The Antarctic Ice Sheet (AIS), holding enough freshwater to raise global sea levels by 58 meters, is experiencing accelerating mass loss due to global warming. This poses a significant and often overlooked risk in economic modeling of climate change. While some studies have touched upon the economic impacts of AIS melting, often using stylized damage functions disconnected from the actual melting process, this study aims to bridge this gap. Previous research has either focused on the West Antarctic Ice Sheet (WAIS) alone or incorporated AIS melting implicitly within broader SLR impact assessments. This research leverages recent advancements in glaciology and coastal economics modeling to provide a more comprehensive and realistic assessment. The study utilizes a reduced-form model of AIS melting, coupled with a detailed model of coastal impacts (CIAM) and embedded within a larger Integrated Assessment Model (IAM, META) to estimate the contribution of AIS melting to the overall social cost of carbon. Understanding the economic consequences of AIS melting is crucial for informing effective climate change mitigation and adaptation strategies, particularly in vulnerable coastal regions.

The existing literature on the economic impacts of AIS melting is limited. Two previous studies stand out. One employed a simplified model of WAIS melting within the DICE IAM, using a survival analysis framework. Another utilized stylized SLR scenarios within the FUND IAM to study WAIS melting. A broader literature exists examining the global economic impacts of SLR from all sources, implicitly including contributions from AIS melting. Recent advances in spatially detailed modeling of global SLR economic costs, utilizing probabilistic local SLR projections, have refined impact assessments but lack the explicit focus on the AIS' unique dynamics. This research builds upon this foundation by incorporating the latest advances in glaciology to construct a more realistic model of ice mass loss, covering the entire AIS, and utilizing a high-resolution coastal impacts model to assess costs under various adaptation scenarios.

The study employs a three-stage modeling approach. First, a reduced-form model of AIS melting is developed, emulating the behavior of complex ice sheet models by incorporating both surface mass balance (SMB) and dynamic contributions. The SMB model uses a linear relationship between SMB and global mean surface temperature change, while the dynamic contribution model emulates basal ice shelf melting and its effect on SLR using data from state-of-the-art ice sheet models (LARMIP-2). Sensitivity analyses are performed using SLR projections that incorporate hydrofracturing and MICI processes (DeConto et al., 2021) and an extreme melt scenario from the ABUMIP project. Second, this AIS melting model is coupled with the Coastal Impact and Adaptation Model (CIAM), which estimates country-level coastal impact costs broken down into different categories, under optimal adaptation and no adaptation scenarios. Global SLR projections are statistically downscaled to the segment level for use within CIAM. Finally, the coupled AIS-CIAM model is integrated into the META IAM, which also accounts for thermal expansion, glacier and small ice cap melting, and GIS melting, allowing for a comprehensive assessment of the contribution of AIS melting to the social cost of carbon. The META IAM also incorporates various uncertainties related to both climate and socio-economic factors. Different Representative Concentration Pathways (RCPs) – RCP2.6, RCP4.5, and RCP8.5 – are utilized to represent different future emission scenarios, and the results are analyzed across these scenarios.

The study's SLR projections from AIS melting are comparable to IPCC AR6 estimates, though slightly higher and more sensitive to emissions scenarios. Under RCP4.5, the median SLR contribution from AIS melting is estimated at 0.16 meters in 2100, with a 90% confidence interval of 0.02-0.55 meters. The economic costs of AIS melting are substantial and unevenly distributed. Without adaptation, global costs reach trillions of dollars annually by 2100. Optimal coastal adaptation dramatically reduces costs by roughly an order of magnitude. SIDS are disproportionately affected, facing the highest costs relative to their GDPs. Sensitivity analyses indicate that incorporating hydrofracturing and MICI processes increases costs but does not significantly change the median cost estimate in 2100. The ABUMIP extreme melt scenario, however, leads to dramatically higher costs, highlighting the tail risk. Finally, the inclusion of AIS melting significantly increases the social cost of carbon, particularly under high emissions scenarios. On RCP8.5-SSP5, the average increase in the social cost of carbon is 53.3%, and in some model runs, the social cost of carbon is more than doubled. The increase is also substantial on lower emissions scenarios, around 7% on average for RCP2.6-SSP1 and RCP4.5-SSP2.

The findings highlight the critical importance of proactive coastal adaptation strategies to mitigate the economic consequences of AIS melting. The significant cost savings achievable through optimal adaptation underscore the need for well-planned and well-resourced adaptation efforts. The uneven distribution of costs emphasizes the need for equitable support to vulnerable countries, particularly SIDS, to cope with the economic challenges of climate change. The large uncertainty associated with AIS melting underscores the value of further research to refine our understanding of ice sheet dynamics and reduce uncertainties. The significant increase in the social cost of carbon from incorporating AIS melting strengthens the economic argument for stringent climate change mitigation policies.

This study integrates recent glaciological and economic modeling to provide a comprehensive assessment of the economic impacts of AIS melting. The results show that AIS melting poses substantial and unevenly distributed economic costs, which can be significantly reduced through effective coastal adaptation. Moreover, the inclusion of AIS melting substantially increases the social cost of carbon, highlighting the urgency of climate action. Future research should focus on reducing uncertainties surrounding AIS melting, improving coastal economic models, and exploring the interactions between AIS melting and other climate tipping points.

The study's limitations include the omission of geophysical interactions with the GIS, limitations in the quantification of SLR uncertainty, uncertainties in the cost of SLR from CIAM (e.g., omitting saltwater intrusion), assumptions of perfect foresight in the CIAM adaptation planning, and limitations of the META IAM, such as the treatment of discounting and damage persistence. The confidence intervals are likely too narrow due to the omission of some sources of uncertainty.