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Oceanic primary production: 2. Estimation at global scale from satellite (Coastal Zone Color Scanner) chlorophyll
Antoine, D.; André, J.-M.; Morel, A. (1996). Oceanic primary production: 2. Estimation at global scale from satellite (Coastal Zone Color Scanner) chlorophyll. Global Biogeochem. Cycles 10(1): 57-69.
In: Global Biogeochemical Cycles. American Geophysical Union: Washington, DC. ISSN 0886-6236; e-ISSN 1944-9224, more
Peer reviewed article  

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  • Antoine, D.
  • André, J.-M.
  • Morel, A.

    A fast method has been proposed [Antoine and Morel, this issue] to compute the oceanic primary production from the upper ocean chlorophyll‐like pigment concentration, as it can be routinely detected by a spaceborne ocean color sensor. This method is applied here to the monthly global maps of the photosynthetic pigments that were derived from the coastal zone color scanner (CZCS) data archive [Feldman et al., 1989]. The photosynthetically active radiation (PAR) field is computed from the astronomical constant and by using an atmospheric model, thereafter combined with averaged cloud information, derived from the International Satellite Cloud Climatology Project (ISCCP). The aim is to assess the seasonal evolution, as well as the spatial distribution of the photosynthetic carbon fixation within the world ocean and for a “climatological year”, to the extent that both the chlorophyll information and the cloud coverage statistics actually are averages obtained over several years. The computed global annual production actually ranges between 36.5 and 45.6 Gt C yr−1 according to the assumption which is made (0.8 or 1) about the ratio of active‐to‐total pigments (recall that chlorophyll and pheopigments are not radiometrically resolved by CZCS). The relative contributions to the global productivity of the various oceans and zonal belts are examined. By considering the hypotheses needed in such computations, the nature of the data used as inputs, and the results of the sensitivity studies, the global numbers have to be cautiously considered. Improving the reliability of the primary production estimates implies (1) new global data sets allowing a higher temporal resolution and a better coverage, (2) progress in the knowledge of physiological responses of phytoplankton and therefore refinements of the time and space dependent parameterizations of these responses.

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