A Novel Scoring Metrics for Quality Assurance of Ocean Color Observations

Interpretation of the ocean bio-optical properties from ocean color observations depends on the quality of the ocean color data, specifically the spectrum of remote sensing reflectance (Rrs). The in situ and remotely measured Rrs spectra are inevitably subject to errors induced by instrument calibration, sea-surface correction and atmospheric correction, and other environmental factors. Great efforts have been devoted to the ocean color calibration and validation. Yet, there exist no objective and consensus criteria for assessment of the ocean color data quality. In this study, the gap is filled by developing a novel metrics for such data quality assurance and quality control (QA/QC). This new QA metrics is not intended to discard “suspicious” Rrs spectra from available datasets. Rather, it takes into account the Rrs spectral shapes and amplitudes as a whole and grades each Rrs spectrum. This scoring system is developed based on a large ensemble of in situ hyperspectral remote sensing reflectance data measured from various aquatic environments and processed with robust procedures. This system is further tested with the NASA bio-Optical Marine Algorithm Data set (NOMAD), with results indicating significant improvements in the estimation of bio-optical properties when Rrs spectra marked with higher quality assurance are used. This scoring system is further verified with simulated data and satellite ocean color data in various regions, and we envision higher quality ocean color products with the implementation of such a quality screening system.