Comparative Study of Two Approaches to Model the Offshore Fish Cages

The goal of this paper is to provide a comparative analysis of two commonly used approaches to discretize offshore fish cages: the lumped-mass approach and the finite element technique. Two case studies are chosen to compare predictions of the LMA(lumped-mass approach) and FEA(finite element analysis) based numerical modeling techniques. In both case studies, we consider several loading conditions consisting of different uniform currents and monochromatic waves. We investigate motion of the cage, its deformation, and the resultant tension in the mooring lines. Both model predictions are sufficient close to the experimental data, but for the first experiment, the DUT-Flex Sim predictions are slightly more accurate than the ones provided by Aqua-FETM. According to the comparisons, both models can be successfully utilized to the design and analysis of the offshore fish cages provided that an appropriate safety factor is chosen.     

On the perception of morphodynamic model skill

The quality of morphodynamic predictions is generally expressed by an overall grid-point based skill score, which measures the relative accuracy of a morphological prediction over a prediction of zero morphological change, using the mean-squared error (MSE) as the accuracy measure. Through a generic ranking for morphodynamic model predictions, this MSE based skill score (MSESS) aims at making model performance comparable across different prediction situations (geographical locations, forcing conditions, time periods, internal dynamics). The implicit assumptions underlying this approach are that the MSE is an appropriate measure of correspondence for morphological predictions and that the accuracy of the initial bed as the reference correctly reflects the inherent difficulty or ease of prediction situations. This paper presents a thorough analysis of the perception of model skill through the MSE skill score. Using synthetic examples, an example from literature and a long-yearly Delft3D model simulation, we demonstrate that unexpected skill may be reported due to a violation of either of the above assumptions. It is shown that the accuracy of the reference fails to reflect the relative difficulty of prediction situations with a different morphological development prior to the evaluation time (for instance trend, cyclic/seasonal, episodic, speed of the development). We further demonstrate that the MSESS tends to favor model results that underestimate the variance of cumulative bed changes, a feature inherited from the MSE. As a consequence of these limitations, the MSESS may report a relative ranking of predictions not matching the intuitive judgment of experts. Guidelines are suggested for how to adjust calibration and validation procedures to be more in line with a morphologist's expert judgment.     

A residual analysis method for quantitative comparison of spatial data from the Iceland-Faeroes Front

A spatial statistical method has been developed from the well-known Kriging technique in geostatistics, as a way of providing quantitative comparison between a pair of spatial data sets, and a measure for such a comparison. This residual analysis method is applied to oceanographic data in order to compare Iceland-Faeroes Front (IFF) model predictions against appropriate field observations, with an aim to assess the IFF model performance and its prediction accuracy. The method is also used to evaluate the model-generated dynamical variability within the model predictions, as well as the natural variability within the frontal observations. From the results, it has been found that the IFF model is highly robust, and gives better predictions at depth 150–350 m than elsewhere. Within such a depth (i.e. 250–350 m), there is also evidence to suggest that the main frontal region is most active above the IF Ridge. The natural variability obtained from the observations appears to be comparable to the model-generated dynamical variability after 20 days of integration, indicating a certain degree of accuracy in the model predictions. The method reported in this paper could also be extended for further use in model data assimilation. Thus, the work not only demonstrates how spatial statistics can be applied to oceanographic data, but also opens up new statistical tools for data handling in ocean modelling.     

Spatial length scale analysis of data from observations and a model of the Iceland-Faeroes front

Hydrographic data from the Iceland-Faeroes Ridge region, covering an area of 59°–69° north and 0°–20° west, have been subjected to a spatial data analysis. The analysis consists of the two-dimensional spectral method (2D-FFT) and the empirical eigenfunction method (EOF). Results from the two methods show good agreement indicating that the significant length scales for horizontal variability present in the data have wavelengths of approximately 339 km, 72 km and 37 km. These wavelengths relevant to the Iceland-Faeroes front are interpreted as the sizes respectively of the warm water intrusion from the south of the front with a diameter of half the wavelength (i.e.,?169 km), and the meander-like and eddy-like features. Predictions of the same frontal system have also been made using a realistic numerical model to provide hydrographic outputs similar to the observations. The hydrographic outputs from the model have been subjected to the same 2D-FFT method to establish the spatial length scale present in the model predictions. A comparison of results from a spectral data analysis between the field measurements and the model predictions shows that the model can predict the sizes of the meander-like and the eddy-like features quite accurately. However, predictions of frontal orientation, frontal slopes and size of the warm water intrusion still require further study. The work presented also demonstrates the importance of spatial statistics in oceanographic research, particularly in ocean predictability studies.     

Data Assimilation Modeling of the Barotropic Tides in the Korea/Tsushima Strait

During 1999–2000, 13 bottom mounted acoustic Doppler current profilers (ADCPs) and 12 wave/tide gauges were deployed along two lines across the Korea/Tsushima Strait, providing long-term measurements of currents and bottom pressure. Tidally analyzed velocity and pressure data from the moorings are used in conjunction with other moored ADCPs, coastal tide gauge measurements, and altimeter measurements in a linear barotropic data assimilation model. The model fits the vertically averaged data to the linear shallow water equations in a least-squares sense by only adjusting the incoming gravity waves along the boundaries. Model predictions are made for the O₁, P₁, K₁, μ₂, N₂, M₂, S₂, and K₂ tides. An extensive analysis of the accuracy of the M₂ surface-height predictions suggests that for broad regions near the mooring lines and in the Jeju Strait the amplitude prediction errors are less than 0.5 cm. Elsewhere, the analysis suggests that errors range from 1 to 4 cm with the exception of small regions where the tides are not well determined by the dataset. The errors in the model predictions are primarily caused by bias error in the model’s physics, numerics, and/or parameterization as opposed to random errors in the observational data. In the model predictions, the highest ranges in sea level height occur for tidal constituents M₂, S₂, K₁, O₁, and N₂, with the highest magnitudes of tidal velocities occurring for M₂, K₁, S₂, and O₁. The tides exhibit a complex structure in which diurnal constituents have higher currents relative to their sea level height ranges than semi-diurnal constituents.     

南海北部沿岸海域潮汐的调和分析

采用t_tide潮汐分析工具对南海北部的5个验潮站2009年全年的逐时潮高资料进行调和分析,计算出各站的调和常数,评估调和常数的准确性、稳定性,并总结了广东沿岸海域潮汐特征.利用对2009年逐时潮高的调和分析结果对2010年全年的潮高进行预测,将各站预测结果与同时间的实测数据进行全年和分季节进行比较,对预测结果与实测数据的残差进行统计分析.通过对残差的散点分布、概率分布、置信区间等统计结果进行分析,检验预测结果的准确性、稳定性和可靠性.结果表明：广东沿岸海域潮汐是以M2分潮为主,K1、O1、S2为次结合的潮汐机制,采用t_tide潮汐分析工具对南海北部潮高的预测结果与实测数据拟合较好,相位预测准确,潮高预测除在时间序列尾部（年尾）有些许较大的误差外,t_tide工具在南海北部潮汐预报中具有较高的准确性和稳定性.预测残差的整体服从正态分布,残差均值小于10-2m量级,方差最大为0.229 4,最小为0.173 2,95%置信区间长度小于10-2.各站季节分析主要分潮的离散度小于0.04的结果充分证明不同季节的分析区别不明显,3个月资料与整年资料的调和分析结果几乎一致,与所选取的季节资料几乎无关.虽然在预测值中,有极个别的残差将近1 m,但并不足以影响到预测的准确性.     

Wave hindcasting off the coast of Portugal

A study was conducted applying a second-generation wave model to predictions in coastal zones. The model was calibrated with wave measurements conducted off the Portuguese coast, for a period of 6 months. The wind fields used in the calculation were supplied by the European Centre for Medium Range Weather Forecast (ECMRWF). The calibrated model allows good predictions of significant wave height. Satisfactory comparisons have been made with predictions of the WAM model     

Large-scale short-term seismicity activation prior to the strongest earthquakes of Japan and the Kurile Islands

The Reverse Tracing of Precursors (RTP) algorithm for the prediction of strong earthquakes has become known owing to the successful predictions of the Tokachi-oki earthquake near Hokkaido Island and the San Simeon earthquake of California in 2003, as well as to other well-documented predictions found on the Internet, some of which also proved to be successful. The RTP predictions with the use of the Japan Meteorological Agency (JMA) data for the zone from Honshu Island to the Middle Kurile Islands deserve special attention. None of the five predictions starting in the middle of 2003, including the last one formulated for the region where the catastrophic earthquake of March 11, 2011, with a magnitude of M = 9 occurred, was a false alarm. One distinctive feature of predictions for this region is the enormous size (about 1000 km) of alarm regions. At the same time, the relatively short alarm interval makes it possible to record a real number of earthquakes with a magnitude of 7.2 and higher during alarm periods, which is about five times larger than on average over the equivalent period, i.e., to reach a probability gain of about five.     

Local model approximation in the real time wave forecasting

The notion of data assimilation is common in most wave predictions. This typically means nudging of wave observations into numerical predictions so as to drive the predictions towards the observations. In this approach, the predicted wave climate is corrected at each time of the observation. However, the corrections would diminish soon in the absence of future observations. To drive the model state predictions towards real time climatology, the updating has to be carried out in the forecasting horizon too. This could be achieved if the wave forecasting at the observational network is made available. The present study addresses a wave forecasting technique for a discrete observation station using local models. Embedding theorem based on the time-lagged embedded vector is the basis for the local model. It is a powerful tool for time series forecasting. The efficiency of the forecasting model as an error correction tool (by combining the model predictions with the measurements) has been brought up in a forecasting horizon from few hours to 24 h. The parameters driving the local model are optimised using evolutionary algorithms.     

Prediction and observation of a model gravity platform on Drammen clay

The results of five centrifuge tests of a stiff circular model platform on overconsolidated undisturbed Drammen clay are reported from Manchester University together with predictions computed at the Norwegian Geotechnical Institute. Towards failure the models developed high shear strain and softening local to the base, accompanied by a permanent settlement or shakedown. A total stress transfer from edge to centre caused a rapid increase of excess pore pressure under the centre, having a high vertical gradient. These features, and failure values which decreased with increase in eccentricity of loading, conformed with previous observations on reconstituted clays. Comparison of observations with predictions highlights the sensitivity of the analytical method to the fineness of the finite element mesh just below the base. The predictions also indicated a sensitivity of the failure load to the degree of overconsolidation associated with a given undrained shear strength. The elastic type analysis did not predict the degree of shakedown which was associated with plastic displacement of clay from just under the base.     

Modelling the spatial distribution of plaice (Pleuronectes platessa), sole (Solea solea) and thornback ray (Raja clavata) in UK waters for marine management and planning

Species distribution maps are needed for ecosystem-based marine management including the development of marine spatial plans. If such maps are based on predictive models then modelling procedures should aim to maximise validation success, and any uncertainty in the predictions needs to be made explicit. We developed a predictive modelling approach to produce robust maps of the distributions of selected marine species at a regional scale. We used 14 years of survey data to map the distributions of plaice, sole and thornback ray in three hydrographic regions comprising parts of the Irish Sea, Celtic Sea and the English Channel with the help of the hybrid technique regression kriging, which combines regression models with geostatistical tools. For each species–region combination we constructed logistic Generalized Linear Models (GLMs) based on presence–absence data using the environmental variables: depth, bottom temperature, bed shear stress and sediment type, as predictors. We selected GLMs using the mean squared error of prediction (MSEP) estimated by cross-validation then conducted a geostatistical analysis of the residuals to incorporate spatial structure in the predictions. In general, we found that species occurrence was positively related to shallow areas, a bed shear stress of between 0 and 1.5 N/m², and the presence of sandy sediment. Predicted species occurrence probabilities were in good agreement with survey observations. This modelling framework selects environmental models based on predictive ability and considers the effect of spatial autocorrelation on predictions, together with the simultaneous presentation of observations, associated uncertainties, and predictions. The potential benefit of these distribution maps to marine management and planning is discussed.     

Shallow-water bottom reverberation measurements

High-frequency bottom reverberation measurements were made at an experimental site in the Gulf of Mexico. The acoustic data were taken as a function of frequency (40-180 kHz) and grazing angle (40-33°). The measured acoustic reverberation results are compared to predictions made by models developed by Jackson et al. (1986, 1996) and Boyle and Chotiros (1995). The models used inputs from the analysis of sediment cores and stereophotography. The model predictions show differences from each other and from the data. The results show reverberation-level variabilities as a function of frequency that cannot be accurately predicted by these models     

Prediction of the total cycle 24 of solar activity by several autoregressive methods and by the precursor method

As follows from the statement of the Third Official Solar Cycle 24 Prediction Panel created by the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), and the International Space Environment Service (ISES) based on the results of an analysis of many solar cycle 24 predictions, there has been no consensus on the amplitude and time of the maximum. There are two different scenarios: 90 units and August 2012 or 140 units and October 2011. The aim of our study is to revise the solar cycle 24 predictions by a comparative analysis of data obtained by three different methods: the singular spectral method, the nonlinear neural-based method, and the precursor method. As a precursor for solar cycle 24, we used the dynamics of the solar magnetic fields forming solar spots with Wolf numbers Rz. According to the prediction on the basis of the neural-based approach, it was established that the maximum of solar cycle 24 is expected to be 70. The precursor method predicted 50 units for the amplitude and April of 2012 for the time of the maximum. In view of the fact that the data used in the precursor method were averaged over 4.4 years, the amplitude of the maximum can be 20–30% larger (i.e., around 60–70 units), which is close to the values predicted by the neural-based method. The protracted minimum of solar cycle 23 and predicted low values of the maximum of solar cycle 24 are reminiscent of the historical Dalton minimum.     

Evaluation of GEV model for frequency analysis of annual maximum water levels in the coast of United States

The three-parameter generalized-extreme-value (GEV) model has been recommended by FEMA [FEMA (Federal Emergency Management Agency of the United States), 2004. Final Draft Guidelines for Coastal Flood Hazard Analysis and Mapping for the Pacific Coast of the United States. http://www.fema.gov/library/viewRecord.do?id=2188] for frequency analysis of annual maximum water levels in the Pacific coast of the United States. Yet, the GEV model's performance in other coastal areas still needs to be evaluated. The GEV model combines three types of probability distributions into one expression. The probability distributions can be defined by one of the three parameters of the GEV model. In this study, annual maximum water levels at nine water-level stations with long history data (more than 70 years) were chosen for analysis in five coastal areas: Pacific, Northeast Atlantic, East Atlantic, Southeast Atlantic, and Gulf of Mexico coasts. Parameters of the GEV model are estimated by the maximum likelihood estimation (MLE) method. Results indicate that probability distributions are characterized by the GEV Type III model at stations in the Pacific, Northeast, and East Atlantic coastal areas, while they are described by GEV Type II in stations of the Southeast Atlantic and Gulf of Mexico coastal areas. GEV model predictions of extreme water levels show good correlation to observations with correlation coefficients of 0.89 to 0.99. For predictions of 10% annual maximum water levels, the GEV model predictions are very good with errors equal to or less than 5% for all nine stations. Comparison of observations and GEV model estimations of annual maximum water levels for the longest recorded return periods, close to 100 years, revealed errors equal to or less than 5% for stations in the Pacific and Northeast Atlantic coastal areas. However, the errors range from 10% to 28% for other stations located in the East and Southeast Atlantic coasts as well as Gulf of Mexico coastal areas. Findings from this study suggest caution regarding the magnitudes of errors in applying the GEV model to the East and Southeast Atlantic coasts and Gulf of Mexico coast for estimating 100-year annual maximum water levels for coastal flood analysis.     

Silt heavy-mineral distributions off the Southeastern United States

Until recently heavy-mineral studies of marine sediments were largely restricted to sand fractions. New techniques permitting analysis of decalcified silt fractions have been applied to sediments off the southeastern United States. Our data, which confirm predictions from the basic relationship among grain size, specific gravity, and equivalent hydraulic transport behavior, show that concentrations and average diameters of the silt heavy minerals progressively decrease seaward. Heavy minerals always constitute a substantially greater weight percent of the silt than of the sand fraction. Despite corroded surface textures suggestive of extensive weathering and dissolution, spatial trends in the detrital heavy-mineral populations are predominantly controlled by source and hydraulic factors.     

Performance Analysis for Matched-Field Source Localization: Simulations and Experimental Results

Matched-field methods concern estimation of source locations and/or ocean environmental parameters by exploiting full wave modeling of acoustic waveguide propagation. Typical estimation performance demonstrates two fundamental limitations. First, sidelobe ambiguities dominate the estimation at low signal-to-noise ratio (SNR), leading to a threshold performance behavior. Second, most matched-field algorithms show a strong sensitivity to environmental/system mismatch, introducing biased estimates at high SNR. In this paper, some theoretical developments on matched-field performance analysis are summarized, including Bayesian performance bounds and probabilistic ambiguity analysis, both incorporating environmental/system uncertainty/mismatch. Performance analysis is then implemented for source localization in a typical shallow water environment chosen from the Shallow Water Evaluation Cell Experiments (SWellEX). The performance predictions describe the simulations of the maximum-likelihood estimator (MLE) well, including the mean-square error (MSE) in all SNR regions as well as the bias at high SNR. The threshold SNR and bias predictions are also validated through SWellEX experimental data processing. The results suggest the current environmental, acoustic, and statistical modeling has developed to such a level that the optimum theoretical matched-field performance can be achieved in a well-controlled experiment.     

3D hydrodynamic modelling of fixed oscillating water column wave power plant by a boundary element methods

A three-dimensional (3D) numerical model of fixed Oscillating Water Column system (OWC) is presented and validated. The steady-state potential flow boundary value problem due to regular wave interaction with the OWC is solved by a first order mixed distribution panel method. Ocean response predictions are derived using a deterministic statistical model based on a spectral analysis method. The model validation focusses on diffraction predictions and involves convergence tests and numerical comparisons with independent potential flow computations. Predictions of both regular and irregular wave responses are also compared against experimental results. Sample results including the yearly-averaged power conversion efficiency are presented in the final section to illustrate the method’s suitability to a 3D hydrodynamic design optimisation.     

TOPEX卫星高度计有效波高数据分析与极值统计预报

利用 TOPEX卫星高度计测量的有效波高资料 ,对中国近海 9个海域进行卫星高度计的 C,Ku两波段测量值的比较分析与处理 ,得出合理的有效波高数值。利用三参数 Weibull分布 ,以渤海海域、上海附近海域和南海东部海域作为特定区进行有效波高的极值统计预报 ,并进行了统计分析     

The Hogarth initiative on the future of the International Whaling Commission

Dr Bill Hogarth of the USA was the Chairman of the International Whaling Commission from 2006 to 2009. In a typical masterpiece of understatement, at the beginning of his term, he launched an initiative to reform the IWC with the words “it would be useful for the Commission to have a general discussion concerning the future of the IWC, given…the number of issues for which polarisation rather than consensus appears to be the norm”. This paper follows his initiative through three annual, and two intersessional meetings of the IWC, commenting on the major issues and events as well as the actions of the main players. It concludes with an analysis of the results of the initiative, and makes some predictions for the future of the IWC.     

Case studies of ERS-1 altimeter data applicating in China Sea

1 IwrRODUcrIONAn initial field of wave height in a computing domain is needed fOr integration ofnumerical wave model. Because real time. observation ocean data are scarce, now most ofinitial fields of ocean wave is produced by either reckoning wind fields or preceding 24hour prediction results. It is possible to form an initiaI field of ocean wave along with the..increasing satellite data, ship report and buoy data. Some of research works have beendone abroad (Janssen et a1, l989; LionelI…