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Author (up) Davidson, F.; Alvera-Azcárate, A.; Barth, A.; Brassington, G.B.; Chassignet, E.P.; Clementi, E.; De Mey-Frémaux, P.; Divakaran, P.; Harris, C.; Hernandez, F.; Hogan, P.; Hole, L.R.; Holt, J.; Liu, G.; Lu, Y.; Lorente, P.; Maksymczuk, J.; Martin, M.; Mehra, A.; Melsom, A.; Mo, H.; Moore, A.; Oddo, P.; Pascual, A.; Pequignet, A.-C.; Kourafalou, V.; Ryan, A.; Siddorn, J.; Smith, G.; Spindler, D.; Spindler, T.; Stanev, E.V.; Staneva, J.; Storto, A.; Tanajura, C.; Vinayachandran, P.N.; Wan, L.; Wang, H.; Zhang, Y.; Zhu, X.; Zu, Z. url  doi
openurl 
  Title Synergies in Operational Oceanography: The Intrinsic Need for Sustained Ocean Observations Type $loc['typeJournal Article']
  Year 2019 Publication Frontiers in Marine Science Abbreviated Journal Front. Mar. Sci.  
  Volume 6 Issue Pages  
  Keywords  
  Abstract Operational oceanography can be described as the provision of routine oceanographic information needed for decision-making purposes. It is dependent upon sustained research and development through the end-to-end framework of an operational service, from observation collection to delivery mechanisms. The core components of operational oceanographic systems are a multi-platform observation network, a data management system, a data assimilative prediction system, and a dissemination/accessibility system. These are interdependent, necessitating communication and exchange between them, and together provide the mechanism through which a clear picture of ocean conditions, in the past, present, and future, can be seen. Ocean observations play a critical role in all aspects of operational oceanography, not only for assimilation but as part of the research cycle, and for verification and validation of products. Data assimilative prediction systems are advancing at a fast pace, in tandem with improved science and the growth in computing power. To make best use of the system capability these advances would be matched by equivalent advances in operational observation coverage. This synergy between the prediction and observation systems underpins the quality of products available to stakeholders, and justifies the need for sustained ocean observations. In this white paper, the components of an operational oceanographic system are described, highlighting the critical role of ocean observations, and how the operational systems will evolve over the next decade to improve the characterization of ocean conditions, including at finer spatial and temporal scales.  
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  ISSN 2296-7745 ISBN Medium  
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  Call Number COAPS @ user @ Serial 1083  
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Author (up) Hiester, H.R.; Morey, S.L.; Dukhovskoy, D.S.; Chassignet, E.P.; Kourafalou, V.H.; Hu, C. url  doi
openurl 
  Title A topological approach for quantitative comparisons of ocean model fields to satellite ocean color data Type $loc['typeJournal Article']
  Year 2016 Publication Methods in Oceanography Abbreviated Journal Methods in Oceanography  
  Volume 17 Issue Pages 232-250  
  Keywords Satellite data; Ocean model; Ocean color; Sea surface salinity; Shape comparison; Hausdorff distance  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2211-1220 ISBN Medium  
  Area Expedition Conference  
  Funding Approved $loc['no']  
  Call Number COAPS @ mfield @ Serial 78  
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Author (up) Smith, S.R.; Briggs, K.; Lopez, N.; Kourafalou, V. url  doi
openurl 
  Title Applying Automated Underway Ship Observations to Numerical Model Evaluation Type $loc['typeJournal Article']
  Year 2016 Publication Journal of Atmospheric and Oceanic Technology Abbreviated Journal J. Atmos. Oceanic Technol.  
  Volume 33 Issue 3 Pages 409-428  
  Keywords Ship observations; Automatic weather stations; Ocean models; Model evaluation/performance; In situ atmospheric observations; Observational techniques and algorithms; Models and modeling; In situ oceanic observations  
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  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 @ mfield @ Serial 53  
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