Seasonal prediction of ocean biogeochemistry in the Northeast U.S. Large Marine Ecosystem using a regional ocean-biogeochemistry model

Abstract. We couple an ocean biogeochemical model to a regional ocean model of the Northwest Atlantic and assess the potential skill of bottom dissolved oxygen, aragonite saturation state, and pH forecasts along the Northeast U.S. Continental Shelf using a reanalysis-forced model run as the true biogeochemical state. Across 30 years of retrospective forecasts initialized four times per year, the model has substantial potential skill for all three variables, with skill generally highest in the deep Gulf of Maine and lowest in the shallower Mid-Atlantic Bight and Georges Bank. Forecasts initialized in January and April benefit from the insulation of the bottom from the unpredictable atmosphere by stratification and tend to have greater skill at longer lead times. Using two case studies, we show how predictable variations in ocean temperature, salinity, and currents are associated with predictable variability in bottom biogeochemistry in both the Mid-Atlantic Bight and Gulf of Maine. The forecast model evaluated in this study has been developed as an operational prototype for NOAA's Changing Ecosystems and Fisheries Initiative, with the goal of applying the forecasts to improve the yield and sustainability of living marine resources.