Tony Smith Publications

Solar radiation modification (SRM) has been proposed as a potential tool to limit increases in global or regional temperatures caused by anthropogenic greenhouse gas emissions. While pre- vious research has extensively examined the climate system’s response to various SRM strategies, as well as their aggregate economic consequences, the spatial distribution of economic impacts has received less attention. In this study, we use NorESM2-Disaggregated Integrated Assessment Model—an Earth System Model coupled to a high-resolution integrated assessment model—to assess the economic impacts, measured in gross domestic product (GDP) per capita, in an ide- alised SRM scenario where incoming solar radiation is reduced by 1%. Our results suggest that, relative to a baseline without SRM, most countries experience economic gains under SRM, with only a few countries facing negative impacts. Low-income countries tend to see the largest benefits, reducing disparities in GDP per capita across countries relative to the baseline. However, reduced damages and smaller disparities in GDP per capita are accompanied by a ‘moral hazard’ effect, in that SRM leads to higher emissions, which may in turn cause additional adverse effects not cap- tured here. These findings highlight potential trade-offs between economic benefits, the distribu- tion of economic impacts, and increased emissions relevant for SRM governance.

Global warming poses substantial risks to natural and human systems worldwide. Understanding the complex interactions between climate change and the economy is essential for designing effective policies and mitigation strategies. Yet, existing modeling tools are often limited by coarse spatial aggregation, simplified climate representation, or lack of interaction between climate and the economy. To address these gaps, we develop a novel framework that couples an Earth System Model (ESM) – the Norwegian Earth System Model version 2 (NorESM2) – with a spatially disaggregated Integrated Assessment Model (IAM), the Disaggregated Integrated Assessment Model (DIAM). The resulting modeling tool, NorESM2–DIAM, incorporates state-of-the-art climate and weather dynamics, allows economic impacts to depend on the full distribution of weather outcomes, and captures realistic spatial heterogeneity. To our knowledge, it is the first framework to fully couple an ESM with a high-resolution cost-benefit IAM. The primary contribution of this paper is to develop and implement the methodology that enables this coupling. We demonstrate the utility of NorESM2–DIAM through a baseline simulation. The results show that the economic impacts of global warming vary dramatically across space and that internal climate variability generates substantial volatility in regional GDP, highlighting the importance of high-resolution economic impact assessments. Although the baseline simulation focuses on regional temperature, the framework can be easily extended to incorporate additional variables such as precipitation and extreme events. It can also be applied to study a wide range of climate policies. NorESM2–DIAM represents an important step towards improving the understanding of economic impacts of climate change and can ultimately become an important source of information for decision-makers.