Emergent constraints on soil carbon feedbacks under climate change
Date: 21 November 2022
University of Exeter
PhD in Mathematics
Global soils are the largest terrestrial store of carbon, and are sensitive to changes in the Earth's climate system due to anthropogenic emissions of CO₂. Predicted changes in soil carbon by Earth System Models (ESMs) represent the greatest uncertainty in quantifying future projections of land carbon storage under climate change. ...
Global soils are the largest terrestrial store of carbon, and are sensitive to changes in the Earth's climate system due to anthropogenic emissions of CO₂. Predicted changes in soil carbon by Earth System Models (ESMs) represent the greatest uncertainty in quantifying future projections of land carbon storage under climate change. Reducing this uncertainty is vital to achieve accurate future projections of global climate change and to successfully mitigate against its effects. The Coupled-Model Intercomparison Project phase 6 (CMIP6) includes the latest ESMs, as used within the latest Intergovernmental Panel on Climate Change 6th Assessment Report (IPCC AR6). Model development since the previous CMIP generation (CMIP5) has aimed to improve the representation of soil carbon related processes within ESMs, and reduce the uncertainty associated with predicted soil carbon change. On top of model development, additional methods such as emergent constraints suggest promise to constrain future uncertainties associated with soil carbon under climate change. The aim of this thesis is to evaluate and analyse soil carbon in CMIP6 ESMs to help quantify future soil carbon changes, and to attempt to reduce uncertainty in future soil carbon projections. Although some improvements are found in CMIP6 compared to CMIP5, significant uncertainties still remain, especially in the below ground processes that determine the effective soil carbon turnover time (Varney et al., 2022). The uncertainty in projected soil carbon stocks is found to be result of counteracting terms due to increasing Net Primary Productivity (NPP) and reductions in soil carbon turnover time (τ), as well as a significant non-linearity between NPP and τ. In the research presented in this thesis, a novel spatial emergent constraint is developed to constrain the subsequent changes in soil carbon due to reductions in τ under global warming (Varney et al., 2020). Comparison to the more standard breakdown of carbon storage changes into linear terms representing the response to changes in CO₂ and global temperature, reveals that there are significant reductions in τ under increasing CO₂, even in the absence of climate change. This effect is traced to 'false priming', which is especially prevalent in the CMIP6 models, and acts to reduce the spread in projected soil carbon changes in CMIP6 compared to CMIP5. These findings suggest some promising avenues for future research.
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