Jennifer Collins

The 2024 North Atlantic (hereafter Atlantic) hurricane season started quickly, with the earliest Category 5 on record (Beryl) and three hurricanes forming through 14 August. Following Ernesto's dissipation on 20 August, the Atlantic hurricane season became extremely quiet during the climatological peak of hurricane season, with only one Category 2 hurricane (Francine) and one tropical storm through 23 September. Several environmental factors likely contributed to this unexpected, prolonged lull. During mid‐to‐late August, subseasonal conditions were broadly favorable for Atlantic hurricanes, but a northward shift in African easterly wave emergence latitude yielded fewer tropical cyclone seed disturbances that also traversed unfavorably cool ocean water. During early‐to‐mid September, subseasonal variability driven by the Madden‐Julian oscillation was less conducive to hurricane activity, with several bouts of increased vertical wind shear across the central Atlantic. Throughout most of the lull, the tropical Atlantic was anomalously dry and subsident, suppressing hurricane formation chances.

This study evaluated ten drought indices focusing on their ability to monitor drought events in Marathwada, a semi-arid region of India. High-resolution gridded monthly total precipitation data for 75 years (1950–2024) from the European Centre for Medium-Range Weather Forecasts (ECMWF) were used to evaluate the drought indices. These indices were computed across six timescales: 1, 3, 4, 6, 9, and 12 months. A Generalized Autoregressive Conditional Heteroscedastic (GARCH) model was employed to detect temporal volatility in precipitation, followed by a second-order geospatial autocorrelation eigenfunction eigendecomposition using Global Moran’s Index statistics to geolocate both aggregated and non-aggregated precipitation locations. The performance of drought indices was assessed using non-parametric Spearman’s correlation to identify the strength, direction, and similarity of regional-specific drought events. The temporal lag interdependence between meteorological and agricultural droughts was assessed using a non-parametric Spearman’s cross correlation function (SCCF). The findings revealed that the GARCH model with a skewed Student’s t distribution effectively captured conditional temporal volatility and asymptotic behavior in the precipitation series. The model’s sensitivity enabled the incorporation of temporal fluctuations related to droughts and extreme meteorological events. The Bhalme and Mooley Drought Index (BMDI-6) and Z-Score Index (ZSI-6) were the most applicable indices for drought monitoring. Spearman’s cross-correlation analysis revealed that meteorological droughts influenced agricultural droughts with a time lag of up to 4 months.

\papertype Original Article The 2024 North Atlantic (hereafter Atlantic) hurricane season started quickly, with the earliest Category 5 on record (Beryl) and three hurricanes forming through 14 August. Following Ernesto’s dissipation on 20 August, the Atlantic hurricane season became extremely quiet during the climatological peak of hurricane season, with only one Category 2 hurricane (Francine) and one tropical storm through 23 September. Several environmental factors likely contributed to this unexpected, prolonged lull. During mid-to-late August, subseasonal conditions were broadly favorable for Atlantic hurricanes, but a northward shift in African easterly wave emergence latitude yielded fewer TC seed disturbances that traversed unfavorably cool ocean water. During early-to-mid September, subseasonal variability driven by the Madden-Julian oscillation was less conducive to hurricane activity, with several bouts of increased vertical wind shear across the central Atlantic. Throughout most of the lull, the tropical Atlantic was anomalously dry and subsident, suppressing hurricane formation chances.

The literature shows that communities under different socio-economic conditions suffer different levels of damage in disasters. In addition to the physical intensity of hazards, such differences are also related to the varying abilities of communities to prepare for and respond to disasters. This study analyzes the spatial patterns of building damage in Hurricane Ian in 2022 and investigates the socio-economic disparities related to the damage. Specifically, this study employs NASA’s Damage Proxy Map (DPM2) to analyze spatial patterns of building damage caused by the hurricane. Then, it uses statistical analysis to assess the relationships between building damage and hurricane intensity, building conditions, and socio-economic variables at the building and census tract levels. Furthermore, the study applies geographically weighted regression (GWR) to examine the spatial variation of the damage factors. The results provide valuable insights into the potential factors related to building damage and the spatial variation in the factors. The results also reveal the uneven distribution of building damage among different population groups, implying socio-economic inequalities in disaster adaptation and resilience. Moreover, the study provides actionable information for policymakers, emergency responders, and community leaders in formulating strategies to mitigate the impact of future hurricanes by identifying vulnerable communities and population groups.

Since the onset of the COVID-19 pandemic, decision-making during disasters fundamentally changed to accommodate the combined risks of hurricanes and infectious diseases. Prior research conducted in 2020 by Collins et al. examined how individuals changed their intended evacuation decision-making during the pandemic or their actual evacuation decisions during Hurricanes Laura and Sally. Hurricane Ida provided further data on evacuation decision-making when vaccinations and masks were widely available. A digital survey was disseminated to individuals affected by Hurricane Ida in 2021. Respondents provided information about their actual evacuation choices and perceptions of public shelters and COVID-19 risks. In comparison with the 2020 hurricane season, more individuals have reduced negative perceptions of hurricane shelters. However, individuals were less likely to utilize public shelters than in the 2020 season, with 11.4% more individuals stating they would definitely or probably avoid using shelters in 2021. Fewer individuals identified that COVID-19 was a primary reason they chose to stay home during Hurricane Ida (19.5% as compared with 86.8% during Hurricanes Laura and Sally). Furthermore, respondents with health risks for severe COVID-19 symptoms were no more likely to evacuate than those respondents who had no health risks. Potentially, as the pandemic progressed and vaccine availability and COVID-19 management improved, COVID-19 has had less impact on evacuation decision-making. The results from this work should guide planners in emergency management and public health in future hurricane seasons and future pandemics or other outbreaks to anticipate behavior changes and properly manage infectious disease threats.