A Synthetic Ensemble of Global Ocean Chlorophyll Concentration

Geneviève Elsworth, NASA Goddard Space Flight Center, Global Modeling and Assimilation Office, Greenbelt, MD, United States, Nicole S Lovenduski, University of Colorado, Department of Atmospheric and Oceanic Sciences, Boulder, CO, United States, Karen A McKinnon, University of California Los Angeles, Departments of Statistics, Institute of the Environment and Sustainability, Los Angeles, CA, United States and Riley Xavier Brady, University of Colorado at Boulder, Department of Atmospheric and Oceanic Sciences, Boulder, CO, United States
Abstract:
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.