Abstract:
Objectives Radiometric benchmark transfer is essential for improving the radiometric consistency and traceability of multi-source optical satellite observations. In ocean color remote sensing, this issue is particularly important because ocean color sensors are designed for low-radiance targets, and small radiometric biases may significantly affect water-leaving radiance and derived ocean products. Clean open-ocean areas, with high spatial homogeneity and relatively stable radiometric characteristics, are suitable target fields for radiometric benchmark transfer. However, weak ocean signals, dynamic air-sea interface conditions, solar glint, atmospheric variability, and sensor differences introduce complex uncertainties. We aim to summarize research progress on uncertainty in radiometric benchmark transfer for ocean targets.
Methods We review studies on ocean-atmosphere radiative transfer modeling, inter-sensor cross-calibration, and uncertainty assessment. Uncertainty sources are organized into four dimensions: temporal, spatial, spectral, and geometric. Temporal uncertainty is related to atmospheric and oceanic changes between satellite overpasses. Spatial uncertainty arises from sampling differences and target-field heterogeneity. Spectral uncertainty is caused by spectral response differences and in-orbit spectral drift, and geometric uncertainty is mainly associated with solar-viewing geometry mismatch and ocean surface bidirectional reflectance. Representative evaluation methods, including radiative transfer simulation, moving-window analysis, spectral band adjustment factor methods, Monte Carlo simulation, and bidirectional reflectance distribution function-based correction, are summarized.
Results Existing studies show that uncertainty in ocean-target radiometric benchmark transfer results from the combined effects of target-field variability, observation-condition mismatch, radiative transfer modeling error, and sensor-state variation. Under constrained conditions, temporal uncertainty can be reduced to below approximately 0.1%. Spatial uncertainty over homogeneous ocean regions is generally about 0.1%-0.15%. Spectral uncertainty is usually below 0.1% for common bands but may reach about 0.5% in sensitive bands, and geometric uncertainty can be controlled to about 0.5% after angular constraint or correction. Nevertheless, most studies still treat these dimensions separately, while real satellite observations often involve coupled effects.
Conclusions Ocean-target radiometric benchmark transfer provides an important basis for establishing consistent and traceable radiometric references among multi-source ocean color satellites. Although existing studies have developed useful methods for evaluating and reducing individual uncertainty components, a unified framework for multi-dimensional uncertainty coupling and propagation remains insufficient. Future research should focus on coupled air-sea and atmospheric modeling, integrated uncertainty assessment across temporal-spatial-spectral-geometric dimensions, and standardized global ocean target fields supported by high-accuracy reference calibration missions.