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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). PREDANTAR, EMODNET Chemistry 2, SeaDataNet II

The genus Patagonotothen is the most common Nototheniid on the Patagonian Shelf and slope and is part of the by-catch species in the bottom trawl fisheries. This paper presents preliminary results from the EC CRAFT project “Promoting higher added value to a finfish species rejected to sea”, aiming to develop the research and the technology necessary to promote higher added value to fishing activity by taking profit from a finfish species (Rockcod, Patagonotothen spp.) not known to consumers and currently discarded by the EU fishing fleet operating in the South West Atlantic in order to supply the EU seafood industry with a good quality raw material for human food manufacturing. Historical fishery data series (26 168 commercial hauls of which 12 745 were positive), including effort, catches and discards, as well as biological and environmental information, from 1988 onwards was used to describe and quantify patterns and spatio-temporal changes in the rockcod fishery. These data was collected by scientific observers on board commercial vessels.GIS analysis was carried out in order to study the seasonal geographical changes in the distribution of abundance, SST and densities calculated from CPUE. Fishery and environmental data as well as SST data derived from the NOAA Advanced Very High Resolution Radiometer (AVHRR), were analysed in order to find monthly variations in spatial and depth distribution of Patagonotothen spp. Preliminary results demonstrated that, within areas of occurrence, there are significant correlations between fish abundance (CPUE), the oceanographic conditions of the area (SST gradients) and depth in certain months.

Three specialized laboratories examined the determination of non-certified trace elements (Al, Fe, Li, Mn and Pb) in a commercial CRM and therefore, produced a so-called laboratory reference material (LRM). The dataset (total mass fractions and their associated uncertainties) were estimated both using parametric and non-parametric methods. The results provided a coherent assessment for all except for Pb, in agreement with the results found by the CRM producer. We discuss the feasibility of the implementation of small-sized specialized laboratory comparisons to produce LRMs (from CRMs) for non-certified chemicals and strongly discourage attempts by a single laboratory. Datasets for aluminium (Al), iron (Fe), lithium (Li), manganese (Mn) and lead (Pb) in the commercial estuarine sediment BCR-277R