LAUSR

Increasing the resolution of atmospheric or oceanic components in the global climate models (GCM) tends to improve the representation of regional climate. However, the magnitude and consistency of this improvement are critical in determining modelling strategies. This study examines the HighResMIP model developed within the PRIMAVERA project to identify the best performing model along with their resolution for the mean and standard deviation of sea surface temperature (SST) as well as two temperature‐based marine extremes (marine heatwaves; MHWs and marine cold spells; MCSs) over the Tropical Indian Ocean (TIO). Notably, HighResMIP models are configured to run at least two different resolutions, with resolution increases applied either to the atmospheric or oceanic components. This study also investigates whether increasing the resolution of these components leads to overall improvements or potential degradations in model performance. Results suggest refining the resolution of either the atmospheric or oceanic component improves the simulation of SST, MHWs, and MCSs, bringing them closer to observed values. However, the extent of the improvement depends on the region, specific metric being evaluated (MHWs/MCSs count, intensity, duration) and model used. Additionally, over a few regions, the model performance is found to be degraded when the resolution is increased, suggesting that inevitably increasing the horizontal resolution alone may not be enough to reduce the persistent biases. Furthermore, in many cases, the improvements achieved by increasing resolution are offset by simultaneous degradations. Hence, overall, benefits appear to be limited but still considerable.