References of "Lenartz, Fabian"
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See detailData Interpolating Empirical Orthogonal Functions (DINEOF): a tool for geophysical data analyses
Alvera Azcarate, Aïda ULg; Barth, Alexander ULg; Sirjacobs, Damien ULg et al

in Mediterranean Marine Science (2011), 12(3), 5-11

An overview of the technique called DINEOF (Data Interpolating Empirical Orthog- onal Functions) is presented. DINEOF reconstructs missing information in geophys- ical data sets, such as satellite imagery ... [more ▼]

An overview of the technique called DINEOF (Data Interpolating Empirical Orthog- onal Functions) is presented. DINEOF reconstructs missing information in geophys- ical data sets, such as satellite imagery or time series. A summary of the technique is given, with its main characteristics, recent developments and future research di- rections. DINEOF has been applied to a large variety of oceanographic variables in various domains of different sizes. This technique can be applied to a single variable (monovariate approach), or to several variables together (multivariate approach), with no complexity increase in the application of the technique. Error fields can be computed to establish the accuracy of the reconstruction. Examples are given to illustrate the capabilities of the technique. DINEOF is freely offered to download, and help is provided to users in the form of a wiki and through a discussion email list. [less ▲]

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See detailEnhanced ocean temperature forecast skills through 3-D super-ensemble multi-model fusion
Lenartz, Fabian ULg; Mourre, B.; Barth, Alexander ULg et al

in Geophysical Research Letters (2010), 37(L19606),

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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 detailCan we use exergy index and the microbenthic loop as indicators of perturbations in Posidonia oceanica (L.) Delile meadows?
Pete, Dorothée ULg; Lenartz, Fabian ULg; Velimirov, Branko et al

Poster (2009, November 27)

Nowadays, many anthropogenic perturbations threaten the Mediterranean Sea. Posidonia oceanica , its endemic phanerogam, is often used as a pollution descriptor. Unfortunately, it does not react very fast ... [more ▼]

Nowadays, many anthropogenic perturbations threaten the Mediterranean Sea. Posidonia oceanica , its endemic phanerogam, is often used as a pollution descriptor. Unfortunately, it does not react very fast because of its low turnover rate (i.e. 1.5y-1). To solve that problem, this project proposes to use the microbenthic loop (meiofauna, bacteria, microphytobenthos and organic matter) of this important coastal ecosystem to detect anthropogenic pollutions earlier, because its components may react more rapidly than the posidonia plant. Every components of the loop are investigated and characterized, in order to determine their reactions to perturbations and use them in the calculation of the exergy index. This index comes from the thermodynamic theory of ecosystems and expresses the distance of an ecosystem, at a given state, from its equilibrium. The higher this index, the closer from its optimum state (climax) the ecosystem is. To calculate it, the biomass of each part of the studied ecosystem, weighted by a factor called β, is needed. This factor is estimated on a genetic basis and given in Jørgensen et al. (2005). The final aim of this project is to show if the exergy index can be used in the Mediterranean Sea as a tool in monitoring strategies, specifically in the sedimentary compartment of P. oceanica meadows. To realise these goals, a reference meadow was chosen near the research station STARESO (STAtion de REcherches Sous-marines et Oceanographiques) in Calvi Bay (Corsica, France). This meadow is studied since the 80’s and its good state of health is proven. Seasonal, spatial (small scale) and bathymetric variations in the microbenthic loop are studied there since 2007, by sediment cores (diameter=4.7cm, length=10cm). Those results are compared for 2008 with the patterns observed in a supposed perturbed site, situated close to a fish farm, in Calvi Bay too. In situ experiments were also led in summer 2009. During three months, a shading experiment and an enrichment of the sediment with sediment coming from under the aquaculture (once a week) were performed. Those experiments aimed to understand reactions of the microbenthic loop to those kinds of perturbations, that are often occurring close to a fish farm. Up to now, that study has led to a better understanding of seasonal and bathymetric patterns in the microbenthic loop of P. oceanica. The most important result obtained is the existence of an important spatial heterogeneity at small scale in that ecosystem. This phenomenon must absolutely be taken into account in every study based on the sediment in P. oceanica meadows. [less ▲]

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See detailSuper-Ensemble techniques: application to surface drift prediction
Vandenbulcke, Luc ULg; Beckers, Jean-Marie ULg; Lenartz, Fabian ULg et al

in Progress in Oceanography (2009), 82(3), 149-167

The prediction of surface drift of floating objects is an important task, with applications such as marine transport, pollutant dispersion, and search-and-rescue activities. But forecasting even the drift ... [more ▼]

The prediction of surface drift of floating objects is an important task, with applications such as marine transport, pollutant dispersion, and search-and-rescue activities. But forecasting even the drift of surface waters is very challenging, because it depends on complex interactions of currents driven by the wind, the wave field and the general prevailing circulation. Furthermore, although each of those can be forecasted by deterministic models, the latter all suffer from limitations, resulting in imperfect predictions. In the present study, we try and predict the drift of two buoys launched during the DART06 (Dynamics of the Adriatic sea in Real-Time 2006) and MREA07 (Maritime Rapid Environmental Assessment 2007) sea trials, using the so-called hyper-ensemble technique: different models are combined in order to minimize departure from independent observations during a training period; the obtained combination is then used in forecasting mode. We review and try out different hyper-ensemble techniques, such as the simple ensemble mean, least-squares weighted linear combinations, and techniques based on data assimilation, which dynamically update the model’s weights in the combination when new observations become available. We show that the latter methods alleviate the need of fixing the training length a priori, as older information is automatically discarded. When the forecast period is relatively short (12 h), the discussed methods lead to much smaller forecasting errors compared with individual models (at least three times smaller), with the dynamic methods leading to the best results. When many models are available, errors can be further reduced by removing colinearities between them by performing a principal component analysis. At the same time, this reduces the amount of weights to be determined. In complex environments when meso- and smaller scale eddy activity is strong, such as the Ligurian Sea, the skill of individual models may vary over time periods smaller than the forecasting period (e.g. when the latter is 36 h). In these cases, a simpler method such as a fixed linear combination or a simple ensemble mean may lead to the smallest forecast errors. In environments where surface currents have strong mean-kinetic energies (e.g. the Western Adriatic Current), dynamic methods can be particularly successful in predicting the drift of surface waters. In any case, the dynamic hyper-ensemble methods allow to estimate a characteristic time during which the model weights are more or less stable, which allows predicting how long the obtained combination will be valid in forecasting mode, and hence to choose which hyper-ensemble method one should use. [less ▲]

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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 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 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 detailSpatial heterogeneity at small scale in the microbenthic loop of Posidonia oceanica meadows
Pete, Dorothée ULg; Lenartz, Fabian ULg; Velimirov, Branko et al

Conference (2008, October)

In the Mediterranean coastal zone, one the most important ecosystem is the Posidonia oceanica meadow. This seagrass is endemic of the Mediterranean Sea and plays many important ecological roles like ... [more ▼]

In the Mediterranean coastal zone, one the most important ecosystem is the Posidonia oceanica meadow. This seagrass is endemic of the Mediterranean Sea and plays many important ecological roles like oxygen production, nursery for numerous commercial species of fishes and protection of coastal zones by reducing the impact of waves. However, there is a severe lack of informations on small scale variations in its sediment compartment. In an attempt to understand spatial variations in the microbenthic loop (bacteria, organic matter, microphytobenthos and meiofauna) of this ecosystem, an experiment was led in Calvi Bay (Corsica, France), in March 2008, at 10 m depth. Twelve points were sampled randomly in a 125 x 125 cm grid, divided into twenty-five 25 x 25 cm squares, to assess and describe the spatial distribution and variations of different parameters of the sediment. Those parameters are granulometry, density of the P. oceanica meadow, nutrients concentration in pore water, bacteria (biomass, abundance, morphotypes), organic matter (biomass), microphytobenthos (biomass), roots and rhizomes (biomass) and meiofauna (biomass). Distribution maps were produced using the DIVA (Data-Interpolating Variational Analysis) method. Our results prove that the sediment compartment is highly heterogeneous at small scale, especially for bacteria and in the first centimeter of sediment cores. Moreover, a correlation has been established between microphytobenhtos variations and phosphate concentration in pore water. For the first time, such small scale variations are depicted in a P. oceanica meadow, which underlines the importance to take them into account in sampling strategies. [less ▲]

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See detailSmall scale variations in the microbenthic loop of Posidonia oceanica meadows: an experimental interpolation design.
Pete, Dorothée ULg; Lenartz, Fabian ULg; Velimirov, Branko et al

Poster (2008, August)

In the sediment compartment of Posidonia oceanica meadows, there is a severe lack of information on small scale variations. In an attempt to understand spatial variations of the microbenthic loop ... [more ▼]

In the sediment compartment of Posidonia oceanica meadows, there is a severe lack of information on small scale variations. In an attempt to understand spatial variations of the microbenthic loop (bacteria, organic matter, microphytobenthos and meiofauna), an experiment based on interpolation methods was led in Calvi Bay (Corsica, France), in March 2008, at 10 m depth. Twelve points were sampled randomly in a 125 x 125 cm square, divided into twenty-five 25 x 25 cm squares, to assess and describe the spatial distribution and variations of different parameters of the sediment. Those parameters are granulometry, density of P. oceanica, concentration in nutrients in the pore water, bacteria (biomass, abundance, morphotypes), organic matter (biomass), microphytobenthos (biomass), roots and rhizomes (biomass) and meiofauna (biomass). Results and distribution maps of the respective sediment parameters will be presented for the first time. [less ▲]

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See detailError analysis of a high-resolution physical model of the Mediterranean Sea
Vandenbulcke, Luc ULg; Barth, Alexander ULg; Alvera Azcarate, Aïda ULg et al

Conference (2007)

We analyze the errors that are inevitably associated to hydrodynamic models, in a realistic case. The error of the GHER model in the Mediterranean Sea has already been studied in e.g. Beckers et al. (2000 ... [more ▼]

We analyze the errors that are inevitably associated to hydrodynamic models, in a realistic case. The error of the GHER model in the Mediterranean Sea has already been studied in e.g. Beckers et al. (2000) by comparing it with other primitive equation models, or in Alvera (2004) by comparing the model with observations and with the climatology, using usual statistical methods and also wavelet decompositions. In this study, we rather study the sensitivity of the model to various variables using an ensemble of models. We chose a relatively high resolution, 1/16°, corresponding to the resolution now used in operational OGCMs covering the Mediterranean, such as the MFS system (http://www.bo.ingv.it/mfs). We explain how we generated an ensemble of model simulations, where various more-or-less well known inputs are allowed to vary according to the uncertainty affecting them. Statistics calculated on this ensemble are, in fact, the response of the non-linear hydrodynamic system to errors on the forcing terms. When those statistics are calculated at a certain timestep, they allow us to provide a spatial analysis of the model error; statistics calculated over the time dimension will show whether errors are intensified by the system, or rather disappear. The model error is interesting as such. However, it can also be used for different purposes. For example, it allows using data assimilation techniques without needing the usual assumptions of reduced-rank Kalman Filters. It also allows studying the sensitivity of coupled model (biological, oil spill, search-and-rescue, …) to physical forcings. [less ▲]

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