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Arctic Ocean gateway fluxes play a crucial role in linking the Arctic with the global ocean and affecting climate and marine ecosystems. We reviewed past studies on Arctic–Subarctic ocean linkages and examined their changes and driving mechanisms. Our review highlights that radical changes occurred in the inflows and outflows of the Arctic Ocean during the 2010s. Specifically, the Pacific inflow temperature in the Bering Strait and Atlantic inflow temperature in the Fram Strait hit record highs, while the Pacific inflow salinity in the Bering Strait and Arctic outflow salinity in the Davis and Fram straits hit record lows. Both the ocean heat convergence from lower latitudes to the Arctic and the hydrological cycle connecting the Arctic with Subarctic seas were stronger in 2000–2020 than in 1980–2000. CMIP6 models project a continuing increase in poleward ocean heat convergence in the 21st century, mainly due to warming of inflow waters. They also predict an increase in freshwater input to the Arctic Ocean, with the largest increase in freshwater export expected to occur in the Fram Strait due to both increased ocean volume export and decreased salinity. Fram Strait sea ice volume export hit a record low in the 2010s and is projected to continue to decrease along with Arctic sea ice decline. We quantitatively attribute the variability of the volume, heat, and freshwater transports in the Arctic gateways to forcing within and outside the Arctic based on dedicated numerical simulations and emphasize the importance of both origins in driving the variability. 

Abstract. With the increase in computational power, ocean models with kilometer-scale resolution have emerged over the last decade. These models have been used for quantifying the energetic exchanges between spatial scales, informing the design of eddy parametrizations, and preparing observing networks. The increase in resolution, however, has drastically increased the size of model outputs, making it difficult to transfer and analyze the data. It remains, nonetheless, of primary importance to assess more systematically the realism of these models. Here, we showcase a cloud-based analysis framework proposed by the Pangeo project that aims to tackle such distribution and analysis challenges. We analyze the output of eight submesoscale-permitting simulations, all on the cloud, for a crossover region of the upcoming Surface Water and Ocean Topography (SWOT) altimeter mission near the Gulf Stream separation. The cloud-based analysis framework (i) minimizes the cost of duplicating and storing ghost copies of data and (ii) allows for seamless sharing of analysis results amongst collaborators. We describe the framework and provide example analyses (e.g., sea-surface height variability, submesoscale vertical buoyancy fluxes, and comparison to predictions from the mixed-layer instability parametrization). Basin- to global-scale, submesoscale-permitting models are still at their early stage of development; their cost and carbon footprints are also rather large. It would, therefore, benefit the community to document the different model configurations for future best practices. We also argue that an emphasis on data analysis strategies would be crucial for improving the models themselves.