Bio-optical model to describe remote sensing signals from a stratified ocean

Abstract

We use a bio-optical model of the optical properties of natural seawaterto investigate the effects of subsurface chlorophyll layers on passiveand active remote sensors. A thin layer of enhanced chlorophyllconcentration reduces the remote sensing reflectance in the blue, whilehaving little effect in the green. As a result, the chlorophyllconcentration inferred from ocean color instruments will fall betweenthe background concentration and the concentration in the layer,depending on the concentrations and the depth of the layer. For lidar,an iterative inversion algorithm is described that can reproduce thechlorophyll profile within the limits of the model. The model isextended to estimate column-integrated primary productivity,demonstrating that layers can contribute significantly to overallproductivity. This contribution also depends on the chlorophyllconcentrations and the depth of the layer. Using passive remote sensingalone to estimate primary productivity can lead to significantunderestimation in the presence of subsurface plankton layers. Activeremote sensing is not affected by this bias. (C) The Authors. Publishedby SPIE under a Creative Commons Attribution 3.0 Unported License.