Evaluating the potential of SMART subsea cable pressure sensors to constrain Subpolar North Atlantic circulation variability through Observing System Simulation Experiments

Matthew Goldberg , An Nguyen, Helen Pillar, Bruce M Howe, Patrick Heimbach

Bolstering global ocean observing infrastructure is critical for understanding, quantifying, and predicting Earth's climate variability and change. The SMART (Science Monitoring And Reliable Telecommunications) Subsea Cables present an opportunity to acquire high-frequency, seafloor-based observations of ocean variables, encouraging assessment of their value prior to deployment. We conduct Observing System Simulation Experiments to quantify potential for constraining ocean circulation using simulated SMART data from a proposed cable in the Subpolar North Atlantic. Synthetic daily SMART ocean bottom pressure anomaly observations from a high-resolution global ``nature run'' are assimilated into a regional ocean model. Model-data misfit is reduced via gradient-based adjustments to atmospheric control variables. Synthetic data value is quantified via the error reduction and improved skill between the regional model and the nature run. Assimilation of synthetic SMART data improves regional estimates of ocean bottom pressure as well as unobserved quantities such as time-mean and time-varying barotropic (depth-integrated) transport and time-mean Arctic freshwater redistribution, demonstrating SMART's potential to constrain basin-scale ocean circulation. On annual timescales SMART cables complement satellite gravimetry data by providing unique constraints on sub-monthly and coastal oceanic mass transport, reducing local ocean bottom pressure uncertainty. Atmospheric pressure, followed by surface winds, is identified as the primary control variable driving daily bottom pressure anomaly correction. The dominance of atmospheric pressure adjustments in inducing ocean mass redistribution and associated bottom pressure changes reflects a departure from the inverse barometer response. Our results underscore the value of high-frequency seafloor pressure data for improving estimation and enhancing the spatiotemporal resolution of climate-relevant ocean transports.