developing npp algorithms for the arctic
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Developing NPP algorithms for the Arctic. 1. Empirical chlorophyll based algorithm. Chukchi Sea. ANCOVA H 0 – means between light levels are equal. P < 0.00 , H 0 is rejected. 1. Empirical chlorophyll based algorithm. Chukchi Sea. 1. Empirical chlorophyll based algorithm. Resolute Bay.

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1 empirical chlorophyll based algorithm6
1. Empirical chlorophyll based algorithm

Combined dataset

Log PP = 1.36 + 1.0.LogChl

  • Average Chlorophyll
  • Resolute Bay 8.1 mg m-3
  • Barents Sea 4.2 mg m-3
  • Chukchi Sea1.2 mg m-3
  • ANCOVA
  • Chl 0.8 – 32 mg m-3
  • P < 0.01
2 model based on c chl ratios
2. Model based on C:Chl ratios
  • Behrenfeld et al. (2005) developed a productivity model based on Chl:C ratios
  • and chlorophyll concentrations derived from ocean color satellite observations.
  • Carbon (POC) is retrieved from backscatter
  • Chlorophyll is retrieved from Rrs ratios (i.e OC4V4, OC3M or OC3Arc)
  • These are coupled with mixed layer light levels from surface PAR and K490
  • observations and growth rates estimated from the literature. The final equation is:
  • NPP = C . µ . Zeu. h(Io)
  • Where C is carbon, µ is growth rate, Zeu is the euphotic depth and h(Io) describes how
  • changes in surface light influence the depth dependent profile
  • of carbon fixation
2 model based on c chl ratios2
2. Model based on C:Chl ratios
  • Model Input
  • Carbon (POC) is retrieved from backscatter – Behrenfeld global relationship
  • Chlorophyll is retrieved from Rrs ratios - OC3Arc
  • Surface PAR – estimated from observations
  • Mixed layer light levels – estimated from observations
  • Growth rate – literature global, 0.5 – 2 divisions d-1
  • h(Io) taken from Behrenfeld and Falkowski (1997)
  • NPP = C . µ . Zeu . h(Io)
  • Model output
  • 1. NPP euphotic zone integrated - g C m-2 day-1
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