Smith, S. R., Bourass, M. A., & Jackson, D. L. (2012). Supporting Satellite Research With Data Collected by Vessels Automated Meteorological Sampling From SAMOS Project Gathers Data Required to Test Satellite Algorithms, Validate Products. Sea Technology , 53 (6), 21–24.
Armstrong, E. M., Bourassa, M. A., Cram, T., Elya, J. L., Greguska, F. R., III, Huang, T., et al. (2018). An information technology foundation for fostering interdisciplinary oceanographic research and analysis. In American Geophysical Union (Vol. Fall Meeting).
Abstract: Before complex analysis of oceanographic or any earth science data can occur, it must be placed in the proper domain of computing and software resources. In the past this was nearly always the scientist's personal computer or institutional computer servers. The problem with this approach is that it is necessary to bring the data products directly to these compute resources leading to large data transfers and storage requirements especially for high volume satellite or model datasets. In this presentation we will present a new technological solution under development and implementation at the NASA Jet Propulsion Laboratory for conducting oceanographic and related research based on satellite data and other sources. Fundamentally, our approach for satellite resources is to tile (partition) the data inputs into cloud-optimized and computation friendly databases that allow distributed computing resources to perform on demand and server-side computation and data analytics. This technology, known as NEXUS, has already been implemented in several existing NASA data portals to support oceanographic, sea-level, and gravity data time series analysis with capabilities to output time-average maps, correlation maps, Hovmöller plots, climatological averages and more. A further extension of this technology will integrate ocean in situ observations, event-based data discovery (e.g., natural disasters), data quality screening and additional capabilities. This particular activity is an open source project known as the Apache Science Data Analytics Platform (SDAP) (https://sdap.apache.org), and colloquially as OceanWorks, and is funded by the NASA AIST program. It harmonizes data, tools and computational resources for the researcher allowing them to focus on research results and hypothesis testing, and not be concerned with security, data preparation and management. We will present a few oceanographic and interdisciplinary use cases demonstrating the capabilities for characterizing regional sea-level rise, sea surface temperature anomalies, and ocean hurricane responses.
O'hara, S. H., Arko, R. A., Clark, D., Chandler, C. L., Elya, J. L., Ferrini, V. L., et al. (2018). Rolling Deck to Repository (R2R) Program Data Services for the Oceanographic Research Community. In American Geophysical Union (Vol. American Geophysical Union, Fall Meeting 2018).
Abstract: Research vessels supported by NSF are critical platforms contributing to academic oceanographic research in the US. The “underway” data sets obtained from the continuously operating geophysical, water column, and meteorological sensors aboard these vessels provide characterization of basic environmental conditions for the oceans and are of high scientific value for building global syntheses, climatologies, and historical time series of ocean properties (e.g the World Ocean Atlas, the GMRT bathymetric synthesis, ICOADS). The Rolling deck to Repository program (www.rvdata.us) provides a central shore-side data gateway that ensures the basic documentation, assessment and submission of all environmental data from ship operators to the NOAA long-term archives for these data. R2R provides a set of data services for the oceanographic research community, including: publishing an online, searchable and browsable master cruise catalog, supported by cruise and data set DOIs; organizing, archiving, and disseminating original underway data and documents; assessing data quality on select data types; creating select post-field data products; and supporting at-sea event logging. In this presentation we will discuss new developments in R2R data services and challenges associated with ship-based data management. A significant challenge is the dramatic increase in data volumes associated with new sensors (e.g. the EK80 Sonar systems) whereby individual cruise distributions can be several terabytes. Ship operators, R2R and NCEI must design a way to move and store these growing volumes. R2R is also working to make information more accessible and complete. A new website has been launched along with API web services that allow users to find and use data more easily. R2R is working to improve device metadata, including working to identify the time sources for all environmental sensors to support accurate comparison and merging of data sets.
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.
Bourassa, M. A., Hughes, P. J., & Smith, S. R. (2008). Surface Turbulent Flux Product Comparison. Flux News , 5 , 22–24.
Smith, S. R., J. T. Rettig, J. Rolph, J. Hu, E. C. Kent, E. Schulz, R. Verein, S. Rutz, and C. Paver. (2010). The Data Management System for the Shipboard Automated Meteorological and Oceanographic System (SAMOS) Initiative. In J. Hall, D. E. Harrison, & D. Stammer (Eds.), Proceedings of OceanObs'09: Sustained Ocean Observations and Information for Society (Vol. 2).
Smith, S. R., M. A. Bourassa, E. F. Bradley, C. Cosca, C. W. Fairall, G. J. Goni, J. T. Gunn, M. Hood, D. L. Jackson, E. C. Kent, G. Lagerloef, P. McGillivary, L. Petit de la Villeon, R. T. Pinker, E. Schulz, J. Sprintall, D. Stammer, A. Weill, G. A. Wick, M. J. Yelland. (2010). Automated Underway Oceanic and Atmospheric Measurements from Ships. In D. D.E. and Stammer Harrison J. Hall (Ed.), Proceedings of OceanObs'09: Sustained Ocean Observations and Information for Society (Vol. 2).
Smith, S. R. (2007). Shipboard Automated Meteorological and Oceanographic System (SAMOS) Initiative. In Report for 4rd session of the JCOMM Ship Observation Team meeting, 16-21 April 2007, Geneva, Switzerland (2).
Smith, S. R. (2004). Report from the 2nd workshop on high-resolution marine meteorology . COAPS Technical Report 04-01. Tallahassee, FL: Center for Ocean-Atmospheric Prediction Studies, Florida State University.
Smith, S. R., Reynolds, R. M., & O'Brien, J. J. (2003). Report and Recommendations from the Workshop on High-Resolution Marine Meteorology . COAPS Technical Report 03-1. Tallahassee, FL: Center for Ocean-Atmospheric Prediction Studies, Florida State University.
