of the synergy between these two measuring strategies are shown, both for large-scale algal blooms in the North Sea as well as for local intense but short-term blooms in the German Bight. Coherence of the data sets can be gained and improved by using water transport models in order to obtain synoptic overviews of the remotely sensed and FerryBox related parameters. Limitations of the currently used algorithms for deriving chlorophyll-a from remote sensing images for coastal and shelf seas (Case-2 water) are discussed, as well as depth related processes which cannot be properly resolved on the basis of water intake at a fixed point. However, in unstratified coastal waters under normal conditions FerryBox data represent average conditions. The importance of future applications of this combination of methods for monitoring of coastal waters is emphasized.     

渤海、黄海、东海冬季海流场温度场数值模拟和同化技术

利用NASA高分辨率的卫星遥感资料SST,采用Nudging同化来模拟渤海、黄海、东海的三维温度场,减小用热通量作上边界条件所带来的误差.结果表明,模拟的海流场能较好地反映渤海、黄海、东海的环流特征.数据同化后的温度场优于未经同化的温度场.3个选择站点的同化值与实测值的均方根误差分别为1.307,0.526,0.744,用热通量资料模拟的水温与实测值的均方根误差分别为2.160,0.979,1.330.尽管只同化了海表温度,但数据同化对三维温度场结构都有影响.     

Spectral wave data assimilation for the prediction of waves in the North Sea

Spectral observations from pitch-and-roll buoys have been assimilated in a North Sea wave model, in order to study their impact on the wave analysis and forecast. The assimilation is based on Optimal Interpolation (OI) of a limited number of characteristic spectral parameters. In a case study, the propagation of the corrections through the model domain is followed, and it is clarified for which wave conditions the data assimilation has the largest influence on the forecast: this is especially the case for swell waves with long travel times between the assimilation site and the location where validation is carried out. A 1-year test has been carried out in which an analysis and subsequent forecast were produced four times a day. From a statistical analysis of the results a modest but systematic improvement of the 12-h forecast is found. When only swell cases are selected, the impact is more pronounced. It is argued that for shelf seas like the North Sea, more progress is to be expected from extension of the ‘conventional' observations network (buoys and wave radars) than from satellite measurements.     

Distribution of suspended particulate matter in the North Sea as inferred from NOAA/AVHRR reflectance images and in situ observations

Distribution patterns of suspended particulate matter (SPM) in the surface water of the North Sea were calculated on the basis of: (1) the 1973–1993 data base of the EC MAST North West European Shelf Programme (NOWESP); and (2) composite reflectance images constructed from data that were collected by the NOAA/AVHRR satellite in 1990–1991. Three models were used for interpolating the in situ data: (1) a distance-weighted interpolation algorithm in which only the in situ data are taken into account; (2) an algorithm in which the ratios between the measured SPM concentrations and reflectances are interpolated, and the distribution of SPM is calculated from the field of interpolated ratios and the synoptic reflectance image; and (3) a distance-weighted algorithm similar to model-1, but with an additional weight factor that is based on local differences in reflectance. The models were tested for periods of 1 and 3 weeks in September 1990 and January 1991, and for the merged set consisting of all in situ data measured in September and January, respectively, between 1973 and 1993. Model-2 and -3 gave largely similar results and had a performance superior to model-1, particularly because they showed more detailed structures in the spatial distributions. Validations and cross-validations showed that the absolute concentrations of SPM predicted by the models were too low at high in situ concentrations and too high at low in situ concentrations. This shortcoming was due to the relatively high degree of smoothing that we applied in the models to account for the large variance of the in situ data. Semivariograms and correlograms indicated that the in situ data had substantial variability and were poorly correlated even at short distances. Only for the 20-year-merged data set did some correlation ( %) exist for stations km from each other. Monthly distributions of SPM were calculated with model-3 and the 20-year data set. The distributions confirm the main patterns previously found by others, such as the turbidity plume crossing the North Sea from southeast England towards the depository in the Skagerrak and the Norwegian Channel. The distributions indicate that materials from this plume may be deposited in the central North Sea in spring and summer and eroded again in autumn and winter. Areas with maximum SPM concentrations were identified off the Belgian coast and north of the Wadden Sea, particularly in winter, from which particles are entrained into the main current in a narrow strip along the continental coast to the German Bight. The results suggest that the two main fluxes of SPM in the North Sea, off England and along the continental coast, remain largely separated until they both end in the Skagerrak.     

黄、东海边界悬浮物输运量的卫星遥感估算

利用2002—2015年的中等分辨率成像光谱仪(Moderate Resolution Imaging Spectroradiometer, MODIS)第4波段反射率产品对黄、东海边界的悬浮物输运情况进行了分析, 同时利用黄、东海2003年现场实测的悬浮物含量数据和这期间准实时的MODIS影像数据, 建立了基于MODIS第4波段遥感反射率的悬浮物含量遥感反演模型。基于该模型, 反演黄、东海表层悬浮物浓度, 并计算悬浮物扩散面积。利用反演得到的表层悬浮物浓度和悬浮物浓度垂向预测模型, 获取垂直方向上的悬浮物浓度, 同时结合水深、扩散面积数据, 计算特定时刻水体中的悬浮物含量。利用插值方法获得整个输运过程中各时刻水体中的悬浮物的含量, 计算各个时刻悬浮物含量的总和作为悬浮物的输送量。对2002年10月至2003年4月黄海向东海的悬浮输送量进行估算, 估算结果为153Mt。     

黄海海雾短时临近预报中云水路径的EnKF同化研究

在海雾的短时临近预报中,初始场的水汽凝结状态扮演着重要角色。为了改进初始场的云水含量,本文提出直接同化雾体云水信息的思路。针对2011年5月一次大范围的黄海海雾,借助EnKF (Ensemble Kalman Filter)方法,尝试进行了极轨卫星反演云水路径数据的同化试验。结果表明:(1)通过利用EnKF将云水混合比增加到背景场和分析场的控制变量中,构建云水观测数据与背景场之间的关系,实现云水路径数据的直接同化是可行的;(2)同化云水路径可显著改善海面气温与湿度状态,大幅提高海雾预报效果;(3)EnKF能够基于集合体动态统计流依赖的背景误差协方差是其取得良好同化效果的主要原因。值得指出的是,受集合样本误差的影响,需要特别关注云水含量与风之间的相关关系。     

空间变异对海洋叶绿素a质量浓度遥感产品精度验证的影响

海洋叶绿素a质量浓度遥感产品是海洋初级生产力与海洋生态系统固碳能力研究的重要数据源,为了保证数据的可靠性,对遥感产品进行精度验证以及验证误差的成因分析尤为重要.遥感产品的验证过程中,由于空间变异的存在,使得遥感像元尺度内的实测数据具有不同的离散程度和统计分布特征,并由此产生了不同的误差统计结果.本文选择MODIS-Aq...     

杭州湾三维悬浮泥沙输运模型初始场的伴随法反演研究

在悬沙输运的数值模拟中,初始场的准确给定至关重要。目前诸多确定初始场的方案均存在一定的缺陷,初始场的准确性有待进一步提高。本文基于一个三维悬沙输运伴随同化模型,通过孪生实验和实际实验,对模型初始场进行了伴随法反演研究。在孪生实验中,首先验证了初始场的相对重要性;其次,探讨了初始场的反演结果对优化算法、初始猜测值、卫星遥感数据数量、同化时间窗口宽度和背景流场误差的敏感性;最后,比较了伴随法和插值法重构初始场的能力。孪生实验结果表明:最速下降法对初始场的优化反演效果要优于三种共轭梯度法和有限记忆BFGS法;初始场的反演效果对初始猜测值、卫星遥感数据数量和背景流场误差不敏感,而对同化窗口宽度较为敏感;与插值法相比,伴随法是重构模型初始场更有效的手段。实际实验中,在杭州湾海域同化典型的小潮时期和大潮时期的GOCI卫星遥感资料所得表层悬沙浓度数据,优化反演了初始场。实际实验结果表明:数据同化后,得到了更符合实际的最优初始场,表明伴随法是实现初始场优化反演的有效手段。该研究对进一步改进悬沙输运模型的初始化方案具有一定的参考价值,也对其他数值模型的初始化方案具有一定的借鉴价值。     

Cloud filling of ocean colour and sea surface temperature remote sensing products over the Southern North Sea by the Data Interpolating Empirical Orthogonal Functions methodology

Optical remote sensing data is now being used systematically for marine ecosystem applications, such as the forcing of biological models and the operational detection of harmful algae blooms. However, applications are hampered by the incompleteness of imagery and by some quality problems. The Data Interpolating Empirical Orthogonal Functions methodology (DINEOF) allows calculation of missing data in geophysical datasets without requiring a priori knowledge about statistics of the full dataset and has previously been applied to SST reconstructions. This study demonstrates the reconstruction of complete space–time information for 4 years of surface chlorophyll a (CHL), total suspended matter (TSM) and sea surface temperature (SST) over the Southern North Sea (SNS) and English Channel (EC). Optimal reconstructions were obtained when synthesising the original signal into 8 modes for MERIS CHL and into 18 modes for MERIS TSM. Despite the very high proportion of missing data (70%), the variability of original signals explained by the EOF synthesis reached 93.5% for CHL and 97.2% for TSM. For the MODIS TSM dataset, 97.5% of the original variability of the signal was synthesised into 14 modes. The MODIS SST dataset could be synthesised into 13 modes explaining 98% of the input signal variability. Validation of the method is achieved for 3 dates below 2 artificial clouds, by comparing reconstructed data with excluded input information. Complete weekly and monthly averaged climatologies, suitable for use with ecosystem models, were derived from regular daily reconstructions. Error maps associated with every reconstruction were produced according to Beckers et al. (2006). Embedded in this error calculation scheme, a methodology was implemented to produce maps of outliers, allowing identification of unusual or suspicious data points compared to the global dynamics of the dataset. Various algorithm artefacts were associated with high values in the outlier maps (undetected cloud edges, haze areas, contrails, and cloud shadows). With the production of outlier maps, the data reconstruction technique becomes also a very efficient tool for quality control of optical remote sensing data and for change detection within large databases.     

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。     

渤海悬浮物分布的遥感研究

利用渤海湾和莱州湾现场实测的悬浮物含量和光谱数据,建立了基于555和670nm波段遥感反射率的悬浮物含量遥感反演模型。经检验,模型平均相对误差优于20%,对输入端误差不敏感。基于该模型,利用ENVISAT MERIS遥感数据,从空间分布格局、大风过程的短期扰动以及季节性差异等方面分析了渤海悬浮物的时空分布特征。(1)渤海悬浮物含量的高值区集中分布在莱州湾(尤其是黄河口和莱州湾湾底)和渤海湾沿岸,此外在辽东湾沿岸海域悬浮物含量也相对较高,而在渤海大部水体悬浮物含量较低。(2)大风过程可在短期内(约1~3d)显著改变全渤海的悬浮物空间分布格局,其中渤海湾和莱州湾响应最为强烈,辽东湾响应相对较弱,这与其各自的水深条件、底质类型和悬浮物粒径等因素有关。(3)渤海悬浮物含量总体上呈春夏低、秋冬高的分布特征;季节性差异最显著的区域是渤海湾、莱州湾和辽东湾,差异性最小的是秦皇岛近岸海域;风力等气候因素是悬浮物分布呈现季节性差异的主要原因,入海径流是另一重要因素。     

Labrador Sea convection and subpolar North Atlantic Deep Water export in the SODA assimilation model

Labrador Sea convection was most intense and reached the greatest depths in the early 1990s, followed by weaker, shallower, and more variable convection after 1995. The Simple Ocean Data Assimilation (SODA) version 2.0.2/2.0.4 assimilation model is used to explore convective activity in the North Atlantic Ocean for the period from 1992 to 2007. Hydrographic conditions, which are relatively well observed during this period, are used to compare modeled and observed winter mixed-layer depths and water mass anomalies in relation to Deep Western Boundary Current transports and meridional overturning circulation (MOC) changes at the exit of the subpolar basin. The assimilation differs markedly from local observations in the March mixed-layer depth, which represents deep convection and water mass transformation. However, mean MOC rates at the exit of the subpolar gyre, forced by stratification in the mid-latitudes, are similar to estimates based on observations and show no significant decrease during the 1992–2007 period. SODA reproduces the deep Labrador Sea Water formation in the western North Atlantic without any clear indication of significant formation in the Irminger Sea while the lighter upper Labrador Sea Water density range is reached in the Irminger Sea in the 1990s, in agreement with existing assumptions of deep convection in the Irminger Sea and also supported by computed lag correlations with the Labrador Sea. Deep Water transformation mainly takes place in the eastern North Atlantic. The introduction of CFC-11 into the SODA model as a tracer reproduces the mean and multiyear variations of observed distributions.