The Daylight Bias: How Solar Tides Skew Satellite Estimates of Coastal Suspended Sediment Concentration

Abstract The long‐term mean Suspended Sediment Concentration (SSC) is a critical parameter for characterizing coastal sediment dynamics and associated ecological effects. While satellite optical remote sensing serves as a primary tool for these observations, standard climatological estimates typically rely on averaging data acquired during fixed daylight hours. This approach implicitly assumes that satellite sampling is random and unbiased, an assumption we demonstrate fails in coastal regions dominated by strong solar semidiurnal tides. In such systems, tidal forcing generates pronounced 12 hr (S2) and 6 hr (S4) variability that becomes harmonically synchronized with the satellite's daylight sampling window. This “stroboscopic effect” aliases periodic fluctuations into a systematic “daylight bias” within climatological means derived from arithmetic averaging. To address this, we propose a Solar‐Phase Harmonic Fitting method that mathematically decouples the background mean from the S2 and S4 components, given sufficient intraday sampling. Application to Korea Bay reveals that tidal advection across a seaward‐decreasing SSC gradient drives strong S2 variability, with satellite daylight sampling phase‐locked to low‐SSC conditions. Consequently, under the framework of daylight sampling, conventional averaging underestimates the long‐term mean SSC by approximately 23.4% in the coatal ocean. Our proposed method mitigates the daylight bias in long‐term mean estimations, yielding less biased results than conventional arithmetic averaging, and offers a framework broadly applicable to other satellite‐derived oceanographic variables influenced by tidal or solar‐driven variability, such as water transparency and chlorophyll‐a.