Hurricanes are devastating natural disasters causing significant economic losses and fatalities. The 2020 Atlantic hurricane season was a record-breaking event, featuring 30 named storms and substantial damage. These storms are fueled by warm ocean temperatures, and human-induced climate change, driven by increased greenhouse gas emissions, has led to a detectable rise in global temperatures. While the impacts of rising sea surface temperatures (SSTs) on hurricanes are complex due to interactions with other factors like wind shear and atmospheric stability, there's growing evidence suggesting an increase in hurricane intensity and extreme precipitation. This study aims to quantify the impact of human-induced warming on the extreme rainfall experienced during the entire 2020 Atlantic hurricane season using a hindcast attribution methodology.

Previous research has examined the impacts of climate change on individual hurricanes, using attribution frameworks to assess the role of human influence on intensity and frequency of extreme weather events. These studies have shown varying degrees of anthropogenic influence on hurricane rainfall, ranging from 2% to 20% depending on the metrics used. However, a comprehensive quantification of climate change's impact on an entire hurricane season's rainfall remained a significant gap in the literature. This study addresses this gap by objectively quantifying the climate change impact on extreme rainfall throughout the 2020 North Atlantic hurricane season.

The study employed a hindcast attribution methodology using the Community Atmospheric Model (CAM), a high-resolution atmospheric model. The methodology compares simulations of the actual 2020 hurricane season with counterfactual simulations representing a world without human influence. The counterfactual simulations were generated by removing the anthropogenic warming fingerprint from the initial conditions, adjusting surface temperatures, three-dimensional atmospheric variables (temperature and humidity) and using preindustrial greenhouse gas concentrations. The Community Earth System Model (CESM) Large Ensemble was used to construct the anthropogenic warming fingerprint. The CAM simulations were initialized every 3 days throughout the hurricane season. Storm tracks and rainfall accumulations were analyzed using the TempestExtremes software package. The analysis focused on storms with winds greater than 17 m/s and considered 3-hourly rainfall rates and 3-day accumulated rainfall amounts. Percentage differences between actual and counterfactual ensembles were calculated to quantify the impact of human-induced climate change on extreme rainfall.

The study's key findings demonstrate a significant human influence on the extreme rainfall during the 2020 hurricane season. Human-induced climate change increased the extreme (99th percentile) 3-hourly storm rainfall rates by 10% and the extreme 3-day accumulated storm rainfall amounts by 5% for storms of at least tropical storm strength. For hurricane-strength storms, the increases were even larger: 11% for 3-hourly rainfall rates and 8% for 3-day accumulated rainfall amounts. The increase in the anthropogenic signal for hurricane-strength storms compared to tropical storms highlights the disproportionate impact on coastal communities. The findings suggest that the increase in 3-day accumulated rainfall is broadly consistent with previous research, while the increase in 3-hourly rainfall is considerably larger than expected. This difference suggests that factors other than simple moisture availability are at play. The study notes that higher resolution simulations would be needed to investigate the underlying mechanisms driving this disproportionate increase in intense, short-duration rainfall events.

The results of this study confirm and extend previous research on the link between climate change and hurricane rainfall. The objective quantification of the impact across an entire hurricane season provides strong evidence for the contribution of human-induced warming to increased extreme rainfall events. The observed differences between the impact on tropical storms and hurricanes highlight the importance of considering the intensity of the storms when assessing climate change impacts. The findings have direct implications for coastal communities, which are particularly vulnerable to extreme rainfall events. The study suggests that future increases in greenhouse gas emissions will likely lead to even more intense rainfall in future North Atlantic hurricane seasons.

This study provides robust evidence for the role of human-induced climate change in intensifying extreme rainfall during the 2020 North Atlantic hurricane season. The findings underscore the need for continued research to understand the complex interactions between climate change and hurricane intensification, and to develop effective adaptation strategies to mitigate the impacts on vulnerable coastal communities. Future research should investigate this disproportionate increase in 3-hourly rainfall rates through higher-resolution simulations and should also explore the impact of climate change on hurricane frequency and development.

The study acknowledges limitations inherent in the hindcast attribution methodology and the use of climate models. The model resolution might limit the ability to capture small-scale processes relevant to precipitation, and uncertainties in the climate model's representation of hurricane dynamics could potentially affect the results. However, the use of a high-resolution model and the robust statistical analysis methods mitigate some of these limitations. The study primarily focuses on rainfall and doesn't explicitly address other aspects of hurricane impacts, such as wind speed or storm surge.