References of "Beckers, Jean-Marie"
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See detailCariaco basin dynamics: Study of the thermocline depth variability and its relation with open ocean conditions
Alvera Azcarate, Aïda ULg; Barth, Alexander ULg; Weisberg, Robert H. et al

Conference (2010, August 11)

The Cariaco basin (Venezuela) is a semi-enclosed trench located along the coast of Venezuela, with maximum depths of about 1400 m. It is connected to the open ocean by two shallow passages of less than ... [more ▼]

The Cariaco basin (Venezuela) is a semi-enclosed trench located along the coast of Venezuela, with maximum depths of about 1400 m. It is connected to the open ocean by two shallow passages of less than 150 m depth. Limited basin ventilation, coupled with a small vertical mixing results in anoxic conditions from about 250 m to the bottom. The dynamics of the Cariaco Basin are studied by means of a three-dimensional hydrodynamic model. The numerical model has a resolution of 1/60 degree and is an implementation of the Regional Ocean Modeling System (ROMS) nested in the global HYCOM solution from the Naval Research Laboratory. Of particular interest are the mechanisms that link the basin's interior to the Caribbean Sea, which can lead to the ventilation of the basin's anoxic sub-surface waters. To assess the influence of the open ocean on the basin, the spatial and temporal evolution of the thermocline depth and width is studied, as well as its relationship with wind variability and chlorophyll-a concentration: at seasonal scales, the interior of the basin reacts to easterly winds intensification with a rising of the thermocline, resulting in a coastal upwelling response, with the consequent increase in chlorophyll-a concentration. Outside the Cariaco basin, where an open-ocean, oligotrophic regime predominates, wind intensification increases mixing of the surface layers and induces therefore a deepening of the thermocline. At shorter time scales (i.e. days), it is shown that other processes, such as the influence of the meandering Caribbean Current, can also influence the thermocline variability within the Cariaco basin. [less ▲]

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See detailHigh-resolution Climatology of the northeast Atlantic using Data-Interpolating Variational Analysis (DIVA)
Troupin, Charles ULg; Machin, Francis; Ouberdous, Mohamed ULg et al

in Journal of Geophysical Research (2010), 115(C08005), 20

Numerous climatologies are available at different resolutions and cover various parts of the global ocean. Most of them have a resolution too low to represent suitably regional processes and the methods ... [more ▼]

Numerous climatologies are available at different resolutions and cover various parts of the global ocean. Most of them have a resolution too low to represent suitably regional processes and the methods for their construction are not able to take into account the influence of physical effects (topographic constraints, boundary conditions, advection, etc.). A high-resolution atlas for temperature and salinity is developed for the northeast Atlantic Ocean on 33 depth levels. The originality of this climatology is twofold: (1) For the data set, data are collected on all major databases and aggregated to lead to an original data collection without duplicates, richer than the World Ocean Database 2005, for the same region of interest. (2) For the method, climatological fields are constructed using the variational method Data-Interpolating Variational Analysis. The formulation of the latter allows the consideration of coastlines and bottom topography, and has a numerical cost almost independent on the number of observations. Moreover, only a few parameters, determined in an objective way, are necessary to perform an analysis. The results show overall good agreement with the widely used World Ocean Atlas, but also reveal significant improvements in coastal areas. Error maps are generated according to different theories and emphasize the importance of data coverage for the creation of such climatological fields. Automatic outlier detection is performed, and its effects on the analysis are examined. The method presented here is very general and not dependent on the region, hence it may be applied for creating other regional atlas in different zones of the global ocean. [less ▲]

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See detailOnboard implementation of the GHER model for the Black Sea, with SST and CTD data assimilation
Vandenbulcke, Luc ULg; Capet, Arthur ULg; Beckers, Jean-Marie ULg et al

in Journal of Operational Oceanography (2010), 3(2), 47-54

The first operational implementation of the GHER hydrodynamic model is described. It took place onboard the research vessel Alliance with all computation and sharing of forecasts being realised from the ... [more ▼]

The first operational implementation of the GHER hydrodynamic model is described. It took place onboard the research vessel Alliance with all computation and sharing of forecasts being realised from the vessel in near-real time. The forecasts were realised in the context of the Turkish Straits System 2008 campaign, which aimed at the real-time characterisation of the Marmara Sea and (south-western) Black Sea. The model performed badly at first, mainly because of poor initial conditions. Hence, as the model includes a reduced-rank extended Kalman filter assimilation scheme, after a hindcast where sea surface temperature and temperature and salinity profiles were assimilated, the model yielded realistic forecasts. Furthermore, the time required to run a one-day simulation (about 300 seconds of simulation, or 500 with pre-processing and data transfers included) was very limited and thus operational use of the model is possible. [less ▲]

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See detailReconstruction of missing data in satellite and in situ data sets with DINEOF (Data Interpolating Empirical Orthogonal Functions)
Alvera Azcarate, Aïda ULg; Barth, Alexander ULg; Beckers, Jean-Marie ULg

Conference (2010, July 12)

DINEOF (Data Interpolating Empirical Orthogonal Functions), a method to reconstruct missing data in geophysical data sets, is presented. Based on a truncated Empirical Orthogonal Functions (EOF) basis ... [more ▼]

DINEOF (Data Interpolating Empirical Orthogonal Functions), a method to reconstruct missing data in geophysical data sets, is presented. Based on a truncated Empirical Orthogonal Functions (EOF) basis, DINEOF uses an iterative procedure to calculate the values at the missing locations. A clear advantage of DINEOF is that no aprioriate knowledge about the statistics of the data set being reconstructed is needed (such as covariance or correlation length): the EOF basis is used internally to infer necessary information about the data, so no estimation of those parameters is needed. This characteristic is specially interesting for heterogeneous data distributions for which is difficult to derive this information. Also obtained are estimations of the error covariance of the reconstructed field, and outliers, i.e. data that present anomalous values with respect to the surrounding information in the original data, for which the residuals are larger than the statistically expected misfit calculated during the analysis. When very few data is available, the estimated covariance between two successive images used in the EOF calculation might not sufficiently robust. As a consequence, spikes appear in the temporal EOFs, which result in unrealistic discontinuities in the reconstruction. A temporal filter has been applied to the covariance matrix used to determined the EOFs, which effectively enhance temporal continuity. This has been applied to a SST data set of the Black Sea and the reconstruction error is estimated by cross-validation. On-going work includes the development of a merging capability within DINEOF that will allow to blend data from different platforms (satellite and in situ data). [less ▲]

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See detailSuper-ensemble techniques applied to wave forecast: performance and limitations
Lenartz, Fabian ULg; Beckers, Jean-Marie ULg; Chiggiato, Jacopo et al

in Ocean Science (2010), 6(2), 595-604

Nowadays, several operational ocean wave forecasts are available for a same region. These predictions may considerably differ, and to choose the best one is generally a difficult task. The super-ensemble ... [more ▼]

Nowadays, several operational ocean wave forecasts are available for a same region. These predictions may considerably differ, and to choose the best one is generally a difficult task. The super-ensemble approach, which consists in merging different forecasts and past observations into a single multi-model prediction system, is evaluated in this study. During the DART06 campaigns organized by the NATO Undersea Research Centre, four wave forecasting systems were simultaneously run in the Adriatic Sea, and significant wave height was measured at six stations as well as along the tracks of two remote sensors. This effort provided the necessary data set to compare the skills of various multi-model combination techniques. Our results indicate that a super-ensemble based on the Kalman Filter improves the forecast skills: The bias during both the hindcast and forecast periods is reduced, and the correlation coefficient is similar to that of the best individual model. The spatial extrapolation of local results is not straightforward and requires further investigation to be properly implemented. [less ▲]

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See detailComparison between in situ and satellite surface temperature in the Western Mediterranean Sea
Alvera Azcarate, Aïda ULg; Barth, Alexander ULg; Troupin, Charles ULg et al

Conference (2010, May 06)

A comparison between satellite and in situ sea surface temperature (SST) data in the Western Mediterranean Sea in 1999 is realised. The aim of this study is to better understand the differences between ... [more ▼]

A comparison between satellite and in situ sea surface temperature (SST) data in the Western Mediterranean Sea in 1999 is realised. The aim of this study is to better understand the differences between these two data sets, in order to realise merged maps of SST using satellite and in situ data. When merging temperature from different platforms, it is crucial to take the expected RMS error of the observations into account and to correct for possible biases. Advanced Very High Resolution Radiometer (AVHRR) SST day-time and night-time satellite data are used, and the in situ data have been obtained from various databases (World Ocean Database’05, Coriolis, Medar/Medatlas and ICES). Statistics about the differences due to the hour of the day, the month of the year, the type of sensor/platform used (CTD, XBT, drifter, etc) and the spatial distribution are made using a combination of error measures, diagrams and statistical hypothesis testing. In addition to quantify the errors between different platforms, several assumptions often made when creating gridded analyses will be critically reviewed: unbiased data sets, non-correlated errors of the observations, spatially uniform variance, and Gaussian-distributed data. [less ▲]

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See detailMultiparametric observations and analysis in the Bay of Calvi (Corsica), an ideal site for studying the human activity effects and climate changes in the Mediterranean Sea; STARESO
Gobert, Sylvie ULg; Alvera Azcarate, Aïda ULg; Barth, Alexander ULg et al

Conference (2010, May)

STARESO (Station de REcherche Sous marine et Océanographique) is the marine and oceanographic research station of the University of Liège (Belgium) managed by the French company STARESO S.A.. Constructed ... [more ▼]

STARESO (Station de REcherche Sous marine et Océanographique) is the marine and oceanographic research station of the University of Liège (Belgium) managed by the French company STARESO S.A.. Constructed in 1969, it is located near Calvi (Corsica, Western Mediterranean Sea) in an oligotrophic area chosen for the exceptional quality of its coastal waters STARESO offers to the oceanographers, by diving or with boats, a direct access to the sea. The variety of the accessible ecosystems is remarkable and unique in the Mediterranean basin: -the Bay of Calvi is characterized by healthy and very diverse biocenosis (e.g. Posidonia meadows, rocky and sandy communities, -a steep submarine canyon, with depths greater than 1 000 meters, is accessible in 15 minutes of navigation; -the Liguro-Provençal front, a major hydrologic structure, is situated between 10 and 15 miles of the coast. STARESO is accessible all the year for everybody and is functioning like an oceanographic research vessel. The Station is a platform for all oceanographic disciplines with a scientific expertise widely based on a long tradition of interdisciplinary work, and a direct access to time series of physical, chemical and biological data registered with automated systems and variety of sensors deployed in the Bay of Calvi since 30 years. This platform provides the opportunity to reach coastal, pelagic, benthic, deep systems with a manageable cost and ship requirements in a pristine zone. [less ▲]

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See detailError assessment of sea surface temperature satellite data relative to in situ data: effect of spatial and temporal coverage
Alvera Azcarate, Aïda ULg; Barth, Alexander ULg; Troupin, Charles ULg et al

Conference (2010, April 30)

A comparison between satellite and in situ sea surface temperature (SST) data in the Western Mediterranean Sea in 1999 is shown. The aim of this study is to better understand the differences between these ... [more ▼]

A comparison between satellite and in situ sea surface temperature (SST) data in the Western Mediterranean Sea in 1999 is shown. The aim of this study is to better understand the differences between these two data sets, in order to compute merged maps of SST using satellite and in situ data. When merging temperature from different platforms, it is crucial to take the expected RMS error of the observations into account and to correct for possible biases. Different in situ data sensors and platforms (CTD, XBT, drifter, etc) are available for the comparison, each with specificities in the nature of the measurement (accuracy and precision of the measures), and with different spatial and temporal distributions. A comparison with satellite data needs to take these factors into account. Statistics about the differences due to the hour of the day, the month of the year, the type of sensor/ platform used and the spatial distribution is therefore realised through a combination of error measures, diagrams and statistical hypothesis testing. The data used are Advanced Very High Resolution Radiometer (AVHRR) SST day-time and night-time satellite data, and in situ temperature data from various databases (World Ocean Database’05, Coriolis, Medar/Medatlas and ICES). [less ▲]

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See detailHigh-resolution measurements and modelling of the Cape Ghir upwelling filament during the CAIBEX survey
Troupin, Charles ULg; Sangrà, Pablo; Arístegui, Javier et al

Poster (2010, April 26)

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See detailSynthesis of regional product activities JRA4-JRA9
Beckers, Jean-Marie ULg; Alvera Azcarate, Aïda ULg; Barth, Alexander ULg et al

Conference (2010, April 01)

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See detailGODIVA: a 4-dimension implementation of DIVA
Troupin, Charles ULg; Ouberdous, Mohamed ULg; Beckers, Jean-Marie ULg

Poster (2010, March 29)

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See detailSeaDataNet regional climatologies: an overview
Troupin, Charles ULg; Ouberdous, Mohamed ULg; Barth, Alexander ULg et al

Poster (2010, March 29)

Detailed reference viewed: 41 (2 ULg)
See detailA web interface for gridding and visualizing oceanographic data sets
Barth, Alexander ULg; Alvera Azcarate, Aïda ULg; Sirjacobs, Damien ULg et al

Conference (2010, March)

Spatial interpolation of observations on a regular grid is a common task in many oceanographic disciplines (and geosciences in general). Diva (Data-Interpolating Variational Analysis) is an analysis tool ... [more ▼]

Spatial interpolation of observations on a regular grid is a common task in many oceanographic disciplines (and geosciences in general). Diva (Data-Interpolating Variational Analysis) is an analysis tool for gridding oceanographic in situ data. Diva takes the error in the observations and the typical spatial scale of the underlying field into account. Barriers due to the coastline and the topography in general are also used to propagate the information of a given observation spatially. Diva is a command-line driven application. To make Diva easier to use, a web interface has been developed. The user can directly upload his/her data in ASCII format and enter several parameters for the analysis. The analyzed field, location of the observations, and the error mask are then directly visualized in the browser. While this interface allows the user to create his/her own gridded field, a web interface is also developed to visualize pre-computed gridded oceanographic data sets. Those data sets are typically four-dimensional (longitude, latitude, depth and time). The system allows to visualize horizontal sections at a given depth and time to study the horizontal distribution of a given variable. It is also possible to display the results on an arbitrary vertical section. To study the evolution of the variable in time, the horizontal and vertical sections can also be animated. The user can customize the plot by changing the color-map, the range of the color-bar, the type of the plot (linearly interpolated color, simple contours, filled contours) and download the current view as a simple image or as Keyhole Markup Language (KML) file for visualization in applications such as Google Earth. The system is build using a client and server architecture. The server is written in Python using the Web Server Gateway Interface. The server implements version 1.1.1 and 1.3.0 of the Web Map Service (WMS) protocol of the Open Geospatial Consortium. On the server, all oceanographic data sets are stored as NetCDF files organized in folders and sub-folders allowing for a hierarchical presentation of the available variables. The client is build as a web application using the OpenLayers Javascript library. The web interface is accessible at http://gher-diva.phys.ulg.ac.be/. It is currently used for climatologies created in the frame of the SeaDataNet project and will be used for the EMODNET project (chemical lot). Thrid-party data centers can also integrate the web interface of Diva to show an interpolated field of in situ data as an additional WMS layer. A demonstration near-real time cloud-free sea surface temperature (SST) product of the Mediterranean Sea is presented. The reconstruction of the data set missing information (due to clouds, for example) is realised using DINEOF (Data Interpolating Empirical Orthogonal Functions). DINEOF is an EOF-based technique that does no need a priori information about the data set (such as signal to noise ratio, or correlation length) and that has shown to be faster and equally reliable than other widely used techniques for reconstructing missing data, such as optimal interpolation. Here we present a daily reconstruction of the Western Mediterranean SST. Cloudy data are downloaded from the Ifremer Medspiration ftp site. After extracting the data from the study zone, they are added to a data set containing the last 6 months of SST. A first DINEOF reconstruction is performed to identify outliers, i.e. pixels for which the analysis-observation difference (the residuals) are larger than the statistically expected misfit calculated during the analysis. Proximity to a cloud edge and deviation respect to a local median also penalize a pixel in the outlier classification. These outliers are removed from the original data set, and a second DINEOF reconstruction is performed, along with the calculation of error maps. Plots are realised, and the reconstruction of the latest 10 days is shown at http://gher-diva.phys.ulg.ac.be/DINEOF/dineof.html, together with the original data, the error maps and identified outliers. The whole procedure takes less than two hours and has been running automatically for more than 5 months. This product is intended as a demonstration of the capabilities of DINEOF as a near-real time technique to reconstruct missing data in satellite data sets. This procedure can be easily applied to other variables and other geographical zones. [less ▲]

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See detailCloud-free satellite data for operational applications using DINEOF
Alvera Azcarate, Aïda ULg; Barth, Alexander ULg; Sirjacobs, Damien ULg et al

Conference (2010, February 24)

DINEOF (Data Interpolating Empirical Orthogonal Functions) is an EOF-based technique to reconstruct missing data in satellite data sets, such as gaps created by the presence of clouds. It is parameter ... [more ▼]

DINEOF (Data Interpolating Empirical Orthogonal Functions) is an EOF-based technique to reconstruct missing data in satellite data sets, such as gaps created by the presence of clouds. It is parameter-free, meaning that no a priori information is needed (such as signal to noise ratio, or correlation length) to calculate the missing data: this information is extracted from the data through the EOF decomposition. In addition, computational time is lower than for other frequently used techniques to reconstruct missing data in satellites, such as optimal interpolation. Multivariate reconstructions can be also done, using extended EOFs. These characteristics make DINEOF very suitable for operational reconstruction of satellite data. Recently added to DINEOF is a technique to filter the temporal covariance matrix which allows to reduce spurious variability in the temporal EOFs, and therefore leads to improved reconstructions. We will present a general description of the technology, with examples of applications to different variables. We will also give an example of a near real time reconstruction of sea surface temperature in the western Mediterranean Sea. Conceived as a demonstration product for DINEOF, it is hosted at http://gher-diva.phys.ulg.ac.be/DINEOF/dineof.html and it is automatically updated daily, presenting the cloud-free sea surface temperature for the last ten days, as well as the original data, outliers and error fields. [less ▲]

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See detailModeling and observation of an upwelling filament off Cape Ghir (NW Africa) during the CAIBEX survey
Troupin, Charles ULg; Sangrà, Pablo; Arístegui, Javier et al

Poster (2010, February 22)

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See detailEnsemble perturbation smoother for optimizing tidal boundary conditions by assimilation of High-Frequency radar surface currents - application to the German Bight
Barth, Alexander ULg; Alvera Azcarate, Aïda ULg; Gurgel, Klaus-Werner et al

in Ocean Science (2010), 6(1), 161-178

High-Frequency (HF) radars measure the ocean surface currents at various spatial and temporal scales. These include tidal currents, wind-driven circulation, density-driven circulation and Stokes drift ... [more ▼]

High-Frequency (HF) radars measure the ocean surface currents at various spatial and temporal scales. These include tidal currents, wind-driven circulation, density-driven circulation and Stokes drift. Sequential assimilation methods updating the model state have been proven successful to correct the density-driven currents by assimilation of observations such as sea surface height, sea surface temperature and in-situ profiles. However, the situation is different for tides in coastal models since these are not generated within the domain, but are rather propagated inside the domain through the boundary conditions. For improving the modeled tidal variability it is therefore not sufficient to update the model state via data assimilation without updating the boundary conditions. The optimization of boundary conditions to match observations inside the domain is traditionally achieved through variational assimilation methods. In this work we present an ensemble smoother to improve the tidal boundary values so that the model represents more closely the observed currents. To create an ensemble of dynamically realistic boundary conditions, a cost function is formulated which is directly related to the probability of each boundary condition perturbation. This cost function ensures that the boundary condition perturbations are spatially smooth and that the structure of the perturbations satisfies approximately the harmonic linearized shallow water equations. Based on those perturbations an ensemble simulation is carried out using the full three-dimensional General Estuarine Ocean Model (GETM). Optimized boundary values are obtained by assimilating all observations using the covariances of the ensemble simulation. [less ▲]

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See detailEnsemble smoother for optimizing tidal boundary conditions and wind forcing by assimilation of High-Frequency Radar surface currents measurements of the German Bight
Barth, Alexander ULg; Alvera Azcarate, Aïda ULg; Staneva, Joanna et al

Conference (2010)

An ensemble smoother scheme is presented to assimilate HF radar surface currents to improve tidal boundary conditions and wind forcings of a circulation model of the German Bight. To create an ensemble of ... [more ▼]

An ensemble smoother scheme is presented to assimilate HF radar surface currents to improve tidal boundary conditions and wind forcings of a circulation model of the German Bight. To create an ensemble of dynamically realistic tidal boundary conditions, a cost function is formulated which is directly related to the probability of each perturbation. This cost function ensures that the perturbations are spatially smooth and that the structure of the perturbations satisfies approximately the harmonic linearized shallow water equations. Based on those perturbations an ensemble simulation is carried out using the full three-dimensional General Estuarine Ocean Model (GETM). Optimized boundary values are obtained using all observations within the assimilation period using the covariances of the ensemble simulation. The approach acts like a smoother scheme since all observations are taken into account. Since the scheme aims to derive the optimal perturbation, it might be called Ensemble Perturbation Smoother. The final analysis is obtained by rerunning the model using the optimal perturbation to the boundary conditions. The analyzed model solution satisfies thus the model equations exactly and does not suffer from spurious adjustments often observed with sequential assimilation schemes. Model results are also compared to independent tide gage data. The assimilation did also reduce the model error compared to those sea level observations. The same scheme has also been used to correct surface winds. Surface winds are crucial for accurately modeling the marine circulation in coastal waters. The method is validated directly by comparing the analyzed wind speed to in situ measurements and indirectly by assessing the impact of the corrected winds on sea surface temperature (SST) relative to satellite SST. [less ▲]

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See detailEstimation of tidal boundary conditions and surface winds by assimilation of high-frequency radar surface currents in the German Bight
Barth, Alexander ULg; Alvera Azcarate, Aïda ULg; Gurgel, Klaus-Werner et al

Conference (2010)

Numerical ocean models are affected by errors of various origins: errors in the initial conditions, boundary conditions and atmospheric forcings, uncertainties in the turbulence parametrization and ... [more ▼]

Numerical ocean models are affected by errors of various origins: errors in the initial conditions, boundary conditions and atmospheric forcings, uncertainties in the turbulence parametrization and discretization errors. In data assimilation, observations are used to reduce the uncertainty in the model solution. Ensemble-based assimilation schemes are often implemented such that the expected error of the model solution is minimized. It is shown that the observations can also be used to obtain improved estimates of the, in general, poorly known boundary conditions and atmospheric forcings. An ensemble smoother scheme is presented to assimilate high-frequency (HF) radar surface currents to improve tidal boundary conditions and wind forcings of a circulation model of the German Bight. To create an ensemble of dynamically realistic tidal boundary conditions, a cost function is formulated which is directly related to the probability of each perturbation. This cost function ensures that the perturbations are spatially smooth and that the structure of the perturbations satisfies approximately the harmonic linearized shallow water equations. Based on those perturbations an ensemble simulation is carried out using the full three-dimensional General Estuarine Ocean Model (GETM). Optimized boundary values are obtained using all observations within the assimilation period using the covariances of the ensemble simulation. The approach acts like a smoother scheme since past and future observations are taken into account. The final analysis is obtained by rerunning the model using the optimal perturbation of the boundary conditions. The analyzed model solution satisfies thus the model equations exactly and does not suffer from spurious adjustments often observed with sequential assimilation schemes. Model results are also compared to independent tide gauge data. The assimilation also reduces the model error compared to those sea level observations. The same scheme is also used to correct surface winds. Surface winds are crucial for accurately modeling the marine circulation in coastal waters. The method is validated directly by comparing the analyzed wind speed to in situ measurements and indirectly by assessing the impact of the corrected winds on sea surface temperature (SST) relative to satellite SST. [less ▲]

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