Uncertainty Analysis of Particle Backscattering Coefficient Measurement for Multiple Highly Turbid Water Areas in Ocean Color Remote Sensing

In this study, we aimed to understand the uncertainty of measured values of the particle backscattering coefficient (b bp ) obtained using the in situ backscattering meter Hydroscat-6P in three highly turbid water bodies with distinct optical properties and assess their impact on the estimation results through inversion.The field observations were conducted in Tokyo Bay, where organic matter dominates, Lake Kasumigaura, where cyanobacteria are abundant and mixed with inorganic suspended matter, and the estuary of Bangpankong River in the Upper Gulf of Thailand, where inorganic suspended matter is highly concentrated.To understand the uncertainty of b bp measurements, radiative transfer simulations were performed using Hydrolight, and the influence of b bp measurements on the reproduction calculation of remote sensing reflectance (R rs ) was assessed.The results revealed that the reproducibility of R rs varied among the water bodies, with a particularly pronounced overestimation compared with the measured values in the highly scattering environments of Lake Kasumigaura and the Upper Gulf of Thailand.This overestimation originated from the optical path length without light attenuation correction (σ correction) in Hydroscat-6P, and the σ correction amplified the overestimation of R rs .Although the cause of this overestimation is unclear, it suggests that the calculation conditions of the radiative transfer model and the effect of multiple scattering between the sensors of Hydroscat-6P may be contributing factors.The magnitude of this overestimation ranged from 64 to 75% in Lake Kasumigaura and from 29 to 39% in the Upper Gulf of Thailand, significantly affecting the accuracy verification of b bp estimation using inversion models.These results highlight the uncertainty of b bp measurements in highly turbid water bodies with high light scattering, emphasizing the need for careful attention to the quality of previously acquired in situ data when evaluating the performance of inversion algorithms.