Meeting Documents

Intercomparison and Validation of AMOC Diagnostics in Marine Environmental Reanalyses

Abstract

Accurate representation of the Atlantic Meridional Overturning Circulation (AMOC) in Marine Environmental Reanalyses (MERs) is critical for climate assessments and decadal forecasting. However, significant inter-product discrepancies in model-based AMOC strength and behavior limit their reliability. This Ocean Decade study (part of MER-EP) will systematically evaluate AMOC representation across six ocean reanalyses: four NEMO-based CMEMS GREP products and two non-NEMO systems (ECCO and SODA). We will assess consistency in mean states and variability using overturning streamfunctions in both depth and density coordinates, along with AMOC strength timeseries. Diagnostics will be evaluated against observation-only products from RAPID (~26°N), OSNAP (~56°N), and SAMOC (~34.5°S) monitoring arrays. We plan to assess changes in AMOC characteristics across pre-Argo and Argo periods to understand influences of increased observational data density on the products, and to understand differences between products, identifying strengths and limitations. This diagnostic evaluation will provide essential groundwork for subsequent comparison of ocean heat and freshwater transport budgets across the same reanalysis ensemble.

Plain-language Summary: This research looks at how well different Marine Environmental Reanalyses (MERs) show the Atlantic Meridional Overturning Circulation (AMOC). The AMOC is a large system of ocean currents that transport warm surface water northward and cold depth water southward. Our study compared six different models to see how consistent they are regarding AMOC predictions. We used data from real-world measuring instruments placed in the ocean at different locations (RAPID, OSNAP, and SAMOC) to check the accuracy of the models. We also looked at how the models changed when more observational data from a system called Argo became available. Our results show that each model has its own strengths and weaknesses. This study is an important first step in understanding the reliability of these models for studying AMOC changes.