An Open Science oriented Bayesian interpolation model for marine parameter observations

Coro G.

Geospatial interpolation  Marine science  Advection-diffusion  Markov chain Monte Carlo  Bayesian models  Artificial intelligence 

Ecological and ecosystem modellers frequently need to interpolate spatiotemporal observations of geophysical and environmental parameters over an analysed area. However, particularly in marine science, modellers with low expertise in oceanography and hydrodynamics can hardly use interpolation methods optimally. This paper introduces an Open Science oriented, open-source, scalable and efficient workflow for 2D marine environmental parameters. It combines a fast, efficient interpolation method with a Bayesian hierarchical model embedding the stationary advection-diffusion equation as a constraint. Our workflow fills the usability gap between interpolation software providers and the users' communities. It can run entirely automatically without requiring expert parametrization. It is also available on a cloud computing platform, with a Web Processing Service compliant interface, supporting collaboration, repeatability, reproducibility, and provenance tracking. We demonstrate that our workflow produces comparable results to a state-of-the-art model (frequently used in oceanography) in interpolating four environmental parameters at the global scale.

Source: Environmental modelling & software (2023). doi:10.1016/j.envsoft.2023.105901

Publisher: Elsevier,, Oxford , Regno Unito

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