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Author (up) Hoffman, R.N.; Privé, N.; Bourassa, M.
Title Comments on “Reanalyses and Observations: What's the Difference?” Type $loc['typeJournal Article']
Year 2017 Publication Bulletin of the American Meteorological Society Abbreviated Journal Bull. Amer. Meteor. Soc.
Volume 98 Issue 11 Pages 2455-2459
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Abstract
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0003-0007 ISBN Medium
Area Expedition Conference
Funding Approved $loc['no']
Call Number COAPS @ mfield @ Serial 371
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Author (up) Hoffman, R.N.; Privé, N.; Bourassa, M.
Title Comments on “Reanalyses and Observations: What's the Difference?” Type $loc['typeJournal Article']
Year 2017 Publication Bulletin of the American Meteorological Society Abbreviated Journal Bull. Amer. Meteor. Soc.
Volume 98 Issue 11 Pages 2455-2459
Keywords GEOPHYSICAL DATA; marine surface winds; energy and water cycles
Abstract Are there important differences between reanalysis data and familiar observations and measurements? If so, what are they? This essay evaluates four possible answers that relate to: the role of inference, reliance on forecasts, the need to solve an ill-posed inverse problem, and understanding of errors and uncertainties. The last of these is argued to be most significant. The importance of characterizing uncertainties associated with results—whether those results are observations or measurements, analyses or reanalyses, or forecasts—is emphasized.
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0003-0007 ISBN Medium
Area Expedition Conference
Funding Approved $loc['no']
Call Number COAPS @ rl18 @ Serial 990
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Author (up) Holbach, H.M.; Bourassa, M.A.
Title Platform and Across-Swath Comparison of Vorticity Spectra From QuikSCAT, ASCAT-A, OSCAT, and ASCAT-B Scatterometers Type $loc['typeJournal Article']
Year 2017 Publication IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Abbreviated Journal IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing
Volume 10 Issue 5 Pages 2205-2213
Keywords Consistency; intercalibration; scatterometer; vorticity
Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1939-1404 ISBN Medium
Area Expedition Conference
Funding Approved $loc['no']
Call Number COAPS @ mfield @ Serial 21
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Author (up) Holbach, H.M.; Bourassa, M.A.
Title The Effects of Gap-Wind-Induced Vorticity, the Monsoon Trough, and the ITCZ on East Pacific Tropical Cyclogenesis Type $loc['typeJournal Article']
Year 2014 Publication Monthly Weather Review Abbreviated Journal Mon. Wea. Rev.
Volume 142 Issue 3 Pages 1312-1325
Keywords Central America; Remote sensing; Vorticity; Valley/mountain flows; Tropical cyclones; Cyclogenesis/cyclolysis
Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0027-0644 ISBN Medium
Area Expedition Conference
Funding Approved $loc['no']
Call Number COAPS @ mfield @ Serial 130
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Author (up) Holbach, H.M.; Uhlhorn, E.W.; Bourassa, M.A.
Title Off-Nadir SFMR Brightness Temperature Measurements in High-Wind Conditions Type $loc['typeJournal Article']
Year 2018 Publication Journal of Atmospheric and Oceanic Technology Abbreviated Journal J. Atmos. Oceanic Technol.
Volume 35 Issue 9 Pages 1865-1879
Keywords Tropical cyclones; Wind; Air-sea interaction; Microwave observations; Remote sensing; Surface observations
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).
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0739-0572 ISBN Medium
Area Expedition Conference
Funding Approved $loc['no']
Call Number COAPS @ rl18 @ Serial 980
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Author (up) Huang, T.; Armstrong, E.M.; Bourassa, M.A.; Cram, T.A.; Elya, J.; Greguska, F.; Jacob, J.C.; Ji, Z.; Jiang, Y.; Li, Y.; Quach, N.T.; McGibbney, L.J.; Smith, S.R.; Wilson, B.D.; Worley S.J.; Yang, C.
Title An Integrated Data Analytics Platform Type $loc['typeJournal Article']
Year 2019 Publication Marine Science Abbreviated Journal Mar. Sci.
Volume 6 Issue Pages
Keywords big data, Cloud computing, Ocean science, data analysis, Matchup, anomaly detection, open source
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.
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Funding Approved $loc['no']
Call Number COAPS @ user @ Serial 1038
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Author (up) Hughes, P. J.; Bourassa, M. A.; Rolph, J.; Smith, S. R.
Title Interdecadal Variability of Surface Heat Fluxes Over the Atlantic Ocean Type $loc['typeReport']
Year 2006 Publication Abbreviated Journal
Volume Issue Pages 2:17-18
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Abstract
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Corporate Author Thesis
Publisher World Meteorological Organization Place of Publication Editor Cote, J.
Language Summary Language Original Title
Series Editor Series Title CAS/JSC Working Group on Numerical Experimentation, Research Activities in Atmospheric and Oceanic Modeling Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Funding NOAA, NSF Approved $loc['no']
Call Number COAPS @ mfield @ Serial 923
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Author (up) Hughes, P.J.; Bourassa, M.A.; Rolph, J.J.; Smith, S.R.
Title Averaging-Related Biases in Monthly Latent Heat Fluxes Type $loc['typeJournal Article']
Year 2012 Publication Journal of Atmospheric and Oceanic Technology Abbreviated Journal J. Atmos. Oceanic Technol.
Volume 29 Issue 7 Pages 974-986
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Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0739-0572 ISBN Medium
Area Expedition Conference
Funding NOAA Approved $loc['no']
Call Number COAPS @ mfield @ Serial 246
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Author (up) Jacob, J. C.; Armstrong, E. M.; Bourassa, M. A.; Cram, T.; Elya, J. L.; Greguska, F. R., III; Huang, T.; Ji, Z.; Jiang, Y.; Li, Y.; McGibbney, L. J.; Quach, N.; Smith, S. R.; Tsontos, V. M.; Wilson, B. D.; Worley, S. J.; Yang, C. P.
Title OceanWorks: Enabling Interactive Oceanographic Analysis in the Cloud with Multivariate Data Type $loc['typeAbstract']
Year 2018 Publication American Geophysical Union Abbreviated Journal AGU
Volume Fall Meeting Issue Pages
Keywords 910 Data assimilation, integration and fusion, INFORMATICSDE: 1916 Data and information discovery, INFORMATICSDE: 1926 Geospatial, INFORMATICSDE: 1942 Machine learning, INFORMATICS
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.
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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ISSN ISBN Medium
Area Expedition Conference
Funding Approved $loc['no']
Call Number COAPS @ user @ Serial 1005
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Author (up) Kara, A.B.; Hurlburt, H.E.; Wallcraft, A.J.; Bourassa, M.A.
Title Black Sea Mixed Layer Sensitivity to Various Wind and Thermal Forcing Products on Climatological Time Scales Type $loc['typeJournal Article']
Year 2005 Publication Journal of Climate Abbreviated Journal J. Climate
Volume 18 Issue 24 Pages 5266-5293
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0894-8755 ISBN Medium
Area Expedition Conference
Funding DOD, NRL Approved $loc['no']
Call Number COAPS @ mfield @ Serial 446
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