Preprints
https://doi.org/10.5194/egusphere-2024-2710
https://doi.org/10.5194/egusphere-2024-2710
11 Oct 2024
 | 11 Oct 2024
Status: this preprint is open for discussion.

Parameterisation toolbox for physical-biogeochemical model compatible with FABM. Case study: the coupled 1D GOTM-ECOSMO E2E for the Sylt-Romo Bight, North Sea

Hoa T. T. Nguyen, Ute Daewel, Neil Banas, and Corinna Schrum

Abstract. Mathematical models serve as invaluable tool for comprehending marine ecosystems. The performance of these models is often highly dependent on their parameters. Traditionally, refining these models involved a time-intensive trial-and-error approach to identify model parameter values that are able to reproduce observations well. However, as ecosystem models grow in complexity, this approach becomes impractical. With advancements in computing power, optimization techniques have emerged as a viable alternative. Yet, these techniques often exhibit model-specific tailoring, limiting their broader application. In this study, we introduce a parameterisation toolbox founded on a Particle Swarm Optimizer (PSO) implemented in the Framework for Aquatic Biogeochemical Models (FABM), which allows its reuse between numerous existing models in FABM, and thus makes the optimizer more accessible to the community. The PSO toolbox's effectiveness is demonstrated through its implementation on a 1D physical-biogeochemical model (GOTM-ECOSMO E2E), which successfully parameterised the Sylt-Romo Bight ecosystem. The toolbox was able to identify most of the tuned parameters and to suggest potential ranges for poorly constrained parameters. In addition, the toolbox uncovers a number of parameter sets with notable differences in some parameter values, but resulting in not much difference in biomass and fluxes. Furthermore, by experimenting with optimisation models of varying complexity, the toolbox was able to define an optimal model for the Sylt-Romo Bight.

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Hoa T. T. Nguyen, Ute Daewel, Neil Banas, and Corinna Schrum

Status: open (until 14 Dec 2024)

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Hoa T. T. Nguyen, Ute Daewel, Neil Banas, and Corinna Schrum
Hoa T. T. Nguyen, Ute Daewel, Neil Banas, and Corinna Schrum

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Short summary
Parameterisation is key in modeling to reproduce observations well but is often done manually. This study presents a Particle Swarm Optimizer-based toolbox for marine ecosystem models, compatible with the Framework for Aquatic Biogeochemical Models, thus enhancing its reusability. Applied to the Sylt ecosystem, the toolbox effectively (1) identified multiple parameter sets that matched observations well, thus providing different insights into ecosystem dynamics, (2) optimized model complexity.