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  • 1
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    Analysis and visualization of coastal ocean model data in the cloud. (2019)
    MDPI
    Details
    Publication Date: 2022-10-27
    Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Signell, R. P., & Pothina, D. Analysis and visualization of coastal ocean model data in the cloud. Journal of Marine Science and Engineering, 7(4), (2019);110, doi:10.3390/jmse7040110.
    Description: The traditional flow of coastal ocean model data is from High-Performance Computing (HPC) centers to the local desktop, or to a file server where just the needed data can be extracted via services such as OPeNDAP. Analysis and visualization are then conducted using local hardware and software. This requires moving large amounts of data across the internet as well as acquiring and maintaining local hardware, software, and support personnel. Further, as data sets increase in size, the traditional workflow may not be scalable. Alternatively, recent advances make it possible to move data from HPC to the Cloud and perform interactive, scalable, data-proximate analysis and visualization, with simply a web browser user interface. We use the framework advanced by the NSF-funded Pangeo project, a free, open-source Python system which provides multi-user login via JupyterHub and parallel analysis via Dask, both running in Docker containers orchestrated by Kubernetes. Data are stored in the Zarr format, a Cloud-friendly n-dimensional array format that allows performant extraction of data by anyone without relying on data services like OPeNDAP. Interactive visual exploration of data on complex, large model grids is made possible by new tools in the Python PyViz ecosystem, which can render maps at screen resolution, dynamically updating on pan and zoom operations. Two examples are given: (1) Calculating the maximum water level at each grid cell from a 53-GB, 720-time-step, 9-million-node triangular mesh ADCIRC simulation of Hurricane Ike; (2) Creating a dashboard for visualizing data from a curvilinear orthogonal COAWST/ROMS forecast model.
    Description: This research benefited from National Science Foundation grant number 1740648, and EarthSim project was funded by ERDC projects PETTT BY17-094SP and PETTT BY16-091SP. This project also benefited from research credits granted by Amazon.
    Keywords: Ocean modeling ; Cloud computing ; Data analysis ; Geospatial data visualization
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 2
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    Ophiolitic pyroxenites record boninite percolation in subduction zone mantle (2019)
    MDPI
    Details
    Publication Date: 2022-10-26
    Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Le Roux, V., & Liang, Y. Ophiolitic pyroxenites record boninite percolation in subduction zone mantle. Minerals, 9(9), (2019): 565, doi: 10.3390/min9090565.
    Description: The peridotite section of supra-subduction zone ophiolites is often crosscut by pyroxenite veins, reflecting the variety of melts that percolate through the mantle wedge, react, and eventually crystallize in the shallow lithospheric mantle. Understanding the nature of parental melts and the timing of formation of these pyroxenites provides unique constraints on melt infiltration processes that may occur in active subduction zones. This study deciphers the processes of orthopyroxenite and clinopyroxenite formation in the Josephine ophiolite (USA), using new trace and major element analyses of pyroxenite minerals, closure temperatures, elemental profiles, diffusion modeling, and equilibrium melt calculations. We show that multiple melt percolation events are required to explain the variable chemistry of peridotite-hosted pyroxenite veins, consistent with previous observations in the xenolith record. We argue that the Josephine ophiolite evolved in conditions intermediate between back-arc and sub-arc. Clinopyroxenites formed at an early stage of ophiolite formation from percolation of high-Ca boninites. Several million years later, and shortly before exhumation, orthopyroxenites formed through remelting of the Josephine harzburgites through percolation of ultra-depleted low-Ca boninites. Thus, we support the hypothesis that multiple types of boninites can be created at different stages of arc formation and that ophiolitic pyroxenites uniquely record the timing of boninite percolation in subduction zone mantle.
    Description: This study was supported by National Science Foundation grants EAR-1220440 to V.L.R. and EAR-1624516 to Y.L. We thank the reviewers for their helpful suggestions, as well as Taylor Hough, Gretchen Swarr, Alberto Saal, Soumen Mallick, and Nilanjan Chatterjee for help with LA-ICP-MS and EPMA analyses, and Mark Kurz for help with sample collection.
    Keywords: Ophiolite ; Boninite ; Pyroxenite ; Josephine peridotite ; REE temperatures ; Diffusion ; Melt percolation ; Subduction zones
    Repository Name: Woods Hole Open Access Server
    Type: Article
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