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29.09.2016 00:09 Age: 210 days
Category: Home Slider, ANFOG, NSW-IMOS

Glider data provides unprecedented high resolution observations of the continental shelf waters of southeastern Australia

A comprehensive data set collected by IMOS ocean gliders has been published in the Nature journal Scientific Data.


Study area and glider paths from the 26 shelf deployments between 2008 and 2015 Figure from Schaeffer et al. 2016 doi:10.1038/sdata.2016.70.

Example of in situ glider measurements for deployment Nemo 18. Figure from Schaeffer et al. 2016 doi:10.1038/sdata.2016.70.

The dataset was collected over 26 glider missions along the continental shelf of southeastern Australia, and is made up of over 33,600 CTD profiles from the surface to within 10 m of the bottom in water depths ranging 25–200 m, provides unprecedented high resolution observations of the continental shelf waters adjacent to a western boundary current, straddling the region where it separates from the coast.

The data descriptor paper, written by Amandine Schaeffer from the University of New South Wales along with a group of researchers from across the country, presents a high-resolution mean hydrography of the continental shelf along southeastern Australia, from repeat glider deployments over 8 years between 29.5°S and 33.5°S.

The data were quality controlled providing for the first time gridded mean fields for temperature, salinity and density, but also dissolved oxygen and chlorophyll-a fluorescence indicative of phytoplankton biomass.

The region is both physically and biologically significant, and is also in a hotspot of ocean warming. This data will be invaluable for understanding shelf stratification, circulation, biophysical and bio-geochemical interactions, as well as for the validation of high-resolution ocean models or serving as teaching material.


To read the full paper Schaeffer, A, Roughan, M, Austin, T, Everett, JD, et, al. 2016, Mean hydrography on the continental shelf from 26 repeat glider deployments along Southeastern Australia, Scientific Data, vol. 3, doi:10.1038/sdata.2016.70