LAUSR

Abstract Using in situ data of spectral remote sensing reflectance (Rrs, sr−1) collected over North American oceanic, coastal and estuarine waters between 2002 and 2016 (N = 942), we evaluate two atmospheric correction approaches applied to MODIS measurements. One is the POLYnomial based approach originally designed for MERIS (POLYMER) but adopted and implemented for MODIS, and the other is the traditional Gordon and Wang (1994b) near-infrared (NIR) approach with iteration to account for non-negligible NIR water-leaving radiance, which is currently embedded in the SeaWiFS Data Analysis System (SeaDAS) software package and used operationally by NASA for processing MODIS data (termed as NASA standard atmospheric correction or NSAC). The approaches are evaluated for both quality and quantity of their retrieved Rrs in the visible domain. The quality is gauged through three statistical measures between in situ and MODIS-retrieved Rrs: root mean square error (RMSE, sr−1), unbiased root mean square (uRMS), and mean bias (δ, sr−1). For common points where both approaches yield valid Rrs retrievals, POLYMER shows worse performance than NSAC for blue bands (