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Data Assimilation for Ocean Drift Trajectories Using Massive Ensembles and GPUs

Sammendrag

In this work, we perform fully nonlinear data assimilation of ocean drift trajectories using multiple GPUs. We use an ensemble of up to 10000 members and the sequential importance resampling algorithm to assimilate observations of drift trajectories into the underlying shallow-water simulation model. Our results show an improved drift trajectory forecast using data assimilation for a complex and realistic simulation scenario, and the implementation exhibits good weak and strong scaling.

Kategori

Vitenskapelig Kapittel/Artikkel/Konferanseartikkel

Oppdragsgiver

  • Research Council of Norway (RCN) / 270053
  • Research Council of Norway (RCN) / 250935
  • Sigma2 / NN9550K

Språk

Engelsk

Forfatter(e)

Institusjon(er)

  • Norges teknisk-naturvitenskapelige universitet
  • SINTEF Digital / Mathematics and Cybernetics
  • OsloMet - storbyuniversitetet
  • Meteorologisk institutt

År

2020

Forlag

Springer

Bok

Finite Volumes for Complex Applications IX - Methods, Theoretical Aspects, Examples

Hefte nr.

323

ISBN

978-3-030-43650-6

Side(r)

715 - 724

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