Articles | Volume 31, issue 3
https://doi.org/10.5194/npg-31-303-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/npg-31-303-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
02 Jul 2024
Research article |
| 02 Jul 2024
| 02 Jul 2024
Selecting and weighting dynamical models using data-driven approaches
Pierre Le Bras
CORRESPONDING AUTHOR
Laboratoire d’Océanographie Physique et Spatiale, IUEM, Univ Brest CNRS IRD Ifremer, Brest, France
IMT Atlantique, Lab-STICC, UMR CNRS 6285, 29238, Brest, France
Odyssey team project, INRIA IMT Atlantique CNRS, Brest, France
Florian Sévellec
Laboratoire d’Océanographie Physique et Spatiale, IUEM, Univ Brest CNRS IRD Ifremer, Brest, France
Odyssey team project, INRIA IMT Atlantique CNRS, Brest, France
Pierre Tandeo
IMT Atlantique, Lab-STICC, UMR CNRS 6285, 29238, Brest, France
Odyssey team project, INRIA IMT Atlantique CNRS, Brest, France
Juan Ruiz
Facultad de Ciencias Exactas y Naturales, Departamento de Ciencias de la Atmósfera y los Océanos, Universidad de Buenos Aires, Buenos Aires, Argentina
Centro de Investigaciones del Mar y la Atmósfera (CIMA), CONICET–Universidad de Buenos Aires, Buenos Aires, Argentina
Instituto Franco-Argentino para el Estudio del Clima y sus Impactos (IRL IFAECI), CNRS–IRD–CONICET–UBA, Buenos Aires, Argentina
Pierre Ailliot
Univ Brest, CNRS UMR 6205, Laboratoire de Mathematiques de Bretagne Atlantique, Brest, France
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Short summary
The goal of this paper is to weight several dynamic models in order to improve the representativeness of a system. It is illustrated using a set of versions of an idealized model describing the Atlantic Meridional Overturning Circulation. The low-cost method is based on data-driven forecasts. It enables model performance to be evaluated on their dynamics. Taking into account both model performance and codependency, the derived weights outperform benchmarks in reconstructing a model distribution.
The goal of this paper is to weight several dynamic models in order to improve the...
