A RUpture-Based detection method for the Active mesopeLagIc Zone (RUBALIZ): A crucial step toward rigorous carbon budget assessments
Determining mesopelagic organic carbon budgets is essential to characterize the ocean's role as a carbon dioxide sink. This is because the biological processes observed in the mesopelagic zone are crucial for understanding the biological carbon pump. Yet, field assessments of carbon budgets are often unbalanced with the carbon demand exceeding its supply. This underlines either methodological issues in the budget calculations or incomplete knowledge of the mesopelagic carbon cycling with potentially missing sources. Carbon budgets are built by partitioning the ocean into vertical depth zones. Vertical boundaries are conventionally defined between 200 and 1000 m depth or using various thresholds. Such approaches lack consistent methodology preventing robust comparison of mesopelagic carbon budget from region to region. Here, using a statistical rupture detection method applied to conductivity–temperature–depth (CTD)-cast variables (fluorescence, O2 concentration, potential temperature, salinity, and density), we aim to provide independent estimates of mesopelagic boundaries. We demonstrate that the so-determined upper boundary is highly correlated with the knee points of the particulate organic carbon (POC) fluxes estimated by a power law and that over 90% of the POC flux attenuation occurs within our method boundaries. The identified zone therefore corresponds to the most active part of the conventional mesopelagic zone and we name it the “active mesopelagic zone” (AMZ). We find that the depths of the mesopelagic zone depend on the region considered. Our results demonstrate that the mesopelagic carbon budget discrepancy can vary up to four folds depending on the boundaries chosen and hence provide novel grounds to reassess existing and future mesopelagic carbon budgets.
Code (2)
Similar Papers 제목 키워드 기반
CEVAR: Centerline Embedding Extraction for Endovascular Aneurysm Repair
Long-term mortality rates after endovascular aneurysm repair (EVAR) remain elevated due to post-EVAR rupture caused by loss of seal in stent graft sealing zones. Structured CT review using centerline measurements improve…
A Multi-Agent Rhizomatic Pipeline for Non-Linear Literature Analysis
Systematic literature reviews in the social sciences overwhelmingly follow arborescent logics -- hierarchical keyword filtering, linear screening, and taxonomic classification -- that suppress the lateral connections, ru…
On the performance of sequential Bayesian update for database of diverse tsunami scenarios
Although the sequential tsunami scenario detection framework was validated in our previous work, several tasks remain to be resolved from a practical point of view. This study aims to evaluate the performance of the prev…
Dynamic Time WarpingAnomaly detection in satellite imagery through temporal inpainting
Detecting surface changes from satellite imagery is critical for rapid disaster response and environmental monitoring, yet remains challenging due to the complex interplay between atmospheric noise, seasonal variations, …
Anomaly DetectionChange DetectionMachine Learning Approach to Earthquake Rupture Dynamics
Simulating dynamic rupture propagation is challenging due to the uncertainties involved in the underlying physics of fault slip, stress conditions, and frictional properties of the fault. A trial and error approach is of…
BIG-bench Machine LearningFriction