Dukhovskoy, D. S., Bourassa, M. A., Petersen, G. N., & Steffen, J. (2017). Comparison of the ocean surface vector winds from atmospheric reanalysis and scatterometer-based wind products over the Nordic Seas and the northern North Atlantic and their application for ocean modeling.
J. Geophys. Res. Oceans, 122(3), 1943–1973.
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.
Gierach, M. M., Bourassa, M. A., Cunningham, P., O'Brien, J. J., & Reasor, P. D. (2007). Vorticity-Based Detection of Tropical Cyclogenesis.
J. Appl. Meteor. Climatol., 46(8), 1214–1229.
Gille, S., Bourassa, M. A., & Clayson, C. A. (2010). Improving Observations of High-Latitude Fluxes Between Atmosphere, Ocean, and Ice: Surface Fluxes: Challenges at High Latitudes; Boulder, Colorado, 17-19 March 2010.
Eos Trans. AGU, 91(35), 307.
Guimond, S. R., Bourassa, M. A., & Reasor, P. D. (2011). A Latent Heat Retrieval and Its Effects on the Intensity and Structure Change of Hurricane Guillermo (1997). Part I: The Algorithm and Observations.
J. Atmos. Sci., 68(8), 1549–1567.
Hanley, D. E., Bourassa, M. A., O'Brien, J. J., Smith, S. R., & Spade, E. R. (2003). A Quantitative Evaluation of ENSO Indices.
J. Climate, 16(8), 1249–1258.
Holbach, H. M., & Bourassa, M. A. (2014). The Effects of Gap-Wind-Induced Vorticity, the Monsoon Trough, and the ITCZ on East Pacific Tropical Cyclogenesis.
Mon. Wea. Rev., 142(3), 1312–1325.
Holbach, H. M., & Bourassa, M. A. (2017). Platform and Across-Swath Comparison of Vorticity Spectra From QuikSCAT, ASCAT-A, OSCAT, and ASCAT-B Scatterometers.
IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing, 10(5), 2205–2213.
Holbach, H. M., Uhlhorn, E. W., & Bourassa, M. A. (2018). Off-Nadir SFMR Brightness Temperature Measurements in High-Wind Conditions.
J. Atmos. Oceanic Technol., 35(9), 1865–1879.
Abstract: Wind and wave-breaking directions are investigated as potential sources of an asymmetry identified in off-nadir remotely sensed measurements of ocean surface brightness temperatures obtained by the Stepped Frequency Microwave Radiometer (SFMR) in high-wind conditions, including in tropical cyclones. Surface wind speed, which dynamically couples the atmosphere and ocean, can be inferred from SFMR ocean surface brightness temperature measurements using a radiative transfer model and an inversion algorithm. The accuracy of the ocean surface brightness temperature to wind speed calibration relies on accurate knowledge of the surface variables that are influencing the ocean surface brightness temperature. Previous studies have identified wind direction signals in horizontally polarized radiometer measurements in low to moderate (0�20 m s−1) wind conditions over a wide range of incidence angles. This study finds that the azimuthal asymmetry in the off-nadir SFMR brightness temperature measurements is also likely a function of wind direction and extends the results of these previous studies to high-wind conditions. The off-nadir measurements from the SFMR provide critical data for improving the understanding of the relationships between brightness temperature, surface wave�breaking direction, and surface wind vectors at various incidence angles, which is extremely useful for the development of geophysical model functions for instruments like the Hurricane Imaging Radiometer (HIRAD).
Huang, T., Armstrong, E. M., Bourassa, M. A., Cram, T. A., Elya, J., Greguska, F., et al. (2019). An Integrated Data Analytics Platform.
Mar. Sci., 6.
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.