Development of a bio-optical model for the Barents Sea to quantitatively link glider and satellite observations

Philos Trans A Math Phys Eng Sci. 2020 Oct 2;378(2181):20190367. doi: 10.1098/rsta.2019.0367. Epub 2020 Aug 31.

Abstract

A bio-optical model for the Barents Sea is determined from a set of in situ observations of inherent optical properties (IOPs) and associated biogeochemical analyses. The bio-optical model provides a pathway to convert commonly measured parameters from glider-borne sensors (CTD, optical triplet sensor-chlorophyll and CDOM fluorescence, backscattering coefficients) to bulk spectral IOPs (absorption, attenuation and backscattering). IOPs derived from glider observations are subsequently used to estimate remote sensing reflectance spectra that compare well with coincident satellite observations, providing independent validation of the general applicability of the bio-optical model. Various challenges in the generation of a robust bio-optical model involving dealing with partial and limited quantity datasets and the interpretation of data from the optical triplet sensor are discussed. Establishing this quantitative link between glider-borne and satellite-borne data sources is an important step in integrating these data streams and has wide applicability for current and future integrated autonomous observation systems. This article is part of the theme issue 'The changing Arctic Ocean: consequences for biological communities, biogeochemical processes and ecosystem functioning'.

Keywords: Arctic Ocean; autonomous observations; bio-optical model; light availability; ocean colour remote sensing.

Publication types

  • Comparative Study

MeSH terms

  • Arctic Regions
  • Carbon Cycle
  • Chlorophyll / analysis
  • Ecosystem*
  • Environmental Monitoring / instrumentation
  • Environmental Monitoring / methods*
  • Global Warming
  • Ice Cover / chemistry
  • Models, Theoretical
  • Norway
  • Oceans and Seas
  • Optical Phenomena
  • Remote Sensing Technology / instrumentation
  • Remote Sensing Technology / methods
  • Satellite Imagery / instrumentation
  • Satellite Imagery / methods*
  • Seawater / analysis*
  • Spectrophotometry / instrumentation
  • Spectrophotometry / methods

Substances

  • Chlorophyll