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See detail5th Diva user workshop
Troupin, Charles ULiege; Barth, Alexander ULiege; Belounis, Mahdia et al

Scientific conference (2010, November 03)

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See detailHigh-resolution measurements and modelling of the Cape Ghir upwelling filament during the CAIBEX cruise
Troupin, Charles ULiege; Beckers, Jean-Marie ULiege; Sangrà, Pablo et al

Conference (2010, April 26)

Detailed reference viewed: 35 (1 ULiège)
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See detailSynthesis of regional product activities JRA4-JRA9
Beckers, Jean-Marie ULiege; Alvera Azcarate, Aïda ULiege; Barth, Alexander ULiege et al

Conference (2010, April 01)

Detailed reference viewed: 22 (3 ULiège)
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See detailSeaDataNet regional climatologies: an overview
Troupin, Charles ULiege; Ouberdous, Mohamed ULiege; Barth, Alexander ULiege et al

Poster (2010, March 29)

Detailed reference viewed: 48 (2 ULiège)
See detailA web interface for gridding and visualizing oceanographic data sets
Barth, Alexander ULiege; Alvera Azcarate, Aïda ULiege; Sirjacobs, Damien ULiege 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 detailEstimation of tidal boundary conditions and surface winds by assimilation of high-frequency radar surface currents in the German Bight
Barth, Alexander ULiege; Alvera Azcarate, Aïda ULiege; 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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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 ULiege; Alvera Azcarate, Aïda ULiege; 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 ▲]

Detailed reference viewed: 20 (1 ULiège)
See detailAssimilation of high-frequency radar surface currents measurements to optimize tidal boundary conditions and wind forcing
Barth, Alexander ULiege; Alvera Azcarate, Aïda ULiege; Gurgel, Klaus-Werner et al

Conference (2010)

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 ... [more ▼]

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 gage 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 ▲]

Detailed reference viewed: 12 (2 ULiège)
See detailEnsemble-based assimilation of high-frequency radar surface currents in regional ocean models
Barth, Alexander ULiege; Alvera Azcarate, Aïda ULiege; Beckers, Jean-Marie ULiege et al

Conference (2010)

The results of coastal ocean models depend critically on the accuracy of boundary and initial conditions and atmospheric forcing. The precision of coastal ocean models is limited among others by ... [more ▼]

The results of coastal ocean models depend critically on the accuracy of boundary and initial conditions and atmospheric forcing. The precision of coastal ocean models is limited among others by uncertainty in those forcing fields. Since high-frequency (HF) radar installations provide measurements over a relatively large area, the assimilation of these data has a high potential to reduce the errors in ocean models and to provide a dynamically consistent estimation of the ocean circulation. The assimilation of HF radar data is not without its own challenges: the spatial variation of the surface currents uncertainty, the high temporal resolution of HF radar data, the simultaneous presence of a wide range of processes with distinct spatial and temporal scales (tides and other surface gravity waves, mesoscale and wind-driven circulation), and the generally strong sensitivity of regional models to errors in the boundary conditions and atmospheric forcings. These processess are important aspects to consider in the application of data assimilation methods to HF radar measurements. The results of two data assimilation experiments on the West Florida Shelf (WFS) and the German Bight are presented. HF radar currents are assimilated in a nested West Florida Shelf based on an ensemble of model realizations with different wind forcings. The model is sequentially updated and a filter is implemented to reduce spurious surface-gravity waves. Results of the WFS model assimilating surface currents show an improvement of the model currents not only at the surface but also at depth compared to independent ADCP observations. This West Florida Shelf assimilation experiment does not include tides. Tides are not generated within the domain, but are rather propagated inside the domain through the boundary conditions. The potential of using HF radar data to reduce errors in tidal boundary conditions is shown in a model setup of the German Bight. For improving the modeled tidal variability it is not sufficient to update the model state without updating the boundary conditions. An ensemble smoother to improve the tidal boundary values is presented and validated with independent HF radar measurements and tide-gage data. The ensemble-scheme is also applied to improve the wind forcing by assimilation of surface currents. The improvement of the analyzed wind forcing is assessed by using in-situ wind measurements. [less ▲]

Detailed reference viewed: 30 (2 ULiège)
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See detailDIVA: new features
Beckers, Jean-Marie ULiege; Alvera Azcarate, Aïda ULiege; Barth, Alexander ULiege et al

Scientific conference (2009, October 23)

Detailed reference viewed: 21 (3 ULiège)
See detailHF radar observations of surface currents in the German Bight: descriptive analysis, model-data comparison and non-sequential ensemble data assimilation
Port, A.; Staneva, J.; Schulz-Stellenfleth, J. et al

Conference (2009, September)

Detailed reference viewed: 44 (3 ULiège)
See detailEnsemble smoother for optimizing tidal boundary conditions and bottom roughness by assimilation of High-Frequency Radar surface currents
Barth, Alexander ULiege; Alvera Azcarate, Aïda ULiege; Staneva, J. et al

Conference (2009, September)

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

High-Frequency (HF) radars measure the ocean 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 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-dimension General Estuarine Ocean Model (GETM). Optimized boundary values are obtained using all observations within the assimilation period using the covariances of the ensemble simulation. [less ▲]

Detailed reference viewed: 52 (10 ULiège)
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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 ULiege; Lenartz, Fabian ULiege; Troupin, Charles ULiege 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 ▲]

Detailed reference viewed: 89 (24 ULiège)
See detailSurface circulation of the Caribbean Sea and Gulf of Mexico using 13 years of satellite altimetry data
Alvera Azcarate, Aïda ULiege; Barth, Alexander ULiege; Weisberg, R. H.

Conference (2009)

The surface circulation of the Caribbean Sea and Gulf of Mexico is studied using thirteen years of satellite altimetry data. In the Caribbean Sea, processes at several temporal scales are analyzed: the ... [more ▼]

The surface circulation of the Caribbean Sea and Gulf of Mexico is studied using thirteen years of satellite altimetry data. In the Caribbean Sea, processes at several temporal scales are analyzed: the Caribbean eddies and meanders characteristics, the annual cycle and its variability through time, and the interannual variability, with a cycle of about 4 years affecting the SSH slope across the current and hence the ntensity of the Caribbean Current. Our analyses suggest that this cycle is related to changes in the wind intensity, wind curl and El Niño Southern Oscillation. In the Gulf of Mexico, the variability of the Loop Current is studied. We analyze the timing of anticyclonic eddy detachment from the Loop Current, the relation between the size of these eddies and the period between detachments, and the intrusion of the Loop Current into the Gulf of Mexico. A series of extreme Loop Current intrusions into the Gulf of Mexico, when the current is observed as far as 92°W, are described. The frequency of such events appears to have increased in recent years, with only one event happening from 1992 to 2002 (in 1993) versus three from 2002 to 2006. [less ▲]

Detailed reference viewed: 54 (1 ULiège)
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 ULiege; Barth, Alexander ULiege; Sirjacobs, Damien ULiege 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 ▲]

Detailed reference viewed: 40 (9 ULiège)