On spreading of Antarctic Bottom Water in fracture zones of the Mid-Atlantic Ridge at 7–8°N
Author:
Dudkov I.1, Kapustina M1, Sivkov V1
Affiliation:
1. Shirshov Institute of Oceanology RAS
Abstract
A Data-Interpolating Variational Analysis in n-dimensions was used to describe a potential temperature distribution in the bottom layer of the fracture zones of the Mid-Atlantic Ridge at 7–8°N. This analysis was based on a new digital terrain model obtained by supplementing the STRM15+ bathymetry data with multibeam echo sounding data from the 33rd cruise of the research vessel
Akademik Nikolaj Strakhov (2016) and oceanological data from the World Ocean Database, supplemented with CTD profiles and reversing thermometer data measured in scientific cruises of the Shirshov Institute of Oceanology, Russian Academy of Sciences in 2014–2016. A 2D model of near-bottom potential temperature distribution in the study area was calculated based on the analysis. The model allows us to propose the Antarctic Bottom Water propagation pattern through the Doldrums, Vernadsky, and Pushcharovsky fracture zones. It is shown that bottom water warms up when passing fracture zones from 1.4°C in Pushcharovsky Fracture Zone up to 1.6–1.7°C in Vernadsky Fracture Zone. Bottom water from Pushcharovsky and Vernadsky fractures propagates in two directions. Northernly, it propagates to the Doldrums Fracture Zone, where its temperature reaches about 1.9–2.0°C. Easterly, it flows along Pushcharovsky Fracture Zone and raising the temperature up to 1.8–2.0°C. We propose the absence of Antarctic Bottom Water's overflow with a temperature less than 1.8°C to the East Atlantic in the study area.
Publisher
Geophysical Center of the Russian Academy of Sciences
Subject
General Earth and Planetary Sciences
Reference46 articles.
1. Barth, A., C. Troupin, et al. (2021), Variational interpolation of high-frequency radar sur-face currents using DIVAnd. Ocean Dynamics, 71, No. 3, 293-308., Barth, A., C. Troupin, et al. (2021), Variational interpolation of high-frequency radar sur-face currents using DIVAnd. Ocean Dynamics, 71, No. 3, 293-308. 2. Barth, A., J. M. Beckers, et al. (2014), divand-1.0: n-dimensional variational data analysis for ocean observations. Geoscientific Model Development, 7, No. 1, 225-241., Barth, A., J. M. Beckers, et al. (2014), divand-1.0: n-dimensional variational data analysis for ocean observations. Geoscientific Model Development, 7, No. 1, 225-241. 3. Beckers, J. M., A. Barth, et al. (2014), Approximate and efficient methods to assess error fields in spatial gridding with data interpolating variational analysis (DIVA). Journal of Atmospheric and Oceanic Technology, 31, No. 2, 515-530., Beckers, J. M., A. Barth, et al. (2014), Approximate and efficient methods to assess error fields in spatial gridding with data interpolating variational analysis (DIVA). Journal of Atmospheric and Oceanic Technology, 31, No. 2, 515-530. 4. Belgacem, M., K. Schroeder, et al. (2021), Climatological distribution of dissolved inorgan-ic nutrients in the Western Mediterranean Sea (1981–2017). Earth System Science Data Discussions, 1-49., Belgacem, M., K. Schroeder, et al. (2021), Climatological distribution of dissolved inorgan-ic nutrients in the Western Mediterranean Sea (1981–2017). Earth System Science Data Discussions, 1-49. 5. Boyer, T.P., O. K. Baranova, et al. (2018), World Ocean Database 2018., Boyer, T.P., O. K. Baranova, et al. (2018), World Ocean Database 2018.
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|