Results 101-120 of 136.
Bookmark and Share    
See detailMapped fields of surface geostrophic currents based on altimetry, and fields of sea surface winds, cloud-free sea surface temperature and chlorophyll concentration using monovariate OI and a multivariate EOF technique
Alvera Azcarate, Aïda ULiege; Barth, Alexander ULiege; Helber, R. W. et al

Conference (2006)

There is an increasing demand for regional oceanic models capable of simulating the regional ocean circulation. Accurate surface forcing functions are necessary to achieve this goal. Here we present ... [more ▼]

There is an increasing demand for regional oceanic models capable of simulating the regional ocean circulation. Accurate surface forcing functions are necessary to achieve this goal. Here we present analyses of several data sets covering the contiguous eastern Gulf of Mexico and southeast Atlantic: a) Wind fields resulting from the blending by optimal interpolation (OI) of NCEP, in situ and QuikSCAT winds. These winds show improvements in the coastal region, where orography and coastal boundary layer effects are important and under-resolved. b) Cloud-free SST, created by merging several SST sources using OI. c) Cloud-free chlorophyll, also created using OI. d) Surface drifter trajectories, generated from geostrophic currents and used to track water masses, with application to the Mississippi River outflow subsequent to Hurricane Katrina. e) Multivariate cloud-free products, using SST and chlorophyll, and SST and QuikSCAT winds, to obtain more accurate reconstructions than the monovariate equivalents. We use an EOF-based method, called DINEOF, which has proven to give similar results to OI-based reconstruction but up to 30 times faster, making it very suitable for operational applications. These data sets, originally created for the West Florida Shelf, have been expanded for the Southeast Atlantic Coastal Ocean Observing System (SEACOOS) and for broader environmental applications. [less ▲]

Detailed reference viewed: 33 (1 ULiège)
See detailA nested West Florida Shelf hydrodynamic model. Application to the 2005 red tide
Barth, Alexander ULiege; Alvera Azcarate, Aïda ULiege; Zheng, L. et al

Conference (2006)

Detailed reference viewed: 17 (1 ULiège)
See detailLocal assimilation of sea surface temperature and elevation in a two-way nested model of the Gulf of Lions, using a single multigrid state vector
Vandenbulcke, Luc ULiege; Barth, Alexander ULiege; Ben Bouallegue, Z. et al

Conference (2005, April)

A three fold nested model is built, covering (a) the Mediterranean Sea (resolution 1/4 degree) (b) its North-Western part (resolution 1/20 degree), and (c) the Gulf of Lions (resolution 1/100 degree). The ... [more ▼]

A three fold nested model is built, covering (a) the Mediterranean Sea (resolution 1/4 degree) (b) its North-Western part (resolution 1/20 degree), and (c) the Gulf of Lions (resolution 1/100 degree). The GHER hydrodynamic model (see e.g. [1]) is used for a simulation of the springs of 1997 and 1998. As the model allows mode splitting, the timestep in each grid is 3 seconds for the barotropic modes, and 3 minutes for the baroclinic modes. ECMWF atmospheric forcings and MODB4/MEDAR climatic data are used. This simulation is run with one-directionnal and bi-directionnal nesting (i.e. without and with statevector feedback), and results are compared. The output of the 1997 and 1998 simulations (3D temperature and salinity fields, and sea surface elevation field) are then used to build 3D multivariate EOFs over the 3 grids alltogether. This guarantees perfect correlations between points from different grids, that are physically at the same location. The following twin experiment is then set up. The simulation from 1998 serves as a control run. A delayed state of this run, serves as initial conditions for the perturbed run. The first 40 EOFs are used to build a reduced-rank model errorspace. Sea surface temperature and sea surface elevation from the reference run, physically located in the Gulf of Lions, are then assimilated in the perturbed run, using a reduced-rank optimal interpolation assimilation scheme. A previous experiment showed non-physical long-range corrections (far outside the Gulf of Lions); these corrections are removed by multiplying the corrections with a radial Gaussian function centered on the corresponding observations. The multivariate statevector ensures corrections are made to temperature, salinity and sea surface elevation fields. Using the corrected fields, the geostrophic equilibrium is used to calculate corrections to the velocity field. In this above twin experiment, observations are assimilated all at once in the 3 grids since a single statevector is used. The results are compared to classic approaches where each grid has a corresponding statevector, and observations are assimilated in a single grid (or in different grids separately). Finally, ongoing research about statistical predictors is presented. Indeed, primitive equation models are too costly to evolve the errorspace in time, even when reducedrank assimilation schemes are used. Statistical methods aim to replace the hydrodynamic model by a much faster method, that would then be used to evolve in time each of the directions of the errorspace, or alternately, the members of an ensemble method. Statistical methods need to be trained on real results; they are thus first tested on the model itself rather than on the errorspace. Preliminary results are presented. [less ▲]

Detailed reference viewed: 35 (2 ULiège)
See detailDerivation of high-resolution ocean surface fields for regional and coastal models
Alvera Azcarate, Aïda ULiege; Barth, Alexander ULiege; He, R. et al

Conference (2005)

Coastal ocean circulation models need high-resolution input fields, such as winds, sea surface height and heat fluxes, to represent the variability of coastal systems. Atmosphere model outputs and ... [more ▼]

Coastal ocean circulation models need high-resolution input fields, such as winds, sea surface height and heat fluxes, to represent the variability of coastal systems. Atmosphere model outputs and satellite data are usually used. However, atmosphere models are usually too coarse and do not represent the high variability of coastal systems, and satellite data do not present a complete coverage, mainly due to cloudiness. In situ observations can accurately represent the complex temporal variability of coastal regions, but usually their spatial coverage is far from optimal. Several products derived from atmosphere models, satellite images and in situ observations are prepared to use as high-resolution input fields suitable for coastal models. An optimally interpolated (OI) wind field has been realized by merging atmosphere model winds, satellite-derived winds (from quikSCAT) and in situ buoy measurements. Other fields, such as geostrophic currents, are derived from Sea Surface Height anomaly obtained from the Topex/Poseidon, Jason, ERS 1/2 and Envisat altimeter product of the CLS center, plus a MICOM mean dynamic topography. Sea Surface Temperature (SST) is also needed to correct surface heat fluxes, but satellite SST is often gappy due to clouds. Two different approaches are investigated in order to obtain complete fields, one using OI and the other using Empirical Orthogonal Functions (EOF) for the reconstruction of missing data. The EOF-based method can reconstruct different variables together, such as SST and surface chlorophyll, by using the correlation between them. This multi-variate approach is used here, and compared to the mono-variate OI product. [less ▲]

Detailed reference viewed: 14 (3 ULiège)
See detailWavelets in the forecast verification of an assimilation experiment in the Ligurian Sea
Alvera Azcarate, Aïda ULiege; Barth, Alexander ULiege; Ben Bouallegue, Z. et al

Conference (2004, June)

Detailed reference viewed: 13 (1 ULiège)
See detailData assimilation in nested-grid models
Vandenbulcke, Luc ULiege; Barth, Alexander ULiege; Ben Bouallegue, Z. et al

Conference (2004, May)

Detailed reference viewed: 22 (3 ULiège)
See detailForecast verification in the Ligurian Sea. Multiresolution analysis and study of the thermocline
Alvera Azcarate, Aïda ULiege; Barth, Alexander ULiege; Rixen, M. et al

Conference (2004, April)

The results of the GHER 3D model are analysed, in order to establish the benefits of a Sea Surface Temperature (SST) assimilation experiment. The influence of the assimilation into the results of the ... [more ▼]

The results of the GHER 3D model are analysed, in order to establish the benefits of a Sea Surface Temperature (SST) assimilation experiment. The influence of the assimilation into the results of the model is examined first in the studied domain, the Ligurian Sea. Then, the benefit of the assimilation outside this domain (in the nearby zones at the surface, and in the Ligurian Sea at depth) is also studied. Finally, the effect of the SST assimilation on the other variables is examined. The procedure for the skill assessment of the model is as follows. First, the classical verification tools are applied: Root Mean Square Error (RMSE), Anomaly Correlation Coefficient (ACC), and Mean Square Error Skill Score (MSESS). Climatology and a free run of the model are used as reference systems. After this, a multiresolution analysis is carried out, to decompose the model results into different spatial scales. At each scale, the error measures mentioned above are applied. This allows to establish which scales are mainly contributing to the error. For this multiresolution analysis, a Discrete Wavelet Transform is used. The study of the assimilation benefits at depth is made by comparison with CTDs. The aim is to study the position and strength of the thermocline, as this zone presents high variability and it has an important impact into the system. A good representation of the thermocline is thus interesting. [less ▲]

Detailed reference viewed: 19 (1 ULiège)
See detailA reduced order data assimilation scheme coupled with a two-way nested model. Application to the Ligurian Sea
Barth, Alexander ULiege; Alvera Azcarate, Aïda ULiege; Beckers, Jean-Marie ULiege et al

Conference (2004, April)

A system of nested models is coupled with a data assimilation module. The system is composed by a low resolution model (1/4 ) covering the whole Mediterranean Sea, an intermediate resolution model (1/20 ... [more ▼]

A system of nested models is coupled with a data assimilation module. The system is composed by a low resolution model (1/4 ) covering the whole Mediterranean Sea, an intermediate resolution model (1/20 ) of the Liguro-Provençal basin and a high resolution model (1/60 ) simulating the fine mesoscale structures in the Ligurian Sea. Boundary conditions and the averaged fields (feedback) are exchanged between two successive nesting levels. A reduced order, optimal interpolation data assimilation scheme was implemented. The state vector is composed by temperature, salinity and sea surface elevation. Novel in the present approach is that these variables from the three nested model grids are assembled to one multigrid state vector. This implementation allows to take into account the correlation of the variables across the nested model grids in order to avoid for example artificial gradients after an assimilation cycle. The eigenvectors of the covariance matrix are constructed by an EOF analysis of the free model run. Cross-grid correlations especially in the overlapping domains are thus consistently represented. Horizontal correlations over long distances are suppressed by multiplying each error mode with a set of radial Gaussian functions. This procedure increases considerably the rank of the covariance matrix but ensures the local impact of each observation. Sea surface temperature (SST, from the DLR EOWEB), sea surface height (SSH, from the CLS) and CTD profiles (SIRENA cruise from SACLANT Center and cruises from the MEDAR/Medatlas database) are assimilated into the model. In overlapping model grids the measurements are related to the highest resolution grid. Since the SSH has a resolution of 1/8 , the surface elevation of the Ligurian Sea and the Liguro-Provençal model are filtered in order to be coherent with the space scales present in the observations. Starting from the 1st January 1998 the low and intermediate resolution models are spun up for 18 months. The initial conditions for the Ligurian Sea are interpolated from the intermediate resolution model. The three models are then integrated until August 1999. During this period SST, SSH and the CTD profiles are assimilated. The results are compared with a free model run. In particular the model forecast just before the assimilation step are compared with the observations. The model forecast and the measurements are then independent and the difference is a measure of the model forecast skill and the impact of the previous assimilation cycles. [less ▲]

Detailed reference viewed: 44 (1 ULiège)
See detailForecast assessment in the mediterranean sea : A structure oriented approach
Ben Bouallegue, Z.; Alvera Azcarate, Aïda ULiege; Vandenbulcke, Luc ULiege et al

Conference (2004, April)

The MFSTEP1 project is an international scientific collaboration program which aims to create an operational forecasting system for the Mediterranean sea. The simulations provided at the basin scale are ... [more ▼]

The MFSTEP1 project is an international scientific collaboration program which aims to create an operational forecasting system for the Mediterranean sea. The simulations provided at the basin scale are 10 days forecasting fields in a 3-D ocean. The hydrodynamic model primitive equations are combined with the data assimilation scheme SOFA2. The data collection is done in a near real time process and the set of XBT and SLA observations are used in one week assimilation cycle. The forecast assessment is traditionally realised using classical statistic tools like RMSE or the bias and the assimilation benefit is estimated by skill scores using as reference the free model, persistence or also climatology. The process is essentially based on the comparison of two fields at a fixed time, one corresponding to the simulations and the other one to the observations. The interest of such statistical methods comes in the quick and sensitive appreciation they provide about the quality, accuracy and consistency of the simulation. However this kind of assessment procedure brings in it self a conceptual contradiction: performances of a dynamical process are measured using a snap shot view of the ocean state. A system evolution assessment procedure is carried out within the framework of the MFSTEP hindcast. The hindcast system is intrinsically analysed (without independent informations) comparing the background forecast evolution with the abrupt variation which occurs at the observations assimilation time steps. The system evolution between two consecutive days is analysed using a decomposition method. The temperature and salinity fields evolution in a sub-region of theWestern Mediterranean basin is seen in a structural point of view and decomposed in three elements : a global spatial(2D) displacement which conserves the internal features, a global intensity variation which expresses the system energy changes, and an internal pattern changes ensemble. The index of evolution used is a mean squared difference between the two consecutive simulations. The displacement contribution is estimated after the determination of the shift (field translation) which minimises the local mean squared difference between the translated field and the next simulation. The intensity variation contribution is calculated as the difference of the squared mean fields. The remaining difference after manipulations is considered as the internal pattern changes contribution to the system evolution. [less ▲]

Detailed reference viewed: 65 (6 ULiège)
See detailA nested-grid model with data assimilation in the Gulf of Lions
Vandenbulcke, Luc ULiege; Barth, Alexander ULiege; Alvera Azcarate, Aïda ULiege et al

Conference (2004, April)

When a model combines the use of nested grids and data assimilation, a preliminary, simple, 1D test case showed the interest of combining the different state vectors coming from the different grids, into ... [more ▼]

When a model combines the use of nested grids and data assimilation, a preliminary, simple, 1D test case showed the interest of combining the different state vectors coming from the different grids, into one single vector, and using global error matrices covering all the grids at once. In this case, the assimilation procedure provides errorspace feedback from the fine grid to the coarser grid, which proves to be even more important than the statevector feedback. For data located in the fine grid, assimilation of the same data in the coarse grids is not necessary anymore, as both model and errorspace feedback is performed during assimilation. Large data transfers from local to basin-scale models can be avoided. The GHER hydrodynamic model (for a full description, see e.g. [1]) is applied to a three times nested model covering (a) the Mediterrannean Sea at 1/4 degree, (b) the Liguro-Provencal Bassin at 1/20 degree, and (c) the Gulf of Lions at 1/100 degree. The simulation starts on Januari 1st, 1998, using ECMWF atmospheric forcings and MODB4/MEDAR climatic data. As the model allows mode splitting, the simulation uses 2D timesteps of 3 seconds, and 3D timesteps of 3 minutes, on each grid. A twin experiment is performed. The perturbed initial condition is a delayed model state of the reference run. An initial reduced-rank model errorspace is constructed from 20 EOFs, themselves built from the reference run, over all three grids at the same time. Surface temperature and salinity from the reference run are assimilated in the model every 24 hours, using reduced-rank optimal interpolation (see [2]). Different simulations are implemented, using different ways to combine grid nesting and data assimilation: with or without state vector feedback, with data assimilation only in the local grid, or in the coarser grids, or both, and with or without errorspace feedback (i.e. with 3 separated statevectors or with one global statevector). The comparison of those experiments comfirms that using one global statevector reduces the error in the coarser grids much faster. The effect of data assimilation, and the performances of the different methods, can be examined by calculating RMS errors between the perturbed runs and the reference run. They can also be observed by following the model state trajectory in the EOFspace (for example, using the first three EOFs). In the context of the twin experiment described above, the first assimilation cycle clearly brings the model back in time. This is consistent with the choice of the perturbed initial conditions, being a delayed state of the reference run. The following assimilation cycles have little effect, as the trajectory is already almost brought back on the reference trajectory. If other parameters are modified too (e.g. the atmospheric fluxes), each assimilation cycle has an important effect on the modelstate trajectory. A new experiment performs assimilation in the Gulf of Lions in the spring of 1998 using real observations. Different variables can be assimilated, using data collected during the FETCH campaign: NOAA/AVHRR SST, temperature and salinity from Atalante CTDs, or altimetric data from the ERS2 or TOPEX satellites. [less ▲]

Detailed reference viewed: 64 (0 ULiège)
Full Text
See detailAssimilation of sea surface temperature and sea surface height in a two-way nested primitive equation model of the Ligurian Sea
Barth, Alexander ULiege

Doctoral thesis (2004)

A coarse grid primitive equation model of 1/4° resolution is implemented covering the whole Mediterranean Sea. Within this grid a 1/20° resolution model of the Liguro-Provençal basin and the northern part ... [more ▼]

A coarse grid primitive equation model of 1/4° resolution is implemented covering the whole Mediterranean Sea. Within this grid a 1/20° resolution model of the Liguro-Provençal basin and the northern part of the Tyrrhenian Sea is embedded. A third fine resolution model of 1/60° is nested in the latter one and simulates the dynamics of the Ligurian Sea. Comparisons between one-way and two-way nesting in representing the Northern Current (NC) are made. This system of nested models is coupled with a simplified Kalman-filter based assimilation method. The state vector for the data assimilation is composed by the temperature, salinity and elevation of the three models. The forecast error is estimated by an ensemble run by perturbing initial conditions and atmospheric forcings. The leading empirical orthogonal functions (EOF) of this ensemble are taken as the error covariance of the model forecast. This error covariance is assumed to be constant in time. Sea surface temperature (SST) and sea surface height (SSH) are assimilated in this system. Data assimilation is also used to couple the hydrodynamic model with a statistical predictor of SST in the Ligurian Sea. The forecast improvement of this hybrid modelling system is shown and applications to operational models are highlighted. [less ▲]

Detailed reference viewed: 56 (8 ULiège)
See detailStudy of the impact of satellite data assimilation into a hydrodynamical model of the ligurian sea. Comparison between sst fields and sst satellite-based predicted fields
Alvera Azcarate, Aïda ULiege; Barth, Alexander ULiege; Rixen, M. et al

Conference (2004)

The verification of a 3D hydrodynamic model of the Ligurian Sea is presented. Two assimilation experiments have been carried out with this model: the assimilation of real SST, and the assimilation of SST ... [more ▼]

The verification of a 3D hydrodynamic model of the Ligurian Sea is presented. Two assimilation experiments have been carried out with this model: the assimilation of real SST, and the assimilation of SST forecasted by a statistical predictor. The aim of the study is to establish the skill of the model in these two configurations. The assimilation of predicted SST can help to increase the model skill when observations are not available, and preliminary results show that both approaches obtained similar results. The verification is done in a multi-scale approach, by decomposing the model results and the observations into several spatial scales, using 2D discrete wavelet transforms. At each scale the error between the model and the observations is calculated, and the scales where the biggest errors occur can be identified. The variability distribution of the model and the observations is also examined at each scale, to study the impact of the assimilation on the model variability. This methodology provides a scale-dependent insight in the study of the assimilation of SST and predicted SST. The differences between both assimilated data and how these differences affect the model results are examined. [less ▲]

Detailed reference viewed: 21 (2 ULiège)
See detailReconstruction of missing data in geophysical fields. resolution of moving patterns
Alvera Azcarate, Aïda ULiege; Barth, Alexander ULiege; Rixen, M. et al

Conference (2004)

A method for the reconstruction of missing data in large data sets is presented. The method, DINEOF (Data INterpolating Empirical Orthogonal Functions), calculates the missing data from an optimal number ... [more ▼]

A method for the reconstruction of missing data in large data sets is presented. The method, DINEOF (Data INterpolating Empirical Orthogonal Functions), calculates the missing data from an optimal number of EOFs determined by cross-validation. A Lanczos method has been used for the EOF decomposition, in order to work with large matrices. DINEOF has been applied to two data sets of sea surface temperature: a set of 105 images in the Adriatic Sea and a set of 216 images in Tanganyika Lake. These data sets present 52% and 37% of missing data respectively, due to cloud coverage. Several validation studies have been carried out: comparison with in situ data and reconstruction of increasing amounts of missing data, from 40% to 80% of the total data, by artificially adding clouds. All tests show that results are robust. DINEOF uses a classical EOF decomposition. In this work we also present a different EOF decomposition, known as Extended EOF (ExEOF) or Singular Spectrum Analysis (SSA). This technique consists in using a lagged version of the matrix being analysed. By taking into account both the spatial and temporal correlation of the data, the ExEOF technique resolves spatio-temporal moving patterns in a more accurate way. Preliminary results show that this technique helps to better reconstruct the missing data in our data sets. [less ▲]

Detailed reference viewed: 21 (3 ULiège)
See detailAssimilation of Sea Surface Temperature predicted by a satellite-based forecasting system in a doubly nested primitive equation model of the Ligurian Sea
Barth, Alexander ULiege; Alvera Azcarate, Aïda ULiege; Alvarez, A. et al

Conference (2004)

Data assimilation is traditionally used to combine model dynamics and observations in a statistical optimal way. Assimilation of observations improves therefore hindcasts and nowcasts of the ocean state ... [more ▼]

Data assimilation is traditionally used to combine model dynamics and observations in a statistical optimal way. Assimilation of observations improves therefore hindcasts and nowcasts of the ocean state than otherwise obtained by the model alone. The observational constraints are necessary to reduce uncertainties and imperfections of the ocean model. Due to the obvious lack of future observations, the model forecast cannot be controlled by observations and the predictive skill degrades as the forecast time lag increases. The error grow is not only caused by the chaotic nature of the system but also by the biases and drifts of the model. The later part can be reduced by considering different models with different imperfections. Data assimilation provides the statistical frame for merging the different model results. A primitive equation model of the Mediterranean Sea (1/4° resolution) has been implemented with two successive grid refinements of the Liguro-Provençal Basin (1/20°) and the Ligurian Sea (1/60°) respectively (Barth et al, 2003). The dependence of the ``parent'' model and the embedded ``child'' model is bi-directional; it involves the exchange of boundary conditions and feedback between the models. Alvarez el al. (2004) developed a statistical predictor for forecasting the SST of the Ligurian Sea with a time lag of 7 days based on the previous remote sensed SST. The degrees of freedom of the SST are reduced by an Empirical Orthogonal Function (EOF) analysis. A genetic algorithm trained by the historical SST evolution in the Ligurian Sea is used to predict the EOF amplitudes. Observed and forecasted SST are assimilated in the hydrodynamic model and the results of this two experiments are compared to the model run without assimilation. The assimilation of the forecasted SST reduces the error of the model by an amount comparable to the assimilation of real SST, showing the potential of skill improvement of combining statistical and hydrodynamic models. [less ▲]

Detailed reference viewed: 18 (1 ULiège)
See detailReconstruction of incomplete satellite images in the Adriatic Sea. Study of an upwelling in the Albanian coast
Alvera Azcarate, Aïda ULiege; Barth, Alexander ULiege; Rixen, M. et al

Conference (2004)

Clouds in satellite images are a common problem. When working with these data is often desirable, if not necessary, to have complete fields. A method for the reconstruction of missing data in large data ... [more ▼]

Clouds in satellite images are a common problem. When working with these data is often desirable, if not necessary, to have complete fields. A method for the reconstruction of missing data in large data sets (Beckers and Rixen 2003, Alvera-Azcárate et al, 2004) is presented. The method, called DINEOF (Data INterpolating Empirical Orthogonal Functions), calculates the missing data from an optimal number of EOFs determined by cross-validation. A Lanczos method has been used for the EOF decomposition, in order to work with large matrices. In this work we present the reconstruction of a cloudy set of AVHRR SST satellite images of the Adriatic Sea. The results obtained are robust, as can be seen when comparing them to in situ observations [CTD profiles from MEDAR/Medatlas database (Medar Group, 2002)]. The results of the reconstruction are analysed, in particular a cold water event in the Albanian coast. This kind of event can be due to the action of winds, namely the Bora wind. Temporal EOFs and surface winds from ECMWF 40 years reanalysis are used to study this event. [less ▲]

Detailed reference viewed: 39 (2 ULiège)