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1.
A complex and highly dynamical ocean region, the Agulhas Current System plays an important role in the transfer of energy, nutrients and organic material from the Indian to the Atlantic Ocean. Its dynamics are not only important locally, but affect the global ocean-atmosphere system. In working towards improved ocean reanalysis and forecasting capabilities, it is important that numerical models simulate mesoscale variability accurately—especially given the scarcity of coherent observational platforms in the region. Data assimilation makes use of scarce observations, a dynamical model and their respective error statistics to estimate a new, improved model state that minimises the distance to the observations whilst preserving dynamical consistency. Qualitatively, it is unclear whether this minimisation directly translates to an improved representation of mesoscale dynamics. In this study, the impact of assimilating along-track sea-level anomaly (SLA) data into a regional Hybrid Coordinate Ocean Model (HYCOM) is investigated with regard to the simulation of mesoscale eddy characteristics. We use an eddy-tracking algorithm and compare the derived eddy characteristics of an assimilated (ASSIM) and an unassimilated (FREE) simulation experiment in HYCOM with gridded satellite altimetry-derived SLA data. Using an eddy tracking algorithm, we are able to quantitatively evaluate whether assimilation updates the model state estimate such that simulated mesoscale eddy characteristics are improved. Additionally, the analysis revealed limitations in the dynamical model and the data assimilation scheme, as well as artefacts introduced from the eddy tracking scheme. With some exceptions, ASSIM yields improvements over FREE in eddy density distribution and dynamics. Notably, it was found that FREE significantly underestimates the number of eddies south of Madagascar compared to gridded altimetry, with only slight improvements introduced through assimilation, highlighting the models’ limitation in sustaining mesoscale activity in this region. Interestingly, it was found that the threshold for the maximum eddy propagation velocity in the eddy detection scheme is often exceeded when data assimilation relocates an eddy, causing the algorithm to interpret the discontinuity as eddy genesis, which directly influences the eddy count, lifetime and propagation velocity, and indirectly influences other metrics such as non-linearity. Finally, the analysis allowed us to separate eddy kinetic energy into contributions from detected mesoscale eddies and meandering currents, revealing that the assimilation of SLA has a greater impact on mesoscale eddies than on meandering currents.  相似文献   

2.
Using Ensemble Adjustment Kalman Filter (EAKF), two types of ocean satellite datasets were assimilated into the First Institute of Oceanography Earth System Model (FIO-ESM), v1.0. One control experiment without data assimilation and four assimilation experiments were conducted. All the experiments were ensemble runs for 1-year period and each ensemble started from different initial conditions. One assimilation experiment was designed to assimilate sea level anomaly (SLA); another, to assimilate sea surface temperature (SST); and the other two assimilation experiments were designed to assimilate both SLA and SST but in different orders. To examine the effects of data assimilation, all the results were compared with an objective analysis dataset of EN3. Different from the ocean model without coupling, the momentum and heat fluxes were calculated via air-sea coupling in FIO-ESM, which makes the relations among variables closer to the reality. The outputs after the assimilation of satellite data were improved on the whole, especially at depth shallower than 1000 m. The effects due to the assimilation of different kinds of satellite datasets were somewhat different. The improvement due to SST assimilation was greater near the surface, while the improvement due to SLA assimilation was relatively great in the subsurface. The results after the assimilation of both SLA and SST were much better than those only assimilated one kind of dataset, but the difference due to the assimilation order of the two kinds of datasets was not significant.  相似文献   

3.
A global ocean data assimilation system based on the ensemble optimum interpolation (EnOI) has been under development as the Chinese contribution to the Global Ocean Data Assimilation Experiment. The system uses a global ocean general circulation model, which is eddy permitting, developed by the Institute of Atmospheric Physics of the Chinese Academy of Sciences. In this paper, the implementation of the system is described in detail. We describe the sampling strategy to generate the stationary ensembles for EnOI. In addition, technical methods are introduced to deal with the requirement of massive memory space to hold the stationary ensembles of the global ocean. The system can assimilate observations such as satellite altimetry, sea surface temperature (SST), in situ temperature and salinity from Argo, XBT, Tropical Atmosphere Ocean (TAO), and other sources in a straightforward way. As a first step, an assimilation experiment from 1997 to 2001 is carried out by assimilating the sea level anomaly (SLA) data from TOPEX/Poseidon. We evaluate the performance of the system by comparing the results with various types of observations. We find that SLA assimilation shows very positive impact on the modeled fields. The SST and sea surface height fields are clearly improved in terms of both the standard deviation and the root mean square difference. In addition, the assimilation produces some improvements in regions where mesoscale processes cannot be resolved with the horizontal resolution of this model. Comparisons with TAO profiles in the Pacific show that the temperature and salinity fields have been improved to varying degrees in the upper ocean. The biases with respect to the independent TAO profiles are reduced with a maximum magnitude of about 0.25°C and 0.1 psu for the time-averaged temperature and salinity. The improvements on temperature and salinity also lead to positive impact on the subsurface currents. The equatorial under current is enhanced in the Pacific although it is still underestimated after the assimilation.  相似文献   

4.
We explore the ocean circulation estimates obtained by assimilating observational products made available by the Global Ocean Data Assimilation Experiment (GODAE) and other sources in an incremental, four-dimensional variational data assimilation system for the Intra-Americas Sea. Estimates of the analysis error (formally, the inverse Hessian matrix) are computed during the assimilation procedure. Comparing the impact of differing sea surface height and sea surface temperature products on both the final analysis error and difference between the model state estimates, we find that assimilating GODAE and non-GODAE products yields differences between the model and observations that are comparable to the differences between the observation products themselves. While the resulting analysis error estimates depend on the configuration of the assimilation system, the basic spatial structures of the standard deviations of the ocean circulation estimates are fairly robust and reveal that the assimilation procedure is capable of reducing the circulation uncertainty when only surface data are assimilated.  相似文献   

5.
The characterization of model errors is an essential step for effective data assimilation into open-ocean and shelf-seas models. In this paper, we propose an experimental protocol to properly estimate the error statistics generated by imperfect atmospheric forcings in a regional model of the Bay of Biscay, nested in a basin-scale North Atlantic configuration. The model used is the Hybrid Coordinate Ocean Model (HYCOM), and the experimental protocol involves Monte Carlo (or ensemble) simulations. The spatial structure of the model error is analyzed using the representer technique, which allows us to anticipate the subsequent impact in data assimilation systems. The results show that the error is essentially anisotropic and inhomogeneous, affecting mainly the model layers close to the surface. Even when the forcings errors are centered around zero, a divergence is observed between the central forecast and the mean forecast of the Monte Carlo simulations as a result of nonlinearities. The 3D structure of the representers characterizes the capacity of different types of measurement (sea level, sea surface temperature, surface velocities, subsurface temperature, and salinity) to control the circulation. Finally, data assimilation experiments demonstrate the superiority of the proposed methodology for the implementation of reduced-order Kalman filters.  相似文献   

6.
ARGO hydrographic profiles, two hydrographic transects and satellite measurements of air–sea exchange parameters were used to characterize the properties and seasonal heat budget variations of the Surface Mixed Layer (SML) south of Africa. The analysis distinguishes the Subtropical domain (STZ) and the Subantarctic Zone (SAZ), Polar Frontal Zone (PFZ) and Antarctic Zone (AZ) of the Antarctic Circumpolar Current. While no Subantarctic Mode Water forms in that region, occurrences of deep SML (up to ∼450 m) are observed in the SAZ in anticyclones detached from the Agulhas Current retroflection or Agulhas Return Current. These are present latitudinally throughout the SAZ, but preferentially at longitudes 10–20° E where, according to previous results, the Subtropical Front is interrupted. Likely owing to this exchange window and to transfers at the Subantarctic Front also enhanced by the anticyclones, the SAZ shows a wide range of properties largely encroaching upon those of the neighbouring domains. Heat budget computations in each zone reveal significant meridional changes of regime. While air–sea heat fluxes dictate the heat budget seasonal variability everywhere, heat is mostly brought through lateral geostrophic advection by the Agulhas Current in the STZ, through lateral diffusion in the SAZ and through air–sea fluxes in the PFZ and AZ. The cooling contributions are by Ekman advection everywhere, lateral diffusion in the STZ (also favoured by the ∼10° breach in the Subtropical Front) and geostrophic advection in the SAZ. The latter likely reflects an eastward draining of water warmed through mixing of the subtropical eddies.  相似文献   

7.
We have studied, for the first time, variations in absolute surface geostrophic currents (SGC) using satellite data only. The proposed approach combines 18 years’ altimetry data, which provide reliable measurements of absolute sea level (ASL), with a gravity field and steady-state ocean circulation explorer geoid model to obtain dynamic topography, and achieves unprecedented precision and accuracy. Our proposal overcomes the main limitations of existing approaches based solely on altimetry data (which suffer from lack of an independent reference for derivation of ASL maps), and approximations based on in-situ data (which are characterized by a sparse and inhomogeneous coverage in time and space). Features of annual variations of SGC are also addressed. As a result of our study we provide new absolute SGC climatology in the form of a 52-week data set of surface current fields, gridded at quarter degree longitude and latitude resolution and resolving spatial scales as short as 140 km. For presentation, this data set is averaged monthly and the results, presented as monthly climatology, are compared with climatology based on in-situ observations from drifter data.  相似文献   

8.
The Mediterranean Forecasting System (MFS) has been operational for a decade, and is continuously providing forecasts and analyses for the region. These forecasts comprise local- and basin-scale information of the environmental state of the sea and can be useful for tracking oil spills and supporting search-and-rescue missions. Data assimilation is a widely used method to improve the forecast skill of operational models and, in this study, the three-dimensional variational (OceanVar) scheme has been extended to include Argo float trajectories, with the objective of constraining and ameliorating the numerical output primarily in terms of the intermediate velocity fields at 350 m depth. When adding new datasets, it is furthermore crucial to ensure that the extended OceanVar scheme does not decrease the performance of the assimilation of other observations, e.g., sea-level anomalies, temperature, and salinity. Numerical experiments were undertaken for a 3-year period (2005–2007), and it was concluded that the Argo float trajectory assimilation improves the quality of the forecasted trajectories with ~15%, thus, increasing the realism of the model. Furthermore, the MFS proved to maintain the forecast quality of the sea-surface height and mass fields after the extended assimilation scheme had been introduced. A comparison between the modeled velocity fields and independent surface drifter observations suggested that assimilating trajectories at intermediate depth could yield improved forecasts of the upper ocean currents.  相似文献   

9.
Summary Methods used by Warren and later modified by Niiller and Robinson have been used to investigate the Agulhas Current and other currents associated with it. The results show that with the assistance of a small bottom current of 4 cm/s in the same direction as the main current, the Agulhas Current can proceed round the Cape of Good Hope during three out of four seasons of the year. During the northern winter season, however, the Agulhas Current is so strong that the bottom current may not be able to be so effective and then the Current doubles back near the Agulhas Plateau to form an Agulhas Return Current. There is, however, all the year round an eastward current flowing south of the Agulhas Current but except during the northern winter season, this fed mainly from outside the Agulhas Current area. With a small bottom current of about 2 cms/ the current gets deflected round the Agulhas Plateau to give a meandering effect.  相似文献   

10.
Geostrophic surface velocities can be derived from the gradients of the mean dynamic topography—the difference between the mean sea surface and the geoid. Therefore, independently observed mean dynamic topography data are valuable input parameters and constraints for ocean circulation models. For a successful fit to observational dynamic topography data, not only the mean dynamic topography on the particular ocean model grid is required, but also information about its inverse covariance matrix. The calculation of the mean dynamic topography from satellite-based gravity field models and altimetric sea surface height measurements, however, is not straightforward. For this purpose, we previously developed an integrated approach to combining these two different observation groups in a consistent way without using the common filter approaches (Becker et al. in J Geodyn 59(60):99–110, 2012; Becker in Konsistente Kombination von Schwerefeld, Altimetrie und hydrographischen Daten zur Modellierung der dynamischen Ozeantopographie 2012). Within this combination method, the full spectral range of the observations is considered. Further, it allows the direct determination of the normal equations (i.e., the inverse of the error covariance matrix) of the mean dynamic topography on arbitrary grids, which is one of the requirements for ocean data assimilation. In this paper, we report progress through selection and improved processing of altimetric data sets. We focus on the preprocessing steps of along-track altimetry data from Jason-1 and Envisat to obtain a mean sea surface profile. During this procedure, a rigorous variance propagation is accomplished, so that, for the first time, the full covariance matrix of the mean sea surface is available. The combination of the mean profile and a combined GRACE/GOCE gravity field model yields a mean dynamic topography model for the North Atlantic Ocean that is characterized by a defined set of assumptions. We show that including the geodetically derived mean dynamic topography with the full error structure in a 3D stationary inverse ocean model improves modeled oceanographic features over previous estimates.  相似文献   

11.
A comparison between in situ and satellite sea surface temperature (SST) is presented for the Western Mediterranean Sea during 1999. Several international databases are used to extract in situ data (World Ocean Database, MEDAR/Medatlas, Coriolis Data Center, International Council for the Exploration of the Sea and International Comprehensive Ocean-Atmosphere Data Set). The in situ data are classified into different platforms or sensors (conductivity–temperature–depth, expendable bathythermographs, drifters, bottles, and ships), in order to assess the relative accuracy of these type of data with respect to Advanced Very High Resolution Radiometer SST satellite data. It is shown that the results of the error assessment vary with the sensor type, the depth of the in situ measurements, and the database used. Ship data are the most heterogeneous data set, and therefore present the largest differences with respect to in situ data. A cold bias is detected in drifter data. The differences between satellite and in situ data are not normally distributed. However, several analysis techniques, as merging and data assimilation, usually require Gaussian-distributed errors. The statistics obtained during this study will be used in future work to merge the in situ and satellite data sets into one unique estimation of the SST.  相似文献   

12.
本文研究了基于泊松小波径向基函数融合多代卫星测高及多源重力数据精化大地水准面模型的方法.分别以沿轨垂线偏差和大地水准面高高差作为卫星测高观测量,研究了使用不同类型测高数据对于大地水准面建模精度的影响.针对全球潮汐模型在浅水区域及部分开阔海域精度较低的问题,引入局部潮汐模型研究了不同潮汐模型对于大地水准面的影响.数值分析表明:相比于使用沿轨垂线偏差作为测高观测量,基于沿轨大地水准面高高差解算得到的大地水准面模型的精度更高,特别是在海域区域,其精度提高了2.3cm.由于使用沿轨大地水准面高高差作为测高观测量削弱了潮汐模型长波误差的影响,采用不同潮汐模型对大地水准面解算的影响较小.总体而言,船载重力及测高观测数据在海洋重力场的确定中呈现互补性关系,联合两类重力场观测量可以提高局部重力场的建模精度.  相似文献   

13.
The National High Frequency (HF) Surface Current Mapping Radar Network is being developed as a backbone system within the U.S. Integrated Ocean Observing System. This paper focuses on the application of HF radar-derived surface current maps to U.S. Coast Guard Search and Rescue operations along the Mid-Atlantic coast of the USA. In that context, we evaluated two algorithms used to combine maps of radial currents into a single map of total vector currents. In situ data provided by seven drifter deployments and four bottom-mounted current meters were used to (1) evaluate the well-established unweighted least squares (UWLS) and the more recently adapted optimal interpolation (OI) algorithms and (2) quantify the sensitivity of the OI algorithm to varying decorrelation scales and error thresholds. Results with both algorithms were shown to depend on the location within the HF radar data footprint. The comparisons near the center of the HF radar coverage showed no significant difference between the two algorithms. The most significant distinction between the two was seen in the drifter trajectories. With these simulations, the weighting of radial velocities by distance in the OI implementation was very effective at reducing both the distance between the actual drifter and the cluster of simulated particles as well as the scale of the search area that encompasses them. In this study, the OI further reduced the already improved UWLS-based search areas by an additional factor of 2. The results also indicated that the OI output was relatively insensitive to the varying decorrelation scales and error thresholds tested.  相似文献   

14.
Ocean Dynamics - The sea level observations from satellite altimetry are characterised by a sparse spatial and temporal coverage. For this reason, along-track data are routinely interpolated into...  相似文献   

15.
We compare different past sea level reconstructions over the 1950–2009 time span using the Empirical Orthogonal Function (EOF) approach. The reconstructions are based on 91 long (up to 60?years) but sparsely distributed tide-gauge records and gridded sea level data from two numerical ocean models over 1958–2007 (the DRAKKAR/NEMO model without data assimilation and the simple ocean data assimilation ocean reanalysis-SODA-) and satellite altimetry data over 1993–2009. We find that the reconstructed global mean sea level computed over the?~60-year-long time span little depends on the input spatial grids. This is unlike the regional variability maps that appear very sensitive to the considered input spatial grids. Using the DRAKKAR/NEMO model, we test the influence of the period covered by the input spatial grids and the number of EOFs modes used to reconstruct sea level. Comparing with tide-gauge records not used in the reconstruction, we determine optimal values for these two parameters. As suggested by previous studies, the longer the time span covered by the spatial grids, the better the fit with unused tide gauges. Comparison of the reconstructed regional trends over 1950–2009 based on the two ocean models and satellite altimetry grids shows good agreement in the tropics and substantial differences in the mid and high latitude regions, and in western boundary current areas as well. The reconstructed spatial variability seems very sensitive to the input spatial information. No clear best case emerges. Thus, using the longest available model-based spatial functions will not necessarily give the most realistic results as it will be much dependent on the quality of the model (and its associated forcing). Altimetry-based reconstructions (with 17-year long input grids) give results somewhat similar to cases with longer model grids. It is likely that better representation of the sea level regional variability by satellite altimetry compensates the shorter input grids length. While waiting for much longer altimetry records, improved past sea level reconstructions may be obtained by averaging an ensemble of different model-based reconstructions, as classically done in climate modelling. Here, we present such a ‘mean’ reconstruction (with associated uncertainty) based on averaging the three individual reconstructions discussed above.  相似文献   

16.
The Argo temperature and salinity profiles in 2005–2009 are assimilated into a coastal ocean general circulation model of the Northwest Pacific Ocean using the ensemble adjustment Kalman filter (EAKF). Three numerical tests, including the control run (CTL) (without data assimilation, which serves as the reference experiment), ensemble free run (EnFR) (without data assimilation), and EAKF experiment (with Argo data assimilation using EAKF), are carried out to examine the performance of this system. Using the restarts of different years as the initial conditions of the ensemble integrations, the ensemble spreads from EnFR and EAKF are all kept at a finite value after a sharp decreasing in the first few months because of the sensitive of the model to the initial conditions, and the reducing of the ensemble spread due to Argo data assimilation is not much. The ensemble samples obtained in this way can well represent the probabilities of the real ocean states, and no ensemble inflation is necessary for this EAKF experiment. Different experiment results are compared with satellite sea surface temperature (SST) data and the Global Temperature-Salinity Profile Program (GTSPP) data. The comparison of SST shows that modeled SST errors are reduced after data assimilation; the error reduction percentage after assimilating the Argo profiles is about 10?% on average. The comparison against the GTSPP profiles, which are independent of the Argo profiles, shows improvements in both temperature and salinity. The comparison results indicated a great error reduction in all vertical layers relative to CTL and the ensemble mean of EnFR; the maximum value for temperature and salinity reaches to 85?% and 80?%, respectively. The standard deviations of sea surface height are employed to examine the simulation ability, and it is shown that the mesoscale variability is improved after Argo data assimilation, especially in the Kuroshio extension area and along the section of 10°N. All these results suggest that this system is potentially useful for improving the simulation ability of oceanic numerical models.  相似文献   

17.

Knowledge of upper ocean currents is needed for trajectory forecasts and is essential for search and rescue operations and oil spill mitigation. This paper addresses effects of surface waves on ocean currents and drifter trajectories using in situ observations. The data set includes colocated measurements of directional wave spectra from a wave rider buoy, ocean currents measured by acoustic Doppler current profilers (ADCPs), as well as data from two types of tracking buoys that sample the currents at two different depths. The ADCP measures the Eulerian current at one point, as modelled by an ocean general circulation model, while the tracking buoys are advected by the Lagrangian current that includes the wave-induced Stokes drift. Based on our observations, we assess the importance of two different wave effects: (a) forcing of the ocean current by wave-induced surface fluxes and the Coriolis–Stokes force, and (b) advection of surface drifters by wave motion, that is the Stokes drift. Recent theoretical developments provide a framework for including these wave effects in ocean model systems. The order of magnitude of the Stokes drift is the same as the Eulerian current judging from the available data. The wave-induced momentum and turbulent kinetic energy fluxes are estimated and shown to be significant. Similarly, the wave-induced Coriolis–Stokes force is significant over time scales related to the inertial period. Surface drifter trajectories were analysed and could be reproduced using the observations of currents, waves and wind. Waves were found to have a significant contribution to the trajectories, and we conclude that adding wave effects in ocean model systems is likely to increase predictability of surface drifter trajectories. The relative importance of the Stokes drift was twice as large as the direct wind drag for the used surface drifter.

  相似文献   

18.
Knowledge of upper ocean currents is needed for trajectory forecasts and is essential for search and rescue operations and oil spill mitigation. This paper addresses effects of surface waves on ocean currents and drifter trajectories using in situ observations. The data set includes colocated measurements of directional wave spectra from a wave rider buoy, ocean currents measured by acoustic Doppler current profilers (ADCPs), as well as data from two types of tracking buoys that sample the currents at two different depths. The ADCP measures the Eulerian current at one point, as modelled by an ocean general circulation model, while the tracking buoys are advected by the Lagrangian current that includes the wave-induced Stokes drift. Based on our observations, we assess the importance of two different wave effects: (a) forcing of the ocean current by wave-induced surface fluxes and the Coriolis–Stokes force, and (b) advection of surface drifters by wave motion, that is the Stokes drift. Recent theoretical developments provide a framework for including these wave effects in ocean model systems. The order of magnitude of the Stokes drift is the same as the Eulerian current judging from the available data. The wave-induced momentum and turbulent kinetic energy fluxes are estimated and shown to be significant. Similarly, the wave-induced Coriolis–Stokes force is significant over time scales related to the inertial period. Surface drifter trajectories were analysed and could be reproduced using the observations of currents, waves and wind. Waves were found to have a significant contribution to the trajectories, and we conclude that adding wave effects in ocean model systems is likely to increase predictability of surface drifter trajectories. The relative importance of the Stokes drift was twice as large as the direct wind drag for the used surface drifter.  相似文献   

19.
To the extent that sea surface temperature and colors can be considered passive tracers, their motions can be tracked to estimate the current velocities, or a conservation equation can be invoked to relate their temporal variations to the velocities. We investigate the latter, the so-called tracer inversion problem, with a particular focus on (1) the conditions under which the problem can be rendered over-determined for least squares solutions, (2) the possibility of using the tracer conservation equation within the “velocity projection” framework to estimate subsurface current profiles in shallow coastal waters, and (3) the accuracy of the tracer inversion calculation in terms of the data resolution and noise. The velocity projection framework refers to relating surface motion, either measured directly or made visible by tracers, to the subsurface current motion through the equations of motion. The accuracy of the tracer inversion calculation is quantified in terms of the spatial and temporal resolution of the tracer distribution. In the presence of irreducible tracer noise, the accuracy of the inversion rapidly degrades, and it is shown that the inversion with velocity projection can help improve accuracy. The tracer inversion method developed in this study is applied to the satellite sea surface temperature data, and the velocity result is compared to the velocity measurements made with the shore-based HF Coastal Current Radar. The potential of improving the velocity estimation with the present approach is indicated.  相似文献   

20.
《Continental Shelf Research》1999,19(15-16):1905-1932
The M2 tidal component of the flow in the Dover Straits is reconstructed using a natural combination of two independent data sources: HF Ocean Surface Current Radar (HF OSCR) system and coastal tidal measurements. The method used is the variational data assimilation technique into a quasi-linearized finite element tidal model. The model uses triangular elements with horizontal resolution varying from 800 to 1200 m. It is controlled by the boundary conditions at open boundaries, which are adjusted to fit the available data in an optimal way. A “weak” formulation of the dynamical constraints is used. The interpolation scheme allows small (0.01%) deviations from the exact dynamics specified by the model. The optimal state of M2 parameters (sea surface elevation and depth-averaged velocities) is used to map both the M2 tidal flux through the strait and the M2 energy flux. The respective values obtained are the tidal flux amplitude 1.18±0.09×106 m3 s−1, the net residual transport (Stoke's drift) 40±3×103 m3 s−1, and the net energy flux 1.19±0.09×1010 W. These figures within the statistically estimated error band are in the close agreement with those obtained by Prandle et al., 1993. A rigorous error analysis is performed using an explicit inversion of the Hessian matrix, associated with the assimilation scheme. As a result, error charts for M2 velocities and sea surface elevation are obtained. It is shown that OSCR data combined with coastal level measurements and constrained by dynamics is able to provide quite accurate velocity estimates whose errors vary within the range of 0.05–0.45 m s−1 depending upon the location. Error maps also enable us to determine areas requiring better coverage by data, thus forming a basis of optimization approach to the design of the HFR measurements. The use of variational assimilation technique in providing integrated interpolation patterns from various sources of data demonstrates its capabilities in relation to future oceanographic monitoring systems of shelf circulation.  相似文献   

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