A comprehensive oceanographic dataset of a subpolar, mid-latitude broad fjord: Fortune Bay, Newfoundland, Canada

• Published in: Earth System Science Data
• Main Authors: Donnet, Sebastien, Lazure, Pascal, Ratsimandresy, Andry, Han, Guoqi
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus GmbH 2020
• Subjects: Canada; Greenland; Newfoundland; Northwest Atlantic
• Online Access: https://archimer.ifremer.fr/doc/00634/74635/74529.pdf; https://archimer.ifremer.fr/doc/00634/74635/77362.pdf; https://doi.org/10.5194/essd-12-1877-2020; https://archimer.ifremer.fr/doc/00634/74635/

While the dynamics of narrow fjords, i.e. narrow with respect to their internal Rossby radius, have been widely studied, it is only recently that interest sparked in studying the physics of broad fjords due to their importance in glacial ice melting (in Greenland, especially). Here, we present a comprehensive set of data collected in Fortune Bay, a broad, mid-latitude fjord located on the Northwest Atlantic shores. Aside from being wide (15–25 km width) and deep (600 m at its deepest), Fortune Bay also has the characteristics of having steep slopes, weak tides and of being strongly stratified from spring to fall. Thus, and since strong along-shore winds also characterise the region, this system is prone to interesting dynamics, generally taking the form of transient upwelling and downwelling travelling along its shores, similar to processes encountered in broad fjords of higher latitudes. The dataset collected to study those dynamics consists of water column physical parameters (temperature, salinity, currents and water level) and atmospheric forcing (wind speed and direction, atmospheric pressure, air temperature and solar radiation) taken at several points around the fjord using oceanographic moorings and land-based stations. The program lasted 2 full years and achieved a good data return of 90 %, providing a comprehensive dataset not only for Fortune Bay studies but also for the field of broad fjord studies. The data are available publically from the SEANOE repository (http://www.seanoe.org/data/00511/62314/; Donnet and Lazure, 2020).