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OPENCoastS: An Open-Access App for Sharing Coastal Prediction Information for Management and Recreation

  • Anabela OliveiraEmail author
  • Marta Rodrigues
  • João Rogeiro
  • André B. Fortunato
  • Joana Teixeira
  • Alberto Azevedo
  • Pedro Lopes
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11540)

Abstract

Coastal forecast systems provide coastal managers with accurate and timely hydrodynamic predictions, supporting multiple uses such as navigation, water monitoring, port operations and dredging activities. They are also useful to support recreational activities. Still, the widespread use of coastal forecasts is limited by the unavailability of open forecasts for consultation, the expertise needed to build operational forecast systems and the human and computational resources required to maintain them in operation every day. A new service for the generic deployment of forecast systems at user-specified locations was developed to address these limitations. Denoted OPENCoastS, this service builds circulation forecast systems for user-selected coastal areas and maintains them in operation using the European Open Science Cloud (EOSC) computational resources. OPENCoastS can be applied to any coastal region and has been in operation since 2018, forced by several regional and global forecasts of the atmospheric and ocean dynamics. It has attracted over 150 users from around 45 institutions across the globe. However, most users come from research institutions. The only requirement needed to use this service – a computational grid of the domain of interest – has proven difficult to obtain by most coastal managers. Herein, a new way to bring coastal managers and the general public to the OPENCoastS community is proposed. By creating an open, scalable and organized repository of computational grids, shared by expert coastal modelers across the globe, the benefits from the use of OPENCoastS can now be extended to all coastal actors.

Keywords

Open data repositories Coastal forecasts Unstructured grids 

Notes

Acknowledgements

This work was partially funded by EC H2020 project EOSC-hub (Grant Agreement No 777536), by Lisboa2020 Operational Program through the INCD project (LISBOA-01-0145-FEDER-022153) and by FCT, UBEST project (PTDC/AAG-MAA/6899/2014).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Anabela Oliveira
    • 1
    Email author
  • Marta Rodrigues
    • 2
  • João Rogeiro
    • 1
  • André B. Fortunato
    • 2
  • Joana Teixeira
    • 1
  • Alberto Azevedo
    • 2
  • Pedro Lopes
    • 1
  1. 1.Information Technology in Water and Environment DivisionLNECLisbonPortugal
  2. 2.Estuaries and Coastal Zones DivisionLNECLisbonPortugal

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