Bio-optics

Ocean colour remote sensing can provide routine, synoptic and highly cost-effective observations of biological and biogeochemical response to physical drivers across oceanic ecosystems, over decadal time scales and at high frequency. In many cases, remotely sensed data are the only systematic observations available for chronically under-sampled marine systems (e.g. the polar oceans), and there is thus a need to maximise the value of these observations by developing ecosystem-appropriate, well characterised products.

A primary focus of SOCCO’s bio-optical research is on gathering the necessary bio-optical and physiological data to develop and validate appropriate regional ocean colour algorithms for the Southern Ocean. This includes bio-optical data in the form of Inherent Optical Properties (IOP’s) (scattering, beam attenuation and absorption) and Apparent Optical Properties (AOP) (radiance, irradiance, reflectance, diffuse attenuation coefficient) and biogeochemical data that characterises the phytoplankton community (e.g. carbon content, size structure and dominant functional type). This information in conjunction with radiative transfer models and reflectance inversion algorithms will allow us to use satellite derived ocean colour data to investigate biological responses (through changes in biomass, community structure and physiology) to event, seasonal and inter-annual variability in ecosystem physical drivers at the required spatial and temporal scales. Given the important relationship between community size and carbon export these approaches will allow us to assess the potential for carbon cycling and carbon sequestration at the regional scale.

  • Scientists on the SA Agulhas collecting biogeochemical data to characterise the phytoplankton community structure.
  • Spatial distribution of mean chlorophyll concentrations for the Southern Ocean south of 30oS for Summer (January) taken from SeaWiFS ocean colour data. Frontal positions calculated from MADT contours are shown for the STF (red), the SAF (black), the PF (orange) and the SACCF (blue).
  • An example of absorption spectra for different monospecific phytoplankton cultures. Note the difference between diatoms grown at different light levels. Figure reproduced from Roesler (2013).
  • A variety of phytoplankton seen from a microscope
  • Filtration rig used to collect biogeochemical data that characterises the phytoplankton community structure.
  • The underway Inherent Optical Property system onboard the SA Agulhas
  • Regression of POC and cp (650 nm) for the Weddel Gyre (red line) compared with a global dataset from six different surveys (black dotted line). Taken from Ceinwen Smith MSc Thesis.
  • Scientists at work in the bio-optics and bio-geochemistry wet lab on the SA Agulhas II.
  • A section of chlorophyll and particulate organic carbon across the Weddell Gyre in the Southern Ocean calculated from the optical properties of fluorescence and beam attenuation respectively. Taken from Ceinwen Smith MSc Thesis.
Related News and Publications

Ocean colour remote sensing can provide routine, synoptic and highly cost-effective observations of biological and biogeochemical response to physical drivers across oceanic ecosystems, over decadal time scales and at high frequency. In many cases, remotely sensed data are the only systematic observations available for chronically under-sampled marine systems (e.g. the polar oceans), and there is thus a need to maximise the value of these observations by developing ecosystem-appropriate, well characterised products.

A primary focus of SOCCO’s bio-optical research is on gathering the necessary bio-optical and physiological data to develop and validate appropriate regional ocean colour algorithms for the Southern Ocean. This includes bio-optical data in the form of Inherent Optical Properties (IOP’s) (scattering, beam attenuation and absorption) and Apparent Optical Properties (AOP) (radiance, irradiance, reflectance, diffuse attenuation coefficient) and biogeochemical data that characterises the phytoplankton community (e.g. carbon content, size structure and dominant functional type). This information in conjunction with radiative transfer models and reflectance inversion algorithms will allow us to use satellite derived ocean colour data to investigate biological responses (through changes in biomass, community structure and physiology) to event, seasonal and inter-annual variability in ecosystem physical drivers at the required spatial and temporal scales. Given the important relationship between community size and carbon export these approaches will allow us to assess the potential for carbon cycling and carbon sequestration at the regional scale.

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