Unprecedented Event Research Articles

Migration and evolutionary analysis of trends in the transformation of maritime education in wartime conditions

The research focuses on analyzing fundamental changes in Ukraine's higher education system occurring under the influence of unprecedented geopolitical events and demographic shifts, with particular emphasis on the maritime education sector. The study examines the period of 2020-2023, characterized by large-scale challenges caused by Russian military aggression and its consequences for the educational sector. Based on the analysis of institutional reports and statistical data, significant changes have been identified in student contingent dynamics, redistribution of educational flows, and transformation of educational practices. The research results demonstrate that despite considerable adaptability and successful implementation of European educational standards, Ukraine's higher education system has faced serious challenges related to forced youth migration and demographic decline. This problem is particularly acute in the maritime education sector, where there is a persistent trend toward decreasing numbers of students. The paper substantiates the necessity of systematic state measures for developing maritime education in Ukraine. The research reveals the complex interaction between demographic trends, educational transformation, and sectoral development under wartime conditions.

A Constantly Updated Flood Hazard Assessment Tool Using Satellite-Based High-Resolution Land Cover Dataset Within Google Earth Engine

This work aims to develop a constantly updated flood hazard assessment tool that utilizes readily available datasets derived by remote sensing techniques. It is based on the recently released global land use/land cover (LULC) dataset Dynamic World, which is readily available, covering the period from 2015 until now, as an open data source within the Google Earth Engine (GEE) platform. The tool is updated constantly following the release rate of Sentinel-2 images, i.e., every 2 to 5 days depending on the location, and provides a near-real-time detection of flooded areas. Specifically, it identifies how many times each 10 m pixel is characterized as flooded for a selected time period. To investigate the fruitfulness of the proposed tool, we provide two different applications; the first one in the Thrace region, where the flood hazard map computed with the presented herein approach was compared against the flood hazard maps developed in the frames of the EU Directive 2007/60, and we found several inconsistencies between the two approaches. The second application focuses on the Thessaly region, aiming to assess the impacts of a specific, unprecedented storm event that affected the study area in September 2023. Moreover, a new economic metric is proposed, named maximum potential economic loss, to assess the socioeconomic implications of the flooding. The innovative character of the presented methodology consists of the use of remotely sensed-based datasets, becoming available at increasing rates, for developing an operational instrument that defines and updates the flood hazard zones in real-time as required.

Anthropogenic effects on flood hazards in a hyper‐arid watershed: The 2015 Atacama floods

AbstractAn unprecedented precipitation event in the hyper‐arid Atacama Desert of Northern Chile occurred in March 2015. Geomorphic alterations to the river channel and the coastal zone, coupled with the exceptional magnitude of the rainfall, caused catastrophic damage and loss of life. On the coast of the El Salado watershed, legacy mine tailings infilled the watershed‐ocean connection, while the river channel was altered both by tailings and urbanization. The consequences of this event resulted from the coupling of anthropogenic geomorphic changes with an unusual climate event. Lack of field data, complex geomorphology and sediment loads influenced by human activity make analysing floods in these regions especially challenging. The objective of this work is to improve our understanding of the factors that control flood hazards by using numerical simulations to reconstruct the 2015 flood in El Salado. We carry out unsteady two‐dimensional simulations fully coupled with the sediment concentration to identify the influence of tailing deposits, considering high‐resolution data of the pre‐ and post‐2015 flood topography. The results highlight the importance of specific event‐based studies, using models that can help designing better strategies for climate change adaptation and risk mitigation, while providing information for risk reduction and channel restoration.

Resilience and Loss During the Iron-Swords War: The Importance of Coping Strategies

The unprecedented events on October 7th in Israel, characterized by little actual and perceived control over the sources of the stress, have affected virtually every household in Israel, either due to the economic and social consequences of the ensuing war or experiencing the loss of relatives and friends. The current study examined the association between traumatic loss of close friends/relatives and resilience during the initial stages of the Iron-Swords war and explored the moderating role of coping strategies for this link. Data were collected from 286 participants (age range 19-82) who completed online scales assessing loss, resilience, and coping strategies during the first weeks of the Iron-Swords war. Results demonstrated a negative association between emotion-focused coping and resilience, as well as a positive association between problem-focused coping and resilience. Moreover, coping strategies moderated the loss-resilience link, which was significant only for individuals reporting low levels of both problem-focused and emotion-focused coping. Our findings support the claim that relying on at least one dominant coping strategy (i.e., problem-focused coping/emotional-focused coping/both) is efficient to reserve resilience levels at times of adversity. The findings of the current study, based on data collected in the first weeks of the Iron-Swords war, highlight the value of different coping styles in preserving individual resilience as a protective factor against stress during adversity.

Where is the Dust Source of 2023 Several Severe Dust Events in China?

Abstract Northern China was hit by 13 unprecedented mega dust events in spring 2023. However, a comprehensive understanding of the relative contributions of potential dust sources to dust concentrations in China remains elusive, threatening air quality, damaging ecosystems, and further complicating dust forecasting and warning efforts. The impact of five major Asian dust sources on China and its downstream regions has been accurately quantified using the Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem). Notably, dust particles originating from Mongolia play a crucial role in downstream air pollution. Approximately 56% (82.7 μg m−3) of the dust in North China originated from Mongolia, while Mongolia contributed nearly 51% (15.9 μg m−3) of the dust in the Korean Peninsula and surroundings. In southwest China, the prevalence of dust was predominantly attributable to sources within Inner Mongolia, China (46%). Due to geographical constraints, dust in the Tibetan Plateau mainly originated from dust sources in Xinjiang, China. Topographic blocking by the Tibetan Plateau and limitations on local dust emissions are further unfavorable to the long-distance transport of dust from South Asia to downstream regions. We also highlight the importance of variation in surface soil parameters in driving frequent dust events in spring 2023. Our findings emphasize the urgent need for collaborative research and policymaking to effectively address international dust disaster mitigation.

Challenges posed by climate hazards to cardiovascular health and cardiac intensive care: implications for mitigation and adaptation.

Global warming, driven by increased greenhouse gas emissions, has led to unprecedented extreme weather events, contributing to higher morbidity and mortality rates from a variety of health conditions, including cardiovascular disease (CVD). The disruption of multiple planetary boundaries has increased the probability of connected, cascading, and catastrophic disasters with magnified health impacts on vulnerable populations. While the impact of climate change can be manifold, non-optimal air temperatures (NOTs) pose significant health risks from cardiovascular events. Vulnerable populations, especially those with pre-existing CVD, face increased risks of acute cardiovascular events during NOT. Factors such as age, socio-economic status, minority populations, and environmental conditions (especially air pollution) amplify these risks. With rising global surface temperatures, the frequency and intensity of heatwaves and cold spells are expected to increase, emphasizing the need to address their health impacts. The World Health Organization recommends implementing heat-health action plans, which include early warning systems, public education on recognizing heat-related symptoms, and guidelines for adjusting medications during heatwaves. Additionally, intensive care units must be prepared to handle increased patient loads and the specific challenges posed by extreme heat. Comprehensive and proactive adaptation and mitigation strategies with health as a primary consideration and measures to enhance resilience are essential to protect vulnerable populations and reduce the health burden associated with NOTs. The current educational review will explore the impact on cardiovascular events, future health projections, pathophysiology, drug interactions, and intensive care challenges and recommend actions for effective patient care.

‘Slim pickings?’: Extreme large recruitment events may induce density-dependent reductions in growth for Alaska sablefish (Anoplopoma fimbria) with implications for stock assessment

Growth processes mediate survival and fecundity within fish populations, which are fundamental in regulating population dynamics. Therefore, accurate estimates of population scale and sustainable exploitation levels in contemporary fishery stock assessment models rely heavily on understanding and accurately characterizing growth processes. However, empirical studies that relate population-level changes in growth patterns to observable ecosystem and population conditions remain scarce. In particular, few studies directly consider the influence of intra-specific competition (i.e., cohort effects) on growth variability, and its associated implications for stock assessment estimates. Focusing on Alaska sablefish as a case study, we illustrate how multiple unprecedented large recruitment events since 2014 resulted in density-dependent declines in growth on the population-level scale, using a state-space growth model. Furthermore, we demonstrate how incorporating cohort-specific growth variability within the Alaska sablefish stock assessment model resulted in substantial differences in estimates of spawning biomass and recommended harvest levels. Overall, results from this study underscore the significance of cohort effects on growth processes and their implications for stock assessment models and associated harvest recommendations.

Behaviour Change Techniques: An Application to Increase Employees' Willingness to Accept a Salary Reduction.

During the COVID-19 pandemic, many organisations worldwide asked their employees to accept a temporary salary reduction to manage the financial consequences of the unprecedented event. In this paper, we use a CEO's salary reduction announcement to all employees and investigate whether a behaviour change intervention using five selected Behaviour Change Techniques (BCTs) increases expat employees' overall willingness to accept a temporary salary reduction. We use mixed qualitative and quantitative methods, including survey and experiment, to test our hypotheses and frame our results. The results show that, while the direction of impact was positive, respondents were overall not significantly more likely to accept a temporary salary reduction. However, a significant effect was found for the individual BCT 'Modelling'. Participants were significantly more likely to accept a pay cut if they knew their senior management took a larger cut than asked of participants. The outcomes of this study suggest that the availability of a financial buffer and the strength of the employer-employee relationship play a, possibly more important, role in employees' willingness to accept a pay reduction. In addition, leadership matters as this study shows that people are more willing to accept a salary reduction when senior management leads the way.

The Attribution of February Extremes over North America: A Forecast-Based Storyline Study

Abstract The importance of extreme event attribution rises as climate change causes severe damage to populations resulting from unprecedented events. In February 2019, a planetary wave shifted along the U.S.–Canadian border, simultaneously leading to troughing with anomalous cold events and ridging over Alaska and northern Canada with abnormal warm events. Also, a dry-stabilized anticyclonic circulation over low latitudes induced warm extreme events over Mexico and Florida. Most attribution studies compare the climate model simulations under natural or actual forcing conditions and assess probabilistically from a climatological point of view. However, in this study, we use multiple ensembles from an operational forecast model, promising statistical as well as dynamically constrained attribution assessment, often referred to as the storyline approach to extreme event attribution. In the globally averaged results, increasing CO2 concentrations lead to distinct warming signals at the surface, resulting mainly from diabatic heating. Our study finds that CO2-induced warming eventually affects the possibility of extreme events in North America, quantifying the impact of anthropogenic forcing over less than a week’s forecast simulation. Our study assesses the validity of the storyline approach conditional on the forecast lead times, which is hindered by rising noise in CO2 signals and the declining performance of the forecast model. The forecast-based storyline approach is valid for at least half of the land area within a 6-day lead time before the target extreme occurrence. Our attribution results highlight the importance of achieving net-zero emissions ahead of schedule to reduce the occurrence of severe heatwaves.

Modeling Across Scales of Heavy Precipitation With a Global Variable‐Resolution Model: A Case Study of a Catastrophic Event in China

AbstractAn unprecedented heavy rainfall event in China (“21.7” extreme rainfall event) was simulated using the global variable‐resolution model (MPAS‐Atmosphere) across the scales (4, 8, 16 and 50 km). Although almost all experiments at different resolutions reproduce the spatiotemporal characteristics of precipitation, the simulated precipitation intensity from high to low is 16, 8, 50, and 4 km, with the 16 km simulation being closest to the observations. Precipitation magnitude is prominently influenced by the difference in simulated large‐scale circulation across a range of grid spacings. Further analysis revealed that the differences in latent heating across scales affect the geopotential height and wind field by altering temperature. The latent heating in 4 km simulation is the minimum while the 16 km simulation is maximum. More latent heating release leads to the low‐level pressure depression, amplifies the water vapor flux convergence, produces stronger upward motion and more clouds, and ultimately results in stronger precipitation. The sensitivity experiments for turning off latent heating tendencies during the event showed that the latent heat release has positive feedback on the “21.7” heavy rainfall event. This study highlights the importance of scale‐awareness of latent heat at different resolutions and suggests that the difference in simulated latent heat release during the event is the main reason for simulated different atmospheric circulation and precipitation across scales.

Internal Variability Dominated the Extreme Cold Wave Over North America in December 2022

AbstractIn December 2022, North America experienced an unprecedented extreme cold event. However, the underlying physical mechanisms of this cold wave, and the extent to which it is driven by internal variability or external forcing, are not fully understood. Using ERA5 reanalysis data and the HadGEM3‐A‐N216 attribution simulations, we identified internal variability as the main cause, contributing −5.14 K to surface air temperature (SAT) anomalies in North America. External forcing slightly mitigated the cold by 0.42 K. An internally generated wave train from the North Pacific, influenced in combination by Pacific‐North American (PNA) and North Pacific Oscillation (NPO) teleconnection patterns, initiated this intense cyclonic event, contributing −2.18 K and −2.12 K to SAT anomalies, respectively. La Niña‐like sea surface temperature anomalies amplified this wave train and resultant cold wave. Additionally, excessive snow cover in the previous November also intensified the December cold anomalies by enhancing surface albedo and reducing solar radiation.

The Failure of Silicon Valley Bank: A Test of Market Efficiency

The unexpected collapse of Silicon Valley Bank (SVB) on March 10, 2023, sent shockwaves through the tech industry. SVB, a long-standing financial institution serving tech startups for nearly four decades, suddenly shifted from solvency to insolvency within 48 hours, marking the second-largest bank failure in U.S. history. This event provides an excellent opportunity to test the Efficient Market Hypothesis (EMH), particularly its semi-strong form, which posits that rapid information absorption prevents significant stock price gains in response to new information. This research uses the standard event study methodology in the finance literature to investigate SVB’s collapse and its impact on the stock prices of 30 banks traded on the New York Stock Exchange. The study aims to discern whether stock returns exhibited reactions prior to, on, or after the public announcement of SVB’s failure, thereby assessing market efficiency. Using historical stock and S&P 500 index data, the study analyzes holding period returns, performs regression analyses for pre-event periods, and calculates average excess returns. Results indicate statistically significant negative impacts on stock prices surrounding and on the event date. Furthermore, consistent with behavioral finance theory, a decline in adjusted stock prices approximately 7 days before the event suggests anticipatory market behavior, in line with semi-strong market efficiency. SVB’s case emphasizes the role of external factors, regulatory changes, and industry concentrations in shaping market responses. This research contributes empirical evidence to the discourse on market efficiency, highlighting the need for a nuanced understanding of market behaviors during crises. Lessons from SVB’s collapse will inform regulatory and risk management strategies, impacting future discussions on market efficiency. Likewise, the study results support the semi-strong form efficient market hypothesis and suggest the possibility of trading on this information up to 7 days prior to the announcement consistent with the behavioral finance literature (Bacon & Howell 2021). This study provides valuable insights into market dynamics during unprecedented events, influencing future discussions on regulation, risk management, and market efficiency.

Influences of wildfire on the soil dissolved organic matter characteristics and its electron-donating capacity

Global increases in the intensity and frequency of wildfires are driving major changes in soil organic matter (SOM) characteristics, including soil dissolved organic matter (DOM). As the most crucial component of SOM, soil DOM plays a pivotal role in the carbon cycle and regulates the environmental fate of contaminants through its versatile reactivities, including electron-donating capacity (EDC). However, it is still being determined how wildfire influences key characteristics of soil DOM and subsequent effects on EDC in forest soils. Thus, we conducted our study to fill this gap with the forest soils of Jinyun Mountain Nature Reserve of China, which experienced an unprecedented wildfire event in 2022. The results from optical characterization, high-performance size-exclusion chromatography (HPSEC), and Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) showed decreasing molecular weight but elevating nitrogen-containing molecular formulas of soil DOM in the burned soils. This could be attributed to the Maillard reaction and microbial re-colonies. Additionally, wildfires increased the condensed aromatics and lignin components in soil DOM. In the burned soils, we observed increasing EDC of soil DOM, which accounts for an increase in lignin-derived phenolic components. Overall, the findings of this study demonstrate that eco-disturbances, such as wildfires, induce alterations in the properties of DOM, leading to variations in its reactivity and potentially influencing the fate of environmental pollutants beyond carbon dynamics alone. Thus, incorporating the dynamic properties of soil DOM, particularly in the context of climate change, can enhance the assessment of risks associated with contaminants in soil and water, providing valuable insights.

Biological, Psychological, Social, and Spiritual Domains of Teachers in a Philippine University

Countries worldwide have experienced an unprecedented event that changed the educational systems and suddenly forced our teachers to adopt online classes. This greatly affected our teacher's mental health. This study aimed to determine the harmony of the biological, psychological, social, and spiritual domains and also looked into the challenges encountered among university teachers during the COVID-19 pandemic. The findings served as bases for the intervention plan. The data were treated using frequency, rank, simple percentage, mean, standard deviation, rank, Chi-square test of independence, and ANOVA. Results showed teachers have poor health habits in the physical domain. In the area of the psychological domain, it showed that teachers experienced severe depression. Results of the spiritual domain suggest that teachers lack spiritual enrichment. In addition, the teachers in the social domain have warm relationships. The biological domain of teachers reveals a meaningful relationship with gender. Also, teachers' civil status is related to the social domain. Results also show that teachers can cope with resourcefulness, adjusting one's mindset and patience. Results show that teachers have biological conditions, severe psychological depression, warm social relationships with people around them, and less spiritual life after the COVID-19 pandemic. Therefore, it is recommended that an intervention plan be implemented, monitored, and evaluated to improve their living conditions while doing their job as facilitators of learning.

Examining human mobility changes during COVID-19 across socioeconomic groups: a comparative analysis of San Diego County and New York City

The COVID-19 pandemic brought unprecedented changes to various aspects of daily life, profoundly affecting human mobility. These changes in mobility patterns were not uniform, as numerous factors, including public health measures, socioeconomic status, and urban infrastructure, influenced them. This study examines human mobility changes during COVID-19 in San Diego County and New York City, employing Latent Profile Analysis (LPA) and various network measures to analyze connectivity and socioeconomic status (SES) within these regions. While many COVID-19 and mobility studies have revealed overall reductions in mobility or changes in mobility patterns, they often fail to specify ’where’ these changes occur and lack a detailed understanding of the relationship between SES and mobility changes. This creates a significant research gap in understanding the spatial and socioeconomic dimensions of mobility changes during the pandemic. This study aims to address this gap by providing a comprehensive analysis of how mobility patterns varied across different socioeconomic groups during the pandemic. By comparing mobility patterns before and during the pandemic, we aim to shed light on how this unprecedented event impacted different communities. Our research contributes to the literature by employing network science to examine COVID-19’s impact on human mobility, integrating SES variables into the analysis of mobility networks. This approach provides a detailed understanding of how social and economic factors influence movement patterns and urban connectivity, highlighting disparities in mobility and access across different socioeconomic groups. The results identify areas functioning as hubs or bridges and illustrate how these roles changed during COVID-19, revealing existing societal inequalities. Specifically, we observed that urban parks and rural areas with national parks became significant mobility hubs during the pandemic, while affluent areas with high educational attainment saw a decline in centrality measures, indicating a shift in urban mobility dynamics and exacerbating pre-existing socioeconomic disparities.

Changing dynamics of Western European summertime cut‐off lows: A case study of the July 2021 flood event

AbstractIn July 2021, a cut‐off low‐pressure system brought extreme precipitation to Western Europe. Record daily rainfall totals led to flooding that caused loss of life and substantial damage to infrastructure. Climate change can amplify rainfall extremes via thermodynamic processes, but the role of dynamical changes is uncertain. We assess how the dynamics involved in this particular event are changing using flow analogues. Using past and present periods in reanalyses and large ensemble climate model data of the present‐day climate and 2°C warmer climate, we find that the best flow analogues become more similar to the cut‐off low‐pressure system observed over Western Europe in 2021. This may imply that extreme rain events will occur more frequently in the future. Moreover, the magnitude of the analogue lows has deepened, and the associated air masses contain more precipitable water. Simulations of future climate show similar events of the future could lead to intense rainfall further east than in the current climate, due to a shift of the pattern. Such unprecedented events can have large consequences for society, we need to mitigate and adapt to reduce future impacts.

Development of a stochastic rainfall generator to yield unprecedented rainfall events

Unprecedented rainfall events are defined as rainfall events that have extremely high magnitude with low probability of occurrence. Although such events have occurred in the recent past, there might be no historical record of unprecedented rainfall. While significant efforts have been made to understand the major drivers of unprecedented events, the use of statistical modelling to estimate the likelihood of unprecedented events has gained little to no attention. The current study proposes a ‘serial’ type stochastic rainfall generator (SRG) to simulate daily rainfall with an additional focus on unprecedented events. The study introduces resampling of model parameters to yield the non-stationarity in simulated rainfall distribution. The proposed approach is applied to simulate daily rainfall over twenty-six grid points in Southeast Texas, which experienced Hurricane Harvey in 2017. Towards this, the study obtains rainfall accumulation data during Harvey from eight weather stations during. We found that the proposed approach can successfully generate unprecedented events if two power law tail tuning parameters are adjusted with respect to future warming levels. Rainfall magnitudes correspond to 50, 100, 250 and 500-year return periods simulated by the proposed model are found to be substantially higher than historical (i.e., observed) return period. Furthermore, the study found that the estimated return periods of Hurricane Harvey like rainfall is almost the same as the return period estimated by a former study of Emmanuel (2017). The potential benefit of the proposed approach in hydrological risk assessment has also been discussed.

Anatomy of the 2022 Scorching Summer in the Yangtze River Basin Using the SINTEX‐F2 Seasonal Prediction System

AbstractIn July and August 2022, the Yangtze River basin (YRB) experienced its hottest summer since 1961. The SINTEX‐F2 seasonal prediction system initialized in early May predicted the hotter‐than‐normal summer due to its successful prediction of central Pacific La Niña, negative Indian Ocean Dipole and the resultant warming in the tropical West Pacific‐East Indian Ocean (TWP_EIO). The common SST forcing explains only about 26% to the heatwave strength, while the internal variations in the anomalous warming in the TWP_EIO and Europe, surplus precipitation in Pakistan, and local land‐air interaction account for approximately 65%, based on the analysis of 108 ensemble members. These factors have collectively increased the maximum temperature over the YRB through the enhancement and westward expansion of western North Pacific subtropical high. Our findings quantify the relative contributions of external forcing and internal variations to the unprecedented hot event, offering insights into its forming mechanism and potential predictability.

Potential reduction of CO2 emissions which is the cause of greenhouse gases during COVID-19

Background: The implementation of education in tertiary institutions contributes significantly to greenhouse gas emissions, particularly carbon dioxide (CO2), which causes the greenhouse effect and global warming. The Intergovernmental Panel on Climate Change (IPCC) identifies transportation, energy supply, and industry as the primary sectors driving CO2 emissions over the past 30 years. However, the COVID-19 pandemic unexpectedly reduced CO2 emissions globally by up to 70% due to restricted activities. In 2020, the pandemic led countries, including Indonesia, to enforce Large-Scale Social Restrictions (PSBB) to curb virus spread, which significantly limited community mobility and vehicle use. Climate change, driven by greenhouse gas emissions, is a critical development challenge for Indonesia. Method: The study uses various calculation methods from journals and websites, incorporating expert opinions and the IPCC's method, to analyze emission reductions. Findings: The findings indicate that the COVID-19 pandemic and associated lockdowns reduced CO2 emissions due to decreased fuel consumption and mobility. Conclusion: This period highlights opportunities for strategies like low-carbon development to continue reducing emissions from vehicles. Novelty/Originality of this Study: This study provides a novel contribution by quantitatively assessing CO2 emission reductions during the COVID-19 lockdown, emphasizing the unique context of an unprecedented global event. It conducts a comprehensive literature review to integrate various CO2 calculation methods, particularly highlighting the sophisticated IPCC method, and offers a comparative analysis of emission reduction techniques.

How Do Climate Model Resolution and Atmospheric Moisture Affect the Simulation of Unprecedented Extreme Events Like the 2021 Western North American Heat Wave?

AbstractAlthough the 2021 Western North America (WNA) heat wave was predicted by weather forecast models, questions remain about whether such strong events can be simulated by global climate models (GCMs) at different model resolutions. Here, we analyze sets of GCM simulations including historical and future periods to check for the occurrence of similar events. High‐ and low‐resolution simulations both encounter challenges in reproducing events as extreme as the observed one, particularly under the present climate. Relatively stronger amplitudes are observed during the future periods. Furthermore, high‐ and low‐resolution short initialized GCM simulations are both able to reasonably predict such strong events and their associated high‐pressure ridge over the WNA with a 1 week forecast lead time. Moisture sensitivity experiments further indicate a drier atmospheric moisture condition results in substantially higher near‐surface temperatures in the simulated heat events.