A Retrospective Analysis of Remote-Sensing Reflectance Products in Coastal and Inland Waters

Constructing a robust ocean color (OC) record(e.g., water transparency, phytoplankton absorption) for long-term assessments of coastal and inland water ecosystems from past, present, and future missions requires high-quality spectral remote sensing reflectance (R-rs) products. Using the GLORIA dataset (Lehmann et al., 2023), we evaluated the quality of R-rs products from the moderate resolution imaging spectroradiometer (MODIS on Terra and Aqua), medium resolution imaging spectrometer (MERIS), and visible infrared imaging radiometer suite (VIIRS) processed via the two-band heritage atmospheric correction method (a combination of near-infrared and shortwave infrared bands) available in the Sea WiFS Analysis Data Analysis System (SeaDAS). Overall, retrieval residuals are consistent within a few percentages among the four missions. Median residuals ranged from similar to 20% in the similar to 550-nm band to>60% in the similar to 412-nm bands. Spectrally averaged root mean squared differences for all the missions were similar to 0.0024 sr(-1)with one standard deviation of similar to 0.001 sr(-1). The corresponding(median) biases in the visible bands varied from-60% to-3%,with the largest biases identified in MERIS and VIIRS products. Despite the lower sensitivity of band-ratio algorithms to residuals in specific spectral regions [e.g., OC3 chlorophyll-a algorithm is less prone to residuals in R-rs(lambda>600 nm)], other algorithms or downstream products that leverage all the visible bands are highly compromised. We underscore the need to improve the quality of Rrsproducts, thereby enabling the reconstruction of baseline OC products of high caliber in global coastal and inland waters that are often near human activity.