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<p>In this study, we examined salinity fields as both passive and active tracers to generate high-resolution sea surface salinity fields using a Lagrangian reconstruction technique, integrating satellite-derived data and numerical advection schemes. Specifically, we employed Version 4.0 of NASA’s Soil Moisture Active Passive (SMAP) Level-3 sea surface salinity product, which features an 8-day running mean and approximately 25&#xa0;km spatial resolution. Geostrophic surface currents at comparable spatial resolution, sourced from satellite altimetry data provided by the Copernicus Marine Environment Monitoring Service (CMEMS), were utilized in this work. By applying backward and forward numerical advection schemes to the SMAP sea surface salinity fields using these altimetry-derived currents, we captured smaller-scale salinity features, generating reconstructed fields on a 4-km output grid. The passive-advection implementation was first verified in the Gulf Stream through comparison with the published reconstruction of Barceló-Llull et al. (2021), after which the framework was applied and further developed for the Bay of Bengal, the primary study region. Utilizing salinity as a passive tracer allowed us to focus exclusively on horizontal advection without accounting for sources, sinks, or mixing. A sensitivity analysis was performed, which determined that the highest feasible resolution using this approach is 4&#xa0;km, with an optimal advection integration period of 14 days. Preliminary validation against ship-based thermo-salinograph observations from 2015 to 2024 demonstrates that High-Resolution Sea Surface Salinity via Passive Advection (HRSSS-PA) achieves RMSEs of 0.19 to 3.19 PSU with correlations of 0.12 to 0.93, generally outperforming SMAP, which shows higher errors (0.21 to 4.78 PSU) and weaker or inconsistent correlations (-0.19 to 0.96). This highlights the ability of HRSSS-PA to capture both magnitude and fine-scale salinity variability. To address cases where the assumptions of passive advection break down, the framework was further extended to an active advection approach, in which salinity values were dynamically adjusted during transport to account for freshwater input and precipitation, enabling improved representation under conditions characterized by strong freshwater forcing, sharp sea-surface salinity gradients, and river-plume influence.</p>

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Lagrangian reconstruction of fine-grid sea surface salinity from SMAP and altimetry in the Bay of Bengal

  • 期刊论文

  • 发表日期：

    2026年7月21日

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  • Jai Kumar,
  • Neeraj Agarwal,
  • Rashmi Sharma

摘要

In this study, we examined salinity fields as both passive and active tracers to generate high-resolution sea surface salinity fields using a Lagrangian reconstruction technique, integrating satellite-derived data and numerical advection schemes. Specifically, we employed Version 4.0 of NASA’s Soil Moisture Active Passive (SMAP) Level-3 sea surface salinity product, which features an 8-day running mean and approximately 25 km spatial resolution. Geostrophic surface currents at comparable spatial resolution, sourced from satellite altimetry data provided by the Copernicus Marine Environment Monitoring Service (CMEMS), were utilized in this work. By applying backward and forward numerical advection schemes to the SMAP sea surface salinity fields using these altimetry-derived currents, we captured smaller-scale salinity features, generating reconstructed fields on a 4-km output grid. The passive-advection implementation was first verified in the Gulf Stream through comparison with the published reconstruction of Barceló-Llull et al. (2021), after which the framework was applied and further developed for the Bay of Bengal, the primary study region. Utilizing salinity as a passive tracer allowed us to focus exclusively on horizontal advection without accounting for sources, sinks, or mixing. A sensitivity analysis was performed, which determined that the highest feasible resolution using this approach is 4 km, with an optimal advection integration period of 14 days. Preliminary validation against ship-based thermo-salinograph observations from 2015 to 2024 demonstrates that High-Resolution Sea Surface Salinity via Passive Advection (HRSSS-PA) achieves RMSEs of 0.19 to 3.19 PSU with correlations of 0.12 to 0.93, generally outperforming SMAP, which shows higher errors (0.21 to 4.78 PSU) and weaker or inconsistent correlations (-0.19 to 0.96). This highlights the ability of HRSSS-PA to capture both magnitude and fine-scale salinity variability. To address cases where the assumptions of passive advection break down, the framework was further extended to an active advection approach, in which salinity values were dynamically adjusted during transport to account for freshwater input and precipitation, enabling improved representation under conditions characterized by strong freshwater forcing, sharp sea-surface salinity gradients, and river-plume influence.