Detecting Changes in Marine Responses to ENSO from 850-2100 CE: Insights from the Ocean Carbon Cycle

Kathrin M Keller1, Fortunat Joos1, Flavio Lehner1,2 and Christoph Raible1, (1)University of Bern, Climate and Environmental Physics, Bern, Switzerland, (2)National Center for Atmospheric Research, Boulder, CO, United States
Abstract:
El Ni\~no--Southern Oscillation (ENSO) is the most important mode of natural variability in the climate system on global scales. In addition to the physical climate state (e.g., winds, rainfall, circulation and thermocline depth), it substantially affects the ocean carbon cycle and marine productivity in the equatorial Pacific region and is the main driver of the inter-annual variability in global air-sea CO$_{2}$ fluxes. It is open whether ENSO varies under climate change, and how potential changes in the marine system are best detectable. We investigate ENSO and its influence on biogeochemical tracers, pH, productivity, and ocean temperature utilizing a continuous 850-2100 CE simulation with the Community Earth System Model (CESM1). The response of variables is investigated by applying composite analysis, thereby accounting for nonlinearity of positive and negative phases of ENSO. The impact of the state of the climate system is evaluated by comparing four different time periods: 1030-1129, Maunder Minimum (1645-1715), the industrial period (1850-2005) and the 21$^{st}$ century (2005-2100, rcp8.5). The modeled variance in ENSO amplitude is significantly higher during the Maunder Minimum cold than during the 21$^{st}$ century warm period. ENSO-driven anomalies in global air-sea CO$_{2}$ flux and marine productivity are two to three times lower and ocean tracer anomalies are generally weaker in the 21$^{st}$ century. Significant changes are detectable in both surface and subsurface waters and are earlier verifiable and more widespread for carbon cycle tracers than for temperature. The results suggest that multi-tracer data of both physical and biogeochemical variables might allow an earlier detection of potential changes in ENSO characteristics than physics-only approaches. This in turn could benefit the planning and cost-efficient implementation of adaptation and mitigation measures.