Phasing and climate forcing potential of the Millennium Eruption of Mt. Baekdu.

The Millennium Eruption of Mt. Baekdu, one of the largest volcanic eruptions in the Common Era, initiated in late 946. It remains uncertain whether its two main compositional phases, rhyolite and trachyte, were expelled in a single eruption or in two. Investigations based on proximal and medial ash have not resolved this question, prompting us to turn to high-resolution ice-core evidence. Here, we report a suite of glaciochemical and tephra analyses of a Greenlandic ice core, identifying the transition from rhyolitic to trachytic tephra with corresponding spikes in insoluble particle fallout. By modeling annual snow accumulation, we estimate an interval of one to two months between these spikes, which approximates the hiatus between two eruptive phases. Additionally, negligible sulfur mass-independent fractionation, near-synchroneity between particle and sulfate deposition, and peak sulfur fallout in winter all indicate an ephemeral aerosol veil. These factors limited the climate forcing potential of the Millennium Eruption.

Fast and full characterization of large earthquakes from prompt elastogravity signals.

Prompt ElastoGravity Signals are light-speed gravity-induced signals recorded before the arrival of seismic waves. They have raised interest for early warning applications but their weak amplitudes close to the background seismic noise have questioned their actual potential for operational use. A deep-learning model has recently demonstrated its ability to mitigate this noise limitation and to provide in near real-time the earthquake magnitude (M w ). However, this approach was efficient only for large earthquakes (M w ≥ 8.3) of known focal mechanism. Here we show unprecedented performance in full earthquake characterization using the dense broadband seismic network deployed in Alaska and Western Canada. Our deep-learning model provides accurate magnitude and focal mechanism estimates of M w ≥ 7.8 earthquakes, 2 minutes after origin time (hence the tsunamigenic potential). Our results represent a major step towards the routine use of prompt elastogravity signals in operational warning systems, and demonstrate its potential for tsunami warning in densely-instrumented areas.

Assessing social equity of federal disaster aid distribution: A nationwide analysis.

In this study, we conduct the first comprehensive, nationwide assessment of social equity performance of multiple federal post- and pre-disaster assistance programs that differ in targeted recipients, project types, forms of aid, and funding requirements. We draw on the social equity and distributive justice theory to develop and test a set of hypotheses on the influence of program design and specificity on their aid distributional patterns and equity performance. The analysis uses panel data of about 3000 US counties to examine the relationship between a county's receipt of federal assistance and its recent disaster damage, socioeconomic, demographic, political, local government, and geographic characteristics in a two-stage random effects Tobit model. Expectedly, we find that post-disaster grants are largely driven by recent disaster damage, while damage is simultaneously influenced by local socioeconomic conditions. For all disaster programs, disproportionately more federal aid is allocated to populous counties. For programs geared toward state and local governments and targeting community recovery and mitigation, more aid is received by counties with better socioeconomic conditions. Conversely, for programs targeting individual relief and recovery, more aid is given to counties with lower incomes and greater social vulnerability. Results also indicate that counties located in high-risk regions receive greater outlays. These findings shed light on the varying degrees of social equity of federal disaster assistance programs tied to their cost-share requirement, funding caps, and inherent complexity of application procedures.

Users' Perspective on Revised Simple Simulator for Calculating Nutritional Food Stocks in Preparation for Large-scale Disasters.

OBJECTIVE: In 2020, Japan's Ministry of Health, Labour and Welfare developed an Excel workbook entitled "Simple Simulator for calculating nutritional food stocks in preparation for large-scale disasters." In September 2021, it was modified as the "Revised Simulator" to plan food stockpiles in normal times and post-disaster meals. This study aimed to further improve the Revised Simulator. METHODS: Eight group interviews were conducted with 12 public health dietitians, 9 disaster management officers, and 2 public health nurses from September to November 2021. They provided nutritional support during previous disasters or prepared for predicted future disasters. Qualitative analysis was conducted on interview transcriptions, then the Revised Simulator was improved based on their feedback. RESULTS: The Revised Simulator was improved to the "Simulator for calculating nutritional food stocks and meals for large-scale disasters" with significant changes such as adding specific tags in the food list to denote long shelf life and elderly-friendly foods, as well as displaying bar graphs to visualize the required and supplied amounts of energy and nutrients. CONCLUSIONS: The Revised Simulator was upgraded for planning and assessing stockpiles and meals in ordinary conditions and emergencies. This study will contribute to enhancing the quality and quantity of food supplies during disasters.

Spatial variability in Arctic-boreal fire regimes influenced by environmental and human factors.

Wildfire activity in Arctic and boreal regions is rapidly increasing, with severe consequences for climate and human health. Regional long-term variations in fire frequency and intensity characterize fire regimes. The spatial variability in Arctic-boreal fire regimes and their environmental and anthropogenic drivers, however, remain poorly understood. Here we present a fire tracking system to map the sub-daily evolution of all circumpolar Arctic-boreal fires between 2012 and 2023 using 375 m Visible Infrared Imaging Radiometer Suite active fire detections and the resulting dataset of the ignition time, location, size, duration, spread and intensity of individual fires. We use this dataset to classify the Arctic-boreal biomes into seven distinct 'pyroregions' with unique climatic and geographic environments. We find that these pyroregions exhibit varying responses to environmental drivers, with boreal North America, eastern Siberia and northern tundra regions showing the highest sensitivity to climate and lightning density. In addition, anthropogenic factors play an important role in influencing fire number and size, interacting with other factors. Understanding the spatial variability of fire regimes and its interconnected drivers in the Arctic-boreal domain is important for improving future predictions of fire activity and identifying areas at risk for extreme events.

Increasing extreme precipitation variability plays a key role in future record-shattering event probability.

Climate events that break records by large margins are a threat to society and ecosystems. Climate change is expected to increase the probability of such events, but quantifying these probabilities is challenging due to natural variability and limited data availability, especially for observations and very rare extremes. Here we estimate the probability of precipitation events that shatter records by a margin of at least one pre-industrial standard deviation. Using large ensemble climate simulations and extreme value theory, we determine empirical and analytical record shattering probabilities and find they are in high agreement. We show that, particularly in high emission scenarios, models project much higher record-shattering precipitation probabilities in a changing relative to a stationary climate by the end of the century for almost all the global land, with the strongest increases in vulnerable regions in the tropics. We demonstrate that increasing variability is an essential driver of near-term increases in record-shattering precipitation probability, and present a framework that quantifies the influence of combined trends in mean and variability on record-shattering behaviour in extreme precipitation. Probability estimates of record-shattering precipitation events in a warming world are crucial to inform risk assessment and adaptation policies.

The development of resilience research in critical infrastructure systems: A bibliometric perspective.

Critical infrastructure systems (CISs) are the cornerstone of modern cities. Substantial economic losses and social impacts are caused once natural disasters or man-made disruptions attack the CISs. As a "resilient city" has become an essential theme of communities' sustainable development, research on resilience and its practice in industries boost the CISs' capacity to respond and adapt to changing environments. From the Web of Science (WOS) Core Collection, this study screened 1,247 scientific articles related to resilience in CISs and conducted a bibliometric analysis to investigate the evolution and future potential in this field. Topic visualized networks were constructed for CIS resilience using CiteSpace, a dedicated tool for visualizing and analyzing trends and patterns in scientific literature. The results demonstrate collaborative research networks among countries, institutions, main scholar/group networks, and leading journals publishing CIS resilience work. This study also explained how the research interest evolved over the last 20 years and found the current frontiers pointing to "power systems resilience" and "supply chain resilience." The reasons were discussed subsequently from the perspectives of the influence that natural hazards (based on the EM-DAT data) and government policies have upon CISs' resilience work.

Methodology and data for quantifying storm erosion potential considering sea level rise.

This dataset quantifies storm intensity of approximately 130 unique historical storms along the New Jersey coastline from 1980 to 2014 for three separate sea level conditions. Namely, (1) as observed in the historical record; (2) detrended to 1997 mean sea level and (3) adjusted to the 2050 and 2100 sea level rise scenarios presented in the International Panel on Climate Change's (IPCC) Sixth Assessment Report (AR6). Projected sea level scenarios are adjusted to include local vertical land movement. Storm intensity is quantified in terms of erosion potential, considering the combination of total water level, wave heights, and storm duration. The observational dataset includes both tropical and extratropical storms and quantifies both the cumulative (duration) and peak (single hour) storm intensity for each storm and sea level rise (SLR) condition. Additionally, hourly time series of wave characteristics and water levels are provided at 13 locations along the New Jersey coast, facilitating hydrodynamic forcing of nearshore models. The dataset provides the means and methods to directly compare historical storms under future SLR conditions.

Breaking Rossby waves drive extreme precipitation in the world's arid regions.

More than a third of the world's population lives in drylands and is disproportionately at risk from hydrometeorological hazards such as drought and flooding. While weather systems governing precipitation formation in humid regions have been widely explored, our understanding of the atmospheric processes generating precipitation in arid regions remains fragmented at best. Here we show, using a variety of precipitation datasets, that Rossby wave breaking is a key atmospheric driver of precipitation in arid regions worldwide. Rossby wave breaking contributes up to 90% of daily precipitation extremes and up to 80% of total precipitation amounts in arid regions equatorward and downstream of the midlatitude storm tracks. The relevance of Rossby wave breaking for precipitation increases with increasing land aridity. Contributions of wave breaking to precipitation dominate in the poleward and westward portions of arid subtropical regions during the cool season. Our findings imply that Rossby wave breaking plays a crucial role in projections and uncertainties of future precipitation changes in societally vulnerable regions that are exposed to both freshwater shortages and flood hazards.

Residential natural hazard risk and mental health effects.

Mental health effects are frequently reported following natural disasters. However, little is known about effects of living in a hazard-prone region on mental health. We analyzed data from 9,312 Gulf Long-term Follow-up Study participants who completed standardized mental health questionnaires including the Patient Health Questionnaire-9 (depression=score≥10), Generalized Anxiety Disorder Questionnaire-7 (anxiety=score≥10), and Primary Care PTSD Screen (PTSD=score≥3). Geocoded residential addresses were linked to census-tract level natural hazard risk scores estimated using the National Risk Index (NRI). We considered an overall risk score representing 18 natural hazards, and individual scores for hurricanes, heatwaves, coastal flooding and riverine flooding. Log binomial regression estimated prevalence ratios (PR) and 95% confidence intervals (CI) for associations between risk scores (quartiles) and mental health outcomes. Increasing hurricane and coastal flooding scores were associated with all mental health outcomes in a suggestive exposure-response manner. Associations were strongest for PTSD, with PRs for the highest vs. lowest quartile of hurricane and coastal flooding risks of 2.29(1.74-3.01) and 1.59(1.23-2.05), respectively. High heatwave risk was associated with anxiety (PR=1.25(1.12-1.38)) and depression (PR=1.19(1.04-1.36)) and suggestively with PTSD (PR=1.20(0.94-1.52)). Results suggest that living in areas prone to natural disasters is one factor associated with poor mental health status.

Explosive eruption style modulates volcanic electrification signals.

Volcanic lightning detection has proven useful to volcano monitoring by providing information on eruption onset, source parameters, and ash cloud directions. However, little is known about the influence of changing eruptive styles on the generation of charge and electrical discharges inside the eruption column. The 2021 Tajogaite eruption (La Palma, Canary Islands) provided the rare opportunity to monitor variations in electrical activity continuously over several weeks using an electrostatic lightning detector. Here we show that throughout the eruption, silicate particle charging is the main electrification mechanism. Moreover, we find that the type of electrical activity is closely linked to the explosive eruption style. Fluctuations in the electrical discharge rates are likely controlled by variations in the mass eruption rate and/or changes in the eruption style. These findings hold promise for obtaining near real-time information on the dynamic evolution of explosive volcanic activity through electrostatic monitoring in the future.

Preferences for index-based crop insurance in South Africa.

The main reason cited for the low participation rate in indexed insurance in Africa is the lack of farmers' involvement in the initial conception. The main aim of this article was, therefore, to design an improved participatory methodology that would help farmers in South Africa gather information on the value they place in new crop insurance initiatives based on weather indices. The main objective of this study was to determine their willingness to pay (WTP) crop insurance in the Eastern Cape. The study adopted a cross-sectional design, and the respondents were selected by using a probability sampling procedure. A sample of 150 respondents was selected. The results from descriptive statistics showed that 62% of the smallholder irrigation scheme farmers were between 52 and above years of age, male and female: 87% and 13%, respectively. The results from the probit model revealed that out of nine variables included in the model, only four namely, logAge square, gender, marital status and age were significantly influencing the WTP index-based crop insurance at 1%, 5% and 10%, respectively. However, age was found to reduce the chances of participating in crop-based insurance. A large proportion of those who were willing to pay insurance had not previously experienced losses because of natural hazards. Therefore, it recommended that the government should use existing extension officers to educate the farmers and promote the importance and benefits of insurance products. Contribution: The results are expected to contribute to the local government to improve disaster resilience through strengthening regional financial funding.

Quantifying the resistance of mixed-forests against natural hazards in the Pyrenees.

Mountain protection forests can prevent natural hazards by reducing their onset and propagation probabilities. In fact, individual trees act as natural barriers against hydrogeomorphic events. However, assessing the structural strength of trees against these hazards is challenging, especially in a context of climate change due to the intensification of extreme events and changes in forest dynamics. Here, we focus on the mechanical analyses of two of the most common tree species across the Pyrenees (Abies alba Mill. and Fagus sylvatica L.) growing in two different areas (Spain and France), and affected by recurrent snow avalanche and rockfall events. We first performed 53 pulling test on mature trees, where the root-plate stiffness and the modulus of elasticity of the stems were evaluated. To further analyse the impact of forest management and climate on protective forests, we yielded information on tree growth using dendroecology techniques. Then, we assessed structure and neighbourhood characteristics for each target tree to account for the surrounding forest structure. Finally, using linear and structured equation models we tested if the mechanical capacity of the trees is determined either by functional traits (e.g. species, tree growth, diameter and height) or forest structural traits (e.g. tree density, tree structure and slenderness) or both. Our results suggest that the forest neighbourhood influences tree mechanical capacity through two pathways, including both functional and structural traits. The individual stiffness parameter of trees is influenced by their functional traits, while their structural traits are more closely related with changes in the modulus of elasticity. Both species exhibit varying levels of dominance in different locations, which is related to their resilience to the diverse natural hazards they confront. Our findings provide relevant insights to anticipating management strategies for forests that serve as a protective barrier against natural hazards in the context of a changing climate.

Mapping the natural disturbance risk to protective forests across the European Alps.

Mountain forests play an essential role in protecting people and infrastructure from natural hazards. However, forests are currently experiencing an increasing rate of natural disturbances (including windthrows, bark beetle outbreaks and forest fires) that may jeopardize their capacity to provide this ecosystem service in the future. Here, we mapped the risk to forests' protective service across the European Alps by integrating the risk components of hazard (in this case, the probability of a disturbance occurring), exposure (the proportion of forests that protect people or infrastructure), and vulnerability (the probability that the forests lose their protective structure after a disturbance). We combined satellite-based data on forest disturbances from 1986 to 2020 with data on key forest structural characteristics (cover and height) from spaceborne lidar (GEDI), and used ensemble models to predict disturbance probabilities and post-disturbance forest structure based on topographic and climatic predictors. Wind and bark beetles are dominant natural disturbance agents in the Alps, with a mean annual probability of occurrence of 0.05%, while forest fires were less likely (mean annual probability <0.01%), except in the south-western Alps. After a disturbance, over 40% of forests maintained their protective structure, highlighting the important role of residual living or dead trees. Within 30 years after wind and bark beetle disturbance, 61% of forests were likely to either maintain or recover their protective structure. Vulnerability to fires was higher, with 51% of forest still lacking sufficient protective structure 30 years after fire. Fire vulnerability was especially pronounced at dry sites, which also had a high fire hazard. Combining hazard and vulnerability with the exposure of protective forests we identified 186 Alpine municipalities with a high risk to protective forests due to wind and bark beetles, and 117 with a high fire risk. Mapping the disturbance risk to ecosystem services can help identify priority areas for increasing preparedness and managing forests towards lower susceptibility under an intensifying disturbance regime.

Severity influences categorical likelihood communications: A case study with Southeast Asian weather forecasters.

Risk assessments are common in multiple domains, from finance to medicine. They require evaluating an event's potential severity and likelihood. We investigate the possible dependence of likelihood and severity within the domain of impact-based weather forecasting (IBF), following predictions derived from considering asymmetric loss functions. In a collaboration between UK psychologists and partners from four meteorological organisations in Southeast Asia, we conducted two studies (N = 363) eliciting weather warnings from forecasters. Forecasters provided warnings denoting higher likelihoods for high severity impacts than low severity impacts, despite these impacts being described as having the same explicit numerical likelihood of occurrence. This 'Severity effect' is pervasive, and we find it can have a continued influence even for an updated forecast. It is additionally observed when translating warnings made on a risk matrix to numerical probabilities.

A Community Mental Health Integrated Disaster Preparedness Intervention for Bushfire Recovery in Rural Australian Communities: Protocol for a Multimethods Feasibility and Acceptability Pilot Study.

BACKGROUND: Natural hazards are increasing in frequency and intensity due to climate change. Many of these natural disasters cannot be prevented; what may be reduced is the extent of the risk and negative impact on people and property. Research indicates that the 2019-2020 bushfires in Australia (also known as the "Black Summer Bushfires") resulted in significant psychological distress among Australians both directly and indirectly exposed to the fires. Previous intervention research suggests that communities impacted by natural hazards (eg, earthquakes, hurricanes, and floods) can benefit from interventions that integrate mental health and social support components within disaster preparedness frameworks. Research suggests that disaster-affected communities often prefer the support of community leaders, local services, and preexisting relationships over external supports, highlighting that community-based interventions, where knowledge stays within the local community, are highly beneficial. The Community-Based Disaster Mental Health Intervention (CBDMHI) is an evidence-based approach that aims to increase disaster preparedness, resilience, social cohesion, and social support (disaster-related help-seeking), and decrease mental health symptoms, such as depression and anxiety. OBJECTIVE: This research aims to gain insight into rural Australian's recovery needs post natural hazards, and to enhance community resilience in advance of future fires. Specifically, this research aims to adapt the CBDMHI for the rural Australian context and for bushfires and second, to assess the acceptability and feasibility of the adapted CBDMHI in a rural Australian community. METHODS: Phase 1 consists of qualitative interviews (individual or dyads) with members of the target bushfire-affected rural community. Analysis of these data will include identifying themes related to disaster preparedness, social cohesion, and mental health, which will inform the adaptation. An initial consultation phase is a key component of the adaptation process and, therefore, phase 2 will involve additional discussion with key stakeholders and members of the community to further guide adaptation of the CBDMHI to specific community needs, building on phase 1 inputs. Phase 3 includes identifying and training local community leaders in the adapted intervention. Following this, leaders will co-deliver the intervention. The acceptability and feasibility of the adapted CBDMHI within the community will be evaluated by questionnaires and semistructured interviews. Effectiveness will be evaluated by quantifying psychological distress, resilience, community cohesion, psychological preparedness, and help-seeking intentions. RESULTS: This study has received institutional review board approval and commenced phase 1 recruitment in October 2022. CONCLUSIONS: The study will identify if the adapted CBDMHI is viable and acceptable within a village in the Northern Tablelands of New South Wales, Australia. These findings will inform future scale-up in the broader rural Australian context. If this intervention is well received, the CBDMHI may be valuable for future disaster recovery and preparedness efforts in rural Australia. These findings may inform future scale-up in the broader rural Australian context. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/53454.

Development of Community-Level Capacity of Resilience to Natural Hazards for Environmental- and Social-Justice-Challenged Communities: 1. Approach, Concepts, and Assessment of Existing Information.

Impoverished and under-served communities are often exposed to the worst environmental and climate hazards. Identifying these communities and building their resilience capacity to withstand such hazards is a vital justice aspect of environmental management. Building community resilience requires five activities: (1) examination of existing information, (2) community engagement and assessment of local knowledge, (3) development of reasonable strategies to build resilience, (4) implementation and these strategies, and (5) monitoring and transability of the process. This manuscript examines the first component of this process. The attributes of multiple parishes in Louisiana are examined using available data and existing models of human well-being, community resilience, and environmental/climate/socioeconomic justice. These existing models and tools were used to determine parish-level resilience to natural hazards including flooding, hurricanes, and other potential natural climatic hazards in central Louisiana (U.S.). Through consultation with state officials and local community groups, candidate environmental justice (EJ) and social justice (SJ) communities were selected to develop resilience capacity enhancement plans to address potential adverse parish and community outcomes of natural hazard events. Of the available parishes, St. Helena Parish was selected as an entity that would significantly benefit from resilience capacity building. The remaining two activities, community engagement and strategy development, will be examined in sister manuscripts. Continuing studies, to be described elsewhere, will describe community engagement and the determination of strategies, implementation plans, and the monitoring of the success of these strategic implementations.

Effects of damage initiation points of depth-damage function on flood risk assessment.

The flood depth in a structure is a key factor in flood loss models, influencing the estimation of building and contents losses, as well as overall flood risk. Recent studies have emphasized the importance of determining the damage initiation point (DIP) of depth-damage functions, where the flood damage is assumed to initiate with respect to the first-floor height of the building. Here we investigate the effects of DIP selection on the flood risk assessment of buildings located in Special Flood Hazard Areas. We characterize flood using the Gumbel extreme value distribution's location (µ) and scale (α) parameters. Results reveal that average annual flood loss (AAL) values do not depend on µ, but instead follow an exponential decay pattern with α when damage initiates below the first-floor height of a building (i.e., negative DIP). A linear increasing pattern of the AAL with α is achieved by changing the DIP to the first-floor height (i.e., DIP = 0). The study also demonstrates that negative DIPs have larger associated AAL, thus contributing substantially to the overall AAL, compared to positive DIPs. The study underscores the significance of proper DIP selection in flood risk assessment.

Time-dependent probabilistic tsunami risk assessment: application to Tofino, British Columbia, Canada, subjected to Cascadia subduction earthquakes.

A new time-dependent probabilistic tsunami risk model is developed to facilitate the long-term risk management strategies for coastal communities. The model incorporates the time-dependency of earthquake occurrence and considers numerous heterogeneous slip distributions via a stochastic source modeling approach. Tidal level effects are examined by considering different baseline sea levels. The model is applied to Tofino, British Columbia, Canada within the Cascadia subduction zone. High-resolution topography and high-quality exposure data are utilized to accurately evaluate tsunami damage and economic loss to buildings. The results are tsunami loss curves accounting for different elapsed times since the last major event. The evolutionary aspects of Tofino's time-dependent tsunami risk profiles show that the current tsunami risk is lower than the tsunami risk based on the conventional time-independent Poisson occurrence model. In contrast, the future tsunami risk in 2100 will exceed the time-independent tsunami risk estimate.

[Heat and heavy rain prevention measures in daycare centres and care facilities: an evaluation of risk perception, communication and information materials]. / Maßnahmen zur Hitze- und Starkregenvorsorge in Kitas und Pflegeeinrichtungen: Eine Evaluation von Risikowahrnehmung, Kommunikation und Informationsmaterialien.

BACKGROUND AND AIM: Heat and heavy rain can have negative health impacts for people in Germany. Vulnerable groups in particular, such as children and the elderly, are at increased risk and require special precautions. This paper examines how employers of the municipal administration and facilitating organisations perceive the risk of heat and heavy rain for daycare centres and care facilities, and to what extent an exchange takes place between the municipal level and the facilities. In addition, specially developed information materials with recommendations for action for adapting to heat and heavy rain that are aimed at such facilities were evaluated. METHODS: In the summer of 2021, we conducted a quantitative survey. A total of 333 respondents from municipal administrations, facilitating organisations and institutions participated. Descriptive analyses and ANOVAs were conducted. RESULTS: Risk perception and adaptation knowledge concerning heat was perceived higher than concerning heavy rain. The intention to support institutions in finding measures for adaptation was also higher with regard to heat. The majority of interviewees from municipal administrations and institutions communicated with institutions through various channels on different topics including the natural hazards mentioned. The information material was evaluated positively. DISCUSSION: This article shows that facilities are seen as very affected by heat waves. Awareness towards heavy rainfall needs to be raised. The feedback on the information material clearly shows a high need in this area.