Ocean primary production constitutes approximately half of global
biospheric production, affecting both fisheries productivity and
biogeochemical cycling. Although climate change is predicted to affect
the ocean's biological productivity, the extent of the global impact is
poorly quantified. Assessing changes in the ocean biosphere using remote
sensing data is challenged by the relatively short length of the
observational record, restricting our ability to disentangle
fluctuations in internal variability from forced anthropogenic trends.
Additionally, the majority of ocean circulation models with embedded
biogeochemistry do not skillfully predict observational records of ocean
chlorophyll at ocean time series locations. To overcome these
limitations, we have constructed a synthetic ensemble of global ocean
chlorophyll concentration. By employing statistical resampling methods
to the SeaWiFS and MODIS ocean color datasets and creating surrogate
climate modes of ENSO and PDO, we quantify the range of internal climate
variability in the 20 year observational record and create multiple
alternate realities for the possible evolution of the ocean biosphere
over time. Our synthetic ensemble can be used for a variety of purposes,
including diagnosing patterns of internal variability and emergence of
anthropogenic trends in observed chlorophyll, and validating Earth
system model representation of such variability.