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Abstract: The transfer of Indian Ocean thermocline and intermediate waters into the South Atlantic via the Agulhas leakage is generally believed to be primarily accomplished through mesoscale eddy processes, essentially anticyclones known as Agulhas Rings. Here we take advantage of a recent eddy tracking algorithm and Argo float profiles to study the evolution and the thermohaline structure of one of these eddies over the course of 1.5 years (May 2013–November 2014). We found that during this period the ring evolved according to two different phases: During the first one, taking place in winter, the mixing layer in the eddy deepened significantly. During the second phase, the eddy subsided below the upper warmer layer of the South Atlantic subtropical gyre while propagating west. The separation of this eddy from the sea surface could explain the decrease in its surface signature in satellite altimetry maps, suggesting that such changes are not due to eddy dissipation processes. It is a very large eddy (7.1×1013 m3 in volume), extending, after subduction, from a depth of 200–1,200 m and characterized by two mode water cores. The two mode water cores represent the largest eddy heat and salt anomalies when compared with the surrounding. In terms of its impact over 1 year, the north‐westward propagation of this long‐lived anticyclone induces a transport of 2.2 Sv of water, 0.008 PW of heat, and 2.2×105 kg s−1 of salt. These results confirm that Agulhas Rings play a very important role in the Indo‐Atlantic interocean exchange of heat and salt.
Jacob, J. C., Armstrong, E. M., Bourassa, M. A., Cram, T., Elya, J. L., Greguska, F. R., III, et al. (2018). OceanWorks: Enabling Interactive Oceanographic Analysis in the Cloud with Multivariate Data. In
American Geophysical Union (Vol. Fall Meeting).
Abstract: NASA's Advanced Information System Technology (AIST) Program sponsors the OceanWorks project to establish an integrated data analytics center at the Physical Oceanography Distributed Active Archive Center (PO.DAAC). OceanWorks provides a series of interoperable capabilities that are essential for cloud-scale oceanographic research. These include big data analytics, data search with subsecond response, intelligent ranking of search results, subsetting based on data quality metrics, and rapid spatiotemporal matchup of satellite measurements with distributed in situ data. The software behind OceanWorks is being developed as an open source project in the Apache Incubator Science Data Analytics Platform (SDAP – http://sdap.apache.org). In this presentation we describe how OceanWorks enables efficient, scalable, interactive and interdisciplinary oceanographic analysis with multivariate data.
Interactivity is enabled by a number of SDAP features. First, SDAP provides Representational State Transfer (REST) interfaces to a number of built-in cloud analytics to compute time series, time-averaged maps, correlation maps, climatological maps, Hovmöller maps, and more. To access these, users simply navigate to a properly constructed parameterized URL in their web browser or issue web services calls in a variety of programming languages or in a Jupyter notebook. Alternatively, Python clients can make function calls via the NEXUS Command Line Interface (CLI). Authenticated users can even inject their own custom code via REST calls or the CLI.
To enable interdisciplinary science, OceanWorks provides access to a rich collection of multivariate satellite and in situ measurements of the oceans (e.g., sea surface temperature, height and salinity, chlorophyll and circulation) and other Earth science data (e.g., aerosol optical depth and wind speed), coupled with on-demand processing capabilities close to the data. We partition the data across space or time into tiles and store them into cloud-aware databases that are collocated with the computations. We will provide examples of scientific studies directly enabled by OceanWorks' multivariate data and cloud analytics.