A simple model for assessing climate control trade-offs and responding to unanticipated climate outcomes. (21st September 2021) - Drake, Henri F; Rivest, Ronald L; Edelman, Alan; Deutch, John
Abstract: Persistent greenhouse gas (GHG) emissions threaten global climate goals and have prompted consideration of climate controls supplementary to emissions mitigation. We present MARGO, an idealized model of optimally-controlled climate change, which is complementary to both simpler conceptual models and more complicated Integrated Assessment Models. The four methods of controlling climate damage—mitigation, carbon dioxide removal (CDR), adaptation, and solar radiation modification (SRM)—are not interchangeable, as they enter at different stages of the causal chain that connects GHG emissions to climate damages. Early and aggressive mitigation is necessary to stabilize GHG concentrations below a tolerable level. While the most cost-beneficial and cost-effective pathways to reducing climate suffering include deployments of all four controls, the quantitative trade-offs between the different controls are sensitive to value-driven parameters and poorly-known future costs and damages. Static policy optimization assumes perfect foresight and obscures the active role decision-makers have in shaping a climate trajectory. We propose an explicit policy response process wherein climate control policies are re-adjusted over time in response to unanticipated outcomes. We illustrate this process in two 'storyline' scenarios: (a) near-term increases in mitigation and CDR are deficient, such that climate goals are expected to slip out of reach; (b) SRM is abruptly terminated after 40 years of successful deployment, causing an extremely rapid warming which is amplified by an excess of GHGs due to deterred mitigation. In both cases, an optimized policy response yields substantial benefits relative to continuing the original policy. The MARGO model is intentionally designed to be as simple, transparent, customizable, and accessible as possible, addressing concerns about previous climate-economic modelling approaches and enabling a more diverse set of stakeholders to engage with these essential and timely topics.