Beyond global mean warming: Pathways to multiple climate targets

• Main Author: Avrutin, Sandy
• Format: Thesis
• Language: English
• Published: University of Southampton 2024
• Subjects: Ocean acidification
• Online Access: https://eprints.soton.ac.uk/487379/; https://eprints.soton.ac.uk/487379/1/AA_Southampton_PhD_Thesis_Corrections.pdf; https://eprints.soton.ac.uk/487379/2/Final_thesis_submission_Examination_Ms_Alexandra_Avrutin.pdf

Climate change is a defining issue of the 21st century, impacting weather patterns, sea levels, crop production, ecosystem function and human health. Currently the global aim to limit climate change is framed by an aim to limit warming, specifically by reducing anthropogenic CO 2 emissions because these are the main driver of warming. As such, remaining carbon budgets (RCBs) are defined by exploiting the near-linear relationship between cumulative CO 2 emissions and warming. This is arguably an incomplete solution. Firstly, although the relationship between warming and cumulative emissions is near-linear, there is uncertainty in the constant of proportionality. There are also aspects of climate change that are not necessarily addressed by limiting global mean warming. These include ocean acidification, which is caused by ocean absorption of CO 2 but not linked to warming, and sea level rise, which is caused by warming but has uncertainty and pathway dependence that is not addressed in policy that aims to limit only warming. This thesis explores how other impacts of climate change (beyond global mean warming) can be used to frame RCBs. This is done with a reduced-complexity Earth systems model with a semi-empirical method for calculating sea level rise. In Chapter 2, an RCB is defined using both warming and surface ocean acidification targets. In Chapter 3, the impact on uncertainty of allowing ice melt to vary nonlinearly with warming is explored. In Chapter 4, the model is used to quantify how much CO 2 must be removed from the atmosphere to reduce the commitment to sea level rise to zero. Using a reduced-complexity model is computationally cheap, so a large ensemble can be used to assess parametric (related to model parameters) uncertainty in climate projections. When warming and acidification are used together to frame an RCB, uncertainty in the RCB is reduced because the upper end of the uncertainty distribution is lowered. Uncertainty is increased by considering a nonlinear relationship between warming and ...