Climate Uncertainty and Global Economic Impacts

Confronting the issue of climate change requires costly, preemptive action coordinated on a global scale. Quantifying the uncertainty around climate change impacts is necessary to concretely incorporate risk in this process. This project seeks to examine the extent and implications of climate uncertainty in the context of projected damages by applying damage functions established in the economics literature to outputs from the Multi-Model Large Ensemble Archive (MMLEA) . Exploring the uncertainty in partial-equilibrium estimates of economic damages from climate change can improve the integration of climate science and economics in climate change impact analysis.

Projections of economic damages require predictions of how the climate will evolve. Ensembles of global climate models that follow the framework set by the Coupled Model Intercomparison Project provide key projections for policy decisions, but contain multiple sources of uncertainty. As models in the ensemble differ structurally, the spread in simulation outputs may be attributed from the combination of within-model uncertainty (that is, each model's inherent internal variability) and between-model (or structural) uncertainty; these two sources of uncertainty have different implications for the optimal mitigation response given learning.

The Multi-Model Large Ensemble Archive and related initiatives have improved quantification of the three sources of uncertainty for projections of global mean temperature and precipitation. Using its inputs, I examine its implications for projected damages from longer-term damage functions, especially with regards to regional and global damage aggregation. The results are expected to shed light on the heterogeneity in economic climate risk as well as the sufficiency of current assumptions in economic integrated assessment models used for policy analysis.

Estimating the variability of global climate damages is necessary to improve current macro-scale climate models; for one, it allows for better estimation of the expectation of damages. However, analysis on a more disaggregated scale may also be useful: Though climate change is expected to disproportionately damage warmer and poorer countries, we know relatively little about the distribution of risk across countries. It is valuable to know if the spread of climate risk for sub-Saharan African economies is wider than that of, say, Finland, especially if damage functions exaggerate the variability in climate realizations. What is the variability around damage estimates? Where do models tend to agree, and where and how do they vary in results? This exercise seeks to address these questions by surveying the spread of climate impact realizations by model on the country and world level in the context of economic impacts and utility.