A semianalytical ocean color inversion algorithm with explicit water column depth and substrate reflectance parameterization

Abstract

A semianalytical ocean color inversion algorithm was developed for improving retrievals of inherent optical properties (IOPs) in optically shallow waters. In clear, geometrically shallow waters, light reflected off the seafloor can contribute to the water-leaving radiance signal. This can have a confounding effect on ocean color algorithms developed for optically deep waters, leading to an overestimation of IOPs. The algorithm described here, the Shallow Water Inversion Model (SWIM), uses pre-existing knowledge of bathymetry and benthic substrate brightness to account for optically shallow effects. SWIM was incorporated into the NASA Ocean Biology Processing Group's L2GEN code and tested in waters of the Great Barrier Reef, Australia, using the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua time series (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013). SWIM-derived values of the total non-water absorption coefficient at 443 nm, a t (443), the particulate backscattering coefficient at 443 nm, b bp (443), and the diffuse attenuation coefficient at 488 nm, K d (488), were compared with values derived using the Generalized Inherent Optical Properties algorithm (GIOP) and the Quasi-Analytical Algorithm (QAA). The results indicated that in clear, optically shallow waters SWIM-derived values of a t (443), b bp (443), and K d (443) were realistically lower than values derived using GIOP and QAA, in agreement with radiative transfer modeling. This signified that the benthic reflectance correction was performing as expected. However, in more optically complex waters, SWIM had difficulty converging to a solution, a likely consequence of internal IOP parameterizations. Whilst a comprehensive study of the SWIM algorithm's behavior was conducted, further work is needed to validate the algorithm using in situ data.

Parameterization of bottom spectral reflectance for shallow water ocean color inversion models

“…Many global physics-based algorithms have been developed to generate synoptic imagery and estimates of water column optical properties from remotely sensed data, but they have neglected the impact of light reflected from the bottom , Werdell et al, 2013. In optically shallow waters the algorithms need to account for the influence of light reflected from the bottom if they are to produce reliable estimates of water column properties , McKinna et al, 2015. Very clear waters often characterize coral reef environments, thus light reflectance of the bottom becomes an issue.…”

“…One example is the Shallow Water Inversion Model (SWIM) (McKinna et al, 2015), recently developed to improve retrievals of inherent optical properties (IOPs) of the water column in shallow water environments. SWIM uses bathymetry and bottom reflectance as input parameters.…”

“…SWIM uses bathymetry and bottom reflectance as input parameters. The algorithm has been incorporated into NASA's SeaWiFS Data Analysis System (SeaDAS) processing code, L2gen (http://oceancolor.gsfc.nasa.gov), as an evaluation product available to the research community (McKinna et al, 2015).…”

“…This can lead to errors in ocean color products of models developed for deep water, such as IOPs (Cannizzaro and Carder, 2006, Qin et al, 2007, Zhao et al, 2013. In recent years, methods to derive IOPs from optically shallow waters have been developed (McKinna et al, 2015, Brando et al, 2012, Barnes et al, 2014. To date, only one of the developed methods, the Shallow Water Inversion Model (SWIM) (McKinna et al, 2015), explicitly uses bathymetry and benthic reflectance datasets to improve IOP retrievals.…”

“…In recent years, methods to derive IOPs from optically shallow waters have been developed (McKinna et al, 2015, Brando et al, 2012, Barnes et al, 2014. To date, only one of the developed methods, the Shallow Water Inversion Model (SWIM) (McKinna et al, 2015), explicitly uses bathymetry and benthic reflectance datasets to improve IOP retrievals. SWIM focuses on IOP retrievals.…”