Submitted as: model description paper 08 Jan 2021

Submitted as: model description paper | 08 Jan 2021

Review status: a revised version of this preprint was accepted for the journal GMD.

Ocean Plastic Assimilator v0.1: Assimilation of Plastics Concentration Data Into Lagrangian Dispersion Models

Axel Peytavin1, Bruno Sainte-Rose1, Gael Forget2, and Jean-Michel Campin2 Axel Peytavin et al.
  • 1The Ocean Cleanup, Batavierenstraat 15, 4-7th floor, 3014 JH Rotterdam, the Netherlands
  • 2Massachusetts Institute of Technology, Dept. of Earth, Atmospheric and Planetary Sciences, USA

Abstract. A numerical scheme to perform data assimilation of concentration measurements in Lagrangian models is presented, along with its first implementation called Ocean Plastic Assimilator, which aims at improving predictions of plastics distributions over the oceans. This scheme uses an ensemble method over a set of particle dispersion simulations. At each step, concentration observations are assimilated across the ensemble members by switching back and forth between Eulerian and Lagrangian representations. We design two experiments to assess the scheme efficacy and efficiency when assimilating simulated data in a simple double gyre model. Analysis convergence is observed with higher accuracy when lowering observation variance or using a more suitable circulation model. Results show that the distribution of plastic mass in an area can effectively be approached with this simple assimilation scheme. Thus, this method is considered a suitable candidate for creating a tool to assimilate plastic concentration observations in real-world applications to forecast plastic distributions in the oceans. Finally, several improvements that could further enhance the method efficiency are identified.

Axel Peytavin et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2020-385', Anonymous Referee #1, 25 Jan 2021
  • RC2: 'Comment on gmd-2020-385', Anonymous Referee #2, 29 Mar 2021
  • AC1: 'Final response to reviewers in GMDD', Axel Peytavin, 06 May 2021

Axel Peytavin et al.

Data sets

Assimilation of Plastics Concentration Data into Lagrangian Dispersion Models: Data Archive A. Peytavin

Model code and software

TheOceanCleanupAlgorithms/Ocean-Plastic-Assimilator: Version 0.1.1 A. Peytavin

Axel Peytavin et al.


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Short summary
We present a new algorithm developed at The Ocean Cleanup to update ocean plastic models based on measurements collected in the field to improve future cleaning operations. Prepared in collaboration with MIT researchers, this initial study presents its use in several test cases in which two observers in a simulated flow field record regular observations to update a plastic forecast. We demonstrate this improves the prediction, even with inaccurate knowledge of the water flows driving plastic.