Processing bio-Argo chlorophyll-A concentration at the DAC level

This document does NOT address the issue of chlorophyll-a quality control (either real-time or delayed mode). As a preliminary step towards that goal, this document seeks to ensure that all countries deploying floats equipped with chlorophyll-a sensors document the data and metadata related to these floats properly. We produced this document in response to action item 3 from the first Bio-Argo Data Management meeting in Hyderabad (November 12-13, 2012). If the recommendations contained herein are followed, we will end up with a more uniform set of chlorophyll-a data within the Bio-Argo data system, allowing users to begin analyzing not only their own chlorophyll-a data, but also those of others, in the true spirit of Argo data sharing.

Statistical Analysis of Sea Surface Temperature and Chlorophyll-a Concentration Patterns in the Gulf of Tadjourah (Djibouti)

The sea surface temperature (SST) and chlorophyll-a concentration (CHL-a) were analysed in the Gulf of Tadjourah from two set of 8-day composite satellite data, respectively from 2008 to 2012 and from 2005 to 2011. A singular spectrum analysis (SSA) shows that the annual cycle of SST is strong (74.3% of variance) and consists of warming (April-October) and cooling (November-March) of about 2.5C than the long-term average. The semi-annual cycle captures only 14.6% of temperature variance and emphasises the drop of SST during July-August. Similarly, the annual cycle of CHL-a (29.7% of variance) depicts high CHL-a from June to October and low concentration from November to May. In addition, the first spatial empirical orthogonal function (EOF) of SST (93% of variance) shows that the seasonal warming/cooling is in phase across the whole study area but the southeastern part always remaining warmer or cooler. In contrast to the SST, the first EOF of CHL-a (54.1% of variance) indicates the continental shelf in phase opposition with the offshore area in winter during which the CHL-a remains sequestrated in the coastal area particularly in the south-east and in the Ghoubet Al-Kharab Bay. Inversely during summer, higher CHL-a quantities appear in the offshore waters. In order to investigate processes generating these patterns, a multichannel spectrum analysis was applied to a set of oceanic (SST, CHL-a) and atmospheric parameters (wind speed, air temperature and air specific humidity). This analysis shows that the SST is well correlated to the atmospheric parameters at an annual scale. The windowed cross correlation indicates that this correlation is significant only from October to May. During this period, the warming was related to the solar heating of the surface water when the wind is low (April-May and October) while the cooling (November-March) was linked to the strong and cold North-East winds and to convective mixing. The summer drop in SST followed by a peak of CHL-a, seems strongly correlated to the upwelling. The second EOF modes of SST and CHL-a explain respectively 1.3% and 5% of the variance and show an east-west gradient during winter that is reversed during summer. This work showed that the seasonal signals have a wide spatial influence and dominate the variability of the SST and CHL-a while the east-west gradient are specific for the Gulf of Tadjourah and seem induced by the local wind modulated by the topography.

Caractérisation du fonctionnement d'une hydrolienne à membrane ondulante pour la récupération de l'énergie des courants marins

This manuscript presents three approaches : analytical, experimental and numerical, to study the behaviour of a flexible membrane tidal energy converter. This technology, developed by the EEL Energy company, is based on periodic deformations of a pre-stressed flexible structure. Energy converters, located on each side of the device, are set into motion by the wave-like motion. In the analytical model, the membrane is represented by a linear beam model at one dimension and the flow by a 3 dimensions potential fluid. The fluid forces are evaluated by the elongated body theory. Energy is dissipated all over the length of the membrane. A 20th scale experimental prototype has been designed with micro-dampers to simulate the power take-off. Trials have allowed to validate the undulating membrane energy converter concept. A numerical model has been developed. Each element of the device is represented and the energy dissipation is done by dampers element with a damping law linear to damper velocity. Comparison of the three approaches validates their ability to represent the membrane behaviour without damping. The energy dissipation applied with the analytical model is clearly different from the two other models because of the location (where the energy is dissipated) and damping law. The two others show a similar behaviour and the same order of power take off repartition but value of power take off are underestimated by the numerical model. This three approaches have allowed to put forward key-parameters on which depend the behaviour of the membrane and the parametric study highlights the complementarity and the advantage of developing three approaches in parallel to answer industrial optimization problems. To make the link between trials in flume tank and sea trials, a 1/6th prototype has been built. To do so, the change of scale was studied. The behaviour of both prototypes is compared and differences could be explained by differences of boundary conditions and confinement effects. To evaluated membrane long-term behaviour at sea, a method of ageing accelerated by temperature and fatigue tests have been carried out on prototype materials samples submerged in sea water.

Développement d'un drone nautique pour le prélèvement d'échantillons d'eau en milieu côtier et estuarien (SPEEdoo)

A nautical drone was designed for the monitoring of estuarine and coastal waters in the context of the Water Framework Directive (WFD) to : - go up to 500 m off the coastline in less than 5 minutes, - perform in situ measurements (temperature, salinity, turbidity), - collect water samples for later analysis in the laboratory (phytoplankton identification, chlorophyll, nutrients, ...).