Validating Ocean General Circulation Models via Lagrangian Particle Simulation and Data from Drifting Buoys

  • Karan Bedi
  • David Gómez-UllateEmail author
  • Alfredo Izquierdo
  • Tomás Fernández Montblanc
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11539)


Drifting Fish Aggregating Devices (dFADs) are small drifting platforms with an attached solar powered buoy that report their position with daily frequency via GPS. We use data of 9,440 drifting objects provided by a buoys manufacturing company, to test the predictions of surface current velocity provided by two of the main models: the NEMO model used by Copernicus Marine Environment Monitoring Service (CMEMS) and the HYCOM model used by the Global Ocean Forecast System (GOFS).


Copernicus CMEMS HYCOM model Lagrangian trajectory simulation Fish Aggregating Devices 


  1. 1.
    Lopez, J., Moreno, G., Boyra, G., Dagorn, L.: A model based on data from echosounder buoys to estimate biomass of fish species associated with fish aggregating devices. Fishery Bull. 114(2), 166–178 (2016)CrossRefGoogle Scholar
  2. 2.
    Castro, J., Santiago, J., Santana-Ortega, A.: A general theory on fish aggregation to floating objects: an alternative to the meeting point hypothesis. Rev. Fish Biol. 11, 255–277 (2002)CrossRefGoogle Scholar
  3. 3.
    Dempster, T., Taquet, M.: Fish aggregation device (FAD) research: gaps in current knowledge and future directions for ecological studies. Rev. Fish Biol. Fish. 14(1), 21–42 (2004)CrossRefGoogle Scholar
  4. 4.
    Chassignet, E.P., et al.: US GODAE global ocean prediction with the hybrid coordinate ocean model (HYCOM). Oceanography 22, 64–75 (2009)CrossRefGoogle Scholar
  5. 5.
    Cummings, J.A.: Operational multivariate ocean data assimilation. Q. J. Roy. Meteorol. Soc. 131, 3583–3604 (2005)CrossRefGoogle Scholar
  6. 6.
    Madec, G., the NEMO team: NEMO ocean engine, Note du Pôle de modélisation 27, Institut Pierre-Simon Laplace (IPSL), France (2008). ISSN 1288-1619Google Scholar
  7. 7.
    Lange, M., Van Sebille, E.:Parcels v0.9: prototyping a Lagrangian ocean analysis framework for the petascale age. Geosci. Model Dev. (2017). Scholar
  8. 8.
    Delandmeter, P., Van Sebille, E.: The parcels v2.0 Lagrangian framework: new field interpolation schemes. Geosci. Model Dev. Discuss. (2019).
  9. 9.
    Van Sebille, E., et al.: Lagrangian ocean analysis: fundamentals and practices. Ocean Model. 121, 49–75 (2018)CrossRefGoogle Scholar
  10. 10.
    Fonteneau, A., Chassot, E., Bodin, N.: Global spatio-temporal patterns in tropical tuna purse seine fisheries on drifting fish aggregating devices (DFADs): taking a historical perspective to inform current challenges. Aquat. Living Resour. 26(1), 37–48 (2013)CrossRefGoogle Scholar
  11. 11.
    Trygonis, V., Georgakarakos, S., Dagorn, L., Brehmer, P.: Spatiotemporal distribution of fish schools around drifting fish aggregating devices. Fish. Res. 177, 39–49 (2016)CrossRefGoogle Scholar
  12. 12.
    Taquet, M., et al.: Characterizing fish communities associated with drifting fish aggregating devices (FADs) in the Western Indian ocean using underwater visual surveys. Aquat. Living Resour. 20(4), 331–341 (2007)CrossRefGoogle Scholar
  13. 13.
    Moreno, G., et al.: Fish aggregating devices (FADs) as scientific platforms. Fish. Res. 178, 122–129 (2016)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of MathematicsIndian Institute of Technology RoorkeeRoorkeeIndia
  2. 2.Higher School of EngineeringUniversity of CádizPuerto RealSpain
  3. 3.Departamento de Física TeóricaUniversidad Complutense de MadridMadridSpain
  4. 4.Applied Physics DepartmentUniversity of CádizPuerto RealSpain
  5. 5.Faculty of Marine Science (CACYTMAR)University of CádizPuerto RealSpain

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