Variability of the ocean carbon cycle in comprehensive Earth system models

Keller, Kathrin (2015). Variability of the ocean carbon cycle in comprehensive Earth system models (Unpublished). (Dissertation, Universität Bern, Philosophisch–naturwissenschaftliche Fakultät, Physikalisches Institut, Abteilung für Klima– und Umweltphysik)

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Global warming is happening and, according to the latest IPCC report, it is extremely likely that it is caused by anthropogenic perturbations of the climate-carbon cycle system. Still, the detection of trends in physical climate characteristics, biogeochemical cycles and ecosystems remains a challenge. A major issue is the presence of natural variability due to both internal phenomena such as climate modes and external processes such as volcanic eruptions or changes in solar irradiation. As a consequence, it is not always clear if an observed trend in a given variable is representative for the long-term evolution, or if it is attributable to natural variability. A thorough understanding of the coupled climate-carbon system and its internal dynamics is thus key for both the detection of trends and the making of robust future projections. This thesis investigates the variability of the ocean carbon cycle using simulations with comprehensive Earth System Models (ESMs); of particular interest is the
variability attributable to climate modes.
The introduction in Chapter 1 gives an overview of the climate-carbon cycle system and its components, feedback processes and natural variability. A special focus is on the ocean carbon cycle. Moreover, anthropogenic climate change and its impacts on the climate system are summarized, followed by a short introduction of climate-carbon cycle modeling.
Chapter 2 introduces the Community Earth System Model version 1 (CESM1) and provides an overview of the simulations performed in the framework of this thesis.
Chapter 3 investigates the response of the ocean carbon cycle to the climate mode North Atlantic Oscillation (NAO). The basis for the analysis are control simulations conducted with six different ESMs. The results indicate that wind-driven dynamics are the main driver of the oceanic response to the NAO, which – via vertical mixing, upwelling and the associated entrainment of dissolved inorganic carbon and nutrients – affects surface pCO2 and the air-sea CO2 flux as well as biological export production, pH and the calcium carbonate saturation state. Large-scale horizontal transport processes are of minor importance. The response is instantaneous and expresses itself in a seesaw pattern between the subtropical gyre and the subpolar Northern Atlantic. As a consequence, the overall effect on the basin-wide air-sea CO2 flux is small due to compensating fluxes on the sub-basin scale. The results are consistent over all models and with observations for a range of physical and biogeochemical variables. Further, all models indicate nonlinearity in the response to the positive and negative phase of the NAO. However, the models differ in regional expression and magnitude, and conflicting results remain concerning the air-sea flux and the partial pressure of CO2. It is concluded that the marine biogeochemical response to the NAO is predominantly governed by vertical exchange processes.
Chapter 4 addresses the issue of Time of Emergence (ToE), i.e., the time needed by a forced trend to emerge from the background noise of natural variability. The concept is applied to different surface ocean variables on the local-to-regional scale using a multi-model ensemble comprising simulations of 17 ESMs. The results indicate that anthropogenic signals emerge on much shorter timescales in ocean biogeochemical variables than in the physical variable sea surface temperature. Considering the changes since the beginning of the industrialization, the rapid emergence of trend signals implies that anthropogenic trends in the surface ocean carbon cycle are already detectable in large parts of the global oceans. In general, the background noise is more important in determining ToE than the strength of the trend signal. In areas with high natural variability even strong trends both in the physical climate and carbon cycle system are masked by variability over decadal timescales, which explains inconsistencies in trends based on time series of insufficient length. A further result is that, in contrast to longer-term trends, natural variability is affected by the seasonal cycle. This has implications for the interpretation of observations, since it implies that intra-annual variability could question the representativeness of irregularly seasonal sampled measurements for the entire year.
Chapter 5 analyzes the climate mode El Ni˜no–Southern Oscillation (ENSO) and its impact on ocean temperature and biogeochemistry during different climate conditions. The analysis is based on a continuous 850-2100 CE simulation with CESM1 (see Appendix B). The model captures essential characteristics of ENSO such as the warm- and cold tongues associated with El Ni˜no and La Ni˜na and an occurrence at periodicities of 2 to 7 years. The modeled variance in ENSO amplitude is significantly higher during the Maunder Minimum cold period in comparison with the 21st century warm period. The response in ocean variables constitutes an east-west seesaw pattern in the equatorial Pacific thermocline. Significant changes between climate conditions are detectable in both surface and subsurface waters and are earlier verifiable and more widespread for carbon cycle tracers than for temperature. ENSO-driven anomalies in global air-sea CO2 flux and marine productivity are two to three times lower and ocean tracer anomalies are generally weaker in the 21st century. The results suggest that multi-tracer data of both physical and biogeochemical variables might allow an earlier detection of changes in marine ENSO responses than physics-only approaches which, in turn, could benefit the planning and cost-efficient implementation of adaptation and mitigation measures.
An outlook is given in Chapter 6 and presents research challenges and potential follow-up studies in the context of climate-carbon cycle system modeling. Appendix A presents preliminary results based on a currently running set of sensitivity experiments with CESM1. Appendix B introduces a continuous 850-2100 CE simulation conducted with CESM1 (see also Chap. 5).

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