Adaptive optical algorithms with differentiation of water bodies based on varying composition of suspended particulate matter: A case study for estimating the particulate organic carbon concentration in the western Arctic seas

Abstract

High complexity and variability in composition of water constituents pose major challenges for development of algorithms to estimate biogeochemical data products from optical observations over the continuum of diverse aquatic environments. To address these challenges, we examined an adaptive optical approach that accounts for variability in composition of suspended particulate matter. We use the ratio of particulate organic carbon to suspended particulate matter concentration, POC/SPM, for optically discriminating water bodies with varying proportions of organic and mineral particles. Through the analysis of field data from the western Arctic seas that exhibit a broad range of water composition and optical properties, we developed empirical algorithms to estimate SPM and POC/SPM either from the particulate inherent optical properties (IOPs) of seawater, i.e., the spectral particulate absorption ap(λ) or backscattering bbp(λ) coefficients, or directly from the spectral remote-sensing reflectance of the ocean, Rrs(λ). The capability to retrieve POC/SPM from optical measurements was used to formulate the particle composition-specific algorithms for estimating POC from particulate IOPs or Rrs(λ). The evaluation of algorithms with the development field dataset demonstrates that the algorithm formulations accounting for changes in POC/SPM provide significant improvements in POC estimates along the continuum of optically-complex Arctic waters compared with algorithms that do not account for variations in particulate composition, such as the current standard POC algorithm used for global satellite applications. The results of example application of the particle composition-specific algorithm and standard global algorithm to satellite observations are consistent with comparisons of these algorithms for our field dataset, which supports a conclusion that the standard algorithm tends to overestimate POC in Arctic waters that exhibit a broad range of particle composition. Although this study demonstrates the adaptive approach using data from the Arctic region, it has broader significance and is amenable to further enhancements by including other optically-derivable water constituent properties. Further validation analyses and efforts are needed towards a unified approach with improved representation of cause-and-effect relationships between water composition and optical properties to enable improved optically-based applications across a wide range of water bodies.