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.     

Assimilation of the data of observations and adaptive prediction of the natural processes

We propose a dynamical model for the prediction of random components of natural processes. The model is based on the system concept of adaptive balance of causes (ABC-model) and contains dynamic equations for the coefficients of influence adapted to the correlations existing in the predicted processes. To improve the accuracy of predictions, we consider two possible schemes of assimilation of the data of observations in the equations of the ABC-model, namely, the Kolmogorov and Kalman schemes. Both schemes are oriented toward the application of sample correlation coefficients for the prediction of time series of measurements and, hence, take into account the nonstationarity of actual natural processes. We present some examples of prediction of the simulated time series clarifying the algorithms of assimilation of the data of observations. A conclusion is made that the methods of systems modeling and adaptive prediction of random processes by the ABC-method are quite promising.     

On model validation for meso/submesoscale currents: Metrics and application to ROMS off Central California

ROMS with horizontal grid spacing of 3.5 km for the region off Central California was compared to RAFOS float observations and satellite altimetry on meso/submesoscales. The approach introduced and used two new metrics for model-data comparison, as well as suggested how to calculate these metrics for different spatio-temporal scales. The first metric consisted of the first two moments of exit time and was used to compare ROMS against RAFOS float observations at mid-depths (between 300 m and 350 m). Exit time is the time a float launched at a point takes to leave a domain for the first time. The second metric was spectral entropy and was used to estimate how well ROMS reproduced variability of the sea surface height (SSH) anomaly field extracted from an AVISO data set (1992–2007) for specified temporal and spatial scales. Calculations showed that ROMS reproduced the mid-depth mesoscale/submesoscale currents next to the coast in a very accurate manner (low-order exit time statistics of floats were reproduced by ROMS with an accuracy better than 95%); but ROMS overestimated the speed of westward drift of floats by as much as 20–30% at distances greater than 350 km from the coastline. ROMS predicted the variability of the mesoscale (100–400 km) SSH anomaly field for temporal scales of 1–12 months with a reasonable accuracy. A wavelet transform modulus maxima technique applied to the spectral entropy of SSH anomaly also demonstrated good agreement between ROMS and satellite altimetry for mesoscales characterized by singular exponents and multi-fractal spectra for 1–12 month time scales.     

Empirical tools for simulating salinity in the estuaries in Everglades National Park,Florida

Salinity in a shallow estuary is affected by upland freshwater inputs (surface runoff, stream/canal flows, groundwater), atmospheric processes (precipitation, evaporation), marine connectivity, and wind patterns. In Everglades National Park (ENP) in South Florida, the unique Everglades ecosystem exists as an interconnected system of fresh, brackish, and salt water marshes, mangroves, and open water. For this effort a coastal aquifer conceptual model of the Everglades hydrologic system was used with traditional correlation and regression hydrologic techniques to create a series of multiple linear regression (MLR) salinity models from observed hydrologic, marine, and weather data. The 37 ENP MLR salinity models cover most of the estuarine areas of ENP and produce daily salinity simulations that are capable of estimating 65–80% of the daily variability in salinity depending upon the model. The Root Mean Squared Error is typically about 2–4 salinity units, and there is little bias in the predictions. However, the absolute error of a model prediction in the nearshore embayments and the mangrove zone of Florida Bay may be relatively large for a particular daily simulation during the seasonal transitions. Comparisons show that the models group regionally by similar independent variables and salinity regimes. The MLR salinity models have approximately the same expected range of simulation accuracy and error as higher spatial resolution salinity models.     

High resolution downscaled ocean waves (DOW) reanalysis in coastal areas

Large-scale wave reanalysis databases (0.1°–1° spatial resolution) provide valuable information for wave climate research and ocean applications which require long-term time series (> 20 years) of hourly sea state parameters. However, coastal studies need a more detailed spatial resolution (50–500 m) including wave transformation processes in shallow waters. This specific problem, called downscaling, is usually solved applying a dynamical approach by means of numerical wave propagation models requiring a high computational time effort. Besides, the use of atmospheric reanalysis and wave generation and propagation numerical models introduce some uncertainties and errors that must be dealt with. In this work, we present a global framework to downscale wave reanalysis to coastal areas, taking into account the correction of open sea significant wave height (directional calibration) and drastically reducing the CPU time effort (about 1000 ×) by using a hybrid methodology which combines numerical models (dynamical downscaling) and mathematical tools (statistical downscaling). The spatial wave variability along the boundaries of the propagation domain and the simultaneous wind fields are taking into account in the numerical propagations to performance similarly to the dynamical downscaling approach. The principal component analysis is applied to the model forcings to reduce the data dimension simplifying the selection of a subset of numerical simulations and the definition of the wave transfer function which incorporates the dependency of the wave spatial variability and the non-uniform wind forcings. The methodology has been tested in a case study on the northern coast of Spain and validated using shallow water buoys, confirming a good reproduction of the hourly time series structure and the different statistical parameters.     

利用卫星测高、GRACE和GOCE资料估计全球海洋表面地转流

重力恢复和气候试验GRACE(gravity recovery and climate experiment)卫星极大地提高了地球重力场的精度和分辨率,特别是中长波分量,联合卫星测高数据可获得全球海洋表面大尺度洋流循环。另外,新一代地球重力和海洋环流探测卫星GOCE(gravity field and steady-state ocean circulation explorer)于2009年3月成功发射,采用卫星重力梯度测量原理,对重力场的高频部分非常敏感,使其高分辨率监测全球海洋循环成为可能。本文利用1~7年GRACE观测数据确定的重力场模型和18个月GOCE观测数据确定的地球重力场模型GO_CONS_GCF_2_TIM_R3,联合卫星测高确定的平均海面高模型MSS_CNES_CLS_11,分别估计全球海洋表面地转流,并且与实测浮标数据结果进行比较。分析表明GOCE重力卫星确定的重力场模型具有更高的空间分辨率,能够确定高精度和高空间分辨率的全球海洋地转流,如墨西哥湾暖流的细节和特征,并且与实测浮标结果基本一致。而基于1~4年GRACE观测资料的模型不能很好估计全球地转流特征,基于7年GRACE观测资料的重力场模型ITG-Grace2010s确定的全球地转流的精度仍低于18个月GOCE观测数据确定的地球重力场模型GO_CONS_GCF_2_TIM_R3的结果,估计的全球地转流仍含有较大的噪声,不能很好地反应中小尺度地转流细节特征。并计算ITG_Grace2010s和GOCE_TIM3的稳态海面地形和全球平均地转流的内符合精度,结果显示,在全球范围内,GOCE_TIM3的稳态海面地形和全球平均地转流的精度都比ITG_Grace2010s结果的精度有着很大的改善,其中ITG_Grace2010s的稳态海面地形的精度为21.6cm,而GOCE_TIM3的结果则为7.45cm,ITG_Grace2010s的全球平均地转流的精度为40.7cm/s,而GOCE_TIM3的结果则为19.6cm/s。     

An evaluation of two alongshore transport equations with field measurements

The performance of two well-known equations to predict the depth-averaged alongshore suspended sediment flux [Van Rijn, L.C., 1984. Sediment transport, part II: suspended load transport. Journal of Hydraulic Engineering 110, 1613–1641; and Bailard, J.A., 1981. An energetics total load sediment transport model for a plane sloping beach. Journal of Geophysical Research 86, 10938–10954] was assessed by comparing predictions with 2306 field estimates based on a vertical stack of three optical backscatter sensors and a single electromagnetic flow meter. The observations were collected at four cross-shore positions on the intertidal beach of Egmond aan Zee, the Netherlands, during calm to storm conditions, with the offshore significant wave height peaking at 3.7 m. Measured hydrodynamics were employed in the computations of both models. Also, default parameter values were used without calibration to the data. We found that both models underpredicted the observations. Overall, the Van Rijn model outperformed the Bailard model, with about 70% of the model prediction lying between 1/5 to 5 of the observations under energetic conditions. For the Bailard model this was only about 20%. The performance of the Van Rijn model is, however, sensitive to the wave-related roughness, one of its highly uncertain free parameters. This may allow for an easy calibration when estimates of the depth-averaged alongshore sediment flux are available but may lead to serious errors in situations without data to constrain the predictions. We suspect that the discrepancy between the observations and model predictions is due to an overestimation of the observed fluxes (high turbidity, air bubbles) and an underestimation of the modeled fluxes because of missing physics related primarily to breaking waves.     

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...     

The mesoscale variability in the Caribbean Sea. Part I: Simulations and characteristics with an embedded model

The variability in the Caribbean Sea is investigated using high resolution (1/15°) general circulation model experiments. For the first time in this region, simulations were carried out with a 2-way nested configuration of the NEMO primitive equation model. A coarse North Atlantic grid (1/3°) reproduces the main features of the North Atlantic and Equatorial circulation capable of influencing ocean dynamics in the Caribbean Sea. This numerical study highlights strong dynamical differences among basins and modifies the view that dynamics are homogeneous over the whole Caribbean Basin. The Caribbean mean flow is shown to organize in two intense jets flowing westward along the northern and southern boundaries of the Venezuela Basin, which merge in the center of the Colombia Basin. Diagnostics of model outputs show that width, depth and strength of baroclinic eddies increase westward from the Lesser Antilles to the Colombia Basin. The widening and strengthening to the west is consistent with altimetry data and drifter observations. Although influenced by the circulation in the Colombia Basin, the variability in the Cayman Basin (which also presents a westward growth from the Chibcha Channel) is deeper and less energetic than the variability in the Colombia/Venezuela Basins. Main frequency peaks for the mesoscale variability present a westward shift, from roughly 50 days near the Lesser Antilles to 100 days in the Cayman Basin, which is associated with growth and merging of eddies.     

黑潮延续体温盐锋的时空变化特征及其声场的初步分析

通过对WOA13多年(1955—2012年)季节平均数据的分析,利用绝对梯度最大值连线的方法,得到日本东海岸黑潮延续体温盐锋轴的空间信息,对锋轴线上的锋强度的季节变化特征进行了分析,并利用BELLHOP模型初步讨论了锋区内的声场特点。认为黑潮延续体锋轴线的位置随深度增加逐渐南移,其温盐强度随季节随深度都有明显变化,1—3月份混合层现象明显,此时水下声道受到声源深度的影响明显。     

Longwaves and primary productivity variations in the equatorial pacific at 0°, 140dgW

High temporal resolution measurements of physical and bio-optical variables were made in the upper ocean using a mooring located at 0°, 140°W from 9 February 1992 to 15 March 1993 as part of the equatorial Pacific Ocean (EgPac) study. Chlorophyll and primary productivity time-series records were generated using the mooring data. Primary productivity varied by about 50% around the mean on time scales of weeks and by over a factor of four within our observational period. The mooring observations encompassed both El Niho and cool conditions. Kelvin waves were evident during the El Nifio phase, and tropical instability waves (TIWs) were dominant during the cool phase. The two extreme conditions also were observed concurrently with complementary ship-based measurements. In addition, bio-optical drifters provided simultaneous spatial data concerning net phytoplankton growth rates during passage of a TIW. The collective data sets have been used to examine the causes of the observed variability in phytoplankton biomass and productivity. Our joint results and analyses appear to support the hypothesis that the vertical transport of iron into the upper layer and primary production rates are modulated by variability of the depth of the Equatorial Undercurrent and by equatorial longwaves. In particular, our results are consonant with the suggestion of Barber et al. (1996) that passage of a TIW may be considered to be a natural analog of a small iron enrichment experiment. Predicting primary productivity and, thus, carbon flux in the equatorial Pacific requires continuous, long-term observations of a few physical, biological, and optical properties that can be used to parameterize the biological variability.     

Diagnostic analysis of the 3D ageostrophic circulation from a multivariate spatial interpolation of CTD and ADCP data

A multivariate (MV) optimal statistical interpolation method is applied to conductivity–temperature–depth (CTD) and ship-mounted acoustic doppler current profiler (ADCP) data from quasi-synoptic oceanographic surveys. MV analysis aims to improve the spatial interpolation of any particular variable (e.g., dynamic height) by including in the analysis observations of other physically related variables (e.g., current). The version used in this work also provides estimates of the non-divergent and irrotational components of the flow. The method is tested in a sharp frontal region to the north of the Western Alborán gyre. After deriving the optimal analysis parameters, we first show that MV statistical dynamic height analysis errors are significantly smaller than those derived from univariate (UV) analysis. In our region, this translates in a more realistic shape for the geostrophic relative vorticity and the vertical velocity field. The latter peaks at about 45 m/day (as given by the quasi-geostrophic omega equation), with a tendency for light water to be upwelled upstream of the gyre while denser water is downwelled downstream of the gyre. For the horizontal velocity we show the existence of large (up to 40 cm/s) ageostrophic velocities. These are mainly non-divergent and can be explained by the cyclostrophic acceleration induced by the anticyclonic gyre. The irrotational velocity component is of the order of 10 cm/s towards the dense side of the front. The robustness of the method is checked by means of several tests that evaluate the sensitivity of results with respect to the synopticity of the data, the analysis parameters, the reference level and the presence of tidal or inertial currents.     

Multi-scale variability of beach profiles at Duck: A wavelet analysis

Beach profiles have been observed to change over a range of spatial and temporal scales; however techniques for quantifying this variability have not been fully established. In this paper, a wavelet technique is introduced as a method to study the multi-scale variability of beach profiles. The beach profile data comprising a 22-year time series surveyed at the US Army Corps of Civil Engineers Field Research Facility (FRF) at Duck are analysed using the adapted maximal overlap discrete wavelet transform (AMODWT). The analysis successfully identifies strong local features in the variability of beach profiles in time and space separately that cannot be isolated by traditional statistical methods. The analysis of spatial wavelet variances provides a new means of investigating the depth of closure. Analysis of variances by temporal scales shows that the combined effects of several temporal scales with one or two dominant scales can be seen at particular points across profiles whilst the dominant temporal scales are different at different portions of the profiles. The method allows for the extremely nonstationary behaviour of beach profile to be analysed into separate frequency bands that can facilitate the interpretation of morphological changes in terms of physical processes.     

Accuracy Evaluation of A Diagnostic Test by Detecting Outliers and Influential Observations

Logit regression analysis is widely applied in scientific studies and laboratory experiments, where skewed observations on a data set are often encountered. A number of problems with this method, for example, oudiers and influential observations, can cause overdispersion when a model is fitted. In this study a systematic statistical approach, including the plotting of several indices is used to diagnose the lack-of-fit of a logistic regression model. The outliers and influential observations on data from laboratory experiments are then detected. Specifically we take account of the interaction of an internal sohtary wave （ISW） with an obstacle, i.e., an underwater ridge, and also analyze the effects of the ridge height, the lower layer water depth, and the potential energy on the amplitude-based transmission rate of the ISW. As concluded, the goodness-of-fit of the revised logit regression model is better than that of the model without this approach.     

A comparison of sequential assimilation schemes for ocean prediction with the HYbrid Coordinate Ocean Model (HYCOM): Twin experiments with static forecast error covariances

We assess and compare four sequential data assimilation methods developed for HYCOM in an identical twin experiment framework. The methods considered are Multi-variate Optimal Interpolation (MVOI), Ensemble Optimal Interpolation (EnOI), the fixed basis version of the Singular Evolutive Extended Kalman Filter (SEEK) and the Ensemble Reduced Order Information Filter (EnROIF). All methods can be classified as statistical interpolation but differ mainly in how the forecast error covariances are modeled. Surface elevation and temperature data sampled from an 1/12° Gulf of Mexico HYCOM simulation designated as the truth are assimilated into an identical model starting from an erroneous initial state, and convergence of assimilative runs towards the truth is tracked. Sensitivity experiments are first performed to evaluate the impact of practical implementation choices such as the state vector structure, initialization procedures, correlation scales, covariance rank and details of handling multivariate datasets, and to identify an effective configuration for each assimilation method. The performance of the methods are then compared by examining the relative convergence of the assimilative runs towards the truth. All four methods show good skill and are able to enhance consistency between the assimilative and truth runs in both observed and unobserved model variables. Prediction errors in observed variables are typically less than the errors specified for the observations, and the differences between the assimilated products are small compared to the observation errors. For unobserved variables, RMS errors are reduced by 50% relative to a non-assimilative run and differ between schemes on average by about 5%. Dynamical consistency between the updated state space variables in the data assimilation algorithm, and the data adequately sampling significant dynamical features are the two crucial components for reliable predictions. The experiments presented here suggest that practical implementation details can have at least as much an impact on the accuracy of the assimilated product as the choice of assimilation technique itself. We also present a discussion of the numerical implementation and the computational requirements for the use of these methods in large scale applications.     

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.     

Wave model predictions in the Black Sea: Sensitivity to wind fields

This paper evaluates the impact of using different wind field products on the performance of the third generation wave model SWAN in the Black Sea and its capability for predicting both normal and extreme wave conditions during 1996. Wind data were obtained from NCEP CFSR, NASA MERRA, JRA-25, ECMWF Operational, ECMWF ERA40, and ECMWF ERA-Interim. Wave data were obtained in 1996 at three locations in the Black Sea within the NATO TU-WAVES project. The quality of wind fields was assessed by comparing them with satellite data. These wind data were used as forcing fields for the generation of wind waves. Time series of predicted significant wave height (H_mo), mean wave period (T_m02), and mean wave direction (DIR) were compared with observations at three offshore buoys in the Black Sea and its performance was quantified in terms of statistical parameters. In addition, wave model performance in terms of significant wave height was also assessed by comparing them against satellite data.The main scope of this work is the impact of the different available wind field products on the wave hindcast performance. In addition, the sensitivity of wave model forecasts due to variations in spatial and temporal resolutions of the wind field products was investigated. Finally, the impact of using various wind field products on predicting extreme wave events was analyzed by focussing on storm peaks and on an individual storm event in October 1996. The numerical results revealed that the CFSR winds are more suitable in comparison with the others for modelling both normal and extreme events in the Black Sea. The results also show that wave model output is critically sensitive to the choice of the wind field product, such that the quality of the wind fields is reflected in the quality of the wave predictions. A finer wind spatial resolution leads to an improvement of the wave model predictions, while a finer temporal resolution in the wind fields generally does not significantly improve agreement between observed and simulated wave data.     

Comparisons of high-frequency acoustic fluctuations with ocean-temperature and sea-surface fluctuations in shallow water

Dynamic ocean processes produce small thermal variations that induce spatial and temporal variability in the ocean's index of refraction and in the spatial scale along an acoustic propagation path. This paper reports measurements and analysis of thermal microstructure effects on ping-to-ping amplitude and phase variability of shallow-water direct-path acoustic propagation in the 20-200 kHz frequency range. These measurements were conducted during a joint experiment conducted by the Naval Research Laboratory and the North Atlantic Treaty Organization Supreme Allied Commander Atlantic (SACLANT) Undersea Research Centre, La Spezia, Italy, in 8 m of water off American Beach, located between Pisa and Livorno, Italy. Experimental observations are compared with predictions for isotropic and anisotropic turbulence, as well as for sea-surface swell. Measured phase and log-amplitude variances coincide with predictions and are relatively insensitive to weak water-column stability. The sea-surface swell dominates phase variances for this data and turbulence dominates log-amplitude variances. These results provide a reasonable lower limit on high-frequency ping-to-ping amplitude and on phase variability produced by benign shallow-water thermal fluctuations.     

Exploring LiDAR data for mapping the micro-topography and tidal hydro-dynamics of mangrove systems: An example from southeast Queensland,Australia

The aim was to explore the use of Light Detection and Ranging (LiDAR) data to map the micro-topography of an intertidal wetland in southeast Queensland Australia. The driver for this was the need to identify and map the habitats of the immature stages of an aedine disease vector mosquito (Aedes vigilax (Skuse)). We derived a high resolution digital elevation model (DEM) data set at a vertical resolution of 0.05 m from LiDAR data. The relative accuracy of the DEM across the site was tested by comparing water depth predictions derived from the DEM against in-situ water depth readings from pressure sensors over a 10-day tidal cycle, which included high spring tides. We found that the field observations of micro-topographic units important for mosquito management matched those delineated from the DEM. The micro-topography included a low berm or central ridge that was more or less continuous across the site, a shallow back basin and fringing mangroves. The fringing mangroves had unimpeded connection to the tidal source, however the central ridge blocked tidal water from the back basin for all but the highest tides. Eggshell survey indicated that the back basin was the area suitable for immature mosquitoes. We conclude that LiDAR data has application for understanding and mapping the structure of mangrove wetlands. We have also demonstrated (in a small area) that LiDAR is useful for modelling the effect of sea level changes on the coastal fringe. LiDAR may be the only method to inform research on changes to land use and ecosystems caused by sea level change.