Search for: All records

Earth system models suggest that anthropogenic climate change will influence marine phytoplankton over the coming century with light-limited regions becoming more productive and nutrient-limited regions less productive. Anthropogenic climate change can influence not only the mean state but also the internal variability around the mean state, yet little is known about how internal variability in marine phytoplankton will change with time. Here, we quantify the influence of anthropogenic climate change on internal variability in marine phytoplankton biomass from 1920 to 2100 using the Community Earth System Model 1 Large Ensemble (CESM1-LE). We find a significant decrease in the internal variability of global phytoplankton carbon biomass under a high emission (RCP8.5) scenario and heterogeneous regional trends. Decreasing internal variability in biomass is most apparent in the subpolar North Atlantic and North Pacific. In these high-latitude regions, bottom-up controls (e.g., nutrient supply, temperature) influence changes in biomass internal variability. In the biogeochemically critical regions of the Southern Ocean and the equatorial Pacific, bottom-up controls (e.g., light, nutrients) and top-down controls (e.g., grazer biomass) affect changes in phytoplankton carbon internal variability, respectively. Our results suggest that climate mitigation and adaptation efforts that account for marine phytoplankton changes (e.g., fisheries, marine carbon cycling) should also consider changes in phytoplankton internal variability driven by anthropogenic warming, particularly on regional scales. 

Abstract Anthropogenically forced changes in ocean biogeochemistry are underway and critical for the ocean carbon sink and marine habitat. Detecting such changes in ocean biogeochemistry will require quantification of the magnitude of the change (anthropogenic signal) and the natural variability inherent to the climate system (noise). Here we use Large Ensemble (LE) experiments from four Earth system models (ESMs) with multiple emissions scenarios to estimate Time of Emergence (ToE) and partition projection uncertainty for anthropogenic signals in five biogeochemically important upper‐ocean variables. We find ToEs are robust across ESMs for sea surface temperature and the invasion of anthropogenic carbon; emergence time scales are 20–30 yr. For the biological carbon pump, and sea surface chlorophyll and salinity, emergence time scales are longer (50+ yr), less robust across the ESMs, and more sensitive to the forcing scenario considered. We find internal variability uncertainty, and model differences in the internal variability uncertainty, can be consequential sources of uncertainty for projecting regional changes in ocean biogeochemistry over the coming decades. In combining structural, scenario, and internal variability uncertainty, this study represents the most comprehensive characterization of biogeochemical emergence time scales and uncertainty to date. Our findings delineate critical spatial and duration requirements for marine observing systems to robustly detect anthropogenic change.