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EARTH SCIENCE | OCEANS | OCEAN TEMPERATURE

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  • This atlas uses all of the available full water column profiles of oxygen, salinity and temperature available as part of the World Ocean Atlas released in 2018. Instead of optimal interpolation we use the Data Interpolating Variational Analysis (DIVA) approach to map the available profiles onto 108 depth levels between the surface and 6800 m, covering more than 99% of ocean volume. This 1/2° x 1/2° degree atlas covers the period 1955 to 2018 in 1 year intervals. The DIVA method has significant benefits over traditional optimal interpolation. It allows the explicit inclusion of advection and boundary constraints thus offering improvements in the representations of oxygen, salinity and temperature in regions of strong flow and near coastal boundaries. We demonstrate these benefits of this mapping approach with some examples from this atlas. We can explore the regional and temporal variations of oxygen in the global oceans. Preliminary analyses confirm earlier analyses that the oxygen minimum zone in the eastern Pacific Ocean has expanded and intensified. Oxygen inventory changes between 1970 and 2010 are assessed and compared against prior studies. We find that the full ocean oxygen inventory decreased by 0.84% ± 0.42%. For this period temperature driven solubility changes explain about 21% of the oxygen decline over the full water column, in the upper 100 m solubility changes can explain all of the oxygen decrease, for the 100-600 m depth range it can explain only 29%, 19% between 600 m and 1000 m, and just 11% in the deep ocean.

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    Biological ocean data collected from ships find reuse in aggregations of historical data. These data are heavily relied upon to document long term change, validate satellite algorithms for ocean biology and are useful in assessing the performance of autonomous platforms and biogeochemical models. There is a need to combine subsurface biological and physical data into one aggregate data product to support reproducible research. Existing aggregate products are dissimilar in source data, have largely been isolated to the surface ocean and most omit physical data. These products cannot easily be used to explore subsurface bio-physical relationships. We present the first version of a biological ocean data reformatting effort (BIO-MATE, https://gitlab.com/KBaldry/BIO-MATE). BIO-MATE uses R software that reformats openly sourced published datasets from oceanographic voyages. These reformatted biological and physical data from underway sensors, profiling sensors and pigments analysis are stored in an interoperable and reproducible BIO-MATE data product for easy access and use.

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    In support of future science missions, an engineering demonstration was conducted to show the ability of the nupiri muka AUV to be deployed and operated at an ice shelf. The AUV was deployed from Davis Station, Antarctica, to conduct underwater surveys in the vicinity of, and beneath, the Sørsdal ice shelf. The AUV conducted several surface transits from the station to the ice shelf, where dive missions at various depths were conducted. The primary mode of operation was the AUV tracking near the seafloor. In addition, a patch survey was conducted near the stations, where several sediment grabs were taken.

  • The ETAS (Eastern TASmania) model is a high-resolution (~2 km in the horizontal) ocean model for eastern Tasmania, providing three-dimensional estimates of mean temperature, salinity, and circulation over the 1993-2016 period. This dataset consists of temperature, salinity, meridional (N-S), zonal (E-W), vertical, along- and cross-shore currents, density, sea level and net surface heat flux organised into yearly files and aggregated daily or monthly. A MATLAB script to extract portions of the data is available here: https://github.com/ecjoliver/extractETAS

  • The ETAS (Eastern TASmania) model is a high-resolution (~2 km in the horizontal) ocean model for eastern Tasmania, providing three-dimensional estimates of daily temperature, salinity, and circulation over the 1993-2014 period. This dataset consists of hourly temperature, salinity, sea level, eastward (u) and northward (v) currents (at depth and vertically-averaged) at selected locations.

  • The ETAS (Eastern TASmania) model is a high-resolution (~2 km in the horizontal) ocean model for eastern Tasmania, providing three-dimensional estimates of daily temperature, salinity, and circulation over the 1993-2014 period. This dataset consists of eastward (u) and northward (v) currents organised into yearly files.

  • The ETAS (Eastern TASmania) model is a high-resolution (~2 km in the horizontal) ocean model for eastern Tasmania, providing three-dimensional estimates of daily temperature, salinity, and circulation over the 1993-2014 period. This dataset consists of temperature, salinity, density, sea level, eastward (u) and northward (v) currents organised into timeseries files.

  • The ETAS (Eastern TASmania) model is a high-resolution (~2 km in the horizontal) ocean model for eastern Tasmania, providing three-dimensional estimates of daily temperature, salinity, and circulation over the 1993-2014 period. This dataset consists of temperature, salinity, along- and cross-shore currents, density and sea level organised into yearly files.

  • The ETAS (Eastern TASmania) model is a high-resolution (~2 km in the horizontal) ocean model for eastern Tasmania, providing three-dimensional estimates of daily temperature, salinity, and circulation over the 1993-2016 period. This dataset consists of temperature, salinity, meridional (N-S), zonal (E-W), vertical, along- and cross-shore currents, density, sea level and net surface heat flux organised into yearly files. A MATLAB script to extract portions of the data is available here: https://github.com/ecjoliver/extractETAS

  • The ETAS (Eastern TASmania) model is a high-resolution (~2 km in the horizontal) ocean model for eastern Tasmania, providing three-dimensional estimates of monthly mean temperature, salinity, and circulation over the 1993-2016 period. This dataset consists of temperature, salinity, meridional (N-S), zonal (E-W), vertical, along- and cross-shore currents, density, sea level and net surface heat flux organised into yearly files. A MATLAB script to extract portions of the data is available here: https://github.com/ecjoliver/extractETAS