Periodic Reporting for period 2 - EPOC (Explaining and Predicting the Ocean Conveyor)
Reporting period: 2024-01-01 to 2025-06-30
The concern now is that in a warming climate, the remaining northern hemisphere ice sheets or the intensification of the hydrological cycle could input sufficient freshwater to the North Atlantic to slow or shutdown the AMOC. The subsequent reorganisation of the climate system following a shutdown of the AMOC could be dramatic, resulting in changing distributions of mean and variable temperatures and weather patterns across Europe and beyond. While the IPCC report in 2021 (chapter 9) indicated high confidence that the AMOC will decline in the 21st century, there is low confidence in the magnitude of the decline and only medium confidence that it will not collapse by 2100. Simultaneously, the IPCC assessment reduced confidence (from medium to low confidence) in whether the AMOC is already declining, citing missing key processes in numerical simulations used to predict future AMOC evolution.
Against this backdrop, EPOC outcomes are anticipated to deepen our process-level understanding of this complex circulation system and contribute to assessment of past AMOC change and future evolution. The project uses multi-observational consistent approaches to diagnose AMOC variability since 1993, and re-evaluation of paleo-proxies for AMOC variability since 1950. EPOC employs high-resolution coupled climate models with grid spacing roughly 10 times finer than standard models, testing the expectation that finer resolution can reduce model biases and increase confidence in AMOC representation.
Beyond contributing to assessments, EPOC works towards a more sustainable next-generation AMOC observing system. Many recent advances in understanding the AMOC and identifying missing processes in climate models are due to observing efforts since 2000; however, the system has not been optimised and represents substantial investments by multiple international programmes. Through modelling and observing tests, EPOC will recommend a future AMOC observing system across the whole Atlantic, incorporating next-generation technologies where appropriate.
The consortium deployed next-generation observing technologies, including drift-free bottom pressure recorders at key AMOC monitoring latitudes and in situ mooring arrays at 47°N to capture transport variability in the transition zone between the subpolar and subtropical regions. Advanced machine learning approaches, particularly Bayesian hierarchical modelling, have been developed and applied to create multi-observational transport records for the AMOC meridional heat transport, integrating satellite altimetry, gravimetry and in situ oceanographic observations. Tools for computing time-varying, synoptic, observationally-based transports into and out of the Arctic for the period 2004–2020 have been developed and tested, providing new capabilities for Arctic-Atlantic connectivity. Systematic re-evaluation of paleoclimate proxy methods has advanced understanding of AMOC variability in the past, and how robustly it can be estimated.
High-resolution coupled climate model experiments have been conducted using a range of grid spacings, enabling detailed analysis of AMOC processes and feedbacks under idealised forcing scenarios. These simulations provide insight into how eddy-rich ocean dynamics influence AMOC variability and connectivity under historical, greenhouse gas and future changes.
Additionally, the project has fostered international collaboration through community workshops on AMOC observing needs, on improving modelling of the AMOC, and on planning for next-generation monitoring.
Advanced observing technologies deployed by EPOC, including drift-free pressure sensors and biogeochemical monitoring capabilities, represent potential tools for next generation AMOC observing. They offer the potential for improved accuracy but are currently undergoing further technical review.
Key needs for further uptake include continued international coordination of observing system design, improved open access to data products with software tools.