|Title||Satellite estimation of carbon export by sinking particles in the California Current calibrated with sediment trap data|
|Publication Type||Journal Article|
|Year of Publication||2020|
|Authors||Kahru M, Goericke R, Kelly T.B, Stukel M.R|
|Type of Article||Article|
|Keywords||algorithms; biological pump; california current ecosystem; carbon export; climate; community; current ecosystem; Export flux; fecal pellets; matter flux; oceanography; open-ocean; particles; Plankton; primary production; sinking; surface chlorophyll; variability|
We evaluate a recent region-specific model of export production (Kelly a al., 2018) and some similar fits to in situ data for the California Current Ecosystem using satellite data. The model is a simple linear function of net primary productivity (NPP): Export = 0.08 x NPP + 72 where EF is export flux in mg C m(-2) d(-1). We confirm that contrary to several global algorithms export efficiency (e-ratio = export/primary productivity) is negatively correlated with net primary productivity. We find that linear models with a steeper slope of EF relative to NPP produce better estimates of the variability range. Choice of the EF model parameterization can more than double the estimate of temporal variability (standard deviation) in satellite-derived EF time series. The best estimates of EF were obtained when using average NPP during a preceding period of similar to 7-8 days. This is in contrast with NPP where the best satellite estimates of in situ NPP were obtained using same day satellite data and the coefficient of determination was monotonically decreasing with increasing time lag. We also find that there is substantial unexplained variability in EF that cannot be explained by existing models.