About the seasonal variability of the Alboran Sea circulation

Data from a mooring line deployed midway between the Alboran Island and Cape Tres Forcas are used to study the time variability of the Alboran Sea from May 1997 to May 1998. The upper layer salinity and zonal velocity present annual and semiannual cycles characterised by a minimum in spring and autumn and a maximum in summer and winter. Temperature has the opposite behaviour to that of salinity indicating changes in the presence of the Atlantic water within the Alboran Passage. A large set of SST images is used to study these cycles. The decrease of salinity and velocity in our mooring location in spring and autumn seems to be related to the eastward drifting of the Western Alboran Gyre (WAG). The increase of salinity and velocity is caused by the Atlantic current flowing south of the Alboran Island and its associated thermohaline front. Conductivity–temperature–depth (CTD) data from two cruises along the 3°W are coherent with current meters and SST interpretations.During the period analysed, summer months are characterised by the stability of the two-gyre system, while in winter, the circulation is characterised by a coastal jet flowing close to the African shore. We use sea level differences across the Strait of Gibraltar for studying the variability of the Atlantic inflow. We discuss the changes in the Alboran Sea circulation and its relation with the variability of the inertial radius of the Atlantic inflow. Though our results are speculative, we find a possible relation between the disappearance of the two-gyre system and a reversal of the circulation in Gibraltar. Longer time series are needed to conclude, but comparison with previous works makes us think that the seasonal cycle described from May 1997 to May 1998 could be the most likely one for the Alboran Sea upper layer.     

Forecasting front displacements with a satellite based ocean forecasting (SOFT) system

Relatively long term time series of satellite data are nowadays available. These spatio–temporal time series of satellite observations can be employed to build empirical models, called satellite based ocean forecasting (SOFT) systems, to forecast certain aspects of future ocean states. The forecast skill of SOFT systems predicting the sea surface temperature (SST) at sub-basin spatial scale (from hundreds to thousand kilometres), has been extensively explored in previous works. Thus, these works were mostly focussed on predicting large scale patterns spatially stationary. At spatial scales smaller than sub-basin (from tens to hundred kilometres), spatio–temporal variability is more complex and propagating structures are frequently present. In this case, traditional SOFT systems based on Empirical Orthogonal Function (EOF) decompositions could not be optimal prediction systems. Instead, SOFT systems based on Complex Empirical Orthogonal Functions (CEOFs) are, a priori, better candidates to resolve these cases.In this work we study and compare the performance of an EOF and CEOF based SOFT systems forecasting the SST at weekly time scales of a propagating mesoscale structure. The SOFT system was implemented in an area of the Northern Balearic Sea (Western Mediterranean Sea) where a moving frontal structure is recurrently observed. Predictions from both SOFT systems are compared with observations and with the predictions obtained from persistence models. Results indicate that the implemented SOFT systems are superior in terms of predictability to persistence. No substantial differences have been found between the EOF and CEOF-SOFT systems.     

Particle fluxes in the Almeria-Oran Front: control by coastal upwelling and sea surface circulation

Particle flux data were obtained from one instrumented array moored under the direct influence of the Almeria-Oran Front (AOF) in the Eastern Alboran Sea, Western Mediterranean Sea, within the frame of the “Mediterranean Targeted Project II-MAss Transfer and Ecosystem Response” (MTPII-MATER) EU-funded research project. The mooring line was deployed from July 1997 to May 1998, and was equipped with three sequential sampling sediment trap-current meter pairs at 645, 1170 and 2210 m (30 m above the seafloor). The settling material was analysed to obtain total mass, organic carbon, opal, calcium carbonate and lithogenic fluxes. Qualitative analyses of SST and SeaWiFS images allowed monitoring the location and development of the Western and Eastern Alboran Sea gyres and associated frontal systems to determine their influence on particle fluxes.Particle flux time series obtained at the three depths showed a downward decrease of the time-weighed total mass flux annual means, thus illustrating the role of pelagic particle settling. The total mass flux was dominated by the lithogenic fraction followed by calcium carbonate, opal and organic carbon. The time series at the various depths were rather similar, with two strong synchronous biogenic peaks (up to 98 mg m⁻² day⁻¹ of organic carbon and 156 mg m⁻² day⁻¹ of opal) recorded in July 1997 and May 1998. Through comparing the fluctuations of the lithogenic and calcium carbonate-rich fluxes with the biogenic flux, we observed that the non-biogenic fluxes remained roughly constant, while the biogenic flux responded strongly to seasonal variations throughout the water column.Overall, the temporal variability of particle fluxes appeared to be linked to the evolution of several tens of kilometres in length sea surface hydrological structures and circulation of the Alboran Sea. Periodic southeastward advective displacements of waters from upwelling events off the southern Spanish coast were observed on SST and SeaWiFS images. In between these periods, widespread phytoplankton blooms were observed. The influence of the varying surface structures resulted in changes in the biogenic particle flux. For example, we observed an opal pulse in April 1998 that resulted from a diatom-rich highly productive frontal surface situation above the mooring line.Estimation of the annual organic carbon export and calculation of a seasonality index indicate that the overall dynamics of the carbon reservoir within the Eastern Alboran Sea appears to be strongly influenced by the sea surface hydrological structures.     

Assessment of sea surface temperature observational networks in the Baltic Sea and North Sea

The satellite and in situ Sea Surface Temperature (SST) observational networks in the Baltic Sea and North Sea are evaluated based on the quality of the gridded SST products generated from the networks. A multi-indicator approach is applied in the assessment. It includes evaluation of data quality, effective data coverage, field reconstruction error and model nowcast error. The results show that the best available full-coverage SST product is generated by assimilating the SST observations to obtain a yearly mean model bias of 0.07 °C and RMSE of 0.64 °C. The effective data coverage rate is 31% by using AVHRR (Advanced Very High Resolution Radiometer) data from NOAA (National Ocean and Atmosphere Administration) satellites 12, 14 and 16. The data redundancy increases rapidly with the number of infrared sensors. Using either NOAA satellite 12 or all 3 satellites makes a small difference with regard to derived effective coverage and the ocean model nowcast error. The influence of using the in situ SST observations in the SST field reconstruction is negligibly small. Instead, the major role of in situ SST observations is in calibrating the satellite observations. To study the relative importance of data quality and data coverage, an assessment is done for two satellite products: one product is based entirely on NOAA 12 data and has larger coverage but lower quality. The other product is a subset of the SAF products (derived from NOAA 14 and 16) and has lower coverage but higher quality. Based on current monitoring, modelling and assimilation technology, the results suggest that the data quality is an important factor in further improving the quality of the gridded SST products. Recommendations are made for possible further improvements of the existing SST observational networks.     

Multigrid state vector for data assimilation in a two-way nested model of the Ligurian Sea

A system of two nested models composed by a coarse resolution model of the Mediterranean Sea, an intermediate resolution model of the Provençal Basin and a high resolution model of the Ligurian Sea is coupled with a Kalman-filter based assimilation method. The state vector for the data assimilation is composed by the temperature, salinity and elevation of the three models. The forecast error is estimated by an ensemble run of 200 members by perturbing initial condition and atmospheric forcings. The 50 dominant empirical orthogonal functions (EOF) are taken as the error covariance of the model forecast. This error covariance is assumed to be constant in time. Sea surface temperature (SST) and sea surface height (SSH) are assimilated in this system.     

Data assimilation into a Princeton Ocean Model of the Mediterranean Sea using advanced Kalman filters

This study investigates the effectiveness of the Singular Evolutive Extended Kalman filter (SEEK) and its variants (SEIK and SFEK filters) for data assimilation into a Princeton Ocean Model (POM) of the Mediterranean Sea. The SEEK filters are sub-optimal Kalman filters based on the approximation of the filter's error covariance matrices by singular low-rank matrices, reducing in this way extensive computational burden. At the initialization, the filters error covariance matrix is parameterized by a set of multivariate empirical orthogonal functions (EOFs) which describe the dominant modes of the system's variability. The Mediterranean model is implemented on a 1/4° × 1/4° horizontal grid with 25 sigma levels and is forced with 6-hour ECMWF re-analysis atmospheric data. Several twin experiments, in which pseudo-observations of altimetric data and/or data profiles were assimilated, were first performed to evaluate the filters performances and to study their sensitivities to different parameters and setups. The results of these experiments were very encouraging and helped in setting up an effective configuration for the assimilation of real data in near-real time situation. In the hindcast experiments, Topex/Poseidon and ERS weekly sea level anomaly data were first assimilated during 1993 and the filters solution was evaluated against independent Reynolds sea surface temperature (SST) analysis. The assimilation system was able to significantly enhance the consistency between the model and the assimilated data, although the improvement with respect to independent SST data was significantly less pronounced. The model SST was only improved after including SST data in the assimilation system.     

Forecast verification of a 3D model of the Mediterranean Sea. The use of discrete wavelet transforms and EOFs in the skill assessment of spatial forecasts

The quality assessment of a nested model system of the Mediterranean Sea is realised. The model has two zooms in the Provençal Basin and in the Ligurian Sea, realised with a two-way nesting approach. The experiment lasts for nine weeks, and at each week sea surface temperature (SST) and sea level anomaly are assimilated. The quality assessment of the surface temperature is done in a spatio-temporal approach, to take into account the high complexity of the SST distribution. We focus on the multi-scale nature of oceanic processes using two powerful tools for spatio-temporal analysis, wavelets and Empirical Orthogonal Functions (EOFs). We apply two-dimensional wavelets to decompose the high-resolution model and observed SST into different spatial scales. The Ligurian Sea model results are compared to observations at each of those spatial scales, with special attention on how the assimilation affects the model behaviour. We also use EOFs to assess the similarities between the Mediterranean Sea model and the observed SST. The results show that the assimilation mainly affects the model large-scale features, whereas the small scales show little or no improvement and sometimes, even a decrease in their skill. The multiresolution analysis reveals the connection between large- and small-scale errors, and how the choice of the maximum correlation length of the assimilation scheme affects the distribution of the model error among the different spatial scales.     

Upwelling mechanisms in the northwestern Alboran Sea

From April 1996 to July 1997, a series of hydrographic surveys were carried out in the Northwestern part of the Alboran Sea to investigate the upwelling that is an almost permanent feature in this area. Simultaneously a mooring line was deployed in the north part of the eastern section of the Strait of Gibraltar to monitor the variability of the Atlantic Jet (AJ). Two mechanisms are shown to be relevant for the upwelling dynamic in the region: the southward drifting of the AJ and wind stress. A linear relation between the angle under which the Jet enters the Alboran Sea and the distance from the coastline to the front associated with the Jet has been found. This angle that has been estimated from the low passed time series of current velocity measured by the uppermost instrument of the moored line has been then used to identify the onshore–offshore excursions of the Jet. Both upwelling mechanisms are identified from hydrographic data, because each of them has associated a different type of water mass, and they take place in different locations. Wind-driven upwelling dominates in coastal zones, on the shelf, while upwelling associated with southward drifting of the AJ prevails further offshore. The amount of sub-surface water brought up to the surface by each one is of the same order. However, wind-driven upwelling contributes to the fertilization of this region in a major extent because water upwelled by wind is richer in nutrient concentration.     

Apparent phytoplankton bloom due to island mass effect

A continuous monitoring of temperature and chlorophyll-a (Chl-a) concentration from a surface water monitoring system and a towed free fall instrument (MVP) around a small island in the Kuroshio showed low sea surface temperature (SST) and high surface Chl-a concentration (SCC) distribution in the lee of the island that indicates typical “island mass effect” phenomena. When the observed Chl-a profiles (0 to 250 m) were integrated, the total amounts in the lee side data were slightly smaller than those of the upstream side of the island. The difference was statistically significant at the 95% confidence level. The cross section diagram of Chl-a indicated the diffusion of subsurface Chl-a maximum (SCM) from the upstream to the downstream flanks of the island. The diffusivity of SCM and the change of potential energy require the same level of strong turbulent dissipation rate at the flanks of the island. That is consistent with our previous direct measurement in a similar hydrodynamic condition. Therefore, the observed high SCC is due to turbulent diffusion of SCM, and clearly showed that high SCC does not require any new production. Although a high fluorescence field behind an isolated island in a strong flow is often visible from satellite images, the images do not necessarily indicate an enhanced primary production at that moment.     

渡船螺旋桨水动力性能的数值预报

采用计算流体力学（CFD）方法对某渡船螺旋桨的水动力性能进行数值预报.先用DTMB P5168桨验证数值模型和方法的准确性与可信性,数值计算其推力系数、力矩系数和敞水效率.整个计算域网格划分均采用全六面体形式,分别采用三种湍流模型进行计算.计算结果与实验的比较表明,SST模型和雷诺应力模型有近乎相同的计算精度,但SST模型的计算速度更快;推力系数误差最大5.8%,力矩系数误差最大为1.7%,敞水效率误差最大为4.3%.然后,将此方法运用到渡船螺旋桨,通过对渡船螺旋桨的网格灵敏度、尺度作用以及相关的流场分析,证明该方法能实现对螺旋桨敞水粘性流场的模拟,以及其敞水性能的预报.     

基于人工神经网络的胶州湾浮游植物生物量模拟

文章首先介绍了BP网络数据标准化、隐层神经元选择、网络训练和有效性检验方法。以2003年胶州湾环境监测资料为基础,建立了多输入单输出的3层BP人工神经网络模型,采用8个水环境因子预测浮游植物生物量(Chla浓度)。检测集样本网络预测值与观测值的相关系数为0.8943,平均绝对误差为11.33%。为避免个别网络输入初值对输出的干扰,采取全局灵敏度的方法,分析了各水环境因子变化对浮游植物生物量的相对影响。结果表明,浮游植物生物量对各水环境因子变化响应的敏感系数顺序为DOCODPO4-PSSTpHOilDINSiO3-Si。     

Air–sea CO2 fluxes in the Caribbean Sea from 2002–2004

Air–sea fluxes in the Caribbean Sea are presented based on measurements of partial pressure of CO₂ in surface seawater, pCO_2sw, from an automated system onboard the cruise ship Explorer of the Seas for 2002 through 2004. The pCO_2sw values are used to develop algorithms of pCO_2sw based on sea surface temperature (SST) and position. The algorithms are applied to assimilated SST data and remotely sensed winds on a 1° by 1° grid to estimate the fluxes on weekly timescales in the region. The positive relationship between pCO_2sw and SST is lower than the isochemical trend suggesting counteracting effects from biological processes. The relationship varies systematically with location with a stronger dependence further south. Furthermore, the southern area shows significantly lower pCO_2sw in the fall compared to the spring at the same SST, which is attributed to differences in salinity. The annual algorithms for the entire region show a slight trend between 2002 and 2004 suggesting an increase of pCO_2sw over time. This is in accord with the increasing pCO_2sw due the invasion of anthropogenic CO₂. The annual fluxes of CO₂ yield a net invasion of CO₂ to the ocean that ranges from − 0.04 to − 1.2 mol m^− 2 year^− 1 over the 3 years. There is a seasonal reversal in the direction of the flux with CO₂ entering into the ocean during the winter and an evasion during the summer. Year-to-year differences in flux are primarily caused by temperature anomalies in the late winter and spring period resulting in changes in invasion during these seasons. An analysis of pCO_2sw before and after hurricane Frances (September 4–6, 2004), and wind records during the storm suggest a large local enhancement of the flux but minimal influence on annual fluxes in the region.     

One-dimensional modelling of the plankton ecosystem of the north-western Corsican coastal area in relation to meteorological constraints

In order to study the influence of wind mixing on the spring variability of the plankton production of the north western Corsican coastal area, a one-dimensional (1D), vertical, coupled hydrodynamic/biological model (ECOHYDROMV) is used. A hydrodynamic 1D model of the water column with a k–l turbulent closure is applied. The biological model comprises six state variables, representing the plankton ecosystem in the spring period: phytoplankton, copepods, nitrate, ammonium, particulate organic matter of phytoplanktonic origin and particulate organic matter of zooplanktonic origin. The system is influenced by turbulence (expressed by the vertical eddy diffusivity), temperature and irradiance. The model takes into account momentum and heat surface fluxes computed from meteorological data in order to simulate a typical spring atmospheric forcing for the considered area. Results show that primary production vertical structure is characterised by a subsurface maximum which deepens with time and is regulated by the opposite gradients of nitrate concentration and irradiance. Surface plankton productivity is mainly controlled by turbulent vertical transport of nutrients into the mixed layer. The short time scale variability of turbulent mixing generated by the wind appears to be responsible for the plurimodal shape of plankton blooms, observed in the considered area. Furthermore, the model is applied to the study of the spring evolution of the plankton communities off the bay of Calvi (Corsica) for the years 1986 and 1988. In order to initiate and validate the model, time series of hydrological, chemical and biological data have been used. The model reproduces accurately the spring evolution of the phytoplankton biomass measured in situ and illustrates that its strong variability in those years was in close relation to the variability of the wind intensity.     

Quantitative estimation of the influence of surface thermal fronts over chlorophyll concentration at the Patagonian shelf

Eighteen-year (1985–2002) mean monthly SST Pathfinder data with 9 km spatial resolution have been used to estimate surface gradients by finite differences. Then the seasonal climatological means have been calculated from the intensity of these gradients, and surface thermal fronts present in the Patagonian Continental Shelf (PCS) have been located. Moreover, 6 years (1998–2003) of SeaWiFS data with approximately 4 km spatial resolution have been used to estimate monthly composite images of surface chlorophyll concentration, after which seasonal climatological means distributions have been generated. Both seasonal distributions have been analyzed together and by combining the knowledge of oceanographic processes and phytoplankton responses to light and nutrient availability, regions where the presence of a thermal front affects photosynthetic activity have been identified. Subjective criteria have been applied to define eighteen areas where phytoplankton biomass is influenced by the presence of a thermal front. In these areas, the surface chlorophyll (spatial mean and total), its relationship with the surface chlorophyll of the whole region, and the seasonal evolution of this relationship have been calculated. All frontal areas cover less than 15% of the total surface, but they contribute with over 23% of the phytoplankton annual mean biomass. Considered as a group, during summer they show high chlorophyll values very similar to those in spring. During the cold period, when the water column is vertically mixed in practically the whole of PCS, the influence of physical fronts over the biological production is minimum. The frontal zone image remains clearly defined during summer, when approximately 85% of the area will have a determined mean chlorophyll concentration, while the other 15% has a 2.45 times larger value. While three pattern trends have been identified in the frontal areas, only two of them condition the pattern of the group, due to their horizontal extension.     

Surface chlorophyll in the Black Sea over 1978–1986 derived from satellite and in situ data

Absolute values of chlorophyll a concentration and its spatial and seasonal variations in the Black Sea were assessed by using satellite CZCS and in situ data. Since the satellite CZCS had operated for the 1978–1986 period, CZCS data was used for assessing the past state of the Black Sea just before the onset of drastic changes observed in late 1980s. The approach used for the calculation of the absolute values of chlorophyll a concentration from CZCS data was based on the direct comparison of in situ chlorophyll a data and those of CZCS and by applying the algorithm developed for the transformation of CZCS data into chlorophyll a values. CZCS Level 2 data related with pigment concentration having a spatial resolution of 1 km at nadir were used. The daily Level 3 files were derived by binning Level 2 values into 4-km grid cells and the monthly and seasonal Level 3 files were created by averaging the daily Level 3 files over the corresponding period. In situ chlorophyll a data were obtained by spectrophotometric and fluorometric methods in 15 scientific cruises over the 1978–1986 period. Total number of ship-measured data used for the comparison with those CZCS values was 590.Chlorophyll a concentration (Chl) was derived from CZCS values (C) with regression equations Chl=kC; the coefficient of transformation k was calculated from six different data sets by taking into account distinctions between subregions and seasons. The reasons for difference in the k values have been analyzed.Statistical comparison of the chlorophyll a values measured in situ and those derived from CZCS data was based on log-transformed data and gave the following results: regression SLOPE=0.842, regression INTERCEPT=−0.081, coefficient of determination (R²)=0.806, root–mean–square ERROR=0.195. The mean monthly chlorophyll a distributions derived from CZCS data over 1978–1986 have been constructed and the mean seasonal chlorophyll a values in different regions have been calculated and analyzed. The significant difference in chlorophyll concentration between the western shelf regions and the open part of the Black Sea has been demonstrated, especially in warm season. At almost all seasons, the highest chlorophyll concentration is observed in the western interior shelf region which is under strong influence of Danube. The summer mean chlorophyll concentration in this region is 18 times higher than that in the open parts and about nine times higher than in the eastern shelf region. The greatest seasonal variations are observed in the open part of the Black Sea: chlorophyll concentration in cold season is four to six times higher than in summer and three to five times higher than in April and October. To the contrary, in the western interior shelf regions, the concentration is higher in May–October (about twice than that in November–March). Seasonal variations in the western outer shelf regions are smoothed out as compared with both the western interior shelf and the open regions.     

On the dense water spreading off the Ross Sea shelf (Southern Ocean)

In this study, current meter and hydrological data obtained during the X Italian Expedition in the Ross Sea (CLIMA Project) are analyzed. Our data show a nice agreement with previous data referring to the water masses present in this area and their dynamics. Here, they are used to further analyze the mixing and deepening processes of Deep Ice Shelf Water (DISW) over the northern shelf break of the Ross Sea. In more detail, our work is focused on the elementary mechanisms that are the most efficient in removing dense water from the shelf: either classical mixing effects or density currents that interact with some topographic irregularity in order to drop to deeper levels, or also the variability of the Antarctic Circumpolar Current (ACC) which, in its meandering, can push the dense water off the shelf, thus interrupting its geostrophic flow. We also discuss in detail the (partial) evidence of dramatic interactions of the dense water with bottom particulate, of geological or biological origin, thus generating impulsive or quasi-steady density-turbidity currents. This complex interaction allows one to consider bottom particular and dense water as a unique self-interacting system. In synthesis, this is a first tentative analysis of the effect of bottom particulate on the dense water dynamics in the Ross Sea.     

半潜式转运平台强度实测与分析

本文对半潜式转运平台的强度进行了实测，为了检验平台结构特性，进行了初始应力的测量，并结合对平台的有限元强度分析，对平台的极限承载能力进行了评估。     

Modelling of wave–current interactions at the mouths of the Danube

The target of the present study is the entrance to the Danube Delta in the Black Sea. The wave conditions in this coastal sector are usually significant from an energetic point of view and the relatively strong currents induced there by the outflow from the Danube lead to interactions between waves and currents. This process modifies considerably both the magnitude and direction waves, affecting also coastal navigation and sediment transport patterns. In order to assess the effects of the wave–current interactions, the simulating waves nearshore (SWAN) model was considered for developing a multilevel wave prediction system. Validations against measured data were carried out for each computational level. Five case studies corresponding to the most relevant patterns of the environmental matrix were analyzed. Finally, in order to assess the current effect for a longer timescale, an analysis concerning the variation of the main wave parameters was performed for a 3-month period considering some reference points. The results show that the currents produce considerable changes in the wave field, especially as regards the significant wave heights, mean wave directions and wavelengths. The Benjamin–Feir index was also estimated. The analysis of the variation induced by the current over this spectral shape parameter indicates that, in certain conditions, in the target area the wave heights cannot be considered Rayleigh distributed and freak waves may also occur.     

Validation of a hybrid optimal interpolation and Kalman filter scheme for sea surface temperature assimilation

A hybrid data assimilation scheme designed for operational assimilation of satellite sea surface temperatures (SST) into an ocean model has been developed and validated against in-situ observations. The scheme consists of an optimal interpolation (OI) part and a greatly simplified Kalman filter (KF) part.The OI is performed only in the longitudinal and latitudinal directions. A climatological field is used as a background field for the interpolation. It is constructed by fitting daily averages of satellite SST to the annual mean, annual, and semiannual harmonics in a 20 km by 20 km grid. The background error covariance is approximated by a spatially varying two-dimensional exponential covariance model. The parameters of the covariance model are fitted to the deviations of the satellite data from the background field using data from a full year.The simplified KF uses ocean model forecasts as a background field. It is based on the assumption that it is possible to neglect horizontal SST covariances in the filter and that the typical time scale for vertical mixing in the mixed layer is much shorter than the average time between observations. We therefore assume that the error variance in a column of water is evenly spread out throughout the mixed layer. The result of these simplifications is a computationally very efficient KF.A one year validation of the scheme is performed for year 2001 using an operational eddy resolving ocean model covering the North Sea and the Baltic Sea. It is found that assimilation of sea surface temperature data reduces the model root mean square error from 1.13 °C to 0.70 °C. The hybrid scheme is found to reduce the root mean square error slightly more than the simplified KF without OI to 0.66 °C. The inclusion of spatially varying satellite error variances does not improve the performance of the scheme significantly.