The attribution of individual extreme weather events to anthropogenic climate change is a complex but increasingly tractable problem. While confidence is high for events like extreme temperatures and precipitation, research on tropical cyclones is still developing. However, sea level rise, driven by human activity, is a clear and quantifiable exacerbating factor in the damage caused by coastal storms. Global mean sea level (GMSL) has risen significantly since 1900, and this rise is accelerating. This means that all recent coastal floods begin from a higher baseline water elevation than they would have historically. Many studies have shown an increase in the frequency, peak height, and damages of coastal floods due to sea level rise. However, these studies often assume a simple linear relationship and haven't isolated the effect of human-caused sea level rise from natural variability. This study aims to quantify the economic damages from Hurricane Sandy specifically attributable to anthropogenic sea level rise (ASLR), excluding other factors like natural variability or land subsidence. Hurricane Sandy, a powerful hybrid cyclone, caused record-high water levels in the New York City metropolitan area. While the storm's intensity or track may not have been directly influenced by climate change, the higher sea level undeniably amplified its impact. The study focuses on the lower bound of climate change influence by examining the effect of ASLR on damage alone, ignoring other potential effects of climate warming on the storm itself.

Existing research demonstrates a clear link between sea-level rise and increased frequency, peak height, and damages from coastal floods. However, most studies simplify the interaction between sea level rise and storm surge, often assuming a simple linear addition. Furthermore, few studies successfully isolate the contribution of anthropogenic sea level rise from other factors affecting local relative sea level change. This gap in understanding motivates the current research, which aims for a more refined attribution of Sandy's damages by explicitly accounting for the anthropogenic component of sea level rise.

The study uses a multi-pronged approach to estimate ASLR and its impact on Sandy's damages. First, ASLR is estimated through two independent methods: budget-based attribution and semi-empirical modeling. The budget-based approach combines literature-derived estimates of sea level rise contributions from various sources (land-ice melt, ocean thermal expansion, land-water storage changes) and applies regional sea level fingerprints to estimate ASLR for the New York area. The semi-empirical approach updates a previous study's model relating global mean sea level to global mean temperature, incorporating various temperature scenarios (stable, cooling, and CMIP5-based) to estimate ASLR at both global and regional scales. These results are combined to generate a total ensemble ASLR estimate. Second, a high-resolution dynamic flood model (ADCIRC) is employed to simulate Sandy's peak flood under both actual and counterfactual (lower sea level) conditions. The counterfactual scenarios use the range of ASLR estimates obtained in the first step. Third, a spatially varying error correction is applied to reduce spatial error correlation in the hydrodynamic model results. Fourth, a damage model (HAZUS-MH) is used to estimate damages from the simulated flood maps, which is compared across different sea levels to determine the fraction of damage attributable to ASLR. The fraction of damages attributed to ASLR is then applied to the total reported damages for New York, New Jersey, and Connecticut to estimate the dollar value of attributable damages. The study also explores the effects of simpler approaches (hydrodynamic simulation alone, and hydrodynamic plus damage, without bias correction) to assess their efficacy as proxies for the full model.

The study found a robust relationship between anthropogenic climate change and global mean sea level rise. Using both budget-based and semi-empirical methods, the total ensemble estimate for ASLR in the New York area for the period 1900-2012 is 9.6 cm (5.6–15.6 cm). Applying this to the hydrodynamic flood model simulations, the study finds that 13% (7.5–22.5%) of Sandy's damages in the tri-state area ($8.1 billion, $4.7B–$14.0B) are attributable to ASLR. This translates to $4.2 billion for New York, $3.7 billion for New Jersey and $0.18 billion for Connecticut. These estimates are consistent across multiple, independent approaches. The analysis reveals that ASLR's impact extends beyond simple spatial exposure, significantly affecting flood volume and depth across the flooded areas. The study estimates that ASLR exposed an additional 71,000 people and 36,000 housing units in the tri-state area. Simpler damage estimation methods that forgo spatial bias correction or utilize flood volume as a proxy for damage yield similar results, suggesting that these approaches might be useful in situations where more detailed modeling isn't feasible. New York City alone experienced $1.5 billion ($0.9B–$2.5B) in damages attributable to ASLR.

The findings strongly support the link between anthropogenic climate change, sea-level rise, and increased damages from coastal storms. The robust estimates of ASLR, obtained through independent methodologies and consistent with observed sea level rise, provide a solid foundation for the damage attribution. The analysis demonstrates that ASLR's influence extends beyond simply increasing the spatial extent of flooding; it also dramatically impacts the depth and volume of flooding, leading to amplified damage. The methodology employed here provides a valuable framework for quantifying the contribution of climate change to past and future coastal flooding events. The consistency of results across different modeling approaches strengthens the overall conclusion.

This study successfully quantifies the substantial economic damages from Hurricane Sandy attributable to anthropogenic climate change-induced sea level rise, demonstrating that ASLR significantly amplified the storm's impact. The robust methodology employed here, combining independent ASLR estimation, high-resolution hydrodynamic modeling, and damage assessment, provides a valuable framework for attributing economic losses from climate change. Future research should apply this approach to other coastal storms to build a more comprehensive understanding of climate change impacts and inform adaptation strategies. Further investigation into non-depth mechanisms of damage would also enhance the accuracy of future studies.

The study focuses solely on the impact of ASLR, excluding other potential effects of climate change on Sandy's intensity, size, or track. Although evidence suggests these other effects were minimal compared to the effect of ASLR, this remains a limitation. The damage model used (HAZUS-MH) does not explicitly account for all factors that contribute to damage, focusing primarily on depth. This may slightly underestimate the overall damages and the fraction attributable to ASLR. Lastly, the accuracy of the damage estimates depends on the reliability of the reported damages from the affected states.