References of "Beckers, Jean-Marie"
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See detailS,T-climatologies of the North Sea using the Variational Inverse Method
Scory, Serge; Ouberdous, Mohamed ULg; Troupin, Charles ULg et al

Poster (2009, April 19)

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See detailA new mechanism of upwelling generated filaments based on potential vorticity balance
Troupin, Charles ULg; Mason, Evan; Beckers, Jean-Marie ULg et al

Poster (2009, April 19)

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See detailWeekly satellite sea surface temperature around Corsica, a DINEOF analysis of AVHRR data (1998), foreseeing comparison with interpolated and modelled fields.
Sirjacobs, Damien ULg; Lenartz, Fabian ULg; Troupin, Charles ULg et al

Poster (2009, January)

Providing wide coverage and high spatio-temporal resolution, SST satellite archives are valuable sources of information for sound understanding of the ocean dynamics, including validation of ... [more ▼]

Providing wide coverage and high spatio-temporal resolution, SST satellite archives are valuable sources of information for sound understanding of the ocean dynamics, including validation of hydrodynamical modelling studies. Yet original SST fields have also many gaps (clouds, retrieval problems), but they are known to exhibit strong spatial and temporal correlations for regions of similar dynamics. This is exploited by the parameter free statistical technique DINEOF (Data Interpolation with Empirical Orthogonal Functions) [Alvera-Azcárate et al. (2005) Ocean Modell.; Beckers et al. (2006) Ocean Sciences] to produce full weekly analysis of the variability of the sea surface temperature (SST) around Corsica and in the Ligurian Sea at weekly temporal resolution during the year 1998. A detection of outliers implemented in DINEOF analysis is tested for pointing out unusual or invalid SST data. This study is realised foreseeing a comparison of DINEOF weekly averaged reconstructed fields with those obtained by interpolating methods on the same dataset (Data Interpolating Variationnal Analysis and Optimal Interpolation schemes), and with outputs of an implementation of the GHER 3D model in this area. [less ▲]

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See detailModelling error of a hydrodynamic model of the Mediterranean Sea
Vandenbulcke, Luc ULg; Rixen, M.; Beckers, Jean-Marie ULg et al

Conference (2009)

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See detailA web interface for griding arbitrarily distributed in situ data based on Data-Interpolating Variational Analysis (Diva)
Barth, Alexander ULg; Alvera Azcarate, Aïda ULg; Troupin, Charles ULg et al

Conference (2009)

Spatial interpolation of observations on a regular grid is a common task in many ceanographic disciplines (and geosciences in general). It is often used to create climatological maps for physical ... [more ▼]

Spatial interpolation of observations on a regular grid is a common task in many ceanographic disciplines (and geosciences in general). It is often used to create climatological maps for physical, biological or chemical parameters representing e.g. monthly or seasonally averaged fields. Since instantaneous observations can not be directly related to a field representing an average, simple spatial interpolation of observations is in general not acceptable. Diva (Data-Interpolating Variational Analysis) is an analysis tool which 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 and also currents estimates (if available) are used to propagate the information of a given observation spatially. Diva is a command-line driven application written in Fortran and Shell Scripts. The observations and parameters are specified by the user using text files. The analyzed field and the expected error variance are returned as NetCDF files. This form of interaction with Diva is very similar to other high-performance codes and is a familiar approach for ocean modelers. However it represents a steep learning curve for oceanographers from other disciplines not familiar with command-line applications and programming. To make Diva easier to use, a web interface has been developed (http://gher-diva.phys.ulg.ac.be). Installation and compilation of Diva is therefore not required. 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 presented as different layers using the Web Map Service protocol. They are visualized in the browser using the Javascript library OpenLayers allowing the user to interact with layers (for example zooming and panning). Finally, the results can be downloaded as a NetCDF file, Matlab file (also readable in Octave, an open source program similar to Matlab) and Keyhole Markup Language (KML) file for visualisation in applications such as Google Earth. [less ▲]

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See detailReconstruction of missing data in satellite data sets using DINEOF with constraints to reduce spurious high-frequency variations in the temporal EOFs
Alvera Azcarate, Aïda ULg; Barth, Alexander ULg; Sirjacobs, Damien ULg et al

Conference (2009)

DINEOF (Data Interpolating Empirical Orthogonal Functions) is a method to reconstruct missing data in geophysical data sets, such as gaps originated by the presence of clouds in infrared satellite sensors ... [more ▼]

DINEOF (Data Interpolating Empirical Orthogonal Functions) is a method to reconstruct missing data in geophysical data sets, such as gaps originated by the presence of clouds in infrared satellite sensors. Based on Empirical Orthogonal Functions (EOFs), DINEOF uses an iterative procedure to calculate the missing values. DINEOF has been compared to Optimal Interpolation, showing that more accurate results are achieved, with up to 30 times less computational time (tests made with sea surface temperature of the Adriatic Sea, and validated with in situ data). Another advantage of this technology is that there is no need for a priori knowledge of the reconstructed data set statistics (such as covariance or correlation length). The technique can be applied to a broad range of data (physical, biological, chemical), and to a variety of platforms (satellite data, in situ data...). Given the nature of the EOFs, it is not necessary that data sets are regularly distributed in time. Irregularly distributed data sets, however, may lead to discontinuities in the temporal EOFs calculated from them, and these discontinuities can affect in turn the quality of the DINEOF reconstruction. In satellite data, some images can present a large amount of cloud cover, and only a few pixels with valid data. EOF projection to such images can also lead to discontinuities in the temporal modes, as there might be an over-fitting to the scarce information present in those images. After briefly describe DINEOF and its applications, we present a study aiming to reduce these discontinuities by including a time constraint to the covariance matrix used in the EOF decomposition. The approach is tested with sea surface temperature data of the Black Sea, and the results are compared to independent data. [less ▲]

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See detailDynamically constrained ensemble perturbations - application to tides on the West Florida Shelf
Barth, Alexander ULg; Alvera Azcarate, Aïda ULg; Beckers, Jean-Marie ULg et al

in Ocean Science (2009), 5(3), 259-270

A method is presented to create an ensemble of perturbations that satisfies linear dynamical constraints. A cost function is formulated defining the probability of each perturbation. It is shown that the ... [more ▼]

A method is presented to create an ensemble of perturbations that satisfies linear dynamical constraints. A cost function is formulated defining the probability of each perturbation. It is shown that the perturbations created with this approach take the land-sea mask into account in a similar way as variational analysis techniques. The impact of the land-sea mask is illustrated with an idealized configuration of a barrier island. Perturbations with a spatially variable correlation length can be also created by this approach. The method is applied to a realistic configuration of the West Florida Shelf to create perturbations of the M2 tidal parameters for elevation and depth-averaged currents. The perturbations are weakly constrained to satisfy the linear shallow-water equations. Despite that the constraint is derived from an idealized assumption, it is shown that this approach is applicable to a non-linear and baroclinic model. The amplitude of spurious transient motions created by constrained perturbations of initial and boundary conditions is significantly lower compared to perturbing the variables independently or to using only the momentum equation to compute the velocity perturbations from the elevation. [less ▲]

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See detailDynamically constrained ensemble perturbations. Application to tides on the West Florida Shelf
Barth, Alexander ULg; Alvera Azcarate, Aïda ULg; Beckers, Jean-Marie ULg et al

Conference (2009)

A method is presented to create an ensemble of perturbations that satisfies linear dynamical constraints. A cost function is formulated defining the probability of each perturbation. It is shown that the ... [more ▼]

A method is presented to create an ensemble of perturbations that satisfies linear dynamical constraints. A cost function is formulated defining the probability of each perturbation. It is shown that the perturbations created with this approach take the land-sea mask into account in a similar way as variational analysis techniques. The impact of the land-sea mask is illustrated with an idealized configuration of a barrier island. Perturbations with a spatially variable correlation length can be also created by this approach. The method is applied to a realistic configuration of the West Florida Shelf to create perturbations of the M2 tidal parameters for elevation and depth-averaged currents. The perturbations are weakly constrained to satisfy the linear shallow-water equations. Despite that the constraint is derived from an idealized assumption, it is shown that this approach is applicable to a non-linear and baroclinic model. The amplitude of spurious transient motions created by constrained perturbations of initial and boundary conditions is significantly lower compared to perturbing the variables independently or to using only the momentum equation to compute the velocity perturbations from the elevation [less ▲]

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See detailEnhancing temporal correlations in EOF expansions for the reconstruction of missing data using DINEOF
Alvera Azcarate, Aïda ULg; Barth, Alexander ULg; Sirjacobs, Damien ULg et al

in Ocean Science (2009), 5(4), 475-485

DINEOF (Data Interpolating Empirical Orthogonal Functions) is an EOF-based technique for the reconstruction of missing data in geophysical fields, such as those produced by clouds in sea surface ... [more ▼]

DINEOF (Data Interpolating Empirical Orthogonal Functions) is an EOF-based technique for the reconstruction of missing data in geophysical fields, such as those produced by clouds in sea surface temperature satellite images. A technique to reduce spurious time variability in DINEOF reconstructions is presented. The reconstruction of these images within a long time series using DINEOF can lead to large discontinuities in the reconstruction. Filtering the temporal covariance matrix allows to reduce this spurious variability and therefore more realistic reconstructions are obtained. The approach is tested in a three years sea surface temperature data set over the Black Sea. The effect of the filter in the temporal EOFs is presented, as well as some examples of the improvement achieved with the filtering in the SST reconstruction, both compared to the DINEOF approach without filtering. [less ▲]

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See detailApplication of a 3-D Super Ensemble to ocean forecast
Lenartz, Fabian ULg; Barth, Alexander ULg; Beckers, Jean-Marie ULg et al

Conference (2009)

Super Ensemble (SE) techniques have recently allowed improving the forecast of various important oceanographic parameters, such as the significant wave height, the speed of sound or the surface drift, by ... [more ▼]

Super Ensemble (SE) techniques have recently allowed improving the forecast of various important oceanographic parameters, such as the significant wave height, the speed of sound or the surface drift, by correcting the prediction at a single or multiple locations, where data were available during the whole training period. However, nowadays common observation systems, such as satellite imagery or drifters, do not always provide information at the exact same locations, hence it is necessary to generalize the approach in order to take benefit of every image or track available. In this study, we try and apply a SE, fed with remote sensing and gliders data, to 3-D hydrodynamic models. The basic idea on which rely the SE methods is that a certain combination of several model runs and possibly data could yield better results than just one single model, even if it has a higher temporal or spatial resolution. As the most efficient techniques are the ones using observations, they rapidly developed and increased in complexity by copying what had been done in the data assimilation community; getting from the simple ensemble mean of the model outputs to their linear combination based on a particle filter. In our present study, we have decided to use the Kalman filter (KF) as it alleviates the need of an a priori determination of the training period length, and does not require the run of a very large ensemble of members. In addition, we apply it in a 3-D framework in order to take benefit of the spatial information contained by each source of measurements. For example, satellite images of sea surface temperature (SST) are very useful to correct the value of this parameter, but depending on the structure of the water column, it can also give a precious guess of how warm or cold is the ocean at 20 m deep. In our experiment the domain of interest is the Ligurian Sea during the last week of September, when part of the set-up for the CalVal08 campaign (SiC Charles Trees) had already taken place. The data assimilated during the training of the filter are SST images from AVHRR, as well as temperature and salinity profiles from two Rutgers University gliders. The models used for the study are three nested models of NCOM, run without data assimilation. The two considered variables are the temperature and the salinity. As our method is designed to work in a multivariate way, salinity forecast can possibly be improved by observing temperature profiles. Statistics are computed for both the training and the testing periods with an independent set of data. In four test cases, we review the impact of both the nature of the assimilated data, and the formulation of the model covariance matrix. At the end, we show that, on the basis of previous model outputs from which we’ve drawn an estimate of the model covariance, RMS error of the forecast in the whole 3-D domain can be reduced by 30%, thanks to the only assimilation of satellite SST images. [less ▲]

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See detailUsing Diva on large datasets: applications and tips
Troupin, Charles ULg; Ouberdous, Mohamed ULg; Lenartz, Fabian et al

Scientific conference (2008, October 16)

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See detailReconstruction of Missing Satellite Total Suspended Matter Data over the Southern North Sea and English Channel using Empirical Orthogonal Function Decomposition of Satellite Imagery and Hydrodynamical Modelling
Sirjacobs, Damien ULg; Alvera Azcarate, Aïda ULg; Barth, Alexander ULg et al

Poster (2008, October)

Optical remote sensing data archives generally have many gaps caused by clouds or other retrieval problems. However, for the light forcing of ecosystem models continuous fields are required. For ... [more ▼]

Optical remote sensing data archives generally have many gaps caused by clouds or other retrieval problems. However, for the light forcing of ecosystem models continuous fields are required. For parameters exhibiting strong spatial and temporal correlations for regions of similar dynamics or from day to day, the missing data can be estimated by use of statistical techniques. In this context, the Data Interpolation with Empirical Orthogonal Functions (DINEOF) method is used for reconstruction of complete space-time information for surface total suspended matter (TSM) and chlorophyll a from a 5-year archive of MODIS and MERIS products over the Southern North Sea and English Channel. The DINEOF univariate methodology has been previously demonstrated for Mediterranean sea surface temperature data (Alvera-Azcarate et al., 2005, Beckers et al., 2006). Alvera-Azcarate et al (2007) showed that SST reconstructions could be improved by using a multivariate approach in which SST, chlorophyll and wind fields were taken into account together for the analyses. Here, TSM images will be used in combination with information from the COHERENS hydrodynamical model to provide a complete and continuous estimate of surface TSM for the Southern North Sea throughout the period 2003-2005. In addition to the remotely sensed TSM, the DINEOF multivariate analysis will consider wind fields, depth integrated currents, surface elevations and bottom stresses. Reconstucted images are compared with the original incomplete images. Validation of the method is achieved by estimation of information removed from the training data by exclusion of entire images and by addition of artificial clouds. The data reconstruction technique has further applications in the processing and quality control of optical remote sensing data. Perspectives will be outlined for improving the quality control of retrieved parameters and for the improvement of retrievals by adding statistical information to the conventional spectral processing. References: Alvera-Azcarate, A., Barth, A., Rixen, M., and Beckers, J.-M.: Reconstruction of incomplete oceanographic data sets using Empirical Orthogonal Functions. Application to the Adriatic Sea, Ocean Modelling, 9, 325–346, 2005. Alvera-Azcarate, A., Barth, A., Beckers, J. M., and Weisberg, R. H.: Multivariate Reconstruction of Missing Data in Sea Surface Temperature, Chlorophyll and Wind Satellite Fields, Journal of Geophysical Research, 112, C03008, doi:10.1029/2006JC003660, 2007. Beckers J.-M., A. Barth & A. Alvera-Azcarate, DINEOF reconstruction of clouded images including error maps. Application to the Sea-Surface Temperature around Corsican Island, Ocean Sciences, 2: 183–199, 2006. [less ▲]

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See detailRemote Sensing of Suspended Particulate Matter in Turbid Waters: State of the Art and Future Perspectives.
Ruddick, Kevin; Nechad, Bouchra; Park, Youngje et al

Conference (2008, October)

Detailed reference viewed: 28 (3 ULg)