Please choose your delivery country and your customer group
With the developments of ocean color remote sensing technology, some ocean color parameters can be derived by satellite globally. These terms, including chlorophyll concentration (Chl), particulate backscattering coefficients (bbp), photosynthetically available radiation (PAR), have been proved to be related to NPP of phytoplankton. Based on these parameters with other auxiliary data, a carbon-based productivity model (CbPM) had been developed. The model derives phytoplankton carbon(C) from bbp and utilizes the ratios of C and Chl to describe the phytoplankton growth rates (μ) which has physiological dependencies on light (through variations in PAR), nutrients, and temperature. This paper indicated how the uncertainties in satellite derived parameters (Chl, bbp and PAR) propagated through the CbPM using Monte Carlo method. Comparisons on the individual contributor to the random uncertainty in NPP between these input items were discussed. The analysis results showed that among the three parameters, the biggest contribution to the uncertainty in the model output came from Chl. Therefore, improvements in the accuracy of Chl would have the largest potential to improve the ability of CbPM in estimating NPP of phytoplankton.