Full Text
See detailImproving SMOS Sea Surface Salinity in the Western Mediterranean Sea through Multivariate and Multifractal Analysis
Olmedo, Estrella; Taupier-Letage, Isabelle; Turiel, Antonio; Alvera Azcarate, Aida

in Remote Sensing (2018), 10(3), 485

A new methodology using a combination of debiased non-Bayesian retrieval, DINEOF (Data Interpolating Empirical Orthogonal Functions) and multifractal fusion has been used to obtain Soil Moisture and Ocean Salinity (SMOS) Sea Surface Salinity (SSS) fields over the North Atlantic Ocean and the Mediterranean Sea. The debiased non-Bayesian retrieval mitigates the systematic errors produced by the contamination of the land over the sea. In addition, this retrieval improves the coverage by means of multiyear statistical filtering criteria. This methodology allows obtaining SMOS SSS fields in the Mediterranean Sea. However, the resulting SSS suffers from a seasonal (and other time-dependent) bias. This time-dependent bias has been characterized by means of specific Empirical Orthogonal Functions (EOFs). Finally, high resolution Sea Surface Temperature (OSTIA SST) maps have been used for improving the spatial and temporal resolution of the SMOS SSS maps. The presented methodology practically reduces the error of the SMOS SSS in the Mediterranean Sea by half. As a result, the SSS dynamics described by the new SMOS maps in the Algerian Basin and the Balearic Front agrees with the one described by in situ SSS, and the mesoscale structures described by SMOS in the Alboran Sea and in the Gulf of Lion coincide with the ones described by the high resolution remotely-sensed SST images (AVHRR).

Full Text
See detailAnalysis of SMOS sea surface salinity data using DINEOF
Alvera Azcarate, Aïda; Barth, Alexander; Parard, Gaëlle; Beckers, Jean-Marie

in Remote Sensing of Environment (2016), 180

n analysis of daily Sea Surface Salinity (SSS) at 0.15 ° × 0.15° spatial resolution from the Soil Moisture and Ocean Salinity (SMOS) satellite mission using DINEOF (Data Interpolating Empirical Orthogonal Functions) is presented. DINEOF allows reconstructing missing data using a truncated EOF basis, while reducing the amount of noise and errors in geophysical datasets. This work represents a first application of DINEOF to SMOS SSS. Results show that a reduction of the error and the amount of noise is obtained in the DINEOF SSS data compared to the initial SMOS SSS data. Errors associated to the edge of the swath are detected in 2 EOFs and effectively removed from the final data, avoiding removing the data at the edges of the swath in the initial dataset. The final dataset presents a centered root mean square error of 0.2 in open waters when comparing with thermosalinograph data at their original spatial and temporal resolution. Constant biases present near land masses, large scale biases and latitudinal biases cannot be corrected with DINEOF because persistent signals are retained in high order EOFs, and therefore these need to be corrected separately. The signature of the Douro and Gironde rivers is detected in the DINEOF SSS. The minimum SSS observed in the Gironde plume corresponds to a flood event in June 2013, and the shape and size of the Douro river shows a good agreement with chlorophyll-a satellite data. These examples show the capacity of DINEOF to remove noise and provide a full SSS dataset at a high temporal and spatial resolution with reduced error, and the possibility to retrieve physical signals in zones with high initial errors.

Full Text
See detailReconstruction and analysis of long-term satellite-derived sea surface temperature for the South China Sea
Huynh, Thi Hong Ngu; Alvera Azcarate, Aïda; Barth, Alexander; Beckers, Jean-Marie

in Journal of Oceanography (2016)

Sea surface temperature (SST) is one of the key variables often used to investigate ocean dynamics, ocean-atmosphere interaction, and climate change. Unfortunately, the SST data sources in the South China Sea (SCS) are not abundant due to sparse measurements of in situ SST and a high percentage of missing data in the satellite-derived SST. Therefore, SST data sets with low resolution and/or a short-term period have often been used in previous researches. Here we used Data INterpolating Empirical Orthogonal Functions, a self-consistent and parameter-free method for filling in missing data, to reconstruct the daily nighttime 4-km AVHRR Pathfinder SST for the long-term period spanning from 1989 to 2009. In addition to the reconstructed field, we also estimated the local error map for each reconstructed image. Comparisons between the reconstructed and other data sets (satellite-derived microwave and in situ SSTs) show that the results are reliable for use in many different researches, such as validating numerical models, or identifying and tracking meso-scale oceanic features. Moreover, the Empirical Orthogonal Function (EOF) analysis of the reconstructed SST and the reconstructed SST anomalies clearly shows the subseasonal, seasonal, and interannual variability of SST under the influence of monsoon and El Niño-Southern Oscillation (ENSO), as well as reveals some oceanic features that could not be captured well in previous EOF analyses. The SCS SST often lags ENSO by about half a year. However, in this study, we see that the time lag changes with the frequencies of the SST variability, from 1 to 6 months.

Full Text
See detailLocal ensemble assimilation scheme with global constraints and conservation
Barth, Alexander; Yan, Yajing; Alvera Azcarate, Aida; Beckers, Jean-Marie

in Ocean Dynamics (2016), 66

Ensemble assimilation schemes applied in their original, global formulation respect linear conservation properties if the ensemble perturbations are set up accordingly. For realistic ocean systems, only a relatively small number of ensemble members can be calculated. A localization of the ensemble increment is therefore necessary to filter out spurious long-range correlations. The conservation of the global properties will be lost if the assimilation is performed locally, since the conservation requires a coupling between all model grid points which is removed by the localization. The distribution of ocean observations is often highly inhomogeneous. Systematic errors of the observed parts of the ocean state can lead to spurious adjustment of the non-observed parts via data assimilation and thus to a spurious increase or decrease in long-term simulations of global properties which should be conserved. In this paper, we propose a local assimilation scheme (with different variants and assumptions) which can satisfy global conservation properties. The proposed scheme can also be used for non-local observation operators. Different variants of the proposed scheme are tested in an idealized model and compared to the traditional covariance localization with an ad-hoc step enforcing conservation. It is shown that the inclusion of the conservation property reduces the total RMS error and that the presented stochastic and deterministic schemes avoiding error space rotation provide better results than the traditional covariance localization.

Full Text
See detailESA's Soil Moisture and Ocean Salinity Mission - Achievements and applications after more than 6 years in orbit
Kerr, Yann; Reul, Nicolas; Martín-Neira, Manuel; Drusch, Matthias; Alvera Azcarate, Aida; Wigneron, Jean Pierre; Mecklenburg, Susanne

in Remote Sensing of Environment (2016), 180

Full Text
See detailAssimilation of sea surface temperature, sea ice concentration and sea ice drift in a model of the Southern Ocean
Barth, Alexander; Canter, Martin; Van Schaeybroeck, Bert; Vannitsem, Stéphane; Massonnet, François; Zunz, Violette; Mathiot, Pierre; Alvera Azcarate, Aïda; Beckers, Jean-Marie

in Ocean Modelling (2015), 93

Current ocean models have relatively large errors and biases in the Southern Ocean. The aim of this study is to provide a reanalysis from 1985 to 2006 assimilating sea surface temperature, sea ice concentration and sea ice drift. In the following it is also shown how surface winds in the Southern Ocean can be improved using sea ice drift estimated from infrared radiometers. Such satellite observations are available since the late seventies and have the potential to improve the wind forcing before more direct measurements of winds over the ocean are available using scatterometry in the late nineties. The model results are compared to the assimilated data and to independent measurements (the World Ocean Database 2009 and the mean dynamic topography based on observations). The overall improvement of the assimilation is quantified, in particular the impact of the assimilation on the representation of the polar front is discussed. Finally a method to identify model errors in the Antarctic sea ice area is proposed based on Model Output Statistics techniques using a series of potential predictors. This approach provides new directions for model improvements.

Full Text
See detailAnalysis of high frequency geostationary ocean colour data using DINEOF
Alvera Azcarate, Aïda; Vanhellemont, Quinten; Ruddick, Kevin; Barth, Alexander; Beckers, Jean-Marie

in Estuarine Coastal and Shelf Science (2015), 159

DINEOF (Data Interpolating Empirical Orthogonal Functions), a technique to reconstruct missing data, is applied to turbidity data obtained through the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board Meteosat Second Generation 2. The aim of this work is to assess if the tidal variability of the southern North Sea in 2008 can be accurately reproduced in the reconstructed dataset. Such high frequency data have not previously been analysed with DINEOF and present new challenges, like a strong tidal signal and long night-time gaps. An outlier detection approach that exploits the high temporal resolution (15 min) of the SEVIRI dataset is developed. After removal of outliers, the turbidity dataset is reconstructed with DINEOF. In situ Smartbuoy data are used to assess the accuracy of the reconstruction. Then, a series of tidal cycles are examined at various positions over the southern North Sea. These examples demonstrate the capability of DINEOF to reproduce tidal variability in the reconstructed dataset, and show the high temporal and spatial variability of turbidity in the southern North Sea. An analysis of the main harmonic constituents (annual cycle, daily cycle, M2 and S2 tidal components) is performed, to assess the contribution of each of these modes to the total variability of turbidity. The variability not explained by the harmonic fit, due to the natural processes and satellite processing errors as noise, is also assessed.

Full Text
See detailApproximate and Efficient Methods to Assess Error Fields in Spatial Gridding with Data Interpolating Variational Analysis (DIVA)
Beckers, Jean-Marie; Barth, Alexander; Troupin, Charles; Alvera Azcarate, Aïda

in Journal of Atmospheric and Oceanic Technology (2014), 31(2), 515-530

We present new approximate methods to provide error fields for the spatial analysis tool Diva. It is first shown how to replace the costly analysis of a large number of covariance functions by a single analysis for quick error computations. Then another method is presented where the error is only calculated in a small number of locations and from there the spatial error field itself interpolated by the analysis tool. The efficiency of the methods is illustrated on simple schematic test cases and a real application in the Mediterranean Sea. These examples show that with these methods one has the possibility for quick masking of regions void of sufficient data and the production of "exact" error fields at reasonable cost. The error-calculation methods can also be generalized for use with other analysis methods such as 3D-Var and are therefore potentially interesting for other implementations.

Full Text
See detailMulti-scale optimal interpolation: application to DINEOF analysis spiced with a local optimal interpolation
Beckers, Jean-Marie; Barth, Alexander; Tomazic, Igor; Alvera Azcarate, Aïda

in Ocean Science Discussions (2014), 11

We present a method in which the optimal interpolation of multi-scale processes can be untangled into a succession of simpler interpolations. First, we prove how the optimal analysis of a superposition of two processes can be obtained by different mathematical formulations involving iterations and analysis focusing on a single process. From the 5 different mathematical equivalent formulations we then select the most efficient ones by analyzing the behavior of the different possibilities in a simple and well controlled test case. The clear guidelines deduced from this experiment are then applied in a real situation in which we combine large-scale analysis of hourly SEVIRI satellite images using DINEOF with a local optimal interpolation using a Gaussian covariance. It is 10 shown that the optimal combination indeed provides the best reconstruction and can therefore be exploited to extract the maximum amount of useful information from the original data

Full Text
See detailPreface to Liège Colloquium Special Issue. Remote sensing of colour, temperature and salinity – new challenges and opportunities
Alvera Azcarate, Aïda; Ruddick, Kevin; Minnett, Peter

in Remote Sensing of Environment (2014), 146

Full Text
See detaildivand-1.0: n-dimensional variational data analysis for ocean observations
Barth, Alexander; Beckers, Jean-Marie; Troupin, Charles; Alvera Azcarate, Aïda; Vandenbulcke, Luc

in Geoscientific Model Development (2014), 7

A tool for multidimensional variational analysis (divand) is presented. It allows the interpolation and analysis of observations on curvilinear orthogonal grids in an arbitrary high dimensional space by minimizing a cost function. This cost function penalizes the deviation from the observations, the deviation from a first guess and abruptly varying fields based on a given correlation length (potentially varying in space and time). Additional constraints can be added to this cost function such as an advection constraint which forces the analysed field to align with the ocean current. The method decouples naturally disconnected areas based on topography and topology. This is useful in oceanography where disconnected water masses often have different physical properties. Individual elements of the a priori and a posteriori error covariance matrix can also be computed, in particular expected error variances of the analysis. A multidimensional approach (as opposed to stacking 2-dimensional analysis) has the benefit of providing a smooth analysis in all dimensions, although the computational cost is increased. Primal (problem solved in the grid space) and dual formulations (problem solved in the observational space) are implemented using either direct solvers (based on Cholesky factorization) or iterative solvers (conjugate gradient method). In most applications the primal formulation with the direct solver is the fastest, especially if an a posteriori error estimate is needed. However, for correlated observation errors the dual formulation with an iterative solver is more efficient. The method is tested by using pseudo observations from a global model. The distribution of the observations is based on the position of the ARGO floats. The benefit of the 3-dimensional analysis (longitude, latitude and time) compared to 2-dimensional analysis (longitude and latitude) and the role of the advection constraint are highlighted. The tool divand is free software, and is distributed under the terms of the GPL license (http://modb.oce.ulg.ac.be/mediawiki/index.php/divand).

Full Text
See detailExperimental in situ exposure of the seagrass Posidonia oceanica (L.) Delile to 15 trace elements
Richir, Jonathan; Luy, Nicolas; Lepoint, Gilles; Rozet, Eric; Alvera Azcarate, Aïda; Gobert, Sylvie

in Aquatic Toxicology (2013), 140-141

The Mediterranean seagrass Posidonia oceanica (L.) Delile has been used for trace element (TE) biomonitoring since decades ago. However, present informations for this bioindicator are limited mainly to plant TE levels, while virtually nothing is known about their fluxes through P. oceanica meadows. We therefore contaminated seagrass bed portions in situ at two experimental TE levels with a mix of 15 TEs (Al, V,Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Mo, Ag, Cd, Pb and Bi) to study their uptake and loss kinetics in P. oceanica. Shoots immediately accumulated pollutants from the beginning of exposures. Once contaminations ended, TE concentrations came back to their original levels within two weeks, or at least showed a clear decrease. P. oceanica leaves exhibited different uptake kinetics depending on elements and leaf age: the younger growing leaves forming new tissues incorporated TEs more rapidly than the older senescent leaves. Leaf epiphytes also exhibited a net uptake of most TEs, partly similar to that of P. oceanica shoots. The principal route of TE uptake was through the water column, as no contamination of superficial sediments was observed. However, rhizomes indirectly accumulated many TEs during the overall experiments through leaf to rhizome translocation processes. This study thus experimentally confirmed that P.oceanica shoots are undoubtedly an excellent short-term bioindicator and that long-term accumulations could be recorded in P. oceanica rhizomes.

Full Text
See detailReconstruction of spatiotemporal capture data by means of orthogonal functions: the case of skipjack tuna (Katsuwonus pelamis) in the Central-east Atlantic
Ganzedo, Unai; Erdaide, Oihane; Trujillo-Santana, Aaron; Alvera Azcarate, Aïda; Castro, José J.

in Scientia Marina (2013), 77(4), 575-584

The information provided by the International Commission for the Conservation of Atlantic Tunas (ICCAT) about captures of skipjack tuna (Katsuwonus pelamis) in the Central-east Atlantic has a number of limitations, such as gaps in the statistics for certain fleets or the level of spatiotemporal detail at which catches are reported. As a result, the quality of such data and their effectiveness for providing management advice is limited. In order to reconstruct missing spatial-temporal data of catches, the present study uses Data INterpolating Empirical Orthogonal Functions (DINEOF), a technique for missing data reconstruction applied here for first time to fisheries data. DINEOF is based on an Empirical Orthogonal Functions (EOF) decomposition performed with a Lanczos method. DINEOF was tested with different amounts of missing data, intentionally removing values from 3.4% to 95.2% of data loss, and then compared to the same data set with no missing data. These validation analyses show that DINEOF is a reliable methodological approach of data reconstruction for the purposes of fishery management advice, even when the amount of missing data is very high.

Full Text
See detailGeneration of analysis and consistent error fields using the Data Interpolating Variational Analysis (Diva)
Troupin, Charles; Barth, Alexander; Sirjacobs, Damien; Ouberdous, Mohamed; Brankart, Jean-Michel; Brasseur, Pierre; Rixen, Michel; Alvera Azcarate, Aïda; Belounis, Mahdia; Capet, Arthur; Lenartz, Fabian; Toussaint, Marie-Eve; Beckers, Jean-Marie

in Ocean Modelling (2012), 52-53

The Data Interpolating Variational Analysis (Diva) is a method designed to interpolate irregularly-spaced, noisy data onto any desired location, in most cases on regular grids. It is the combination of a particular methodology, based on the minimisation of a cost function, and a numerically efficient method, based on a finite-element solver. The cost function penalises the misfit between the observations and the reconstructed field, as well as the regularity or smoothness of the field. The intrinsic advantages of the method are its natural way to take into account topographic and dynamic constraints (coasts, advection, . . . ) and its capacity to handle large data sets, frequently encountered in oceanography. The method provides gridded fields in two dimensions, usually in horizontal layers. Three-dimension fields are obtained by stacking horizontal layers. In the present work, we summarize the background of the method and describe the possible methods to compute the error field associated to the analysis. In particular, we present new developments leading to a more consistent error estimation, by determining numerically the real covariance function in Diva, which is never formulated explicitly, contrarily to Optimal Interpolation. The real covariance function is obtained by two concurrent executions of Diva, the first providing the covariance for the second. With this improvement, the error field is now perfectly consistent with the inherent background covariance in all cases. A two-dimension application using salinity measurements in the Mediterranean Sea is presented. Applied on these measurements, Optimal Interpolation and Diva provided very similar gridded fields (correlation: 98.6%, RMS of the difference: 0.02). The method using the real covariance produces an error field similar to the one of OI, except in the coastal areas.

Full Text
See detailOutlier detection in satellite data using spatial coherence
Alvera Azcarate, Aïda; Sirjacobs, Damien; Barth, Alexander; Beckers, Jean-Marie

in Remote Sensing of Environment (2012), 119

Satellite data sets often contain outliers (i.e., anomalous values with respect to the surrounding pixels), mostly due to undetected clouds and rain or to atmospheric and land contamination. A methodology to detect outliers in satellite data sets is presented. The approach uses a truncated Empirical Orthogonal Function (EOF) basis. The information rejected by this EOF basis is used to identify suspect data. A proximity test and a local median test are also performed, and a weighted sum of these three tests is used to accurately detect outliers in a data set. Most satellite data undergo automated quality-check analyses. The approach presented exploits the spatial coherence of the geophysical fields, therefore detecting outliers that would otherwise pass such checks. The methodology is applied to infrared sea surface temperature (SST), microwave SST and chlorophyll-a concentration data over different domains, to show the applicability of the technique to a range of variables and temporal and spatial scales. A series of sensitivity tests and validation with independent data are also conducted.

Full Text
See detailThermocline characterisation in the Cariaco basin: A modelling study of the thermocline annual variation and its relation with winds and chlorophyll-a concentration
Alvera Azcarate, Aïda; Barth, Alexander; Weisberg, Robert H.; Castañeda, Julián J.; Vandenbulcke, Luc; Beckers, Jean-Marie

in Continental Shelf Research (2011), 31(1), 73-84

The spatial and temporal evolution of the thermocline depth and width of the Cariaco basin (Venezuela) is analysed by means of a three-dimensional hydrodynamic model. The thermocline depth and width are determined through the fitting of model temperature profiles to a sigmoid function. The use of whole profiles for the fitting allows for a robust estimation of the thermocline characteristics, mainly width and depth. The fitting method is compared to the maximum gradient approach, and it is shown that, under some circumstances, the method presented in this work leads to a better characterization of the thermocline. After assessing, through comparison with independent {\it in situ} data, the model capabilities to reproduce the Cariaco basin thermocline, the seasonal variability of this variable is analysed, and the relationship between the annual cycle of the thermocline depth, the wind field and the distribution of chlorophyll-a concentration in the basin is studied. The interior of the basin reacts to easterly winds intensification with a rising of the thermocline, resulting in a coastal upwelling response, with the consequent increase in chlorophyll-a concentration. Outside the Cariaco basin, where an open-ocean, oligothrophic regime predominates, wind intensification increases mixing of the surface layers and induces therefore a deepening of the thermocline. The seasonal cycle of the thermocline variability in the Cariaco basin is therefore related to changes in the wind field. At shorter time scales (i.e. days), it is shown that other processes, such as the influence of the meandering Caribbean Current, can also influence the thermocline variability. The model thermocline depth is shown to be in good agreement with the two main ventilation events that took place in the basin during the period of the simulation.

Full Text
See detailCloud filling of ocean colour and sea surface temperature remote sensing products over the Southern North Sea by the Data Interpolating Empirical Orthogonal Functions methodology.
Sirjacobs, Damien; Alvera Azcarate, Aïda; Barth, Alexander; Lacroix, Geneviève; Park, Youngje; Nechad, Bouchra; Ruddick, Kevin; Beckers, Jean-Marie

in Journal of Sea Research (2011), 65(1), 114-130

Optical remote sensing data is now being used systematically for marine ecosystem applications, such as the forcing of biological models and the operational detection of harmful algae blooms. However, applications are hampered by the incompleteness of imagery and by some quality problems. The Data Interpolating Empirical Orthogonal Functions methodology (DINEOF) allows calculation of missing data in geophysical datasets without requiring a priori knowledge about statistics of the full data set and has previously been applied to SST reconstructions. This study demonstrates the reconstruction of complete space-time information for 4 years of surface chlorophyll a (CHL), total suspended matter (TSM) and sea surface temperature (SST) over the Southern North Sea (SNS) and English Channel (EC). Optimal reconstructions were obtained when synthesising the original signal into 8 modes for MERIS CHL and into 18 modes for MERIS TSM. Despite the very high proportion of missing data (70%), the variability of original signals explained by the EOF synthesis reached 93.5 % for CHL and 97.2 % for TSM. For the MODIS TSM dataset, 97.5 % of the original variability of the signal was synthesised into 14 modes. The MODIS SST dataset could be synthesised into 13 modes explaining 98 % of the input signal variability. Validation of the method is achieved for 3 dates below 2 artificial clouds, by comparing reconstructed data with excluded input information. Complete weekly and monthly averaged climatologies, suitable for use with ecosystem models, were derived from regular daily reconstructions. Error maps associated with every reconstruction were produced according to Beckers et al. (2006) [6]. Embedded in this error calculation scheme, a methodology was implemented to produce maps of outliers, allowing identification of unusual or suspicious data points compared to the global dynamics of the dataset. Various algorithms artefacts were associated with high values in the outlier maps (undetected cloud edges, haze areas, contrails, cloud shadows). With the production of outlier maps, the data reconstruction technique becomes also a very efficient tool for quality control of optical remote sensing data and for change detection within large databases.

Full Text
See detailMultiparametric observation and analysis of the Sea
Alvera Azcarate, Aïda; Poulain, Pierre-Marie

in Ocean Dynamics (2011)

Full Text
See detailData Interpolating Empirical Orthogonal Functions (DINEOF): a tool for geophysical data analyses
Alvera Azcarate, Aïda; Barth, Alexander; Sirjacobs, Damien; Lenartz, Fabian; Beckers, Jean-Marie

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 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.

Full Text
See detailComparison between satellite and in situ sea surface temperature data in the Western Mediterranean Sea
Alvera Azcarate, Aïda; Troupin, Charles; Barth, Alexander; Beckers, Jean-Marie

in Ocean Dynamics (2011), 61(6), 767-778

A comparison between in situ and satellite sea surface temperature (SST) is presented for the western Mediterranean Sea during 1999. Several international databases are used to extract in situ data (World Ocean Database (WOD), MEDAR/Medatlas, Coriolis Data Center, International Council for the Exploration of the Sea (ICES) and International Comprehensive Ocean-Atmosphere Data Set (ICOADS)). The in situ data are classified into different platforms or sensors (CTD, XBT, drifters, bottles, ships), in order to assess the relative accuracy of these type of data respect to AVHRR (Advanced Very High Resolution Radiometer) SST satellite data. It is shown that the results of the error assessment vary with the sensor type, the depth of the in situ measurements, and the database used. Ship data are the most heterogeneous data set, and therefore present the largest differences with respect to in situ data. A cold bias is detected in drifter data. The differences between satellite and in situ data are not normally distributed. However, several analysis techniques, as merging and data assimilation, usually require Gaussian-distributed errors. The statistics obtained during this study will be used in future work to merge the in situ and satellite data sets into one unique estimation of the SST.

Full Text
See detailReconstruction of MODIS total suspended matter time series maps by DINEOF and validation with autonomous platform data
Nechad, Bouchra; Alvera Azcarate, Aïda; Ruddick, Kevin; Greenwood, Naomi

in Ocean Dynamics (2011)

In situ measurements of total suspended matter (TSM) over the period 2003–2006, collected with two autonomous platforms from the Centre for Environment, Fisheries and Aquatic Sciences (Cefas) measuring the optical backscatter (OBS) in the southern North Sea, are used to assess the accuracy of TSM time series extracted from satellite data. Since there are gaps in the remote sensing (RS) data, due mainly to cloud cover, the Data Interpolating Empirical Orthogonal Functions (DINEOF) is used to fill in the TSM time series and build a continuous daily “recoloured” dataset. The RS datasets consist of TSM maps derived from MODIS imagery using the bio-optical model of Nechad et al. (Rem Sens Environ 114: 854–866, 2010). In this study, the DINEOF time series are compared to the in situ OBS measured in moderately to very turbid waters respectively in West Gabbard and Warp Anchorage, in the southern North Sea. The discrepancies between instantaneous RS, DINEOF-filled RS data and Cefas data are analysed in terms of TSM algorithm uncertainties, space–time variability and DINEOF reconstruction uncertainty.

Full Text
See detailReconstruction of sea surface temperature by means of DINEOF: a case study during the fishing season in the Bay of Biscay
Ganzedo, Unai; Alvera Azcarate, Aïda; Esnaola, Ganix; Ezcurra, Agustin; Saenz, Jon

in International Journal of Remote Sensing (2011), 32(4), 933-950

The Spanish surface fishery operates mainly during the summer season in the waters of the Bay of Biscay. Sea surface temperature (SST) data recovered from satellite images are being used to improve the operational efficiency of fishing vessels (e.g. reduce search time and increase catch rate) and to improve the understanding of the variations in catch distribution and rate needed to properly manage fisheries. The images used for retrieval of SST often present gaps due to the existence of clouds or satellite malfunction periods. The data gaps can totally or partially affect the area of interest. Within this study, an application of a technique for the reconstruction of missing data called DINEOF (data interpolating empirical orthogonal functions) is analysed, with the aim of testing its applicability in operational SST retrieval during summer months. In this case study, the Bay of Biscay is used as the target area. Three months of SST Moderate Resolution Imaging Spectroradiometer (MODIS) images, ranging from 1 May 2006 to 31 July 2006, were used. The main objective of this work is to test the overall performance of this technique, under potential operational use for the support of the fleet during the summer fishing season. The study is designed to analyse the sensitivity of the results of this technique to several details of the methodology used in the reconstruction of SST, such as the number of empirical orthogonal functions (EOFs) retained, the handling of the seasonal cycle or the length (number of images) of the SST database used. The results are tested against independent SST data from International Comprehensive Ocean–Atmosphere Data Set (ICOADS) ship reports and standing buoys and estimations of the error of the reconstructed SST fields are given. Conclusions show that over this area three months of data are enough for efficient SST reconstruction, which yields four EOFs as the optimal number needed for this case study. An extended EOF experiment with SST and SST with a lag of one day was carried out to analyse whether the autocorrelation of the SST data allows better performance in the SST reconstruction, although theexperiment did not improve the results. The validation studies show that the reconstructed SSTs can be trusted, even when the amount of missing data is very high. The mean absolute deviation maps show that the error is greatest near to the coast and mainly in the upwelling areas close to the French and north-western Spanish coasts.

Full Text
See detailCorrecting surface winds by assimilating High-Frequency Radar surface currents in the German Bight
Barth, Alexander; Alvera Azcarate, Aïda; Beckers, Jean-Marie; Staneva, Joanna; Emil V., Stanev; Johannes, Schulz-Stellenfleth

in Ocean Dynamics (2011), 61(5), 599-610

Surface winds are crucial for accurately modeling the surface circulation in the coastal ocean. In the present work, high-frequency (HF) radar surface currents are assimilated using an ensemble scheme which aims to obtain improved surface winds taking into account ECMWF (European Centre for Medium-Range Weather Forecasts) winds as a first guess and surface current measurements. The objective of this study is to show that wind forcing can be improved using an approach similar to parameter estimation in ensemble data assimilation. Like variational assimilation schemes, the method provides an improved wind field based on surface current measurements. However, the technique does not require an adjoint and it is thus easier to implement. In addition, it does not rely on a linearization of the model dynamics. The method is validated directly by comparing the analyzed wind speed to independent in situ measurements and indirectly by assessing the impact of the corrected winds on model sea surface temperature (SST) relative to satellite SST.

Full Text
See detailA web interface for griding arbitrarily distributed in situ data based on Data-Interpolating Variational Analysis (DIVA)
Barth, Alexander; Alvera Azcarate, Aïda; Troupin, Charles; Ouberdous, Mohamed; Beckers, Jean-Marie

in Advances in Geosciences (2010), 28(28), 29-37

Spatial interpolation of observations on a regular grid is a common task in many oceanographic 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. 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 the 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/Octave file and Keyhole Markup Language (KML) file for visualization in applications such as Google Earth.

Full Text
See detailEnsemble perturbation smoother for optimizing tidal boundary conditions by assimilation of High-Frequency radar surface currents - application to the German Bight
Barth, Alexander; Alvera Azcarate, Aïda; Gurgel, Klaus-Werner; Staneva, Joanna; Port, Alex; Beckers, Jean-Marie; Stanev, Emil V

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

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

Full Text
See detailThe Surface Circulation of the Caribbean Sea and the Gulf of Mexico as Inferred from Satellite Altimetry
Alvera Azcarate, Aïda; Barth, Alexander; Weisberg, Robert H.

in Journal of Physical Oceanography (2009), 39(3), 640657

The surface circulation of the Caribbean Sea and Gulf of Mexico is studied using 13 years of satellite altimetry data. Variability in the Caribbean Sea is evident over several time scales. At the annual scale, sea surface height (SSH) varies mainly by a seasonal steric effect. Interannually, a longer cycle affects the SSH slope across the current and hence the intensity of the Caribbean Current. This cycle is found to be related to changes in the wind intensity, the wind stress curl, and El Niño–Southern Oscillation. At shorter time scales, eddies and meanders are observed in the Caribbean Current, and their propagation speed is explained by baroclinic instabilities under the combined effect of vertical shear and the β effect. Then the Loop Current (LC) is considered, focusing on the anticyclonic eddies shed by it and the intrusion of the LC into the Gulf of Mexico through time. Twelve of the 21 anticyclonic eddies observed to detach from the LC are shed from July to September, suggesting a seasonality in the timing of these events. Also, a relation is found between the intrusion of the LC into the Gulf of Mexico and the size of the eddies shed from it: larger intrusions trigger smaller eddies. A series of extreme LC intrusions into the Gulf of Mexico, when the LC is observed as far as 92°W, are described. The analyses herein suggest that the frequency of such events has increased in recent years, with only one event occurring in 1993 versus three from 2002 to 2006. Transport through the Straits of Florida appears to decrease during these extreme intrusions.

Full Text
See detailA nested model of the Cariaco Basin (Venezuela): description of the basin’s interior hydrography and interactions with the open ocean
Alvera Azcarate, Aïda; Barth, Alexander; Weisberg, Robert H.

in Ocean Dynamics (2009), 59(1), 97-120

A high-resolution (1/60°), three-dimensional numerical circulation model of the Cariaco Basin (Venezuela) is constructed by nesting the Regional Ocean Modeling System (ROMS) in the 1/12° global Hybrid Coordinate Ocean Model (HYCOM). A new bathymetry, computed by merging DBDB2 data and in situ depth measurements using optimal interpolation, is described. This new bathymetry corrects the depth of the channels that connect the Cariaco Basin with the open ocean and which play a very important role in the basin circulation. Results from a 2004 ROMS hindcast are presented. Observations (temperature, salinity, and currents) are used to validate the model results before using the model to describe the annual cycle of the Cariaco Basin and the interactions between the basin and the open ocean. Two modes of interaction are described, the first being the meanders and eddies that travel westward with the Caribbean Current, and the second being a subsurface eastward current that flows along the north coast of South America. The circulation path within the basin is directly related to the intensity of this current. Both mechanisms described play a role in the ventilation of the basin. The present study is also an example of the feasibility of one of the objectives of GODAE (Global Ocean Data Assimilation Experiment): downscaling from a large-scale model to a regional model. In particular, the nesting ratio of 5 used in this work demonstrates that a high-resolution model can be successfully nested in HYCOM.

Full Text
See detailEnhancing temporal correlations in EOF expansions for the reconstruction of missing data using DINEOF
Alvera Azcarate, Aïda; Barth, Alexander; Sirjacobs, Damien; Beckers, Jean-Marie

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 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.

Full Text
See detailDynamically constrained ensemble perturbations - application to tides on the West Florida Shelf
Barth, Alexander; Alvera Azcarate, Aïda; Beckers, Jean-Marie; Weisberg, R. H.; Vandenbulcke, Luc; Lenartz, Fabian; Rixen, Michel

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 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.

Full Text
See detailA coordinated coastal ocean observing and modeling system for the West Florida Continental Shelf
Weisberg, R. H.; Barth, Alexander; Alvera Azcarate, Aïda; Zheng, L. Y.

in Harmful Algae (2009), 8(4), 585-597

The evolution of harmful algal blooms, while dependent upon complex biological interactions, is equally dependent upon the ocean circulation since the circulation provides the basis for the biological interactions by uniting nutrients with light and distributing water properties. For the coastal ocean, the circulation and the resultant water properties, in turn, depend on interactions between both the continental shelf and the deep-ocean and the continental shelf and the estuaries since the deep-ocean and the estuaries are primary nutrient sources. Here we consider a coordinated program of observations and models for the West Florida Continental Shelf (WFS) intended to provide a supportive framework for K. brevis red-tide prediction as well as for other coastal ocean matters of societal concern. Predicated on lessons learned, the goal is to achieve a system complete enough to support data assimilative modeling and prediction. Examples of the observations and models are presented and application is made to aspects of the 2005 red-tide. From an observational perspective, no single set of measurements is adequate. Required are a broad mix of sensors and sensor delivery systems capable of describing the three-dimensional structure of the velocity and density fields. Similarly, models must be complete enough to include the relevant physical processes, and data assimilation provides the integrative framework for maximizing the joint utility of the observations and models. While we are still in the exploratory stages of development, the lessons learned and application examples may be useful to similar programs under development elsewhere. One scientific finding is that the key to understanding K. brevis red-tide on the WFS lies not at the surface, but at depth

Full Text
See detailAssimilation of high-frequency radar currents in a nested model of the West Florida Shelf
Barth, Alexander; Alvera Azcarate, Aïda; Weisberg, R. H.

in Journal of Geophysical Research. Oceans (2008), 113(C8),

High-frequency radar currents are assimilated in a West Florida Shelf (WFS) model based on the Regional Ocean Model System (ROMS), which is nested in the Atlantic Hybrid Coordinate Ocean Model (HYCOM) for the purpose of including both local and deep-ocean forcing, particularly the Gulf of Mexico Loop Current. Tides are not included in this model. An ensemble simulation of the WFS model is carried out under different wind-forcings in order to estimate the error covariance of the model state vector and the covariance between ocean currents and winds. Radial currents measured by high-frequency radar antennas near Saint Petersburg and Venice, Florida, USA, are assimilated using this ensemble-based error covariance. Different assimilation techniques using a time-average ensemble, a filter to reduce surface-gravity waves and an extended state vector including wind stress were tested. Results of the WFS model assimilating surface currents show an improvement of the model currents not only at the surface but also at depth.

Full Text
See detailA nested model study of the Loop Current generated variability and its impact on the West Florida Shelf
Barth, Alexander; Alvera Azcarate, Aïda; Weisberg, R. H.

in Journal of Geophysical Research. Oceans (2008), 113(C5),

A West Florida Shelf model based on the Regional Ocean Modeling System (ROMS) is nested in the North Atlantic Hybrid Coordinate Ocean Model (NAT HYCOM). The focus of this work is the study of the impact of the Loop Current on the West Florida Shelf. In order to assess the model's accuracy, it is compared quantitatively to in situ temperature and velocity measurements on the shelf. A series of sensitivity experiments are conducted to determine the appropriate wind forcing, sea surface temperature relaxation, and mixing scheme. By the inclusion of the Loop Current, we are able to study the propagation of an anticyclonic vortex detaching from the Loop Current. We found that the ambient gradient of potential vorticity is able to explain the vortex path and speed. The statistics of such Loop Current generated flow features were examined by including a tracer marking Loop Current water. This allows to track the Loop Current water on the West Florida Shelf and to quantify the amount of Loop Current water reaching the shelf.

Full Text
See detailBenefit of nesting a regional model into a large-scale ocean model instead of climatology. Application to the West Florida Shelf
Barth, Alexander; Alvera Azcarate, Aïda; Weiberg, R. H.

in Continental Shelf Research (2008), 28(4-5), 561-573

The impact of open boundary conditions on the dynamics and accuracy of a regional West Florida Shelf model is addressed. A ROMS-based model nested in monthly climatological temperature and salinity and in the North Atlantic HYCOM model is implemented. The model results of these nesting implementations are compared to altimetry, in situ temperature time series, and ADCP and high-frequency (HF) radar currents. A significant improvement of the model results is found using the boundary conditions of the HYCOM model over the climatology. The ageostrophic nature of the LC is studied and the benefit using the velocity and surface elevation boundary conditions is shown. (C) 2007 Elsevier Ltd. All rights reserved.

Full Text
See detailAn analysis of the error space of a high-resolution implementation of the GHER hydrodynamic model in the Mediterranean Sea
Vandenbulcke, Luc; Rixen, M.; Alvera Azcarate, Aïda; Barth, Alexander; Beckers, Jean-Marie

in Ocean Modelling (2008), 24(1-2), 46-64

An ensemble of 250 model setups covering the Mediterranean Sea is built by perturbing various parameters: the bathymetry, the initial conditions, atmospheric forcing fields (air temperature, cloud coverage, wind), and internal model parameters (diffusion coefficients). The ensemble is then forwarded in time using the GHER hydrodynamic model, allowing to obtain information about the expected error associated with the forecast in a natural way. The evolution of this error is analyzed. In particular, we examine the time evolution and stationarity of its spatial average, and the spatial distribution of the error at different instants, by means of its first to fourth order moments, and of empirical orthogonal functions. We verify whether the a posteriori error distribution is Gaussian using the Anderson-Darling test. From these results, we are able to assess what parameters and forcing fields are most critical for the forecast. Qualitative conclusions are obtained throughout the text, in accordance with our expectations. Moreover, quantitative estimations of the expected error are also given. (C) 2008 Elsevier Ltd. All rights reserved.

Full Text
See detailMultigrid state vector for data assimilation in a two-way nested model of the Ligurian Sea
Barth, Alexander; Alvera Azcarate, Aïda; Beckers, Jean-Marie; Rixen, Michel; Vandenbulcke, Luc

in Journal of Marine Systems (2007), 65(1-4), 41-59

A system of two nested models composed by a coarse resolution model of the Mediterranean Sea, an intermediate resolution model of the Provencal Basin and a high resolution model of the Ligurian Sea is coupled with a 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 of 200 members by perturbing initial condition and atmospheric forcings. The 50 dominant empirical orthogonal functions (EOF) 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. (c) 2006 Elsevier B.V. All rights reserved.

Full Text
See detailForecast verification of a 3D model of the Mediterranean Sea. The use of discrete wavelet transforms and EOFs in the skill assessment of spatial forecasts
Alvera Azcarate, Aïda; Barth, Alexander; Ben Bouallegue, Zied; Rixen, Michel; Beckers, Jean-Marie

in Journal of Marine Systems (2007), 65(1-4), 460-483

The quality assessment of a nested model system of the Mediterranean Sea is realised. The model has two zooms in the Provencal Basin and in the Ligurian Sea, realised with a two-way nesting approach. The experiment lasts for nine weeks, and at each week sea surface temperature (SST) and sea level anomaly are assimilated. The quality assessment of the surface temperature is done in a spatio-temporal approach, to take into account the high complexity of the SST distribution. We focus on the multi-scale nature of oceanic processes using two powerful tools for spatio-temporal analysis, wavelets and Empirical Orthogonal Functions (EOFs). We apply two-dimensional wavelets to decompose the high-resolution model and observed SST into different spatial scales. The Ligurian Sea model results are compared to observations at each of those spatial scales, with special attention on how the assimilation affects the model behaviour. We also use EOFs to assess the similarities between the Mediterranean Sea model and the observed SST. The results show that the assimilation mainly affects the model large-scale features, whereas the small scales show little or no improvement and sometimes, even a decrease in their skill. The multiresolution analysis reveals the connection between large- and small-scale errors, and how the choice of the maximum correlation length of the assimilation scheme affects the distribution of the model error among the different spatial scales. (c) 2006 Elsevier B.V. All rights reserved.

Full Text
See detailApplication of a SEEK filter to a 1D biogeochemical model of the Ligurian Sea: Twin experiments and real in-situ data assimilation
Raick, Caroline; Alvera Azcarate, Aïda; Barth, Alexander; Brankart, J. M.; Soetaert, K.; Grégoire, Marilaure

in Journal of Marine Systems (2007), 65(1-4), 561-583

The Singular Evolutive Extended Kalman (SEEK) filter has been implemented to assimilate in-situ data in a 1D coupled physical-ecosystem model of the Ligurian Sea. The biogeochemical model describes the partly decoupled nitrogen and carbon cycles of the pelagic food web. The GHER hydrodynamic model (1D version) is used to represent the physical forcings. The data assimilation scheme (SEEK filter) parameterizes the error statistics by means of a set of empirical orthogonal functions (EOFs). Twin experiments are first performed with the aim to choose the suitable experimental protocol (observation and estimation vectors, number of EOFs, frequency of the assimilation,...) and to assess the SEEK filter performances. This protocol is then applied to perform real data assimilation experiments using the DYFAMED data base. By assimilating phytoplankton observations, the method has allowed to improve not only the representation of the phytoplankton community, but also of other variables such as zooplankton and bacteria that evolve with model dynamics and that are not corrected by the data assimilation scheme. The validation of the assimilation method and the improvement of model results are studied by means of suitable error measurements. (c) 2006 Elsevier B.V. All rights reserved.

Full Text
See detailFiltering inertia-gravity waves from the initial conditions of the linear shallow water equations
Barth, Alexander; Beckers, Jean-Marie; Alvera Azcarate, Aïda; Weisberg, R.

in Ocean Modelling (2007), 19(3-4), 204-218

A method for filtering inertia-gravity waves from elevation and depth-averaged velocity is described. This filtering scheme is derived from the linear shallow water equations for constant depth and constant Coriolis frequency. The filtered solution is obtained by retaining only the eigenvectors corresponding to the geostrophic equilibrium and by discarding explicitly the eigenvectors corresponding to the fast moving inertia-gravity waves. An alternative formulation is derived using a variational approach. Both filtering methods are tested numerically for a periodic domain with constant depth and the variational approach is implemented for a closed domain with large topographic variations. The filtering methods significantly reduce the amplitudes of the inertia-gravity waves while preserving the mean flow. The variational method is compared to the Incremental Analysis Update technique and the benefits of the variational filter are presented. (C) 2007 Elsevier Ltd. All rights reserved.

Full Text
See detailMultivariate reconstruction of missing data in sea surface temperature, chlorophyll, and wind satellite fields
Alvera Azcarate, Aïda; Barth, Alexander; Beckers, Jean-Marie; Weisberg, Robert H

in Journal of Geophysical Research. Oceans (2007), 112(C3), 03008

An empirical orthogonal function–based technique called Data Interpolating Empirical Orthogonal Functions (DINEOF) is used in a multivariate approach to reconstruct missing data. Sea surface temperature (SST), chlorophyll a concentration, and QuikSCAT winds are used to assess the benefit of a multivariate reconstruction. In particular, the combination of SST plus chlorophyll, SST plus lagged SST plus chlorophyll, and SST plus lagged winds have been studied. To assess the quality of the reconstructions, the reconstructed SST and winds have been compared to in situ data. The combination of SST plus chlorophyll, as well as SST plus lagged SST plus chlorophyll, significantly improves the results obtained by the reconstruction of SST alone. All the experiments correctly represent the SST, and an upwelling/downwelling event in the West Florida Shelf reproduced by the reconstructed data is studied.

Full Text
See detailStudy of the combined effects of data assimilation and grid nesting in ocean models – application to the Gulf of Lions
Vandenbulcke, Luc; Barth, Alexander; Rixen, Michel; Alvera Azcarate, Aïda; Ben Bouallegue, Zied; Beckers, Jean-Marie

in Ocean Science (2006), 2

Modern operational ocean forecasting systems routinely use data assimilation techniques in order to take observations into account in the hydrodynamic model. Moreover, as end users require higher and higher resolution predictions, especially in coastal zones, it is now common to run nested models, where the coastal model gets its open-sea boundary conditions from a low-resolution global model. This configuration is used in the "Mediterranean Forecasting System: Towards environmental predictions" (MFSTEP) project. A global model covering the whole Mediterranean Sea is run weekly, performing 1 week of hindcast and a 10-day forecast. Regional models, using different codes and covering different areas, then use this forecast to implement boundary conditions. Local models in turn use the regional model forecasts for their own boundary conditions. This nested system has proven to be a viable and efficient system to achieve high-resolution weekly forecasts. However, when observations are available in some coastal zone, it remains unclear whether it is better to assimilate them in the global or local model. We perform twin experiments and assimilate observations in the global or in the local model, or in both of them together. We show that, when interested in the local models forecast and provided the global model fields are approximately correct, the best results are obtained when assimilating observations in the local model.

Full Text
See detailDINEOF reconstruction of clouded images including error maps. Application to the Sea-Surface Temperature around Corsican Island
Beckers, Jean-Marie; Barth, Alexander; Alvera Azcarate, Aïda

in Ocean Science (2006), 2

We present an extension to the Data INterpolating Empirical Orthogonal Functions (DINEOF) technique which allows not only to fill in clouded images but also to provide an estimation of the error covariance of the reconstruction. This additional information is obtained by an analogy with optimal interpolation. It is shown that the error fields can be obtained with a clever rearrangement of calculations at a cost comparable to that of the interpolation itself. The method is presented on the reconstruction of sea-surface temperature in the Ligurian Sea and around the Corsican Island (Mediterranean Sea), including the calculation of inter-annual variability of average surface values and their expected errors. The application shows that the error fields are not only able to reflect the data-coverage structure but also the covariances of the physical fields.

Full Text
See detailCoupling a two-way nested primitive equation model and a statistical SST predictor of the Ligurian Sea via data assimilation
Barth, Alexander; Alvera Azcarate, Aïda; Beckers, Jean-Marie; Rixen, Michel

in Ocean Modelling (2006), 13(3-4), 255-270

A primitive equation model and a statistical predictor are coupled by data assimilation in order to combine the strength of both approaches. In this work, the system of two-way nested models centred in the Ligurian Sea and the satellite-based ocean forecasting (SOFT) system predicting the sea surface temperature (SST) are used. The data assimilation scheme is a simplified reduced order Kalman filter based on a constant error space. The assimilation of predicted SST improves the forecast of the hydrodynamic model compared to the forecast obtained by assimilating past SST observations used by the statistical predictor. This study shows that the SST of the SOFT predictor can be used to correct atmospheric heat fluxes. Traditionally this is done by relaxing the model SST towards the climatological SST. Therefore, the assimilation of SOFT SST and climatological SST are also compared. (c) 2006 Elsevier Ltd. All rights reserved.

Full Text
See detailReconstruction of incomplete oceanographic data sets using empirical orthogonal functions: application to the Adriatic Sea surface temperature
Alvera Azcarate, Aïda; Barth, Alexander; Rixen, Michel; Beckers, Jean-Marie

in Ocean Modelling (2005), 9(4), 325-346

A method for the reconstruction of missing data based on an EOF decomposition has been applied to a large data set, a test case of Sea Surface Temperature satellite images of the Adriatic Sea. The EOF decomposition is realised with a Lanczos method, which allows optimising computational time for large matrices. The results show that the reconstruction method leads to accurate reconstructions as well as a low cpu time when dealing with realistic cases. The method has been tested with different amounts of missing data, artificially adding clouds ranging from 40% to 80% of data loss, and then compared to the same data set with no missing data. A comparison with in situ data has also been made. These validation studies show that results are robust, even when the amount of missing data is very high. The reconstruction of the data from the Adriatic Sea shows realistic features and a reliable temperature distribution. In addition, the method is compared to an Optimal Interpolation reconstruction. The results obtained with both methods are very similar. The main difference is the computational time, which is reduced nearly 30 times with the method presented here. Once the reconstruction has been performed, the EOF decomposition is analysed to show the method's reliability, and a cold event on the Albanian coast is studied. The reconstructed data reflect the effect of wind on the Albanian coast, that led to a cold-water episode in this zone for a 6-day period. (c) 2004 Elsevier Ltd. All rights reserved.

Full Text
See detailTwo-way nested model of mesoscale circulation features in the Ligurian Sea
Barth, Alexander; Alvera Azcarate, Aïda; Rixen, Michel; Beckers, Jean-Marie

in Progress in Oceanography (2005), 66(2-4), 171-189

A coarse resolution primitive equation model of 1/4 degrees resolution is implemented covering the whole Mediterranea Sea. Within this grid a 1/20 degrees resolution model of the Liguro-Provencal basin and the northern part of the Tyrrhenian Sea is embedded. A third fine resolution model of 1/60 degrees is nested in the latter one and simulates the dynamics of the Ligurian Sea. Comparisons between one-way and two-way nesting in simulating the Northern Current (NC) are made. The properties of the Eastern and Western Corsican Current and the Northern Current are investigated with this nesting system. Special attention is given to the variability of the NC. Meanders and interactions with Winter Intermediate Water lenses are shown. Topographic features also lead to a highly variable NC. (c) 2005 Elsevier Ltd. All rights reserved.

Full Text
See detailModelling eutrophication in mesotidal and macrotidal estuaries. The role of intertidal seaweeds.
Alvera Azcarate, Aïda; Ferreira, Joao; Nunes, Joao

in Estuarine Coastal and Shelf Science (2003), 57

The role of intertidal seaweeds in the primary production of mesotidal and macrotidal estuaries has been examined by means of a model, applied to the Tagus Estuary (Portugal). Special attention was paid to the description of the underwater light climate in intertidal areas, and to the importance of the formation of tidal pools. Two approaches were compared for the simulation of suspended particulate matter (SPM) in the pool areas, using three algal species. The use of an erosion–deposition approach to simulate the distribution of SPM in tidal pools gives an increase in net primary productivity per unit area of between 130 and 1300%, when compared to the more conventional approach where the suspended matter in the overlying water in intertidal areas is considered identical to that in the channels. The upscaled erosion–deposition model was applied to tidal pool areas and combined with the more conventional model for other intertidal areas. Results show that annual carbon fixation by intertidal seaweeds in the estuary exceeds 13,500 t C yr−1, and accounts for 21% of the total carbon fixed by all primary producers. The corresponding nitrogen removal by seaweeds corresponds to the annual nutrient loading of a population of 490,000 inhabitants.

Full Text
See detailSolar Photocatalytic Destruction of p-Nitrophenol: A Pedagogical Use of Lab Wastes
Herrera-Melián, J. A.; Doña-Rodríguez, J. M.; Tello Rendón, E.; Soler Vila, A.; Brunet Quetglas, M.; Alvera Azcarate, Aïda; Pascual Pariente, L.

in Journal of Chemical Education (2001), 78(6), 775-777

In this article we propose the destruction of p-nitrophenol wastes obtained in a previous lab experiment, to generate a new lab experiment. The recommended destruction technique is solar TiO2-photocatalysis. When the effects of TiO2 and sunlight are tested separately, a slight decrease of p-nitrophenol is observed; but when TiO2 and sunlight are employed together p-nitrophenol disappears in 1 or 2 h. These experiments do not require sophisticated equipment or special lab training for the students. Groups of students tested different experimental conditions, such as the effect of different light intensities and sources (800-W UV-lamp, sunlight on sunny days, and sunlight on a cloudy day) or the addition of H2O2. p-Nitrophenol is degraded under the three light sources but at different rates. The addition of H2O2 to the TiO2-plus-sunlight system enhances p-nitrophenol degradation kinetics when compared with the TiO2 plus sunlight and H2O2 plus sunlight combinations.