Jul 2026· International Seminar on Intelligent Technology and Its Applications· pp. 444-449· 0 citations· 20 references
Abstract
Indonesia hosts one of the most dynamically complex marine systems due to the interaction of the Indonesian Throughflow, monsoonal circulation, and complex bathymetry. These processes generate strong mesoscale variability that can be quantified using Eddy Kinetic Energy (EKE). This study proposes a satellite-altimetry-based framework for estimating EKE across the Indonesian Seas using Jason-3 observations integrated with Sea Level Anomaly (SLA) products from the Copernicus Marine Environment Monitoring Service (CMEMS). Geostrophic velocity anomalies were derived from SLA gradients and subsequently used to calculate EKE. Several preprocessing steps, including geophysical corrections, noise filtering, and anomaly normalization, were applied to improve data quality. An intelligent monitoring framework was developed to support automated data ingestion, EKE computation, and anomaly detection. Results indicate pronounced spatial variability of EKE, with elevated values observed in the Makassar Strait, Banda Sea, and southern Java waters. Seasonal analysis reveals stronger EKE during the southeast monsoon, while interannual variability demonstrates links with ENSO and the Indian Ocean Dipole. The proposed framework highlights the potential of integrating satellite altimetry and intelligent monitoring systems for operational ocean observation, environmental assessment, and coastal resilience applications.
The advanced 2-D sea surface height (SSH) observations from the surface water and ocean topography (SWOT) satellite have achieved a global average geoid resolution better than 13 km, as estimated from spectral analysis of adjacent single-cycle observations. However, in regions with complex oceanic dynamics (the ocean off southwestern Argentina and east of Japan), SWOT observations show significant temporal variability across cycles. This variability greatly hampers the satellite’s ability to detect and precisely measure steady-state marine geoid signals. Even with multicycle data stacking, resolution remains poor in some regions, sometimes underperforming conventional satellite altimetry. To solve this issue, this study employs a multiresolution coherent spatio-temporal scale separation (mrCOSTS) method to analyze sea surface height anomaly (SSHA) data from 26 SWOT cycles, aiming to isolate stable signal components and reconstruct the geoid. The approach notably improves geoid resolution in regions with intricate ocean features, with the maximum enhancement reaching up to 76%. This resolution reflects the spatial scales of features reproducibly resolved by two independent SWOT geoid estimates, rather than a direct improvement in absolute marine geoid accuracy. The method effectively suppresses ocean dynamic signals while preserving the static oceanic component, and it also contributes to improving the recovery of the marine gravity field in regions characterized by complex ocean dynamics. Furthermore, in regions with relatively high resolution, the method achieves additional subtle improvements, which are of considerable significance for obtaining a stable static field.
Sihai Zhao, Shengjun Zhang, Xiangxue Kong et al.· IEEE Transactions on Geoscie...· 0 citations
Despite significant advances in observational systems such as the global Argo array of autonomous profiling floats, the spatiotemporal coverage of subsurface ocean observations remains limited compared to the dense data provided by satellite platforms. This study develops a data‐driven framework to reconstruct synthetic profiles of upper ocean temperature and salinity by training a self‐attention‐based neural network with satellite‐derived sea surface height (SSH) and sea surface temperature anomalies, using 17 years of collocated Argo float measurements. Daily synthetic profiles for the upper 650 m of the Philippine Sea were generated for the entirety of 2010 and assimilated into a regional ocean model via 4D‐Var data assimilation. Results show overall improved effectiveness of state estimation when synthetic profiles are utilized. Diagnostic variables like temperature, salinity, SSH, horizontal velocity all show improvement. Synthetic profiles of subsurface temperature had an overall positive impact on SSH analysis and forecast, especially in regions east of the Luzon Strait and the southern domain influenced by the North Equatorial Current. In the vertical range of 150–600 m, the impact of synthetic profiles on various observations was promising, leading to substantial reductions in the analysis and forecast error.
Guangpeng Liu, B. Powell· Journal of Advances in Model...· 0 citations
This study reviews the unusual lifecycle and reach of Cyclone Asna (August–September 2024) over the North Arabian Sea with special focus on its inland re-intensification after landfall, a behavior not typically seen in that region. Remote sensing satellite platforms combined with geographic information systems (GIS) allow a multi-parameter assessment of Asna's track, rain patterns, flood extents, and resulting damage across Pakistan's coastal belt and deeper inland areas. Sentinel's 2 NDWI images map surface water changes before and after the storm, while integrated IMERG rainfall estimates and time-stamped damage reports identify high-risk areas and illuminate the cyclone's social and economic costs. Karachi and adjacent coastal towns recorded isolated totals above 266 mm, sparking extensive urban floods, power outages, and collapse of key transport links, all driven by Asna's slow forward motion and prolonged onshore presence. Asna's inland intensification was caused by a rare overlap of monsoon moisture feeding in from both the Arabian Sea and Bay of Bengal, upper-level divergence, saturated soils, high surface heat flux, and persistent mid- to upper-level cyclonic vorticity factors that together sustained the storm's vertical structure far beyond normal landfall limits. Broadly speaking, both the warmer Arabian Sea and its greater moisture-holding capacity are driving a recent increase in hybrid cyclone systems across the region. This study confirms that trend and points to satellite monitoring as an invaluable tool for bettering disaster preparedness and adaptive planning. As the case of cyclone Asna shows, predictive models and urban resilience plans must now be revised to reflect unusual cyclone behavior strengthened by evolving climate dynamics.
M. Bilal· Natural and Applied Sciences...· 0 citations
This study presents a novel cyclostrophic balance correction method for estimating submesoscale ocean surface currents in the Northern Arabian Sea using surface water and ocean topography (SWOT) mission altimetry. High-resolution Ocean Color Monitor (OCM-3) data from the EOS-06 satellite reveal fine-scale eddies and filaments with high chlorophyll-a concentrations (>0.4 mg m−3), spatially coherent with geostrophic current patterns from SWOT. At these scales, the geostrophic assumption is invalid; therefore, we introduce a curvature-based cyclostrophic correction that accounts for enhanced centripetal accelerations. Validation against high-resolution model simulations shows that our approach is in better agreement with model outputs than uncorrected and previously published corrected fields, particularly in regions with strong vorticity and strain. When applied to SWOT data, the corrected velocities demonstrate spatial correspondence with chlorophyll patterns and suppress spurious gradients. Probability density functions of normalized vorticity and strain also match theoretical expectations, emphasizing the potential of SWOT for advancing submesoscale ocean dynamics.
N. Agarwal, Aditya Chaudhary, J. M. et al.· IEEE Journal of Selected Top...· 0 citations
Sea surface salinity (SSS) modulates upper-ocean stratification, air–sea coupling, and freshwater redistribution in the North Indian Ocean, yet its interannual variability in the eastern Arabian Sea (EAS) remains insufficiently quantified. This study evaluates satellite-derived SSS from the Soil Moisture and Ocean Salinity, Soil Moisture Active Passive, and European Space Agency-Climate Change Initiative (CCI) products using high-precision shipborne measurements across the EAS. Validation results show that CCI SSS exhibits strong agreement with in situ observations and best reproduces the spatiotemporal variability of the in situ gridded dataset (Willmott skill score 0.81). CCI also exhibit relatively lower spatial root-mean-square error (0.93 PSU) compared to other Satellite derived datasets. The analysis of interannual SSS variability using the CCI dataset during 2010–2023 reveals two contrasting regimes: a salinification phase during 2015–2019 (+0.5 PSU) followed by a pronounced freshening phase during 2020–2023 (−0.5 PSU). Analysis of precipitation, ocean circulation, and climate indices indicates that reduced rainfall and weak horizontal advection dominated the salinification phase. In contrast, the freshening phase was driven by enhanced precipitation and intensified freshwater transport from the Bay of Bengal. This period coincides with the rare triple-dip La Niña (2020–2022), which strengthened coastal Kelvin waves and the East India Coastal Current, facilitating transport of low-salinity waters through the “River-in-the-Sea”(RIS) pathway. These results highlight the sensitivity of EAS salinity to coupled local and remote freshwater processes and demonstrate the importance of multi-sensor satellite SSS products for monitoring climate-driven hydrological variability.
Vivek V Rajiv, V. Suneel, Arjun K Sabu et al.· Environmental Research Lette...· 0 citations
This study presents a pilot, data-driven framework for detecting nearshore seabed dynamics based on shoreline variability derived from high-resolution satellite imagery, integrated with in situ bathymetric measurements along the Hel Peninsula in the southern Baltic Sea. The approach focuses on assessing whether satellite-derived shoreline displacement can serve as an indirect indicator of changes in seabed morphology within the sedimentologically active coastal zone. Four cross-shore transects were analyzed using Pléiades satellite imagery and field bathymetric data collected during two monitoring campaigns conducted in 2019 and 2022. Changes in seabed elevation were quantified through cross-sectional profile analysis, while key morphodynamic parameters, including closure depth and the length of the active seabed, were estimated using empirical formulations proposed by Hallermeier, Birkemeier, and Houston. To provide hydrodynamic context, wave and current conditions were characterized using Copernicus Marine Service reanalysis data. The results reveal pronounced spatial variability in seabed response along the Hel Peninsula, with erosion-dominated conditions in high-energy open-coast sectors and limited morphological change in semienclosed, low-energy environments. Among the tested formulations, Birkemeier’s equation showed the closest agreement with field-derived closure depths, while all empirical models systematically overestimated closure depth in low-energy settings. The findings demonstrate the potential of satellite-based shoreline observations as a supporting tool for coastal morphodynamic assessment while highlighting the limitations imposed by measurement uncertainty, short observation windows, and simplified process representation. Overall, the proposed framework should be regarded as a proof-of-concept application requiring longer observational time series, improved uncertainty quantification, and local calibration before operational implementation can be considered
Patryk Sapiega, T. Zalewska· Photogrammetric Engineering...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
