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11.
Deterministic sea-wave prediction (DSWP) models are appearing in the literature designed for quiescent interval prediction in marine applications dominated by large swell seas. The approach has focused upon spectral methods which are straightforward and intuitively attractive. However, such methods have the disadvantage that while the sea is aperiodic in nature, the standard discrete spectral processing techniques force an absolutely periodic structure onto the resulting sea surface prediction models. As it is the shape of the sea surface that is important in such applications, particularly near the end of the domain which is important, the standard windowing techniques used in signal processing work to reduce leakage artifacts cannot be employed. This has necessitated the use of end matching methods that can be both inconvenient and may reduce the fraction of the time for which legitimate predictions are available. As a result, an investigation has been undertaken of the use of finite impulse response prediction filters to provide the necessary dispersive phase shifting required in DSWP systems. The present work examines the theoretical basis for such filters and explores their properties together with their application to both long and short crested swell seas. It is shown that wide band forms of such filters are only convergent in the sense of distributions having both infinite duration impulse responses and asymptotically divergent first derivatives. However, appropriate band limitation can produce useful finite impulse responses allowing implementation via standard discrete convolution methods. It is demonstrated that despite the prediction filters having a non-causal impulse response such filters can be used in practice due to a combination of the asymmetric nature of the impulse response and the fundamental nature of the prediction process. The findings are confirmed against actual sea-wave data. 相似文献
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本文在对位于黄海南部陆架上的朝连岛站30年水温资料进行分析时发现,该站的表层水温有周期大于20个月的低频振动,其中以准两年周期和6年周期最显著。陆架水温的这种低频振动是对东亚季风异常的响应。这种低频振动在冬季与渤海冰情的变化同步;在夏季与黄海底层冷水团的强弱相关。同时,这种低频振动在对马暖流上也有一定的反映。 相似文献
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海洋天然气水合物调查地震采集技术——调查初始阶段研究 总被引:1,自引:0,他引:1
地震调查方法在水合物中的应用分为两个主要阶段:调查初始阶段和调查深入阶段。调查初始阶段以“突出天然气水合物的四大主要识别标志(似海底反射、振幅空白带、穿层特征、振幅和速度结构异常)”为主要目的,为资料的处理、解释提供丰富的地震信息。从而圈定天然气水合物富集程度高、成藏条件好的“目标”靶区,开展深入调查,更好地展现“天然气水合物矿体立体上的形态特征”,了解“水合物矿体的厚度、顶底界面及富集程度”。文中从震源技术研究、高分辨率地震调查技术的调谐组合参数研究和野外施工方法等方面的内容出发,根据大量野外技术试验资料和有关科研成果,总结了在天然气水合物调查初始阶段的特点及相应的地震调查技术。 相似文献
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Parameter sensitivity of three Kalman filter schemes for assimilation of water levels in shelf sea models 总被引:2,自引:0,他引:2
In applications of data assimilation algorithms, a number of poorly known assimilation parameters usually need to be specified. Hence, the documented success of data assimilation methodologies must rely on a moderate sensitivity to these parameters. This contribution presents a parameter sensitivity study of three well known Kalman filter approaches for the assimilation of water levels in a three dimensional hydrodynamic modelling system. The filters considered are the ensemble Kalman filter (EnKF), the reduced rank square root Kalman filter (RRSQRT) and the steady Kalman filter. A sensitivity analysis of key parameters in the schemes is undertaken for a setup in an idealised bay. The sensitivity of the resulting root mean square error (RMSE) is shown to be low to moderate. Hence the schemes are robust within an acceptable range and their application even with misspecified parameters is to be encouraged in this perspective. However, the predicted uncertainty of the assimilation results are sensitive to the parameters and hence must be applied with care. The sensitivity study further demonstrates the effectiveness of the steady Kalman filter in the given system as well as the great impact of assimilating even very few measurements. 相似文献
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V. Carmillet J. -M. Brankart P. Brasseur H. Drange G. Evensen J. Verron 《Ocean Modelling》2001,3(3-4)
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. 相似文献
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A primitive equation model and a statistical predictor are coupled by data assimilation in order to combine the strength of both approaches. In this work, the system of two-way nested models centred in the Ligurian Sea and the satellite-based ocean forecasting (SOFT) system predicting the sea surface temperature (SST) are used. The data assimilation scheme is a simplified reduced order Kalman filter based on a constant error space. The assimilation of predicted SST improves the forecast of the hydrodynamic model compared to the forecast obtained by assimilating past SST observations used by the statistical predictor. This study shows that the SST of the SOFT predictor can be used to correct atmospheric heat fluxes. Traditionally this is done by relaxing the model SST towards the climatological SST. Therefore, the assimilation of SOFT SST and climatological SST are also compared. 相似文献
20.
以低成本陆用航姿参考系统(AHRS)/GPS紧耦合系统为研究对象,建立了基于伪距、伪距率、航向角的组合观测数学模型。引入强跟踪滤波(STF)算法,利用渐消因子的作用,增强滤波器对状态快速变化的跟踪能力。同时,针对微惯性器件漂移过大的缺点,采用二阶EKF(QEKF)方法,通过对Hessian矩阵的求解,补偿系统观测方程线性化的二阶截断误差。仿真表明:STQEKF方法可高速准确地逼近系统非线性模型,实现陆地载体导航控制,在传感器精度有限的情况下,使姿态和位置的控制效果较标准EKF分别提高了约8.9%-38.2%和48.7%-54.4% 相似文献