Despite an extensive bibliography for the circulation of the Mediterranean Sea and its sub-basins, the debate on mesoscale dynamics and their impacts on bio-chemical processes is still open because of their intrinsic time scales and of the difficulties in their sampling. In order to clarify some of these processes, the "Algerian BAsin Circulation Unmanned Survey-ABACUS" project was proposed and realized through access to the JERICO Trans National Access (TNA) infrastructure between September and December 2014. In this framework, a deep glider cruise was carried out in the area between the Balearic Islands and the Algerian coast to establish a repeat line for monitoring of the basin circulation. During the mission a mesoscale eddy, identified on satellite altimetry maps, was sampled at high-spatial horizontal resolution (4 km) along its main axes and from the surface to 1000 m depth. Data were collected by a Slocum glider equipped with a pumped CTD and biochemical sensors that collected about 100 complete casts inside the eddy. In order to describe the structure of the eddy, in situ data were merged with next generation remotely sensed data: daily synoptic sea surface temperature (SST) and chlorophyll concentration (Chl-a) images from the MODIS satellites, as well as sea surface height and geostrophic velocities from AVISO. From its origin along the Algerian coast in the eastern part of the basin, the eddy propagated northwest at a mean speed of about 4 km/day, with a mean diameter of 112-130 km, mean amplitude of 15.7 cm; the eddy was clearly distinguished from the surrounding waters thanks to its higher SST and Chl-a values. Temperature and salinity values over the water column confirm the origin of the eddy from the Algerian Current (AC) showing the presence of recent Atlantic water in the surface layer and Levantine Intermediate Water (LIW) in the deeper layer. The eddy footprint is clearly evident in the multiparametric vertical sections conducted along its main axis. Deepening of temperature, salinity and density isolines at the center of the eddy is associated with variations in Chl-a, oxygen concentration and turbidity patterns. In particular, at 50 m depth along the eddy borders, Chl-a values are higher (1.1-5.2 μg/l) in comparison with the eddy center (0.5-0.7 μg/l) with maximum values found in the southeastern sector of the eddy. Calculation of geostrophic velocities along transects and vertical quasi-geostrophic velocities (QG-w) over a regular 5 km grid from the glider data helped to describe the mechanisms and functioning of the eddy. QG-w presents an asymmetric pattern, with relatively strong downwelling in the western part of the eddy and upwelling in the southeastern part. This asymmetry in the vertical velocity pattern, which brings LIW into the euphotic layer as well as advection from the northeastern sector of the eddy, may explain the observed increases in Chl-a values.
The early autumn voyage of RV Sikuliaq to the southern Beaufort Sea in 2015 offered very favorable opportunities for observing the properties and thicknesses of frazil‐pancake ice types. The operational region was overlaid by a dense network of retrieved satellite imagery, including synthetic aperture radar (SAR) imagery from Sentinel‐1 and COSMO‐SkyMed (CSK). This enabled us to fully test and apply the SAR‐waves technique, first developed by Wadhams and Holt (1991), for deriving the thickness of frazil‐pancake icefields from changed wave dispersion. A line of subimages from a main SAR image (usually CSK) is analyzed running into the ice along the main wave direction. Each subimage is spectrally analyzed to yield a wave number spectrum, and the change in the shape of the spectrum between open water and ice, or between two thicknesses of ice, is interpreted in terms of the viscous equations governing wave propagation in frazil‐pancake ice. For each of the case studies considered here, there was good or acceptable agreement on thickness between the extensive in situ observations and the SAR‐wave calculation. In addition, the SAR‐wave analysis gave, parametrically, effective viscosities for the ice covering a consistent and narrow range of 0.03–0.05 m2 s−1.
Antarctic sea ice is constantly exported from the shore by strong near surface winds that open leads and large polynyas in the pack ice. The latter, known as wind-driven polynyas, are responsible for significant water mass modification due to the high salt flux into the ocean associated with enhanced ice growth. In this article, we focus on the wind-driven Terra Nova Bay (TNB) polynya, in the western Ross Sea. Brine rejected during sea ice formation processes that occur in the TNB polynya densifies the water column leading to the formation of the most characteristic water mass of the Ross Sea, the High Salinity Shelf Water (HSSW). This water mass, in turn, takes part in the formation of Antarctic Bottom Water (AABW), the densest water mass of the world ocean, which plays a major role in the global meridional overturning circulation, thus affecting the global climate system. A simple coupled sea iceâ\u80\u93ocean model has been developed to simulate the seasonal cycle of sea ice formation and export within a polynya. The sea ice model accounts for both thermal and mechanical ice processes. The oceanic circulation is described by a one-and-a-half layer, reduced gravity model. The domain resolution is 1 km Ã\u97 1 km, which is sufficient to represent the salient features of the coastline geometry, notably the Drygalski Ice Tongue. The model is forced by a combination of Era Interim reanalysis and in-situ data from automatic weather stations, and also by a climatological oceanic dataset developed from in situ hydrographic observations. The sensitivity of the polynya to the atmospheric forcing is well reproduced by the model when atmospheric in situ measurements are combined with reanalysis data. Merging the two datasets allows us to capture in detail the strength and the spatial distribution of the katabatic winds that often drive the opening of the polynya. The model resolves fairly accurately the sea ice drift and sea ice production rates in the TNB polynya, leading to realistic polynya extent estimates. The model-derived polynya extent has been validated by comparing the modelled sea ice concentration against MODIS high resolution satellite images, confirming that the model is able to reproduce reasonably well the TNB polynya evolution in terms of both shape and extent
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