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Adams, D. K., McGillicuddy, D. J. J., Zamudio, L., Thurnherr, A. M., Liang, X., Rouxel, O., et al. (2011). Surface-generated mesoscale eddies transport deep-sea products from hydrothermal vents. Science, 332(6029), 580–583.
Abstract: Atmospheric forcing, which is known to have a strong influence on surface ocean dynamics and production, is typically not considered in studies of the deep sea. Our observations and models demonstrate an unexpected influence of surface-generated mesoscale eddies in the transport of hydrothermal vent efflux and of vent larvae away from the northern East Pacific Rise. Transport by these deep-reaching eddies provides a mechanism for spreading the hydrothermal chemical and heat flux into the deep-ocean interior and for dispersing propagules hundreds of kilometers between isolated and ephemeral communities. Because the eddies interacting with the East Pacific Rise are formed seasonally and are sensitive to phenomena such as El Nino, they have the potential to introduce seasonal to interannual atmospheric variations into the deep sea.
|Ahern, K. K. (2019). Hurricane Boundary Layer Structure during Intensity Change: An Observational and Numerical Analysis.|
|Ali, M. M., Bhat, G. S., Long, D. G., Bharadwaj, S., & Bourassa, M. A. (2013). Estimating Wind Stress at the Ocean Surface From Scatterometer Observations. IEEE Geosci. Remote Sensing Lett., 10(5), 1129–1132.|
|Ali, M. M., Bourassa, M. A., Bhowmick, S. A., Sharma, R., & Niharika, K. (2016). Retrieval of Wind Stress at the Ocean Surface From AltiKa Measurements. IEEE Geosci. Remote Sensing Lett., 13(6), 821–825.|
|Ali, M. M., Nagamani, P. V., Sharma, N., Venu Gopal, R. T., Rajeevan, M., Goni, G. J., et al. (2015). Relationship between ocean mean temperatures and Indian summer monsoon rainfall. Atmos. Sci. Lett., 16(3), 408–413.|
Armstrong, E. M., Bourassa, M. A., Cram, T. A., DeBellis, M., Elya, J., Greguska III, F. R., et al. (2019). An Integrated Data Analytics Platform. Front. Mar. Sci., 6, 354.
Abstract: An Integrated Science Data Analytics Platform is an environment that enables the confluence of resources for scientific investigation. It harmonizes data, tools and computational resources to enable the research community to focus on the investigation rather than spending time on security, data preparation, management, etc. OceanWorks is a NASA technology integration project to establish a cloud-based Integrated Ocean Science Data Analytics Platform for big ocean science at NASA’s Physical Oceanography Distributed Active Archive Center (PO.DAAC) for big ocean science. It focuses on advancement and maturity by bringing together several NASA open-source, big data projects for parallel analytics, anomaly detection, in situ to satellite data matchup, quality-screened data subsetting, search relevancy, and data discovery. Our communities are relying on data available through distributed data centers to conduct their research. In typical investigations, scientists would (1) search for data, (2) evaluate the relevance of that data, (3) download it, and (4) then apply algorithms to identify trends, anomalies, or other attributes of the data. Such a workflow cannot scale if the research involves a massive amount of data or multi-variate measurements. With the upcoming NASA Surface Water and Ocean Topography (SWOT) mission expected to produce over 20PB of observational data during its 3-year nominal mission, the volume of data will challenge all existing Earth Science data archival, distribution and analysis paradigms. This paper discusses how OceanWorks enhances the analysis of physical ocean data where the computation is done on an elastic cloud platform next to the archive to deliver fast, web-accessible services for working with oceanographic measurements.
|Bellow, J. G. (2006). El Niño-Southern Oscillation Effects and Forecasting Chill Unit Accumulation for Deciduous Fruit Crops in the Southeastern USA. In Southern Region American Society for Horticultural Science 66th Annual Meeting. Feb. 4-6, Orlando, Florida, United States.|
|Bourassa, M. A. (2009). Uncertainty in scatterometer derived vorticity. In 2009 IEEE International Geoscience and Remote Sensing Symposium (III-pp. 805– III-808).|
|Bourassa, M. A., & O'Brien, J. J. (1998). Non-inertial flow in NSCAT observations of Tehuantepec winds. In Proceedings of the NSCAT/QuikSCAT Science Team Workshop, Kona, Hawaii, USA.|
|Bourassa, M. A., & Weissman, D. E. (2003). The development and application of a sea surface stress model function for the QuikSCAT and ADEOS-II SeaWinds scatterometers. In IEEE International Symposium on Geoscience and Remote Sensing (IGARSS) (pp. 239–241).|