Search Results (3)

This study examined the seasonal variations and influencing factors for black carbon (BC) concentrations and aerosol optical depth (AOD) at the Socheongcho Ocean Research Station (SORS) on the Korean Peninsula from July 2019 to December 2020. An AOD algorithm was developed and validated using the Geo-KOMPSAT-2A (GK-2A) satellite. The GK-2A AOD demonstrated comparable performance to that of Low Earth Orbit satellites, including the Terra/MODIS (R² = 0.86), Aqua/MODIS (R² = 0.83), and AERONET AODs (R² = 0.85). Multi-angle absorption photometry revealed that seasonal average BC concentrations were the highest in winter (0.91 ± 0.80 µg·m⁻³), followed by fall (0.80 ± 0.66 µg·m⁻³), wet summer (0.75 ± 0.55 µg·m⁻³), and dry summer (0.52 ± 0.20 µg·m⁻³). The seasonal average GK-2A AOD was higher in wet summer (0.45 ± 0.37 µg·m⁻³) than in winter. The effects of meteorological parameters, AERONET AOD wavelength, and gaseous substances on GK-2A AOD and BC were investigated. The SHapley Additive exPlanations-based feature importance analysis for GK-2A AOD identified temperature, relative humidity (RH), and evaporation as major contributors. BC concentrations were increased, along with PM_2.5 and CO levels, due to the effects of combustion processes during fall and winter. Analysis of high-aerosol-loading cases revealed an increase in the fine-mode fraction, emphasizing the meteorological effects on GK-2A AOD. Thus, long-range transport and local BC sources played a critical role at the SORS. Full article

A seasonal variability in flow and sediment flux at the Socheongcho Ocean Research Station (SORS) on the west coast of Korea in 2018 was investigated to elucidate the formation of a two-layered flow structure and changes in sediment transport during stratification. An analysis of SORS data revealed stable temperatures (5–10 °C) in deeper waters, while surface temperatures rose from 6 °C in April to a peak of 30 °C in late August, gradually declining and leading to full water column mixing by late November. This temperature variation induced stratification, influencing the development of a two-layered flow structure. In winter, a singular flow structure was observed, contrasting with the emergence of a two-layered structure as stratification progressed. In the surface layer, residual currents flowed northward in summer and southward in winter, consistent with previous studies. In deeper layers, a southward residual current persisted, irrespective of the season. Sediment flux consistently moved southward, regardless of the season or water depth, with notably higher cumulative sediment flux in the deeper layer (1300 kg·m⁻²s⁻¹) compared to the surface layer (300 kg·m⁻²s⁻¹). These findings diverge notably from previous studies, providing new insights into ocean currents and material transport in the Yellow Sea. Full article

The geostationary ocean color imager (GOCI), as the world’s first operational geostationary ocean color sensor, is aiming at monitoring short-term and small-scale changes of waters over the northwestern Pacific Ocean. Before assessing its capability of detecting subdiurnal changes of seawater properties, a fundamental understanding of the uncertainties of normalized water-leaving radiance (nLw) products introduced by atmospheric correction algorithms is necessarily required. This paper presents the uncertainties by accessing GOCI-derived nLw products generated by two commonly used operational atmospheric algorithms, the Korea Ocean Satellite Center (KOSC) standard atmospheric algorithm adopted in GOCI Data Processing System (GDPS) and the NASA standard atmospheric algorithm implemented in Sea-Viewing Wide Field-of-View Sensor Data Analysis System (SeaDAS/l2gen package), with Aerosol Robotic Network Ocean Color (AERONET-OC) provided nLw data. The nLw data acquired from the GOCI sensor based on two algorithms and four AERONET-OC sites of Ariake, Ieodo, Socheongcho, and Gageocho from October 2011 to March 2019 were obtained, matched, and analyzed. The GDPS-generated nLw data are slightly better than that with SeaDAS at visible bands; however, the mean percentage relative errors for both algorithms at blue bands are over 30%. The nLw data derived by GDPS is of better quality both in clear and turbid water, although underestimation is observed at near-infrared (NIR) band (865 nm) in turbid water. The nLw data derived by SeaDAS are underestimated in both clear and turbid water, and the underestimation worsens toward short visible bands. Moreover, both algorithms perform better at noon (02 and 03 Universal Time Coordinated (UTC)), and worse in the early morning and late afternoon. It is speculated that the uncertainties in nLw measurements arose from aerosol models, NIR water-leaving radiance correction method, and bidirectional reflectance distribution function (BRDF) correction method in corresponding atmospheric correction procedure. Full article