The Physical Limit of Neural Hypoxia Detection in the Black Sea from Satellite Observations

Fuente: arXiv
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Main Authors: Mangeleer, Victor, Vandenbulcke, Luc, Grégoire, Marilaure, Louppe, Gilles
Format: Preprint
Published: 2026
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author Mangeleer, Victor
Vandenbulcke, Luc
Grégoire, Marilaure
Louppe, Gilles
author_facet Mangeleer, Victor
Vandenbulcke, Luc
Grégoire, Marilaure
Louppe, Gilles
contents Coastal hypoxia (O_2 < 63 [mmol / m^3]) threatens ocean health worldwide. On continental shelves, summer stratification prevents bottom oxygen consumed by respiration from being renewed, making monitoring essential to protect vulnerable ecosystems and reduce biodiversity loss. Although satellite observations are increasingly available, their potential to infer subsurface oxygen remains largely unexplored. This can be framed as a Bayesian inverse problem relating surface observations to the complete Black Sea states. Here, we solve it using a deep generative neural network trained on numerical model outputs, providing a tractable and computationally efficient approximation of the true posterior distribution of sea states. We find that accurate state estimation is limited to the mixed layer, because its homogeneity makes surface conditions representative of subsurface states. During summer, we detect 38% of all hypoxic events shelf-wide with a precision of 47%. Improving results will likely require longer assimilation windows or sub-surface observations.
format Preprint
id arxiv_https___arxiv_org_abs_2604_25608
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle The Physical Limit of Neural Hypoxia Detection in the Black Sea from Satellite Observations
Mangeleer, Victor
Vandenbulcke, Luc
Grégoire, Marilaure
Louppe, Gilles
Atmospheric and Oceanic Physics
Coastal hypoxia (O_2 < 63 [mmol / m^3]) threatens ocean health worldwide. On continental shelves, summer stratification prevents bottom oxygen consumed by respiration from being renewed, making monitoring essential to protect vulnerable ecosystems and reduce biodiversity loss. Although satellite observations are increasingly available, their potential to infer subsurface oxygen remains largely unexplored. This can be framed as a Bayesian inverse problem relating surface observations to the complete Black Sea states. Here, we solve it using a deep generative neural network trained on numerical model outputs, providing a tractable and computationally efficient approximation of the true posterior distribution of sea states. We find that accurate state estimation is limited to the mixed layer, because its homogeneity makes surface conditions representative of subsurface states. During summer, we detect 38% of all hypoxic events shelf-wide with a precision of 47%. Improving results will likely require longer assimilation windows or sub-surface observations.
title The Physical Limit of Neural Hypoxia Detection in the Black Sea from Satellite Observations
topic Atmospheric and Oceanic Physics
url https://arxiv.org/abs/2604.25608