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Abstract The Oyashio Extension (OE) frontal zone in the northwest Pacific Ocean is associated with strong gradients of sea surface temperature (SST) and salinity. The OE front enhances baroclinicity and anchors the storm tracks; changes in its position and strength may impact atmospheric variability. North–south shifts in the OE front are often defined using the leading principal component for the latitude of the absolute maximum SST gradient in the northwest Pacific (145°–170°E), the so-called Oyashio Extension index (OEI). We show that the OEI is sensitive to the choice of SST dataset used in its construction, and that the significance of regressions of atmospheric fields onto the OEI also depends on the choice of SST datasets, leading to nonrobust results. This sensitivity primarily stems from the longitudinal domain used to define the OEI including a region with parallel or indistinct frontal zones in its central section (155°–164°E), leading to divergent results across datasets. We introduce a new index that considers the extent to which the SST front across this central section departs from climatology, the frontal disturbance index (FDI). For the months considered and over short time lags, the FDI produces more consistent results on air–sea interactions and associated high-frequency storm-track metrics than the conventional OEI, with a southward shift of the storm track for a more positive FDI. The FDI appears to be related to oceanic mesoscale eddy activity in the central OE region. There are significant asymmetric associations between the FDI and storm-track metrics dependent on the sign of the FDI. Significance StatementIn this study, we aim to understand how the choice of dataset may influence the interpretation of interactions between the ocean and the overlying atmosphere near sea surface temperature (SST) fronts. We find that using different SST datasets affects the results, due to slight differences in the representation of the location of the maximum SST gradient. To understand this, we develop a new index which relates to the degree of disturbance of the SST front. The new index produces regression results that are more consistent across the different datasets. We also identify some possible links between the frontal disturbance and the presence of ocean eddies. We advise that the sensitivity to dataset choice is given due consideration in regions near SST fronts. 

Abstract Decadal variability in the North Atlantic Ocean impacts regional and global climate, yet changes in internal decadal variability under anthropogenic radiative forcing remain largely unexplored. Here we use the Community Earth System Model 2 Large Ensemble under historical and the Shared Socioeconomic Pathway 3-7.0 future radiative forcing scenarios and show that the ensemble spread in northern North Atlantic sea surface temperature (SST) more than doubles during the mid-twenty-first century, highlighting an exceptionally wide range of possible climate states. Furthermore, there are strikingly distinct trajectories in these SSTs, arising from differences in the North Atlantic deep convection among ensemble members starting by 2030. We propose that these are stochastically triggered and subsequently amplified by positive feedbacks involving coupled ocean-atmosphere-sea ice interactions. Freshwater forcing associated with global warming seems necessary for activating these feedbacks, accentuating the impact of external forcing on internal variability. Further investigation on seven additional large ensembles affirms the robustness of our findings. By monitoring these mechanisms in real time and extending dynamical model predictions after positive feedbacks activate, we may achieve skillful long-lead North Atlantic decadal predictions that are effective for multiple decades. 

Abstract. Agulhas Leakage transports warm and salty Indian Ocean waters into the Atlantic Ocean  and as such is an important component of the global ocean circulation. These waters are part of the upper limb of the Atlantic Meridional Overturning Circulation (AMOC), and Agulhas Leakage variability has been linked to AMOC variability. Agulhas Leakage is expected to increase under a warming climate due to a southward shift in the South Hemisphere westerlies, which could further influence the AMOC dynamics. This study uses a set of high-resolution pre-industrial control and historical and transient simulations with the Community Earth System Model (CESM) with a nominal horizontal resolution of 0.1° for the ocean and sea-ice and 0.25° for the atmosphere and land. At these resolutions, the model represents the necessary scales to investigate the Agulhas Leakage transport variability and its relation to the AMOC. The simulated Agulhas Leakage transport of 19.7 ± 3 Sv lies well within the observed range of 21.3 ± 4.7 Sv. A positive correlation between the Agulhas Current and the Agulhas Leakage is shown, meaning that an increase of the Agulhas Current transport leads to an increase in Agulhas Leakage. The Agulhas Leakage impacts the strength of the AMOC through Rossby wave dynamics that alter the cross-basin geostrophic balance with a time-lag of 2–3 years. Furthermore, the  salt flux associated with the Agulhas Leakage influences AMOC dynamics through the salt-advection feedback by reducing the AMOC’s freshwater transport at 34° S. The Agulhas Leakage transport indeed increases under a warming climate due to strengthened and southward shifting winds. In contrast, the Agulhas Current transport decreases, both due to a decrease in the Indonesian Throughflow as well as the strength of the wind-driven subtropical gyre. The increase in Agulhas Leakage is accompanied by a higher salt flux into the Atlantic Ocean, which suggests a destabilisation of the AMOC by salt-advection-feedback. 

Accurate prediction of sea surface temperatures (SSTs) in the tropical North Atlantic on multiyear timescales is of paramount importance due to its notable impact on tropical cyclone activity. Recent advances in high-resolution climate predictions have demonstrated substantial improvements in the skill of multiyear SST prediction. This study reveals a notable enhancement in high-resolution tropical North Atlantic SST prediction that stems from a more realistic representation of the Atlantic Meridional Mode and the associated wind-evaporation-SST feedback. The key to this improvement lies in the enhanced surface wind response to changes in cross-equatorial SST gradients, resulting from Intertropical Convergence Zone bias reduction when atmospheric model resolution is increased, which, in turn, amplifies the positive feedback between latent and sensible surface heat fluxes and SST anomalies. These advances in high-resolution climate prediction hold promise for extending tropical cyclone forecasts at multiyear timescales. 

Abstract. Large-scale interaction between the three tropical ocean basins is an area of intense research that is often conducted through experimentation with numerical models. A common problem is that modeling groups use different experimental setups, which makes it difficult to compare results and delineate the role of model biases from differences in experimental setups. To address this issue, an experimental protocol for examining interaction between the tropical basins is introduced. The Tropical Basin Interaction Model Intercomparison Project (TBIMIP) consists of experiments in which sea surface temperatures (SSTs) are prescribed to follow observed values in selected basins. There are two types of experiments. One type, called standard pacemaker, consists of simulations in which SSTs are restored to observations in selected basins during a historical simulation. The other type, called pacemaker hindcast, consists of seasonal hindcast simulations in which SSTs are restored to observations during 12-month forecast periods. TBIMIP is coordinated by the Climate and Ocean – Variability, Predictability, and Change (CLIVAR) Research Focus on Tropical Basin Interaction. The datasets from the model simulations will be made available to the community to facilitate and stimulate research on tropical basin interaction and its role in seasonal-to-decadal variability and climate change. 

Abstract The Kuroshio Extension (KE) has far-reaching influences on climate as well as on local marine ecosystems. Thus, skillful multi-year to decadal prediction of the KE state and understanding sources of skill are valuable. Retrospective forecasts using the high-resolution Community Earth System Model (CESM) show exceptional skill in predicting KE variability up to lead year 4, substantially higher than the skill found in a similarly configured low-resolution CESM. The higher skill is attained because the high-resolution system can more realistically simulate the westward Rossby wave propagation of initialized ocean anomalies in the central North Pacific and their expression within the sharp KE front, and does not suffer from spurious variability near Japan present in the low-resolution CESM that interferes with the incoming wave propagation. These results argue for the use of high-resolution models for future studies that aim to predict changes in western boundary current systems and associated biological fields. 

Abstract. Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. Consequently, the role of enhanced horizontal resolution in improved process representation in all components of the climate system continues to be of great interest. Recent simulations suggest the possibility of significant changes in both large-scale aspects of the ocean and atmospheric circulations and in the regional responses to climate change, as well as improvements in representations of small-scale processes and extremes, when resolution is enhanced. The first phase of the High-Resolution Model Intercomparison Project (HighResMIP1) was successful at producing a baseline multi-model assessment of global simulations with model grid spacings of 25–50 km in the atmosphere and 10–25 km in the ocean, a significant increase when compared to models with standard resolutions on the order of 1° that are typically used as part of the Coupled Model Intercomparison Project (CMIP) experiments. In addition to over 250 peer-reviewed manuscripts using the published HighResMIP1 datasets, the results were widely cited in the Intergovernmental Panel on Climate Change report and were the basis of a variety of derived datasets, including tracked cyclones (both tropical and extratropical), river discharge, storm surge, and impact studies. There were also suggestions from the few ocean eddy-rich coupled simulations that aspects of climate variability and change might be significantly influenced by improved process representation in such models. The compromises that HighResMIP1 made should now be revisited, given the recent major advances in modelling and computing resources. Aspects that will be reconsidered include experimental design and simulation length, complexity, and resolution. In addition, larger ensemble sizes and a wider range of future scenarios would enhance the applicability of HighResMIP. Therefore, we propose the High-Resolution Model Intercomparison Project phase 2 (HighResMIP2) to improve and extend the previous work, to address new science questions, and to further advance our understanding of the role of horizontal resolution (and hence process representation) in state-of-the-art climate simulations. With further increases in high-performance computing resources and modelling advances, along with the ability to take full advantage of these computational resources, an enhanced investigation of the drivers and consequences of variability and change in both large- and synoptic-scale weather and climate is now possible. With the arrival of global cloud-resolving models (currently run for relatively short timescales), there is also an opportunity to improve links between such models and more traditional CMIP models, with HighResMIP providing a bridge to link understanding between these domains. HighResMIP also aims to link to other CMIP projects and international efforts such as the World Climate Research Program lighthouse activities and various digital twin initiatives. It also has the potential to be used as training and validation data for the fast-evolving machine learning climate models. 

Abstract Many fish and marine organisms are responding to our planet’s changing climate by shifting their distribution. Such shifts can drive international conflicts and are highly problematic for the communities and businesses that depend on these living marine resources. Advances in climate prediction mean that in some regions the drivers of these shifts can be forecast up to a decade ahead, although forecasts of distribution shifts on this critical time-scale, while highly sought after by stakeholders, have yet to materialise. Here, we demonstrate the application of decadal-scale climate predictions to the habitat and distribution of marine fish species. We show statistically significant forecast skill of individual years that outperform baseline forecasts 3–10 years ahead; forecasts of multi-year averages perform even better, yielding correlation coefficients in excess of 0.90 in some cases. We also demonstrate that the habitat shifts underlying conflicts over Atlantic mackerel fishing rights could have been foreseen. Our results show that climate predictions can provide information of direct relevance to stakeholders on the decadal-scale. This tool will be critical in foreseeing, adapting to and coping with the challenges of a changing future climate, particularly in the most ocean-dependent nations and communities.