Many human activities rely on accurate knowledge of the sea surface dynamics. This is especially true during storm events, when wave‐current interactions might represent a leading order process of the upper ocean. In this study, we assess and analyze the impact of including three wave‐dependent processes in the ocean momentum equation of the Met Office North West European Shelf ocean‐wave forecasting system on the accuracy of the simulated surface circulation. The analysis is conducted using ocean currents and Stokes drift data produced by different implementations of the coupled forecasting systems to simulate the trajectories of surface (iSphere) and 15 m drogued (SVP) drifters affected by four storms selected from winter 2016. Ocean and wave simulations differ only in the degree of coupling and the skills of the Lagrangian simulations are evaluated by comparing model results against the observed drifter tracks. Results show that, during extreme events, ocean‐wave coupling improves the accuracy of the surface dynamics by 4%. Improvements are larger for ocean currents on the shelf (8%) than in the open ocean (4%): this is thought to be due to the synergy between strong tidal currents and more mature decaying waves. We found that the Coriolis‐Stokes forcing is the dominant wave‐current interaction for both type of drifters; for iSpheres the secondary wave effect is the wave‐dependent sea surface roughness while for SVPs the wave‐modulated water‐side stress is more important. Our results indicate that coupled ocean‐wave systems may play a key role for improving the accuracy of particle transport simulations.

The latest assessment report from the Intergovernmental Panel on Climate Change concluded that the Atlantic Meridional Overturning Circulation (AMOC) was very likely to decline over the twenty-first century under all emissions scenarios; however, there was low confidence in the magnitude of the decline. Recent research has highlighted that model biases in the mean climate state can affect the AMOC in its mean state, variability and its response to climate change. Hence, understanding and reducing these model biases is critical for reducing uncertainty in the future changes of the AMOC and in its impacts on the wider climate. We discuss how model biases, in particular salinity biases, influence the AMOC and deep convection. We then focus on biases in the UK HadGEM3-GC3-1 climate model and how these biases change with resolution. We also discuss ongoing model development activities that affect these biases, and highlight priorities for improved representation of processes, such as the position of the North Atlantic Current, transports in narrow boundary current, resolution (or improved parameterization) of eddies and spurious numerical mixing in overflows.This article is part of a discussion meeting issue ‘Atlantic overturning: new observations and challenges’.

We present a numerical platform named Structured and Unstructured grid Relocatable ocean platform for Forecasting (SURF). The platform is developed for short-time forecasts and is designed to be embedded in any region of the large-scale Mediterranean Forecasting System (MFS) via downscaling. We employ CTD data collected during a campaign around the Elba island to calibrate and validate SURF. The model requires an initial spin up period of a few days in order to adapt the initial interpolated fields and the subsequent solutions to the higher-resolution nested grids adopted by SURF. Through a comparison with the CTD data, we quantify the improvement obtained by SURF model compared to the coarse-resolution MFS model