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    This in situ temperature data was collected from HOBO pendent loggers at Cayo Mario and Cayo Enrique, La Parguera, Puerto Rico, from 06/30/2017 to 06/20/2019. The loggers were placed at different depths around the reefs, and the goal was to compare the in situ temperature to satellite SST to see how representative the satellite SST was of the temperature at the depth of the corals.

  • 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.

  • This record describes the conductivity-temperature-depth (CTD) data and underway water sample data collected during the CSIRO Investigator transit voyage IN2024_T01, between 9 March and 20 March 2024. The objective of the voyage was for a safe transit from Fremantle, Western Australia, to Hobart, Tasmania. This record was part of a piggyback project whereby undergraduate students attained at-sea training through the Institute of Marine and Antarctic Studies and the University of Tasmania. The project aim was for students to gain experience with oceanographic data collection, processing and analysis. The CTD data includes 7 CTD profiles that measured conductivity, temperature, pressure, dissolved oxygen, salinity, fluorescence, turbidity and photosynthetically active radiation (PAR). Each of these parameters were collected during each CTD profile. The CTD data also includes calculated measurements of ammonium, nitrate, nitrite, phosphate, silicate, as well as chlorophyll-a, from select rosette bottles. The underway water sample data includes 41 duplicate samples of calculated measurements of chlorophyll-a and associated calculated measurements of ammonium, nitrate, nitrite, phosphate and silicate nutrient concentrations. In both data files, ODV quality flags have been used to indicate data quality.