Web-based visualization of gridded dataset usings OceanBrowser

OceanBrowser is a web-based visualization tool for gridded oceanographic data sets. Those data sets are typically four-dimensional (longitude, latitude, depth and time). OceanBrowser allows one to visualize horizontal sections at a given depth and time to examine the horizontal distribution of a given variable. It also offers the possibility to display the results on an arbitrary vertical section. To study the evolution of the variable in time, the horizontal and vertical sections can also be animated. Vertical section can be generated by using a fixed distance from coast or fixed ocean depth. The user can customize the plot by changing the color-map, the range of the color-bar, the type of the plot (linearly interpolated color, simple contours, filled contours) and download the current view as a simple image or as Keyhole Markup Language (KML) file for visualization in applications such as Google Earth. The data products can also be accessed as NetCDF files and through OPeNDAP. Third-party layers from a web map service can also be integrated. OceanBrowser is used in the frame of the SeaDataNet project (http://gher-diva.phys.ulg.ac.be/web-vis/) and EMODNET Chemistry (http://oceanbrowser.net/emodnet/) to distribute gridded data sets interpolated from in situ observation using DIVA (Data-Interpolating Variational Analysis)

Numerical discretization of rotated diffusion operators in ocean models

A method to improve the behavior of the numerical discretization of a rotated diffusion operator such as, for example, the isopycnal diffusion parameterization used in large-scale ocean models based on the so-called z-coordinate system is presented. The authors then focus exclusively on the dynamically passive tracers and analyze some different approaches to the numerical discretization. Monotonic schemes are designed but are found to be rather complex, while simpler, linear schemes are shown to produce unphysical undershooting and overshooting. It is suggested that the choice of an appropriate discretization method depends on the importance of the rotated diffusion in a given simulation, whether the field to be diffused is dynamically active or not

Enhancing temporal correlations in EOF expansions for the reconstruction of missing data using DINEOF

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

Concepts actuels de l'hyperaldostéronisme primaire

peer reviewe

Data Interpolating Empirical Orthogonal Functions (DINEOF): a tool for geophysical data analyses

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.RECOLOU

Seasonal hypoxia in the Black Sea north-western shelf. Is there any recovery after eutrophication ?

peer reviewedThe Black Sea North-western shelf (NWS) is a shallow eutrophic area in which seasonal tratification of the water column isolates bottom waters from the atmosphere and prevents entilation to compensate for the large consumption of oxygen, due to respiration in the bottom aters and in the sediments. A 3D coupled physical biogeochemical model is used to investigate he dynamics of bottom hypoxia in the Black Sea NWS at different temporal scales from seasonal o interannual (1981-2009) and to differentiate the driving factors (climatic versus eutrophication) f hypoxic conditions in bottom waters. Model skills are evaluated by comparison with 14500 in- itu oxygen measurements available in the NOAA World Ocean Database and the Black Sea ommission data. The choice of skill metrics and data subselections orientate the validation rocedure towards specific aspects of the oxygen dynamics, and prove the model’s ability to esolve the seasonal cycle and interannual variability of oxygen concentration as well as the patial location of the oxygen depleted waters and the specific threshold of hypoxia. During the eriod 1981-2009, each year exhibits seasonal bottom hypoxia at the end of summer. This henomenon essentially covers the northern part of the NWS, receiving large inputs of nutrients rom the Danube, Dniestr and Dniepr rivers, and extends, during the years of severe hypoxia, owards the Romanian Bay of Constanta. In order to explain the interannual variability of bottom ypoxia and to disentangle its drivers, a statistical model (multiple linear regression) is proposed sing the long time series of model results as input variables. This statis- tical model gives a eneral relationships that links the intensity of hypoxia to eutrophication and climate related variables. The use of four predictors allows to reproduce 78% of hypoxia interannual variability: he annual nitrate discharge (N ), the sea surface temperature in the month preceding tratification (T ), the amount of semi-labile organic matter in the sediments (C) and the duration f the stratification (D). Eutrophication (N ,C) and climate (T ,D) predictors explain a similar mount of variability (∼ 35%) when considered separately. A typical timescale of 9.3 years is found to describe the inertia of sediments in the recovering process after eutrophication. From his analysis, we find that under standard conditions (i.e. average atmospheric conditions, ediments in equi- librium with river discharges), the intensity of hypoxia can be linked to the evel of nitrate discharge through a non-linear equation (power law). Bottom hypoxia does not ffect the whole Black Sea NWS but rather exhibits an important spatial variability. This heterogeneous distribution, in addition to the seasonal fluctuations, complicates the monitoring f ottom hypoxia leading to contradictory conclusions when the interpretation is done from different ets of data. We find that it was the case after 1995 when the recovery process was verestimated due to the use of observations concentrated in areas and months not typically ffected by hypoxia. This stresses out the urging need of a dedicated monitoring effort in the WS f the Black Sea focused on the areas and the period of the year concerned by recurrent hypoxic events.P