Bourassa, M. A., H. Bonekamp, P. Chang, D. Chelton, J. Courtney, R. Edson, J. Figa, Y. He, H. Hersbach, K. Hilburn, Z. Jelenak, T. Lee, W. T. Liu, D. Long, K. Kelly, R. Knabb, E. Lindstorm, W. Perrie, M. Portabella, M. Powell, E. Rodriguez, D. Smith, A. Stoffelen, V. Swail, F. Wentz. (2010). Remotely Sensed Winds and Wind Stresses for Marine Forecasting and Ocean Modeling. In D. D.E. and Stammer Harrison J. Hall (Ed.),
Proceedings of OceanObs'09: Sustained Ocean Observations and Information for Society (Vol. 2).
Bourassa, M. A., Hughes, P. J., & Smith, S. R. (2008). Surface Turbulent Flux Product Comparison.
Flux News, 5, 22–24.
Hilburn, K. A., Bourassa, M. A., & O'Brien, J. J. (2002).
Development of scatterometer-derived research-quality surface pressure fields for the Southern Ocean. Orlando, FL: AMS.
Bourassa, M. A. (2001). Tehuantepec wind and pressure changes associated with tropical cyclones. In
11th Conference on Interactions of the Sea and Atmosphere, Amer. Meteor. Soc., San Diego, CA, USA (pp. 27–28).
Fairall, C. W., Barnier, B., Berry, D.I, Bourassa, M.A., Bradley, E.F., Clayson, C.A., de Leeuw, G., Drennan, W.M., Gille, S.T., Gulev, S.K., Kent, E.C., McGillis, W.R., Quartly, G.D., Ryabinin, V., Smith, S.R., Weller, R.A., Yelland, M.J. and Zhang, H-M. (2010). Observations to Quantify Air-Sea Fluxes and Their Role in Climate Variability and Predictability. In D.(eds.) D.E. and Stammer Harrison J. Hall (Ed.),
Proceedings of OceanObs'09: Sustained Ocean Observations and Information for Society, Vol. 2 (pp. 299–313). European Space Agency.
Weissman, D. E., Morey, S., & Bourassa, M. (2017). Studies of the effects of rain on the performance of the SMAP radiometer surface salinity estimates and applications to remote sensing of river plumes. In
IEEE International Symposium on Geoscience and Remote Sensing IGARSS (pp. 1491–1494).
Ardhuin, F., Chapron, B., Maes, C., Romeiser, R., Gommenginger, C., Cravatte, S., et al. (2019). Satellite Doppler observations for the motions of the oceans.
Bull. Amer. Meteor. Soc., .
Abstract: Satellite remote sensing has revolutionized oceanography, starting from sea surface temperature, ocean color, sea level, winds, waves, and the recent addition of sea surface salinity, providing a global view of upper ocean processes. The possible addition of a direct measurement of surface velocities related to currents, winds and waves opens great opportunities for research and applications.
Katsaros, K. B., Bentamy, A., Bourassa, M., Ebuchi, N., Gower, J., Liu, W. T., et al. (2011). Climate Data Issues from an Oceanographic Remote Sensing Perspective. In D. Tang (Ed.),
Remote Sensing of the Changing Oceans (pp. 7–32). Berlin: Springer.
Bourassa, M., Gille, S., Jackson, D., Roberts, J. B., & Wick, G. (2010). Ocean Winds and Turbulent Air-Sea Fluxes Inferred From Remote Sensing.
Oceanog., 23(4), 36–51.
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.