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Climate communication scientists search for effective message strategies to engage the ambivalent public in support of climate advocacy. The personal experience of wildfire is expected to render climate change impacts more concretely, pointing to a potential message strategy to engage the public. This study examined Twitter discourse related to climate change during the onset of 20 wildfires in California between the years 2017 and 2021. In this mixed method study, we analyzed tweets geographically and temporally proximal to the occurrence of wildfires to discover framings and examined how frequencies in climate framings changed before and after fires. Results identified three predominant climate framings: linking wildfire to climate change, suggesting climate actions, and attributing climate change to adversities besides wildfires. Mean tweet frequencies linking wildfire to climate change and attributing adversities increased significantly after the onset of fire. While suggesting climate action tweets also increased, the increase was not statistically significant. Temporal analysis of tweet frequencies for the three themes of tweets showed that discussion increased after the onset of a fire but persisted typically no more than 2 weeks. For fires that burned for longer periods of more than a month, external events triggered climate discussions. Our findings contribute to identifying how the personal experience of wildfire shapes Twitter discussion related to climate change, and how these framings change over time during wildfire events, leading to insights into critical time points after wildfire for implementing message strategies to increase public engagement on climate change impacts and policy.

This study examines the relationship between extreme weather conditions and the S&P500 return index, representing the U.S. stock market. The literature review and analysis show extreme weather events can impact the S&P500 return index. This effect is observed in two ways. First, extreme weather events create a market anomaly in the U.S. stock market, indicating that prices move in a way that cannot be explained by a rational model. Second, extreme weather events create financial uncertainty and have a negative impact on firms' future cash flows. These findings suggest that investors and financial markets should be more cautious about extreme weather events. In addition, the impact of extreme weather on the U.S. stock market is weak. This can be explained in two ways. First, extreme weather events are predictable and seasonally recurring. Second, the American stock market is close to the efficient market hypothesis. [ABSTRACT FROM AUTHOR]

The aim of this study is to assess future hazards due to extreme meteorological events in the Wielkopolska region, Poland, based on five climate model projections and three scenarios: SSP126, 370, and 585. The paper analyzes the changes of mean and extreme precipitation, mean and extreme temperatures, and humidity index, as well as changes in difference between maximum temperatures observed from day to day and changes in difference between mean atmospheric pressure at the sea level observed from day to day. Additionally, we look at possible future occurrence of wildfires due to changes in fire weather conditions. Based on climate model projections, future hazard due to extreme meteorological events in Wielkopolska region is to be more serious and will be most noticeable in the end of twenty-first century and for two higher scenarios: SSP370 and SSP585. For near future, 2021–2050, projected conditions of meteorological extremes for analyzed scenarios are quite consistent. Therefore, there is a strong need for implementing adaptation actions. Nevertheless, such activities are so far lacking, and several adaptation options are not present in local and national legislation, even though they are recognized as effective. [ABSTRACT FROM AUTHOR]

Land cover change due to rapid urbanization and industrialization has been known to increase the land surface temperature around the world. For this reason, examining the variation of land surface temperatures and mitigating the related impacts remain a challenge. The changing land cover pattern in urban areas also affects the quality of life in urban areas by altering its environment, deteriorating air quality and increasing the frequency of extreme climatic events like high-intensity rainfall, drought, and development of urban heat islands conditions. Düzce, located in the Western Black Sea Region, where urbanization and industrialization have been expanding rapidly in Türkiye since 2000s, was selected as the study area. In the study area, natural disasters with hydrometeorological character have occurred frequently in recent years. Düzce is climate change sensitive and ecologically vulnerable areas. For this purpose, temporal and spatial changes in the land surface temperature were determined by Land Surface Temperature and Normalized Difference Vegetation Index Analysis with Landsat 7 ETM + in 2000 and Landsat 9 OLI in 2022. Landsat 7 ETM + in 2000 and Sentinel-2 in 2022 were analysed for land cover with object-based classification. Daily temperature and precipitation data were used for climatological analysis. Statistical data were used for population growth and hydrometeorological disaster. According to the results, settlement areas expanded, and an average temperature increase was observed in 2022 compared with 2000. The areas where land surface temperature values increase are determined as settlement areas, industrial and agricultural areas. [ABSTRACT FROM AUTHOR]

Objective: Over the last five decades, extreme weather events (EWEs) have made a substantial contribution to the overall climate change impacts in India. Intergovernmental Panel on Climate Change (IPCC) has predicted that India will experience an increase in extreme weather events in the future. The primary aim of the study was to gain insights into India's overall occurrence of EWEs between 1970 and 2019 across different states. Methods: In the present study, data from the Indian Meteorological Department (IMD) spanning the last five decades (1970–2019) was examined to understand how specific EWEs have changed in India over varying regions and time spans. The analysis involved descriptive statistics using heatmaps, and trend analysis using the Mann- Kendall test. Findings: In the past 50 years (1970–2019), around 11,158 EWEs occurred in India. EM-DAT data shows a rise from 4 + events in the 1950s to 20 + in 2018, while IMD data indicates an increase from 50 + events in the 1970s to 400 + in 2019. The event-wise trend analysis of 50 years of data on EWEs in India revealed a consistent increase in the incidence of each EWE. The Mann–Kendall test, conducted to detect trends in EWEs over 50 years revealed a significant upward trend at 1% level for total EWEs, including heat waves, floods, heavy rains, and thunderstorms. Heat map and spatial analysis revealed that significant regions for heat waves include Maharashtra, Odisha, West Bengal, Uttar Pradesh, Rajasthan, and Uttarakhand. Cold waves have increased in Uttar Pradesh, Uttarakhand, Rajasthan, Bihar, and Jharkhand. Floods, heavy rains, thunderstorms, and lightning are common in Maharashtra, West Bengal, Kerala, Assam, and Karnataka. Conclusion: The findings of the study have critical implications for climate resilience strategies and disaster management in India. The increasing frequency and geographical concentration of EWEs call for region-specific preparedness and mitigation plans. By knowing the trends of EWEs and hotspot states through retrospective data records, the Government can proactively plan for future adverse events to prioritize high-risk areas, implementing targeted preparedness and mitigation strategies to prevent significant mortality and morbidity. [ABSTRACT FROM AUTHOR]

Across the globe, mobile species are key components of ecosystems. Migratory birds and nomadic antelope can have considerable conservation, economic or societal value, while irruptive insects can be major pests and threaten food security. Extreme weather events, which are increasing in frequency and intensity under ongoing climate change, are driving rapid and unforeseen shifts in mobile species distributions. This challenges their management, potentially leading to population declines, or exacerbating the adverse impacts of pests. Near‐term, within‐year forecasting may have the potential to anticipate mobile species distribution changes during extreme weather events, thus informing adaptive management strategies. Here, for the first time, we assess the robustness of near‐term forecasting of the distribution of a terrestrial species under extreme weather. For this, we generated near‐term (2 weeks to 7 months ahead) distribution forecasts for a crop pest that is a threat to food security in southern Africa, the red‐billed quelea Quelea quelea. To assess performance, we generated hindcasts of the species distribution across 13 years (2004–2016) that encompassed two major droughts. We show that, using dynamic species distribution models (D‐SDMs), environmental suitability for quelea can be accurately forecast with seasonal lead times (up to 7 months ahead), at high resolution, and across a large spatial scale, including in extreme drought conditions. D‐SDM predictive accuracy and near‐term hindcast reliability were primarily driven by the availability of training data rather than overarching weather conditions. We discuss how a forecasting system could be used to inform adaptive management of mobile species and mitigate impacts of extreme weather, including by anticipating sites and times for transient management and proactively mobilising resources for prepared responses. Our results suggest that such techniques could be widely applied to inform more resilient, adaptive management of mobile species worldwide. [ABSTRACT FROM AUTHOR]

Aim: As global climate changes, there is a clear mismatch between the temporal and spatial characteristics of body temperature and environmental temperature, confounding the assessment of thermal stress for organisms in many ecological studies. Here, we hindcast the hourly body temperatures of intertidal molluscs to explore the differences between them and environmental temperatures (air and water temperatures) in multiple metrics of thermal stress. Location: Intertidal shores in East Asia (0°–45°N, 100°E–140°E). Time Period: 40 years, 1980 to 2019. Major Taxa Studied: Mollusca. Methods: We collected habitat zonation data and measured the morphological characteristics of 25 intertidal molluscs living in East Asia. For three different types of intertidal molluscs (i.e., bivalves, limpets and snails), we built corresponding heat budget models (HBMs) to hindcast the hourly body temperatures from 1980 to 2019. We analysed the thermal stress of intertidal species faced in three metrics, annual extreme high temperatures (T99), seasonal daily maximum temperatures (DMT) and heatwaves, and compared them with environmental temperatures. Results: We found that T99 of body temperatures and their interannual warming rates are significantly higher than those of environmental temperatures. Moreover, there were non‐negligible mismatches between the seasonal thermal pattern and heatwaves of body temperatures and environmental temperatures, suggesting that the deleterious impacts of global warming on intertidal species are underestimated and cannot be directly revealed by environmental temperatures. Main Conclusions: Thermal stress patterns of body temperature were significantly different from those of environmental temperature, and the thermal stress faced by intertidal species had been persistently underestimated. These results emphasise that body temperature should be used as the appropriate metric for evaluating and predicting the impacts of global warming and weather extremes in the intertidal biological system. [ABSTRACT FROM AUTHOR]

Reliable performance of the electricity distribution networks is critical to avoid outages and disruptions which may lead to substantial economic losses. Some of the important components of the electricity distribution networks include overhead cables, utility poles, cross-arms, substations, and transformers. These components are subjected to deterioration with aging and pose risks of failure creating safety concerns, specially under extreme weather conditions. Efficient maintenance and the use of accurate condition assessment techniques to monitor the integrity of the aforementioned components are key factors to be considered in managing the electricity distribution assets. This article presents a review of different condition assessment techniques employed for monitoring the electricity distribution infrastructure. The conventional inspection techniques and advancements in non-destructive testing methods are discussed outlining the relative advantages and disadvantages. Other than the normal failures of distribution infrastructure due to component ageing, unexpected and less frequent extreme weather events can have significant impacts on the resilience of the electrical power infrastructure. Thus, the effects of extreme weather conditions on the reliability of the electricity distribution networks and the failure rates of assets are reviewed in this study. Further, the maintenance and decision-making approaches implemented in the power distribution networks are also discussed. [ABSTRACT FROM AUTHOR]

Considering the projected impacts of climate change in upcoming decades, innovative educational approaches should encourage inventive problem-solving techniques and societal change, fostering transformative climate adaptation. The value of drama in climate adaptation education remains a novel area in the environmental education research literature and requires further exploration of its potential benefits to Climate Change Education (CCE). This article presents a proposal for CCE to include various elements in a drama workshop by evaluating a methodological framework. Participants in the workshop studied the vulnerabilities that arose from flooding and droughts while dramatizing different social conflicts to develop building adaptation scenarios. Through the exploration of problems via playful activities, participants collaboratively construct narratives and texts rich with meaning, based on a critical and creative perception of themes, needs, desires, and overlapping ideologies. This short-term experience manifests efficacy in elucidating the underpinnings of social systems structures, human values, and motivations. This article analyzes workshop results, providing a pedagogical structure and theoretical foundation, contributing to a better comprehension of drama in education and the creation of capacities towards CCE. [ABSTRACT FROM AUTHOR]

Grain filling is a critical process for improving crop production under adverse conditions caused by climate change. Here, using a quantitative method, we quantified post-anthesis source–sink relationships of a large dataset to assess the contribution of remobilized pre-anthesis assimilates to grain growth for both biomass and nitrogen. The dataset came from 13 years of semi-controlled field experimentation, in which six bread wheat genotypes were grown at plot scale under contrasting temperature, water, and nitrogen regimes. On average, grain biomass was ~10% higher than post-anthesis above-ground biomass accumulation across regimes and genotypes. Overall, the estimated relative contribution (%) of remobilized assimilates to grain biomass became increasingly significant with increasing stress intensity, ranging from virtually nil to 100%. This percentage was altered more by water and nitrogen regimes than by temperature, indicating the greater impact of water or nitrogen regimes relative to high temperatures under our experimental conditions. Relationships between grain nitrogen demand and post-anthesis nitrogen uptake were generally insensitive to environmental conditions, as there was always significant remobilization of nitrogen from vegetative organs, which helped to stabilize the amount of grain nitrogen. Moreover, variations in the relative contribution of remobilized assimilates with environmental variables were genotype dependent. Our analysis provides an overall picture of post-anthesis source–sink relationships and pre-anthesis assimilate contributions to grain filling across (non-)environmental factors, and highlights that designing wheat adaptation to climate change should account for complex multifactor interactions. [ABSTRACT FROM AUTHOR]

This study advances the precision and efficiency of precipitation nowcasting, particularly under extreme weather conditions. Traditional forecasting methods struggle with precision, spatial feature generalization, and recognizing long-range spatial correlations, challenges that intensify during extreme weather events. The Enhanced Temporal Correlation Jump Prediction Network (ETCJ-PredNet) introduces a novel attention mechanism that optimally leverages spatiotemporal data correlations. This model scrutinizes and encodes information from previous frames, enhancing predictions of high-intensity radar echoes. Additionally, ETCJ-PredNet addresses the issue of gradient vanishing through an innovative jump connection strategy. Comparative experiments on the Moving Modified National Institute of Standards and Technology (Moving-MNIST) and Hong Kong Observatory Dataset Number 7 (HKO-7) validate that ETCJ-PredNet outperforms existing models, particularly under extreme precipitation conditions. Detailed evaluations using Critical Success Index (CSI), Heidke Skill Score (HSS), Probability of Detection (POD), and False Alarm Ratio (FAR) across various rainfall intensities further underscore its superior predictive capabilities, especially as rainfall intensity exceeds 30 dbz,40 dbz, and 50 dbz. These results confirm ETCJ-PredNet's robustness and utility in real-time extreme weather forecasting. [ABSTRACT FROM AUTHOR]

The accuracy of ERA5 reanalysis datasets and their applicability in the coastal area of Bohai Bay are crucial for weather forecasting and environmental protection research. However, synthesis evaluation of ERA5 in this region remains lacking. In this study, using a tropospheric wind profile radar (CFL-06L) placed in coastal Huanghua city, the deviations of ERA5 reanalysis data are assessed from the ground to an altitude of 5 km. The results indicate that the wind speed of ERA5 reanalysis data exhibits good consistency from the surface to the tropospheric level of about 5 km, with R2 values ranging from 0.5 to 0.85. The lowest mean wind speed error, less than 3 m/s, occurs in the middle layer, while larger errors are observed at the surface and upper layers. Specifically, at 150 m, the R2 is as low as 0.5, with numerous outliers around 5000 m. Seasonal analysis shows that the ERA5 wind field performs best in summer and worst in autumn and winter, especially at lower levels affected by circulation systems, high stratus clouds, and aerosols, with errors reaching up to 10 m/s. Further analysis of extreme weather events, such as heavy rain; hot, dry winds; and snowstorms, reveals that the effects of sea-land winds and strong convective systems significantly impact the observation of wind profiles and the assimilation of reanalysis data, particularly under the constrain of boundary layer height. Additionally, we also find that the transition of sea-land breeze is capable of triggering the nighttime low-level jet, thereby downward transporting the aloft ozone to the ground and resulting in an abnormal increase in the surface ozone concentration. The study provides a scientific basis for improving meteorological forecasting, optimizing wind energy resource utilization, and formulating environmental protection policies, highlighting its significant scientific and practical application value. [ABSTRACT FROM AUTHOR]

The Sundarbans is the world's largest contiguous mangrove forest with an area of about 10,000 square kilometers and shared between Bangladesh and India. This world-renowned mangrove forest, located on the lower Ganges floodplain and facing the Bay of Bengal, has long served as a crucial barrier, shielding southern coastal Bangladesh from cyclone hazards. However, the Sundarbans mangrove ecosystem is now increasingly threatened by climate-induced hazards, particularly tropical cyclones originating from the Indian Ocean. To assess the cyclone vulnerability of this unique ecosystem, using geospatial techniques, we analyzed the damage caused by past cyclones and the subsequent recovery across three salinity zones, i.e., Oligohaline, Mesohaline, and Polyhaline. Our study also examined the relationship between cyclone intensity with the extent of damage and forest recovery. The findings of our study indicate that the Polyhaline zone, the largest in terms of area and with the lowest elevation, suffered the most significant damage from cyclones in the Sundarbans region, likely due to its proximity to the most cyclone paths. A correlation analysis revealed that cyclone damage positively correlated with wind speed and negatively correlated with the distance of landfall from the center of the Sundarbans. With the expectation of more extreme weather events in the near future, the Sundarbans mangrove forest faces a potentially devastating outlook unless both natural protection processes and human interventions are undertaken to safeguard this critical ecosystem. [ABSTRACT FROM AUTHOR]

This paper analyzes the theoretical foundation and practical implications of recognizing the right to a stable climate as a fundamental human right. Further, it examines the intersection of human rights, right to climate, and the intensification of extreme climate events. Through a bibliometric analysis, the study highlights the increase in scholarly attention paid to this nexus. The intensification of extreme climate events, such as the Cumbre Vieja volcano in Spain, is also analyzed as a catalyst for recognizing the right to climate as a human right, as a fundamental requirement for its enactment. Indeed, it is argued that this recognition is necessary to achieve climate justice. These thoughts about the necessity of recognizing the right to climate as a human right are also based on a similar case, the enactment of the rights to water and sanitation, which is presented as a case study, demonstrating how specific environmental rights can be integrated into human rights discourse. The results and discussion section synthesizes these findings, highlighting the imperative of recognizing climate rights to ensure justice and sustainability amidst escalating climate challenges. [ABSTRACT FROM AUTHOR]

With the increasing frequency of extreme weather events, heavy rainfall and flooding pose significant pressure on the flood discharge systems of tailings dams. Simple discharge systems are insufficient to meet the flood discharge requirements of tailings dams, while complex discharge systems, with their greater flood discharge capacity, are gradually being promoted. Although complex discharge systems can increase the flood discharge capacity of tailings dams, the flow patterns within the discharge systems become more complex. As a new type of discharge system layout, existing research lacks systematic analysis, and its complex flow characteristics are not clear. This paper relies on the flood discharge system of a large tailings dam to carry out theoretical calculations and derivations of the hydraulic characteristics of the complex flood discharge system. Hydraulic characteristics are observed through hydraulic model tests and verified using numerical simulations. Based on these three methods, a basis for further research on the hydraulic characteristics of complex flood discharge systems is provided. The main results are as follows: (1) The formulas for calculating the discharge flow rate Q under different flow states in the tailings dam design manual are not applicable to complex discharge systems; (2) Formulas for calculating the discharge flow rate Q under different flow states in complex discharge systems are proposed; by comparing model test values and numerical simulation values, the accuracy of the formulas for calculating the discharge flow rate Q in complex discharge systems is verified; (3) If the traditional mode is used to calculate the discharge flow rate Q in complex discharge systems, it is recommended to take the reduction coefficient as 0.55–0.56, and the model test values should also be referred to during flow state transitions.

This study examines the relationship between extreme weather conditions and the S&P500 return index, representing the U.S. stock market. The literature review and analysis show extreme weather events can impact the S&P500 return index. This effect is observed in two ways. First, extreme weather events create a market anomaly in the U.S. stock market, indicating that prices move in a way that cannot be explained by a rational model. Second, extreme weather events create financial uncertainty and have a negative impact on firms’ future cash flows. These findings suggest that investors and financial markets should be more cautious about extreme weather events. In addition, the impact of extreme weather on the U.S. stock market is weak. This can be explained in two ways. First, extreme weather events are predictable and seasonally recurring. Second, the American stock market is close to the efficient market hypothesis.

Abstract Background Extreme weather events affect health by directly and indirectly increasing illness burdens and changing healthcare usage patterns. These effects can be especially severe in rural and remote areas, exacerbating existing health disparities, and necessitating urgent mitigation or adaptation strategies. Despite increased research on health and climate change, studies focusing on rural and remote populations remain limited. This study aimed to review the relationships among extreme weather events, healthcare utilization, and health outcomes in rural and remote populations, identify research gaps, and inform policy development for adaptation and disaster management in these settings. Methods A systematic scoping review was registered and conducted following the PRISMA-ScR guidelines. The search databases included PubMed, Web of Science, Scopus, the Cochrane Library, ProQuest, and the WHO IRIS. The included studies were primary research, focused on rural or remote areas, and investigated the effects of extreme weather events on either health outcomes or healthcare utilization. There were no methodological, date or language restrictions. We excluded protocols, reviews, letters, editorials, and commentaries. Two reviewers screened and extracted all data, other reviewers were invited to resolve conflicts. Findings are presented numerically or narratively as appropriate. Results The review included 135 studies from 31 countries, with most from high-income countries. Extreme weather events exacerbate communicable and noncommunicable diseases, including cardiorespiratory, mental health, and malnutrition, and lead to secondary impacts such as mass migration and increased poverty. Healthcare utilization patterns changed during these events, with increased demand for emergency services but reduced access to routine care due to disrupted services and financial constraints. Conclusions The results highlighted the essential role of community and social support in rural and remote areas during extreme weather events and the importance of primary healthcare services in disaster management. Future research should focus on developing and implementing effective mitigation and adaptation programs tailored to the unique challenges faced by these populations.

Abstract Background The impact of weather on human health has been proven, but the impact of extreme weather events on cardiometabolic multimorbidity (CMM) needs to be urgently explored. Objectives Investigating the impact of extreme temperature, relative humidity (RH), and laboratory testing parameters at admission on adverse events in CMM hospitalizations. Designs Time-stratified case-crossover design. Methods A distributional lag nonlinear model with a time-stratified case-crossover design was used to explore the nonlinear lagged association between environmental factors and CMM. Subsequently, unbalanced data were processed by 1:2 propensity score matching (PSM) and conditional logistic regression was employed to analyze the association between laboratory indicators and unplanned readmissions for CMM. Finally, the previously identified environmental factors and relevant laboratory indicators were incorporated into different machine learning models to predict the risk of unplanned readmission for CMM. Results There are nonlinear associations and hysteresis effects between temperature, RH and hospital admissions for a variety of CMM. In addition, the risk of admission is higher under low temperature and high RH conditions with the addition of particulate matter (PM, PM2.5 and PM10) and O3_8h. The risk is greater for females and adults aged 65 and older. Compared with first quartile (Q1), the fourth quartile (Q4) had a higher association between serum calcium (HR = 1.3632, 95% CI: 1.0732 ~ 1.7334), serum creatinine (HR = 1.7987, 95% CI: 1.3528 ~ 2.3958), fasting plasma glucose (HR = 1.2579, 95% CI: 1.0839 ~ 1.4770), aspartate aminotransferase/ alanine aminotransferase ratio (HR = 2.3131, 95% CI: 1.9844 ~ 2.6418), alanine aminotransferase (HR = 1.7687, 95% CI: 1.2388 ~ 2.2986), and gamma-glutamyltransferase (HR = 1.4951, 95% CI: 1.2551 ~ 1.7351) were independently and positively associated with unplanned readmission for CMM. However, serum total bilirubin and High-Density Lipoprotein (HDL) showed negative correlations. After incorporating environmental factors and their lagged terms, eXtreme Gradient Boosting (XGBoost) demonstrated a more prominent predictive performance for unplanned readmission of CMM patients, with an average area under the receiver operating characteristic curve (AUC) of 0.767 (95% CI:0.7486 ~ 0.7854). Conclusions Extreme cold or wet weather is linked to worsened adverse health effects in female patients with CMM and in individuals aged 65 years and older. Moreover, meteorologic factors and environmental pollutants may elevate the likelihood of unplanned readmissions for CMM.

There is an ongoing debate on the relationship between accelerated warming in the Arctic and extreme weather patterns in mid-latitudes. As extreme weather events have dramatic socioeconomic costs, it is important to investigate the possibility of the increased risk of such events in mid-latitudes. We investigated changes in the frequency of extreme weather events in Eastern Europe and Western to Central Asia (30–60 ∘ N, 20–75 ∘ E) in the post-Arctic amplification (2002–2022) compared to the pre-Arctic amplification (1979–1999) period. We analyzed the daily detrended near-surface temperature and precipitation of the ERA5 data. There is no robust evidence for the contribution of Arctic amplification to changes in extreme precipitation in Eastern Europe and Western to Central Asia. Most regions of the study area have experienced a decrease in annual precipitation in the post-Arctic amplification period. We also identified an increase in consecutive dry days in most parts of Central Asia by approximately 16 days per year, which could be attributed to a warmer climate because dry areas generally become drier in a warmer climate. Greater warming of the Earth in the more recent period has been associated with a significant increase in both warm days and nights and a significant decrease in cold days and nights over Eastern Europe and Western to Central Asia. Depending on the season, we identified both intensification and weakening of the upper tropospheric jet stream in the post-Arctic amplification period. The jet stream is intensified from the eastern Black Sea toward northern Kazakhstan and southeastern Russia in spring. In contrast, it has significantly weakened in the northern Mediterranean Sea and western Kazakhstan in summer and the Caspian Sea and Caucasus in autumn. Our results have important implications for a better understanding of the potential impact of rapid Arctic warming on extreme weather events in mid-latitudes. [ABSTRACT FROM AUTHOR]

Previous research has shown a link between extreme weather events and people's beliefs about climate change and their pro-environmental behaviour. This indicates that people may become more environmentally friendly amid increasing extreme weather events. Still, the influence of experiencing extreme weather events on actual behaviour has rarely been tested with large-scale individual-level data and longitudinal methods. This study links panel data from 35,678 individuals to floods across England and heatwaves across the UK and applies within-person estimators to account for pre-existing differences between affected and unaffected individuals. Results reveal that individuals are more likely to believe in climate change after being affected by a geographically proximate flood or a temporally proximate heatwave. This association is stronger among initially right-leaning partisans and those initially more sceptic about the existence of climate change, thereby indicating attitudinal updating due to experiential learning. However, those exposed to extreme weather events do not change their environmental behaviour such as energy saving, sustainable shopping or mode of transportation. Even among those who are more likely to believe in climate change, people's behaviour does not react to extreme weather events. [ABSTRACT FROM AUTHOR]

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Climate change, a pressing global concern, poses significant challenges to agricultural systems worldwide. Among the myriad impacts of climate change, the cultivation of kiwifruit trees (Actinidia spp.) faces multifaceted challenges. In this review, we delve into the intricate effects of climate change on kiwifruit production, which span phenological shifts, distributional changes, physiological responses, and ecological interactions. Understanding these complexities is crucial for devising effective adaptation and mitigation strategies to safeguard kiwifruit production amidst climate variability. This review scrutinizes the influence of rising global temperatures, altered precipitation patterns, and a heightened frequency of extreme weather events on the regions where kiwifruits are cultivated. Additionally, it delves into the ramifications of changing climatic conditions on kiwifruit tree physiology, phenology, and susceptibility to pests and diseases. The economic and social repercussions of climate change on kiwifruit production, including yield losses, livelihood impacts, and market dynamics, are thoroughly examined. In response to these challenges, this review proposes tailored adaptation and mitigation strategies for kiwifruit cultivation. This includes breeding climate-resilient kiwifruit cultivars of the Actinidia species that could withstand drought and high temperatures. Additional measures would involve implementing sustainable farming practices like irrigation, mulching, rain shelters, and shade management, as well as conserving soil and water resources. Through an examination of the literature, this review showcases the existing innovative approaches for climate change adaptation in kiwifruit farming. It concludes with recommendations for future research directions aimed at promoting the sustainability and resilience of fruit production, particularly in the context of kiwifruit cultivation, amid a changing climate. [ABSTRACT FROM AUTHOR]

This study investigated the tolerance of resting eggs of Eurytemora pacifica to storage under low temperatures, which is of particular interest in light of the recent use of nauplii as living food in aquaculture, other than conditions experienced also in the wild during winter cold events in the Northern Hemisphere. Sediment samples collected in August 2020 were used to store the resting eggs at two different freezing temperatures (−5 and −20 °C) for five different durations (1, 3, 6, 9, and 12 months). The mean hatching success rates of the resting eggs after one month of storage were 85.3 ± 1.5% (−5 °C) and 85.0 ± 3.6% (−20 °C), with no significant difference between freezing temperatures. However, significant differences emerged over time, with the mean hatching success rate remaining at 85.0 ± 3.6% at −5 °C after three months, while it dropped sharply to 1.7 ± 2.1% at −20 °C. For the non-freezing conditions, the hatching success at 10 °C increased gradually over the one-month incubation period, ultimately reaching 71.0%. These findings demonstrate the remarkable cold tolerance of E. pacifica but also indicate a limit to this tolerance at longer durations. These results underscore the importance of considering the adoption of storage freezing for resting eggs to be used for aquaculture and also suggest the possibility of the species better surviving the extreme weather events in comparison with other species. [ABSTRACT FROM AUTHOR]

Background: The impact of weather on human health has been proven, but the impact of extreme weather events on cardiometabolic multimorbidity (CMM) needs to be urgently explored. Objectives: Investigating the impact of extreme temperature, relative humidity (RH), and laboratory testing parameters at admission on adverse events in CMM hospitalizations. Designs: Time-stratified case-crossover design. Methods: A distributional lag nonlinear model with a time-stratified case-crossover design was used to explore the nonlinear lagged association between environmental factors and CMM. Subsequently, unbalanced data were processed by 1:2 propensity score matching (PSM) and conditional logistic regression was employed to analyze the association between laboratory indicators and unplanned readmissions for CMM. Finally, the previously identified environmental factors and relevant laboratory indicators were incorporated into different machine learning models to predict the risk of unplanned readmission for CMM. Results: There are nonlinear associations and hysteresis effects between temperature, RH and hospital admissions for a variety of CMM. In addition, the risk of admission is higher under low temperature and high RH conditions with the addition of particulate matter (PM, PM2.5 and PM10) and O3_8h. The risk is greater for females and adults aged 65 and older. Compared with first quartile (Q1), the fourth quartile (Q4) had a higher association between serum calcium (HR = 1.3632, 95% CI: 1.0732 ~ 1.7334), serum creatinine (HR = 1.7987, 95% CI: 1.3528 ~ 2.3958), fasting plasma glucose (HR = 1.2579, 95% CI: 1.0839 ~ 1.4770), aspartate aminotransferase/ alanine aminotransferase ratio (HR = 2.3131, 95% CI: 1.9844 ~ 2.6418), alanine aminotransferase (HR = 1.7687, 95% CI: 1.2388 ~ 2.2986), and gamma-glutamyltransferase (HR = 1.4951, 95% CI: 1.2551 ~ 1.7351) were independently and positively associated with unplanned readmission for CMM. However, serum total bilirubin and High-Density Lipoprotein (HDL) showed negative correlations. After incorporating environmental factors and their lagged terms, eXtreme Gradient Boosting (XGBoost) demonstrated a more prominent predictive performance for unplanned readmission of CMM patients, with an average area under the receiver operating characteristic curve (AUC) of 0.767 (95% CI:0.7486 ~ 0.7854). Conclusions: Extreme cold or wet weather is linked to worsened adverse health effects in female patients with CMM and in individuals aged 65 years and older. Moreover, meteorologic factors and environmental pollutants may elevate the likelihood of unplanned readmissions for CMM. [ABSTRACT FROM AUTHOR]

Extreme weather events such as floods, bushfires, cyclones, and drought, are projected to increase in eastern Australia. Understanding how these events influence the combined, sustainable well-being of humans, animals, and ecosystems - that is One Health - will enable development of transdisciplinary and ultimately more effective interventions. A scoping review was conducted to explore the research associated with the effects of extreme weather events in eastern Australia using a One Health lens, specifically identifying the type of extreme weather events studied, the research conducted in the context of One Health, and gaps to inform improved One Health implementation. The review followed JBI guidelines (based on PRISMA). Eligible research was peer-reviewed, in English, and published since 2007, in which primary research studies investigated the impact of extreme weather events in eastern Australia on at least two of ecosystems, human health, and animal health. Using structured search terms, six databases were searched. Following removal of duplicates, 870 records were screened by two reviewers. Eleven records were eligible for data extraction and charting. The scope of extreme weather events studied was relatively limited, with studies in flood and bushfire settings predominating, but relatively little research on cyclones. Major health themes included more than the impact of extreme weather events on physical health (zoonotic and vector-borne diseases) through investigation of social well-being and mental health in the context of the human-animal bond in evacuation behaviors and drought. Research gaps include studies across a broader range of extreme weather events and health topics, as well as a more comprehensive approach to including the impacts of extreme weather events on all three domains of One Health. The limited research focus inevitably translates to limited recommendations for policy, planning and response to manage extreme weather event emergencies. Given the expected increase in frequency of these events, there is a critical need for more comprehensive primary research to better identify strategies and facilitate implementation of One Health promotion for improved outcomes in extreme weather event emergencies. [ABSTRACT FROM AUTHOR]

The Mediterranean region contains some of the areas with the highest urban density in the world, and these areas keep expanding, making this region a "hotspot" of climate change. Life in the Mediterranean unfolds predominantly outdoors throughout the year, exposing its inhabitants to an evolving climate that is progressively harsher and punctuated by increasingly frequent extreme weather events. More and more people are going to be exposed to severe heat waves, droughts, water shortage, dust storms, forest fires and poor air quality on the one hand, and torrential rains and floods on the other hand. The urban heat island further increases thermal stress of city dwellers and plays a key role in citizens' health and well‐being. In this exhaustive review, based on state‐of‐the‐art studies we delve into the realm of climate change and extreme weather phenomena as they intersect with urban populations in Mediterranean cities, both in the present and in the foreseeable future. Our focus lies on identifying knowledge gaps, inconsistencies in observed climatic hazards and shortcomings in assessing the associated risks and their societal and environmental ramifications. Moreover, we undertake a comprehensive survey of future predictions exploring the variables thermal stress, air pollution, air quality and characteristics of the hydro‐climatic systems, that is, droughts, fires and floods. Yet, critical knowledge gaps persist in understanding the science, the coping mechanisms, the strategies for preparedness and adaptation and the intricate interplay between these facets and societal dynamics. The developing countries in the Mediterranean region stand exceptionally vulnerable. It is imperative for more affluent nations to share their expertise and extend assistance to less developed counterparts, aiding them in navigating climate‐related challenges, devising adaptive strategies and facilitating their implementation. [ABSTRACT FROM AUTHOR]

Large‐scale dynamical and thermodynamical processes are common environmental drivers of high‐impact weather systems causing extreme weather events. However, such large‐scale environmental conditions often display systematic biases in climate simulations, posing challenges to evaluating high‐impact weather systems and extreme weather events. In this paper, a machine learning (ML) approach was employed to bias correct the large‐scale wind, temperature, and humidity simulated by the atmospheric component of the Energy Exascale Earth System Model (E3SM) at ∼1° resolution. The usefulness of the ML approach for extreme weather analysis was demonstrated with a focus on three high‐impact weather systems, including tropical cyclones (TCs), extratropical cyclones (ETCs), and atmospheric rivers (ARs). We show that the ML model can effectively reduce climate bias in large‐scale wind, temperature, and humidity while preserving their responses to imposed climate change perturbations. The bias correction is found to directly improve water vapor transport associated with ARs, and representations of thermodynamical flows associated with ETCs. When the bias‐corrected large‐scale winds are used to drive a synthetic TC track forecast model over the Atlantic basin, the resulting TC track density agrees better with that of the TC track model driven by observed winds. In addition, the ML model insignificantly interferes with the mean climate change signals of large‐scale storm environments as well as the occurrence and intensity of three weather systems. This study suggests that the proposed ML approach can be used to improve the downscaling of extreme weather events by providing more realistic large‐scale storm environments simulated by low‐resolution climate models. Plain Language Summary: A machine learning model is employed to bias correct the large‐scale dynamical and thermodynamical fields simulated by a low‐resolution global climate model. The impact of the machine learning model on the large‐scale storm environment associated with tropical cyclones (TCs), extratropical cyclones (ETCs), and atmospheric rivers (ARs) was evaluated. It is found that the ML bias correction can effectively reduce the mean climate biases in large‐scale wind, temperature, and humidity fields associated with the three types of high‐impact weather systems. For storms such as ETCs and ARs that can be partly resolved by the low‐resolution climate models, the machine learning bias correction shows skills in improving the long‐term statistics of these weather events. For storms such as TCs that can not be well resolved in the low‐resolution climate models, the machine learning approach produces more realistic statistics of the tropical cyclone tracks by providing more realistic large‐scale steering winds for downscaling approaches. By reducing model biases without affecting the climate change signals in large‐scale storm environments derived from the low‐resolution climate model simulations, machine learning bias correction has the potential to provide more reliable projections for assessing future changes in extreme weather events. Key Points: A machine learning approach with a long short‐term memory network is used to bias correct climate simulations from the E3SM atmosphere modelThe approach effectively reduces biases in the simulated large‐scale model states while preserving their responses to climate changeImproving large‐scale storm environment with bias correction facilitates modeling of high‐impact weather systems and their future changes [ABSTRACT FROM AUTHOR]

Public agencies are increasingly required to respond to multiple and evolving threats. Perceptions of risk are important triggers of organizational responses and motivate adaptive strategies. Integrating administrative data with a survey of public managers employed across the 300 largest transit agencies in the US, we examine how outsourcing decisions and reliance on scientific and professional sources of information influence public agencies' perceptions of extreme weather events' risks. Results show that reliance on scientific and professional sources of information is positively associated with perceived risk of extreme weather events. The effect of contracting on risk perceptions depends on agencies' outsourcing strategies. [ABSTRACT FROM AUTHOR]

Extreme weather events are increasingly disrupting schooling. Yet, these are underrepresented in the climate change literature. Of 15 review articles on the economic impacts of climate change published since 2010, only three mention the impacts of climate change on education. We review available literature on the effects of weather extremes on education. We outline key pathways through which these events impact education outcomes, as well as the magnitude of those impacts. Evidence implies a significant and adverse relationship between heat and learning. Studies suggest surpassing a high temperature threshold makes learning difficult and results in learning losses. Across studies, each additional day subject to extreme heat reduces learning. Tropical cyclones, floods, and wildfires precipitate school closures, which halt learning. Evidence suggests that one day of school closures leads to one day of learning lost. Weather extremes also negatively impact education outcomes through health, nutrition, poverty, and fragility, among other distal pathways. We discuss the implications of this evidence for policy, including the need to adapt education systems to climate change. Mitigation and adaptation are both urgently needed as extreme weather events become more frequent and severe in the context of climate change. [ABSTRACT FROM AUTHOR]

Climate change is causing significant disruptions worldwide, and Swat, Khyber Pakhtunkhwa (KP), is no exception. This qualitative research delves into the extensive effects of climate change on the health of Swat's residents, particularly those in vulnerable communities. By conducting in-depth interviews with healthcare professionals, local authorities, and affected individuals, alongside employing data collection methods such as audio recordings and meticulous note-taking, a comprehensive understanding of the situation was developed. The study highlights the multifaceted factors contributing to climate change in the region, including deforestation, glacial melting, and unpredictable weather patterns, and explores their cascading effects on public health. The findings reveal that climate change is exacerbating various health issues, including a rise in respiratory problems due to increased air pollution, a surge in waterborne diseases from contaminated water sources, heat-related illnesses stemming from rising temperatures, and a growing prevalence of mental health challenges as communities struggle with climate-induced stress and displacement. To address these impacts, urgent measures are needed, including substantial investment in resilient infrastructure, strengthening local healthcare systems to cope with emerging health threats, improving water management practices to ensure safe drinking water, enhancing early warning systems for extreme weather events, promoting public health education focused on climate adaptation, empowering communities through participatory approaches, and integrating mental health support into climate response strategies. The study emphasizes the importance of coordinated and proactive measures at both local and governmental levels to mitigate the socio-economic and psychological consequences of climate change. By offering valuable insights from respondents, the study concludes by recommending specific actions to alleviate the adverse impacts of climate change on health in Swat, KP, and calls for a comprehensive, multisectoral approach to ensure the well-being of the region's inhabitants. [ABSTRACT FROM AUTHOR]

The official adoption of Buddhism by the Tibetan state in the mid-8th Century (761-762 CE) was relatively late compared to its permeation from northern India to elsewhere in south and east Asia, due to the country’s geographical isolation. Whilst reasons for its adoption remain uncertain, it is thought that the religion provided a strong unifying influence permitting both the consolidation and subsequent expansion of the Tibetan Empire. Early historical records suggest that the religion was prohibited in 739-741 CE and again in 841-842 CE, the latter coinciding with the fall of the Tibetan Empire. This research presents a detailed examination of Tibetan and Chinese historical records and also of recent fine-resolution palaeoclimatic reconstructions to demonstrate that the ‘oscillating fate’ of Buddhism during the Tibetan Empire (618-842 CE), was not only linked to the economic fortunes of the Tibetan state as previously envisaged, but also inextricably to disease, the long-term regional climatic deterioration and possibly also to a series of natural disasters, many of which were recorded in the north and north-west of the Tang Empire adjacent to Tibet, as well as in Tibet itself. These ‘disasters’ noted in the historic records, and both catalogued and quantified here, indicate extreme pressures placed on the rural economy of the Tibetan Plateau and adjoining areas by crop failures, the death of many livestock and associated widespread famine and human mortality. The ‘chaos & disorder’ of the latter stages of the reign of Emperor Ralpachen (815-836/838 CE), as well as the Second Prohibition of Buddhism by the last Tibetan Emperor Lang Darma can therefore now not only be related to climatic-environmental deterioration, but also to the likely loss of public faith in both Tibetan Emperors and in Buddhism. It is possible that in the eyes of superstitious Tibetans, neither their rulers nor the state religion could address an accelerating spiral of crises. Devine displeasure could have been further signified by a devastating earthquake in Tibet sometime between 839-842 CE and the subsequent ‘implosion’ of the Tibetan Empire should no longer be considered surprising. [ABSTRACT FROM AUTHOR]

The rise in extreme weather conditions poses a formidable menace to the ecosystem services (ES) bestowed by ecosystems upon humanity. A precise comprehension of the ramifications of extreme weather events on ES is imperative to establish a robust scientific foundation for mitigating the adverse consequences of such phenomena. Despite the extensive corpus of international studies on the impact of extreme weather events on ES, there is a lack of literature reviews and nuanced discussions regarding forthcoming research aims. Therefore, this paper selects to focus on drought, extreme precipitation, heatwaves, and extreme cold--representatives of extreme weather with substantial global ramifications and notable threats. It summarizes the effects of extreme weather events with substantial global on ES, identifies current research issues, and outlines future prospects. Research indicates that the impact of extreme weather events on ES is predominantly negative. Extreme weather affects ecological processes and human needs, subsequently influencing the supply-demand relationship and trade-offs between ES. The diversity of research methods is influenced by differences in research objectives and scales. The interaction of various extreme weather events and the complex coupling with human activities make the mechanisms of extreme weather events impact on ES more intricate. A deficiency exists in the systematic exploration of the dynamic characterization of supply-demand relationships and trade-off dynamics under the sway of extreme weather. Additionally, there is a paucity of research addressing the recovery processes and underlying mechanisms governing ecosystem services (ES) in the aftermath of extreme weather events. Additionally, there is a need for in-depth attention to the spatial scale characteristics of ES under the influence of extreme weather, which is crucial for understanding the mechanism of impacts. [ABSTRACT FROM AUTHOR]

Extreme floods can cause significant damage to infrastructure, property, and human life and have long-lasting social, economic, and environmental impacts. Flood risk assessment is critical in areas where the frequency of flood events is altering due to climate change, anthropogenic warming, land use changes. Since the primary goal of flood risk management is to reduce the risk to a tolerable level, the risk assessment based on hydrological, hydrodynamic modeling, and damage analysis is essential to identify areas that are at risk of flooding, assessing the vulnerability of assets in the area, and evaluating the potential impacts on the human life, economy, and environment. The purpose of this study is developing a transferred approach between similar catchments to observe how the catchment response in terms of discharge and damage based on a particular extreme flood event in the past. To conduct the research, the meteorological variables from the Ahr River valley extreme flood event are acquired, and an approach is developed to transfer the same dataset into the Mulde River catchment to observe consequences of the event.

Using a scoring technique, we have developed a Water Security Reporting Index (WSRI) to assess the disclosed information pertaining to the preparedness for extreme water events among 15 Brazilian water utilities. This evaluation is based on the analysis of annual reports from water and sanitation companies. The WSRI incorporates seven dimensions: (i) Climate changes and their impacts on water availability; (ii) Water availability evaluation and measurement; (iii) Improvements in supply infrastructure systems; (iv) Demand-side infrastructure improvements; (v) User awareness creation; (vi) Water availability prediction; and (vii) Actions to prevent water availability issues. The findings reveal a paradoxical scenario where the WSRI falls significantly below the maximum score. Simultaneously, the growing concerns about the impacts of global change, leading to an increase in the frequency and magnitude of extreme weather events, highlight a pressing issue in Brazil. Neglecting this concern implies disregarding the impending scarcity of water, the primary focus of water utilities. User awareness creation emerges as the dimension with the highest score. Conversely, water availability evaluation and prediction, along with demand-side infrastructure improvements, receive the least attention from water utility managers in terms of water security. This study underscores the disparity between the clear understanding that water supply companies possess regarding the impacts of climate change on the water industry and their failure to effectively communicate the actions they have adopted and planned.

Ethiopia’s vulnerability to climate change is exacerbated by high poverty rates, rapid population growth, increasing prevalence of vector-borne diseases, and heavy reliance on rain-fed agriculture. This narrative review aims to compile existing data on the impacts of climate extremes on the physical environment, public health, and livelihoods in Ethiopia, thereby highlighting the significance of this region for such a study. Data were sourced from peer-reviewed journal articles from databases like PubMed, Scopus, and Web of Science, as well as reports and other unpublished documents. Results show that Ethiopia is facing increasing frequency, severity, duration, and timing of climate-related extreme events. Key challenges include environmental degradation, reduced crop yields, recurring floods, droughts, famines, increased heat waves, and spread of infectious diseases. Average daily rainfall is projected to decrease from 2.04 mm (1961–1990) to 1.97 mm (2070–2099), indicating a worsening climate trend. Moreover, the average annual temperature has risen by 1.3°C since 1960, at a rate of 0.28°C per decade. Flood records indicate a sharp rise, with 274 flood incidents recorded in 2020, causing extensive damage, including an annual soil loss of 1 billion tons in the Ethiopian highlands, reducing land productivity by 2.2% annually. Droughts from 1964 to 2023 affected 96.5 million people, reduced GDP by 4%, decreased agricultural output by 12%, and increased inflation rates by 15%. The regions of Afar, Somali, Gambella, and Benshangul Gumuz exhibit extreme vulnerability to health impacts due to rising temperatures. Addressing climate extremes is critical to mitigate their adverse effects on Ethiopia’s environment, public health, and livelihoods.

The mortality of trees in humid tropical forests plays a fundamental role in understanding forest development, particularly after disturbances such as those caused by logging and extreme weather events. The aim of this study was to evaluate estimates of individual tree mortality following Reduced Impact Logging (RIL) in the Eastern Brazilian Amazon at biennial intervals from 2005 to 2012. RIL is based on operations planning, personnel training, and investments in forest management, and harvesting through RIL must: (a) minimize environmental damage, (b) diminish operation cost by increasing work efficiency, and (c) reduce operational waste. A mortality model was constructed based on the estimation of three distance-independent competition-indices (DII) and five models for predicting the probability of individual tree mortality. The Kolmogorov-Smirnov statistical test was used to determine the most representative model, from which a Neural Network Autoregressive (NNAR) model was constructed to forecast mortality after RIL. Mortality data was correlated with the El Niño–Southern Oscillation (ENSO) and climate (Rainfall, Maximum, Minimum, and Average air temperature). The tested models showed similar and accurate estimates with R2 exceeding 0.90, although underestimation and overestimation trends were observed. The NNAR satisfactorily represented species mortality over the simulated years. The period from 2012 to 2014 was characterized by a Neutral and Weak El Niño event, and exhibited the highest mortality value for a 25 cm DBH (diameter at breast height), the smallest DBH class measured in this study. In the correlation matrix analysis, maximum air temperature showed the highest positive correlation with trees mortality. Despite the challenges in estimating individual tree mortality in tropical forests after selective logging, accurate estimates were achieved using traditional regression techniques and NNAR. These results can support technical and silvicultural decisions regarding forest management in the Eastern Amazon region of Brazil.

Climate change has intensified extreme weather events, posing major challenges to agriculture-dependent regions like Northern Maharashtra. This study analyzed temperature and precipitation extremes across five districts—Nashik, Dhule, Nandurbar, Jalgaon and Ahmednagar using data from 1982 to 2022 with the help of RClimDex model. Key temperature indices, including tropical nights (TR25), warm days (TX90p), and frost days (FD13) showed an increase in warm events and a decline in cool nights and frost days. Reduced diurnal temperature range (DTR) indicated less nighttime cooling, consistent with global warming. For precipitation, extreme rainfall events are rising as indicated by the maximum 1-day precipitation (Rx1day), while consecutive dry days (CDD) are shortening. These shifts heighten risks such as crop heat stress, altered growing seasons, soil erosion, and water management challenges. The study underscores the urgent need for adaptive agricultural strategies, improved irrigation, and early warning systems to mitigate the impacts of climate change and enhance resilience in Northern Maharashtra.

ABSTRACTBackground: The perinatal period is a time of increased vulnerability for perinatal mood and anxiety disorders (PMADs). Emotional trauma is a risk factor for PMAD development and is common among survivors of extreme weather events (EWEs), which are becoming more frequent and intense as the climate crisis progresses. EWE-related stress and anxiety have not been extensively studied in the perinatal population. However, the limited available data suggest a negative impact of EWE exposure on perinatal mental health, warranting further investigation and investment.Objective: To address this knowledge gap, we interviewed new Australian mothers to understand how EWEs affect the mental health of the perinatal population.Method: Australian mothers (18 years of age or older) with a baby under 12 months of age were recruited to participate in a single virtual focus group session (seven group sessions were run in total) and complete an anonymous survey. Participants were asked questions regarding their concerns about extreme weather and its impact, as well as their general maternal functioning. Maternal functioning, depression, and climate distress were measured via the survey.Results: The study sample comprised 31 Australian mothers (Mage = 31.74, SD = 4.86), predominantly located in Queensland. Findings from the focus groups suggested six key themes; however, of focus to this study are three themes related to maternal mental health: health and well-being, helplessness and avoidant coping, and resilience and adaptation. Predominant subthemes focused on trauma resulting from EWE exposure, economic and heat concerns, social isolation, hopelessness about the future, and feelings of resilience.Conclusions: The evidence linking adverse perinatal mental health outcomes with climate change and EWEs highlights the urgent need for interventions in this context to protect perinatal mental health and well-being. By acknowledging the traumatic impact of these experiences on mothers, this study supports advocacy for policies that specifically address this issue.

Introduction: There has been a global rise in land-surface air temperature by 1.53 °C which can pose a threat to agricultural yields, undermine food security, and exacerbate malnutrition. In India, modern agricultural systems heavily rely on cereal crops which are susceptible to climate-induced stressors, leading to potential yield losses; whereas millets, resilient to stress and nutritionally rich, offer a sustainable alternative. Case presentation: Odisha's vulnerability to natural calamities like droughts, floods, and cyclones has significantly impacted crop production, particularly rice, prompting the reintroduction of millets. The Odisha Millets Mission (OMM), was launched to promote millets in tribal areas, revitalize traditional farming practices, increasing millet cultivation, yield rates, and gross value per household. Millets offer health benefits, environmental advantages, and potential solutions to combat malnutrition and climate change. Discussion: Integrating millets into public diets and food security programs can enhance nutritional resilience and foster sustainable food systems nationwide. The success of OMM underscores the potential for replicating similar initiatives across India, thereby elevating livelihoods, nutritional well-being, and climate resilience among vulnerable populations. Conclusion: The success of OMM highlights the potential for similar initiatives worldwide, benefiting livelihoods, nutrition, and climate resilience among vulnerable populations. Future research can prioritize enhancing millet productivity and profitability through improved varieties, enhanced agronomic practices, and modern technology adoption.

This review studies the cascading impacts of extreme weather events on the Water-Energy-Carbon (WEC) Nexus, with a focus on their combined and sequential effects. It synthesizes research on how droughts, floods, heatwaves, hurricanes, and wildfires each initiate a chain reaction within the interconnected domains of water, energy, and carbon. Key insights include the analysis of drought impacts, like in California, where hydroelectric power's share dropped from 18% to 7%, leading to a 34%increase in emissions from natural gas plants. In Europe, flooding led to operational challenges for power plants, with a projected loss of 0.6–4.6 TWh in energy generation by 2030 due to water temperature rises. The 2023 European heatwave saw Spain's energy demand spike by 20%, driven by increased use of air conditioning, and a corresponding 15–20% rise in carbon emissions in affected countries due to greater reliance on fossil fuels. The review emphasizes the need for integrated resilience strategies, leveraging the provided quantitative data to argue for policies that address these interdependent challenges. It urges for a nuanced understanding of the WEC Nexus's dynamics to inform more effective responses to the rising tide of climate change-induced extreme weather events. Furthermore, this review expands its examination to include cases from developing countries, showcasing how their unique challenges and responses within the WEC Nexus contribute to a more comprehensive understanding of global resilience strategies against extreme weather. This review brings to the forefront the ripple effects of alterations in energy production on water resources and carbon dynamics, underscoring the critical need for a nuanced understanding and integrated approaches in managing the WEC Nexus in the face of extreme weather events.

Summary: In the present context of climate change and extreme weather events, understanding the impact of flood events on Mediterranean riverine ecosystems is key for conserving landscapes while preserving local biodiversity. In this study, we examined the impact of a major flood that occurred in November 2014 on the Baillaury River (Southern France) where a population of the Mediterranean Pond Turtle Mauremys leprosa (Schweigger, 1812) was monitored from 2012 to 2022. Survival, recruitment, and transition probabilities were estimated before and after the flood using Pradel Robust-Design and Multistate models. Although turtle population size decreased by 16 % immediately after flooding, the adult population rapidly returned to its initial state with a balanced sex ratio. This study highlights that neither the structure nor the temporal dynamics of the adult population were altered over a ten year period underlying the fast resilience of the species. The flood however mainly impacted the spatial dynamics of the population by increasing downstream movements of turtles, which resulted in changes of their distribution along the river.