Chlorophyll a algorithms for oligotrophic oceans: A novel approach based on three‐band reflectance difference

Abstract

A new empirical algorithm is proposed to estimate surface chlorophyll a (Chl) concentrations in the global ocean for Chl ≤ 0.25 mg m−3(∼78% of the global ocean area). The algorithm is based on a color index (CI), defined as the difference between remote‐sensing reflectance (Rrs, sr−1) in the green and a reference formed linearly between Rrs in the blue and red. For low‐Chl waters, in situ data showed a tighter (and therefore better) relationship between CI and Chl than between traditional band ratios and Chl, which was further validated using global data collected concurrently by ship‐borne and Sea‐viewing Wide Field‐of‐view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua instruments. Model simulations showed that for low‐Chl waters, compared with the band‐ratio algorithm, the CI‐based algorithm (CIA) was more tolerant to changes in chlorophyll‐specific backscattering coefficient and performed similarly for different relative contributions of nonphytoplankton absorption. Simulations using existing atmospheric correction approaches further demonstrated that the CIA was much less sensitive than band‐ratio algorithms to various errors induced by instrument noise and imperfect atmospheric correction (including sun glint and whitecap corrections). Image and time series analyses of SeaWiFS and MODIS/Aqua data also showed improved performance in terms of reduced image noise, more coherent spatial and temporal patterns, and better consistency between the two sensors. The reduction in noise and other errors is particularly useful to improve the detection of various ocean features such as eddies. Preliminary tests over Medium‐Resolution Imaging Spectrometer and Coastal Zone Color Scanner data indicate that the new approach should be generally applicable to all past, current, and future ocean color instruments.