Ensemble analysis and forecast of ecosystem indicators in the North Atlantic using ocean colour observations and prior statistics from a stochastic NEMO–PISCES simulator

Popov, Mikhail; Brankart, Jean-Michel; Capet, Arthur; Cosme, Emmanuel; Brasseur, Pierre

doi:https://doi.org/10.5194/os-20-155-2024

Articles | Volume 20, issue 1

https://doi.org/10.5194/os-20-155-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/os-20-155-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 20, issue 1

Research article

|

16 Feb 2024

Research article |

| 16 Feb 2024

Ensemble analysis and forecast of ecosystem indicators in the North Atlantic using ocean colour observations and prior statistics from a stochastic NEMO–PISCES simulator

Mikhail Popov, Jean-Michel Brankart, Arthur Capet, Emmanuel Cosme, and Pierre Brasseur

Model code and software

Development of a probabilistic ocean modelling system based on NEMO4.0: a contribution to the SEAMLESS project M. Popov et al. https://doi.org/10.5281/zenodo.6303007

brankart/ensdam: ensdam Jean-Michel Brankart https://doi.org/10.5281/zenodo.10617516

brankart/sesam: sesam Jean-Michel Brankart https://doi.org/10.5281/zenodo.10617526

brankart/ensemble-ocean-colour: ensemble-ocean-color Jean-Michel Brankart https://doi.org/10.5281/zenodo.10617498

Short summary

This study contributes to the development of methods to estimate targeted ocean ecosystem indicators, including their uncertainty, in the framework of the Copernicus Marine Service. A simplified approach is introduced to perform a 4D ensemble analysis and forecast, directly targeting selected biogeochemical variables and indicators (phenology, trophic efficiency, downward flux of organic matter). Care is taken to present the methods and discuss the reliability of the solution proposed.