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Interactions between ocean surface currents, winds and waves at the atmosphere-ocean interface are key controls of lateral and vertical exchanges of water, heat, carbon, gases and nutrients in the global Earth System. The SeaSTAR satellite mission concept proposes to better quantify and understand these important dynamic processes by measuring two-dimensional fields of total surface current and wind vectors with unparalleled spatial and temporal resolution (1 × 1 km2 or finer, 1 day) and unmatched precision over one continuous wide swath (100 km or more). This paper presents a comprehensive numerical analysis of the expected performance of the Earth Explorer 11 (EE11) SeaSTAR mission candidate in the case of idealised and realistic 2D ocean currents and wind fields. A Bayesian framework derived from satellite scatterometry is adapted and applied to SeaSTAR's bespoke inversion scheme that simultaneously retrieves total surface current vectors (TSCV) and ocean surface vector winds (OSVW). The results confirm the excellent performance of the EE11 SeaSTAR concept, with Root Mean Square Errors (RMSE) for TSCV and OSVW at 1 × 1 km2 resolution consistently better than 0.1 m/s and 0.4 m/s, respectively. The analyses highlight some performance degradation in some relative wind directions, particularly marked at near range and low wind speeds. Retrieval uncertainties are also reported for several variations around the SeaSTAR baseline three-azimuth configuration, indicating that RMSEs improve only marginally (by ∼0.01 m/s for TSCV) when including broadside Radial Surface Velocity or broadside dual-polarisation data in the inversion. In contrast, our results underscore (a) the critical need to include broadside Normalised Radar Cross Section data in the inversion; (b) the rapid performance degradation when broadside incidence angles become steeper than 20° from nadir; and (c) the benefits of maintaining ground squint angle separation between fore and aft lines-of-sight close to 90°. The numerical results are consistent with experimental performance estimates from airborne data and confirm that the EE11 SeaSTAR concept satisfies the requirements of the mission objectives. [ABSTRACT FROM AUTHOR]

Coastal seas, shelf seas and marginal ice zones are dominated by small-scale ocean surface dynamic processes that play a vital role in the transport and exchange of climate-relevant properties such as carbon, heat, water and nutrients between land, ocean, ice and atmosphere. Mounting evidence indicates that ocean scales below 10 km have far-ranging impacts on air–sea interactions, lateral ocean dispersion, vertical stratification, ocean carbon cycling and marine productivity – governing exchanges across key interfaces of the Earth system, the global ocean, and atmosphere circulation and climate. Yet, these processes remain poorly observed at the fine spatial and temporal scales necessary to resolve them. The Ocean Surface Current Airborne Radar (OSCAR) is a new airborne instrument with the capacity to inform these questions by mapping vectorial fields of total ocean surface currents and winds at high resolution over a wide swath. Developed for the European Space Agency (ESA), OSCAR is the airborne demonstrator of the satellite mission concept SeaSTAR, which aims to map total surface current and ocean wind vectors with unprecedented accuracy, spatial resolution and temporal revisit across all coastal seas, shelf seas and marginal ice zones. Like SeaSTAR, OSCAR is an active microwave synthetic aperture radar along-track interferometer (SAR-ATI) with optimal three-azimuth sensing enabled by unique highly squinted beams. In May 2022, OSCAR was flown over the Iroise Sea, France, in its first scientific campaign as part of the ESA-funded SEASTARex project. The campaign successfully demonstrated the capabilities of OSCAR to produce high-resolution 2D images of total surface current vectors and near-surface ocean vector winds, simultaneously, in a highly dynamic, macrotidal coastal environment. OSCAR current and wind vectors show excellent agreement with ground-based X-band-radar-derived surface currents, numerical model outputs and NovaSAR-1 satellite SAR imagery, with root mean square differences from the X-band radar better than 0.2 ms-1 for currents at 200 m resolution. These results are the first demonstration of simultaneous retrieval of total current and wind vectors from a high-squint three-look SAR-ATI instrument and the first geophysical validation of the OSCAR and SeaSTAR observing principle. OSCAR presents a remarkable new ocean observing capability to support the study of small-scale ocean dynamics and air–sea interactions across the Earth's coastal, shelf and polar seas. [ABSTRACT FROM AUTHOR]

Eurasian rivers provide a quarter of total fresh water to the Arctic, maintaining a persistent fresh layer that covers the surface Arctic Ocean. This freshwater export controls Arctic Ocean stratification, circulation, and basin-wide sea ice concentration. The Lena River supplies the largest volume of runoff and plays a key role in this system, as runoff outflows into the Laptev Sea as a particularly shallow plume. Previous in situ and modelling studies suggest that local wind forcing is a driver of variability in Laptev sea surface salinity (SSS) but there is no consensus on the roles of Lena River discharge and sea ice cover in contributing to this variability or on the dominant driver of variability. Until recently, satellite SSS retrievals were insufficiently accurate for use in the Arctic. However, retreating sea ice cover and continuous progress in satellite product development have significantly improved SSS retrievals, giving satellite SSS data true potential in the Arctic. In this region, satellite-based SSS is found to agree well with in situ data (r>0.8) and provides notable improvements compared to the reanalysis product used in this study (r>0.7) in capturing patterns and variability observed in in situ data. This study demonstrates a novel method of identifying the dominant drivers of interannual variability in Laptev Sea dynamics within reanalysis products and testing if these relationships appear to hold in satellite-based SSS, sea surface temperature (SST) data, and in situ observations. The satellite SSS data firmly establish what is suggested by reanalysis products and what has previously been subject to debate due to the limited years and locations analysed with in situ data; the zonal wind is the dominant driver of offshore or onshore Lena River plume transport. The eastward wind confines the plume to the southern Laptev Sea and drives alongshore transport into the East Siberian Sea, and westward wind drives offshore plume transport into the northern Laptev Sea. This finding is affirmed by the strong agreement in SSS pattern under eastward and westward wind regimes in all reanalyses and satellite products used in this study, as well as with in situ data. The pattern of SST also varies with the zonal wind component and drives spatial variability in sea ice concentration. [ABSTRACT FROM AUTHOR]

Coastal seas, shelf seas and marginal ice zones are dominated by small-scale ocean surface dynamic processes that play a vital role in the transport and exchange of climate-relevant properties like carbon, heat, water and nutrients between land, ocean, ice and atmosphere. Mounting evidence indicates that ocean scales below 10 km have far-ranging impacts on air-sea interactions, lateral ocean dispersion, vertical stratification, ocean carbon cycling, and marine productivity – governing exchanges across key interfaces of the Earth System, the global ocean and atmosphere circulation and climate. Yet, these processes remain poorly observed at the fine spatial and temporal scales necessary to resolve them. Ocean Surface Current Airborne Radar (OSCAR) is a new airborne instrument with the capacity to inform these questions by mapping vectorial fields of total ocean surface currents and winds at high resolution over a wide swath. Developed for the European Space Agency (ESA), OSCAR is the airborne demonstrator of the satellite mission concept 'SeaSTAR', which aims to map total surface current and ocean wind vectors with unprecedented accuracy, spatial resolution and temporal revisit across all coastal seas, shelf seas and marginal ice zones. Like SeaSTAR, OSCAR is an active microwave Synthetic Aperture Radar Along-Track Interferometer (SAR-ATI) with optimal three-azimuth sensing enabled by unique highly-squinted beams. In May 2022, OSCAR was flown over the Iroise Sea, France, in its first scientific campaign as part of the ESA-funded SEASTARex project. The campaign successfully demonstrated the capabilities of OSCAR to produce high-resolution 2D images of total surface current vectors and near-surface ocean vector winds, simultaneously, in a highly dynamic, macrotidal coastal environment. OSCAR current and wind vectors show excellent agreement against ground-based X-band radar derived surface currents, numerical model outputs and NovaSAR-1 satellite SAR imagery, with Root-Mean-Square differences against X-band radar better than 0.2 m s-1 for currents at 200 m resolution. These results are the first demonstration of simultaneous retrieval of total current and wind vectors from a high-squint three-look SAR-ATI instrument, and the first geophysical validation of the OSCAR and SeaSTAR observing principle. OSCAR presents a remarkable new ocean observing capability to support the study of small-scale ocean dynamics and air-sea interactions across the Earth's coastal, shelf and polar. [ABSTRACT FROM AUTHOR]

Eurasian Rivers provide a quarter of total fresh water to the Arctic, maintaining a persistent fresh layer that covers the surface Arctic Ocean. The Lena River supplies the largest volume of runoff and plays a key role in this system, as runoff outflows into the Laptev Sea as a particularly shallow plume. This freshwater export controls Arctic Ocean stratification, circulation, and basin-wide sea ice area. Previous in-situ and modelling studies suggest that local wind forcing is a primary driver of variability in Laptev sea surface salinity (SSS) with no consensus over the roles of Lena river discharge and sea ice cover in contributing to this variability. Until recently, satellite SSS retrievals were insufficiently accurate for use in the Arctic, due to the low sensitivity of the L-band signal they utilise in cold water and challenges of retrieval near sea ice. However, retreating sea ice cover and continuous progress in satellite product development have significantly improved SSS retrievals, giving satellite SSS data true potential in the Arctic. This study demonstrates a novel method of using satellite-based SSS, sea surface temperature (SST) data, in-situ observations, and reanalysis products to identify the dominant drivers of interannual variability in Laptev Sea dynamics. Satellite-based SSS is found to agree well with in-situ data in this region (r > 0.8) and provides notable improvements compared to the reanalysis product used in this study (r > 0.7) in capturing patterns and variability observed in in-situ data. The satellite SSS data firmly establishes what has previously been subject to debate due to the limited years and locations analysed with in-situ data: that the zonal wind is the dominant driver of offshore or onshore Lena river plume transport. This finding is affirmed by the strong agreement in SSS pattern in all reanalyses and satellite products used in this study under eastward and westward wind regimes. The pattern of SST also varies with the zonal wind component, and drives spatial variability in sea ice area. The strong correspondence between large scale and local zonal wind dynamics and the key role of SSS and SST variability in driving sea ice and stratification dynamics demonstrates the importance of changes in large-scale atmospheric dynamics for variability in this region as well as for future Arctic sea ice dynamics and freshwater transport. [ABSTRACT FROM AUTHOR]

Validation of satellite sea surface salinity (SSS) products is typically based on comparisons with in-situ measurements at a few meters' depth, which are mostly done at a single location and time. The difference in term of spatio-temporal resolution between the in-situ near-surface salinity and the two-dimensional satellite SSS results in a sampling mismatch uncertainty. The Climate Change Initiative (CCI) project has merged SSS from three satellite missions. Using an optimal interpolation, weekly and monthly SSS and their uncertainties are estimated at a 50 km spatial resolution over the global ocean. Over the 2016–2018 period, the mean uncertainty on weekly CCI SSS is 0.13, whereas the standard deviation of weekly CCI minus in-situ Argo salinities is 0.24. Using SSS from a high-resolution model reanalysis, we estimate the expected uncertainty due to the CCI versus Argo sampling mismatch. Most of the largest spatial variability of the satellite minus Argo salinity is observed in regions with large estimated sampling mismatch. A quantitative validation is performed by considering the statistical distribution of the CCI minus Argo salinity normalized by the sampling and retrieval uncertainties. This quantity should follow a Gaussian distribution with a standard deviation of 1, if all uncertainty contributions are properly taken into account. We find that (1) the observed differences between Argo and CCI data in dynamical regions (river plumes, fronts) are mainly due to the sampling mismatch; (2) overall, the uncertainties are well estimated in CCI version 3, much improved compared to CCI version 2. There are a few dynamical regions where discrepancies remain and where the satellite SSS, their associated uncertainties and the sampling mismatch estimates should be further validated. [ABSTRACT FROM AUTHOR]