An assessment of land-based climate and carbon reversibility in the Australian Community Climate and Earth System Simulator

Future levels of climate change depend not only on carbon emissions but also on carbon uptake by the land and the ocean. Here we are using the Earth system model (ESM1) version of the Australian Community Climate and Earth System Simulator (ACCESS) to explore the potential and impact of removing carbon dioxide (CO₂) from the atmosphere through the climate and carbon cycle reversibility experiment. This experiment builds on the standard Coupled Model Intercomparison Project (CMIP) experiment, increasing CO₂ at 1% per year until 4xCO₂ is reached. The atmospheric CO₂ levels are then decreased at the same rate which brings the CO₂ back to pre-industrial levels. We then continue to run the model with constant CO₂ for another 350 years. Our analysis focuses on the response of the land carbon cycle. We find that carbon stores are largely reversible at the global scale over the timescale of changing CO₂. However, carbon stores continue to decrease after CO₂ returns to its initial value, and the land loses another 40 Pg of carbon (PgC) with the largest change in the tropics. It takes about 300 years beyond the period of changing CO₂ for the carbon stores to recover. Interestingly, we saw strong regional variations in the strength of the land response to changing CO₂. Australia showed the largest increase/decrease in biomass carbon (about 40%) and the largest variability in productivity, which was strongly correlated with rainfall. This highlights the importance of assessing the regional response to understanding the processes underlying the response and the sensitivity of these processes within each model. This understanding will benefit future multi-model analyses of this reversibility experiment. It also illustrates more generally the potential to use Earth system model experiments as part of the evaluation of proposed applications of carbon dioxide removal (CDR) technologies. As such, we recommend that these types of modelling experiments be included when mitigation policies are developed.

     

The effects of parametric uncertainties in simulations of a reactive plume using a Lagrangian stochastic model

A combined Lagrangian stochastic model with micro-mixing and chemical sub-models is used to investigate a reactive plume of nitrogen oxides (NO_x) released into a turbulent grid flow doped with ozone (O₃). Sensitivities to the model input parameters are explored for different source NO_x scenarios. The wind tunnel experiments of Brown and Bilger (1996) provide the simulation conditions for the first case study where photolysis reactions are not included and the main uncertainties occur in parameters defining the turbulence scales, source size and reaction rate of NO with O₃. Using nominal values of the parameters from previous studies, the model gives a good representation of the radial profile of the conserved mean scalar ${\overline{\Gamma }}_{{\text{NO}}_{\text{x}}}$ although slightly over predicts peak mean NO₂ concentrations ${\overline{\Gamma }}_{{\text{NO}}_{\text{2}}}$ compared to the experiments. The high dimensional model representation (HDMR) method is used to investigate the effects of uncertainties in model inputs on the simulation of chemical species concentrations. For this scenario, the Lagrangian velocity structure function coefficient has the largest impact on simulated ${\overline{\Gamma }}_{{\text{NO}}_{\text{x}}}$ profiles. Photolysis reactions are then included in a chemical scheme consisting of eight reactions between species NO, O, O₃ and NO₂. Independent and interactive effects of 22 input parameters are studied for two source NO_x scenarios using HDMR, including turbulence parameters, temperature dependant rate parameters, photolysis rates, temperature, fraction of NO in total NO_x at the source and background ozone concentration [O₃]. For this reactive case, the variance in the predicted mean plume centre ${\overline{\Gamma }}_{{\text{O}}_{\text{3}}}$ is caused by parameters describing both physical (mixing time-scale coefficient) and chemical processes (activation energy for the reaction O₃+NO). The variance in predicted plume centre ${\overline{\Gamma }}_{{\text{NO}}_{\text{2}}}$ and root mean square NO₂ concentration ${\gamma }_{{\text{NO}}_{\text{2}}}^{\prime }$, is strongly influenced by the fraction of NO in the source NO_x, and to a lesser extent the mixing time-scale coefficient. Adjusting the latter gives improved agreement with the Brown and Bilger experiment. Some weak parameter interactions are observed.