Preprints
https://doi.org/10.5194/sp-2024-36
https://doi.org/10.5194/sp-2024-36
14 Oct 2024
 | 14 Oct 2024
Status: this preprint is currently under review for the journal SP.

Connecting Ocean Observations with Prediction

Pierre-Yves Le Traon, Antonio Novellino, and Andrew M. Moore

Abstract. Ocean prediction relies on the integration between models, satellite and in-situ observations through data assimilation techniques. Satellites offer nowadays high-resolution observations of essential ocean variables at the surface, widely adopted in combination with precise but sparse in-situ measurements that, from the surface to the deep ocean, can constrain large scale variability in models. Moreover, observations are a valuable source of information for validating and assessing model products, for improving them and for developing the next generation of machine learning algorithms aimed at enhancing the accuracy and scope of ocean forecasts. The authors discuss the role of observations in operational ocean forecasting systems, describing the state-of-the-art of satellite and in-situ observing networks and defining the paths for addressing multi-scale monitoring and forecasting.

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Pierre-Yves Le Traon, Antonio Novellino, and Andrew M. Moore

Status: open (until 28 Dec 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on sp-2024-36', Peter Oke, 18 Oct 2024 reply
    • AC1: 'Reply on CC1', Pierre-Yves Le Traon, 25 Oct 2024 reply
    • RC2: 'Comment on SP-2024-36', Peter Oke, 03 Dec 2024 reply
      • AC4: 'Reply on RC2', Pierre-Yves Le Traon, 03 Dec 2024 reply
  • RC1: 'Comment on sp-2024-36', Anonymous Referee #1, 23 Nov 2024 reply
    • AC3: 'Reply on RC1', Pierre-Yves Le Traon, 25 Nov 2024 reply
  • AC2: 'Reply on RC1', Pierre-Yves Le Traon, 25 Nov 2024 reply
Pierre-Yves Le Traon, Antonio Novellino, and Andrew M. Moore
Pierre-Yves Le Traon, Antonio Novellino, and Andrew M. Moore

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Short summary
Ocean prediction relies on the integration between models, satellite and in-situ observations through data assimilation techniques. The authors discuss the role of observations in operational ocean forecasting systems, describing the state-of-the-art of satellite and in-situ observing networks and defining the paths for addressing multi-scale monitoring and forecasting.
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