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Humanity is facing a polycrisis, including climate change, loss of biodiversity, and economic inequalities. This commentary examines the role of physical activity (PA) research in the context of climate change, highlighting 3 perspectives: PA as a victim, as a perpetrator, and as part of the solution. The first perspective conceptualizes PA as a victim of climate change, as heat waves, extreme weather events, and high ozone levels pose a threat to health-enhancing PA and sports; adaptation strategies are needed and potentially lifesaving. The second perspective describes PA as a perpetrator to climate change due to the significant carbon footprint of some forms of PA and sport. The third perspective focuses on PA as a solution to climate change, as some forms of PA—such as active transport and urban gardening—have both individual and planetary health benefits. In addition, PA provides health benefits in extreme situations by reducing stress and maintaining health in times of crisis. Each of these 3 perspectives can guide future research in the field of PA and health. [ABSTRACT FROM AUTHOR]

The Journal of Physical Activity and Health has evolved over the past 20 years to address global challenges such as climate change, social inequalities, and pandemics. A special issue titled "Physical Activity as a Necessary Solution to Current Global Health Challenges" explores the multifaceted relationship between physical activity and various global issues. The issue covers topics ranging from climate change to equity, highlighting the importance of promoting physical activity for mental and social health benefits. Moving forward, the journal advocates for a mission-oriented research paradigm that emphasizes collaboration, equity, advocacy, and implementation of policies to address the complexities of physical inactivity in the modern era. [Extracted from the article]

To feed a rapidly growing human population in an era of climate change and increasingly uncertain weather—such as drought and flood—humanity will need crops with increased yields, greater resiliency to extreme weather, and more resistance to disease. Appropriately enough in the Century of Biology, that means turning to genetic tools such as CRISPR. [ABSTRACT FROM AUTHOR]

Extreme weather has a direct and significant impact on buildings and infrastructure, resulting in billions of dollars of damage each year. This problem continues to grow as climate patterns change and buildings are exposed to new and different hazards than what they were designed to withstand. In order to better plan for the long-range sustainment, restoration, modernization, and eventual recapitalization of these buildings, organizations with large building portfolios, such as the U.S. Department of Defense (DoD), must have an awareness of the risks that these extreme weather events present. This research aimed to develop an approach to estimate condition loss and reduction in service life for the components of a building due to extreme weather hazards, to understand the risks that may be present in certain buildings and building systems. To achieve this objective, a damage association matrix was developed that categorizes climate hazards, the damage modes that they produce, and the individual component types impacted. This damage matrix formally links state-of-the-art climate model output, which provides projections of the probability of various climate hazards with a damage effects model that quantifies the consequence on component-level condition and service life. This method is applied to an actual portfolio of buildings in a particular geographic location and with a pre-defined component inventory that comprises the building. This approach can be aggregated to the system-, facility-, and site-level thus helping support billions of dollars in recapitalization decisions related to restoration/modernization of facilities.

International Workshop on Stratosphere-Troposphere Interactions and Prediction of Monsoon Weather Extremes (STIPMEX) What: This workshop was held to assess the influence of stratosphere-troposphere Interaction processes on extreme weather against the backdrop of frequent extreme weather events and to explore future pathways for prediction of monsoon weather extremes. When: 2-7 June 2024 Where: Pune, India KEYWORDS: Climate change; Convective storms; Hydrologic cycle; Atmospheric chemistry, 1. Introduction The extreme weather events cause a large damage to life and ecosystem. Since the last few decades, there has been an increase in extreme weather events in South [...]

INTRODUCTION: Climate change is a global phenomenon with far-reaching consequences, and its impact on human health is a growing concern. The intricate interplay of various factors makes it challenging to accurately predict and understand the implications of climate change on human well-being. Conventional methodologies have limitations in comprehensively addressing the complexity and nonlinearity inherent in the relationships between climate change and health outcomes. OBJECTIVES: The primary objective of this paper is to develop a robust theoretical framework that can effectively analyze and interpret the intricate web of variables influencing the human health impacts of climate change. By doing so, we aim to overcome the limitations of conventional approaches and provide a more nuanced understanding of the complex relationships involved. Furthermore, we seek to explore practical applications of this theoretical framework to enhance our ability to predict, mitigate, and adapt to the diverse health challenges posed by a changing climate. METHODS: Addressing the challenges outlined in the objectives, this study introduces the Complex Adaptive Systems (CAS) framework, acknowledging its significance in capturing the nuanced dynamics of health effects linked to climate change. The research utilizes a blend of field observations, expert interviews, key informant interviews, and an extensive literature review to shape the development of the CAS framework. RESULTS AND DISCUSSION: The proposed CAS framework categorizes findings into six key sub-systems: ecological services, extreme weather, infectious diseases, food security, disaster risk management, and clinical public health. The study employs agent-based modeling, using causal loop diagrams (CLDs) tailored for each CAS sub-system. A set of identified variables is incorporated into predictive modeling to enhance the understanding of health outcomes within the CAS framework. Through a combination of theoretical development and practical application, this paper aspires to contribute valuable insights to the interdisciplinary field of climate change and health. Integrating agent-based modeling and CLDs enhances the predictive capabilities required for effective health outcome analysis in the context of climate change. CONCLUSION: This paper serves as a valuable resource for policymakers, researchers, and public health professionals by employing a CAS framework to understand and assess the complex network of health impacts associated with climate change. It offers insights into effective strategies for safeguarding human health amidst current and future climate challenges.

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Food insecurity in Ethiopia is an immediate humanitarian crisis that is expected to worsen due to population growth and climate change. This study applied GIS-based approaches to evaluate the feasibility of deploying an emergent type of single-cell protein (SCP) technology to supplement the nutritional needs of Ethiopian citizens who are most vulnerable to drought. The technology—power-to-protein (PtP)—uses H2 and O2 from water electrolysis and CO2 from woody biomass combustion in a two-stage bioprocess to produce nutrient-rich protein powder for human consumption. Population density, land use, and other geographical data were used to identify optimal site locations for these PtP systems based on two deployment strategies: large centralized plants vs. small decentralized units. The model also accounted for biomass availability, collection, and distribution logistics. The analysis revealed three sites that are both (highly) vulnerable/food-insecure and accessible within walking distance. The identified sites are proximate to the urban areas of Mekele in northern Ethiopia, Addis Ababa in central Ethiopia, and Hawasa south of Addis Ababa. If centralized PtP were deployed, the protein requirements of these populations could be sustained for several months, assuming a modest biomass collection radius of 35 km. Decentralized PtP deployment was similarly effective, requiring a distribution density of 5.4–11.0 PtP units per km2 under conservative estimates and 0.76–1.1 units per km2 under optimistic estimates. Lastly, a theoretical comparison showed that PtP is more efficient than conventional agricultural food production regarding biomass-to-protein conversion yields. Overall, our study suggests that PtP technology would be a feasible approach to supplement the nutritional needs of Ethiopian people in times of drought-related emergencies. However, given logistical limitations and considering social preference factors, it would be more practical to implement PtP in conjunction with standard emergency food aid measures. [ABSTRACT FROM AUTHOR]

This study examines the severe weather event on 3 March 2015 in Msalala District, where surface convergence and enhanced atmospheric instability played a crucial role in storm development. Evaluation of numerical weather models revealed variations in accuracy, with the Global Forecast System (GFS) model performing better at predicting observed conditions than other models. These findings highlight the need for improved observational data networks in regions like Tanzania to enhance the understanding of localised severe weather events. High‐resolution data shows potential for improving forecast accuracy, strengthening early warning systems and enhancing preparedness for extreme weather events. [ABSTRACT FROM AUTHOR]

Knowledge of how animals respond to weather and changes in their physical environment is increasingly important, given the higher frequency of extreme weather recorded in recent years and its forecasted increase globally. 1,2 Even species considered to be highly adapted to extremes of weather, as albatrosses are to strong winds, 3,4,5 may be disadvantaged by shifts in those extremes. Tracked albatrosses were shown recently to avoid storms and the strongest associated winds. 6 The drivers of this response are so far unknown, though we hypothesize that turbulent storm conditions restrict foraging success, possibly by reducing the detectability or accessibility of food, and albatrosses divert toward more profitable conditions where possible. We tested the impact of the physical environment—wind speed, rainfall, water clarity, and time of day—on feeding activity and success of two species of albatrosses with contrasting foraging strategies. We tracked 33 wandering and 48 black-browed albatrosses from Bird Island (South Georgia) with GPS and immersion loggers, and 19 and 7 individuals, respectively, with stomach-temperature loggers to record ingestions, providing an in-depth picture of foraging behavior. Reduced foraging profitability (probability of prey capture and overall mass) was associated with stormy conditions, specifically strong winds and heavy rain in surface-seizing wandering albatrosses, and the probability of prey capture was reduced in strong winds in black-browed albatrosses. We show that even highly wind-adapted species may frequently encounter conditions that make foraging difficult, giving context to storm avoidance in albatrosses. [Display omitted] [Display omitted] • Albatrosses exploit wind for flight but seemingly avoid the strongest winds in storms • We use multi-stream biologging data to relate albatross foraging to the environment • Our two study species experience reduced foraging success in stormy conditions • Wandering albatross land repeatedly in very strong winds, possibly to avoid injury Strong winds reduce the energy required for flight and takeoff in albatrosses; however, little is known about how wind impacts other behaviors, such as foraging. Darby et al. combined at-sea behavior and stomach-temperature data from two species of albatross to demonstrate the negative impact of stormy weather on foraging behavior and prey capture. [ABSTRACT FROM AUTHOR]

As the rising extreme weather events occurring in the Philippines, the extreme heat index during El Niño and consecutive tropical typhoons during La Niña created construct consciousness of the Filipinos with regards to climate change that is also increasing over the period; this consciousness may be labeled as a psychological term to "Ecoanxiety" which may create an adverse impact in terms of emotional and physical aspects. Thus, this study aims to investigate awareness, explore factors, and propose programs regarding eco- anxiety inside the urban locale area and was done in collaboration with the City Environment Service Department (CESD)- Bacoor (formerly known as City Environment and Natural Resources Office (CENRO). The research was conducted in the three areas of Bacoor, namely San Nicolas III, Molino III, and Molino IV, which employed mixed- methods design, incorporated both qualitative and quantitative approaches, and used validated instruments for interviews and survey questionnaires. There were 400 survey respondents, and 15 participants were interviewed. The data was analyzed using the following statistical treatment of frequency count and percentage and weighted mean for descriptive interpretation; the Colaizzi method was utilized for qualitative analysis. As such, results indicated that participants experienced eco-anxiety at a relatively low level. Coping mechanisms included relaxation techniques, optimism, and engaging in recreational activities. Physical manifestations of eco-anxiety included sleeping difficulties and fatigue. While it generally had a minor impact on social relationships, some respondents reported occasional disruptions and conflicts, especially related to differing environmental perspectives. The study recommends considering areas that are directly impacted by climate change, such as flood-prone areas. Additionally, the higher level of the term awareness may create significant contributions towards environmental sustainability in communities. [ABSTRACT FROM AUTHOR]

In challenging visibility conditions, the reliability of existing port lighting systems is significantly affected by abrupt changes in environmental factors (primarily stemming from ocean weather). This study proposes a cloud-edge collaborative dimming model that integrates a combined filter, enabling dynamic adaptation to these weather variations to ensure the stability of the lighting system. Additionally, the application of edge computing not only alleviates computational pressure but also facilitates the model's ability to achieve effective regional adaptive dimming in accordance with environmental regulations. Experimental results indicate that this method is suitable for scenarios with unknown mutations under extreme conditions, providing a more reliable and intelligent solution for port lighting systems within the Internet of Things (IoT) framework. [ABSTRACT FROM AUTHOR]

Pacific Island Countries (PICs) are vulnerable to climate change impacts, including sea level rise, extreme weather events and other environmental changes. Planned relocation can be an adaptive response to climatic threats. In Fiji, six communities have already relocated. While there is growing interest in planned relocation, there are few empirical case studies from which to learn. Narikoso village, in the Kadavu Province of Fiji, undertook partial relocation in 2020. Drawing on qualitative research (interviews, group discussions, observation), informed by Vanua methodology in 2022, this study examines the impacts of partial planned relocation on people's lives and livelihoods. Seven sustainable livelihood assets – or forms of 'capital' – are explored: natural, social, financial, human, physical and cultural, with the addition of spiritual. Our research found that planned relocation altered forms of capital that underpin sustainable livelihoods, leading to both benefits and problems. We argue that planned relocation must not only reduce exposure to climatic and environmental risk, but promote and preserve the integrity of local ecosystems, value continuity of culture and sustain and develop diverse assets that support sustainable livelihoods. This demands deep engagement with climate change‐affected communities to ensure that planned relocations sustain people's livelihoods, dignity and survival. [ABSTRACT FROM AUTHOR]

In recent years, climate change has significantly impacted European river systems, reshaping streamflow patterns with far-reaching consequences for ecosystems and water resources. This study investigates hydrological variability across 16 major European rivers. Cross-correlation analysis reveals strong climatic influences, with the Danube showing robust positive correlations with rivers such as the Elbe, Oder, Rhine, and Vistula, suggesting shared climatic drivers. In contrast, negative correlations between Central European rivers, like the Danube and Drava, and Southern European and UK rivers highlight the influence of distinct climatic regimes and geographical factors. To assess trends and identify abrupt changes in streamflow, the study applies the Mann-Kendall (MK), Seasonal Kendall (SK), and Regional Kendall (RK) tests, along with the Bayesian Estimator of Abrupt Change, Seasonal Change, and Trend (BEAST) algorithm. Hierarchical clustering analysis identifies four distinct groups: one cluster dominated by a strong negative trend in the Ebro River, another with a positive trend in the Thames, and two additional clusters representing Eastern and Western European rivers, with a few exceptions. The findings from the MK and SK tests reveal declining trends in rivers such as the Danube, Drava, and Nemunas, likely driven by long-term climatic shifts. In contrast, the Thames exhibits significant increases in streamflow, likely reflecting unique climatic conditions in Southern UK. The RK test further corroborates these observations, showing an overall pattern of declining streamflow across the studied rivers. BEAST analysis uncovers historical variability by identifying important transitions on long-term trends and abrupt changes in streamflow. Rivers like Danube, Loire, Drava, Nemunas and Vistula transitioned from positive to negative trends starting in the 1970s to 1990s. BEAST reveals also more complex dynamics in rivers like Rio Ebro and Thames, where both upward and downward abrupt changes reflect the impact of extreme weather events. [ABSTRACT FROM AUTHOR]

The accelerating impacts of climate change present significant challenges to sustainable urban development, testing the resilience of current governance frameworks and stakeholder responsibilities. In alignment with the EU's Green Deal, robust adaptation strategies and proactive climate risk anticipation are essential. Traditional discussions emphasize overcoming technological, financial and institutional barriers; however, social and individual factors also significantly hinder adaptation. This study explores the pivotal role of citizen engagement in climate risk management and adaptation, focusing on the Lithuanian context and comparing the results with a survey in Sweden. The research evaluates both external influences, such as experiences with climate‐related hazards and adaptation actions, and internal factors, including beliefs, values and individual adaptive capacity. Key findings reveal that adaptation behaviour in Lithuania and in Sweden is deeply influenced by past experiences with extreme weather events and economic considerations, with a significant portion of the population having faced such events recently. Factors such as economic considerations (low costs, financial benefits) are identified as critical motivators for future adaptation actions in Lithuania. On the other hand, in Sweden, respondents first preferred ecological factors (such as contributing to climate change mitigation) when considering future adaptation actions. The study underscores the need for targeted educational interventions to enhance community resilience, highlighting the importance of socio‐cultural contexts in shaping adaptation strategies. It emphasizes the necessity for comprehensive, inclusive educational programmes that address local climate impacts and promote proactive community involvement. The findings advocate for further comparative studies across diverse socio‐cultural settings to deepen insights into effective adaptation measures and to support the development of resilient communities worldwide. [ABSTRACT FROM AUTHOR]

Significant advancements in the development of machine learning (ML) models for weather forecasting have produced remarkable results. State-of-the-art ML-based weather forecast models, such as FuXi, have demonstrated superior statistical forecast performance in comparison to the high-resolution forecasts (HRES) of the European Centre for Medium-Range Weather Forecasts (ECMWF). However, a common limitation of these ML models is their tendency to generate increasingly smooth predictions as forecast lead times increase, which often results in the underestimation of intensities of extreme weather events. To address this challenge, we developed the FuXi-Extreme model, which employs a denoising diffusion probabilistic model (DDPM) to enhance finer-scale details in the surface forecast data generated by the FuXi model in 5-day forecasts. An evaluation of extreme total precipitation (TP), 10-meter wind speed (WS10), and 2-meter temperature (T2M) illustrates the superior performance of FuXi-Extreme over both FuXi and HRES. Moreover, when evaluating tropical cyclone (TC) forecasts based on International Best Track Archive for Climate Stewardship (IBTrACS) dataset, both FuXi and FuXi-Extreme shows superior performance in TC track forecasts compared to HRES, but they show inferior performance in TC intensity forecasts in comparison to HRES. [ABSTRACT FROM AUTHOR]

Extreme cold events, which have become more frequent, can revert the direction of long-term responses to climate change. In 2021, record snowstorms swept the United States, causing wildlife die-offs that may have been associated with rapid natural selection. Our objective was to determine whether the snowstorms caused natural selection in Eastern Bluebirds (Sialia sialis). To test which mechanism most influenced their survival, we measured the morphology and coloration of fatalities and survivors at three sites. Survival was associated with a longer tarsus and with a wider, longer, and deeper beak, in support of the starvation and thermal endurance hypotheses. Additionally, bluebirds with more-ornamented plumage were less likely to have survived, perhaps because of an early energy investment in mate and site acquisition. As bluebirds encounter increasingly warm summer conditions, the longer extremities favored during the snowstorms may continue to be favored through their thermoregulatory benefits. However, the dull plumage coloration favored by natural selection during the snowstorms may be opposed by sexual selection benefits of more-ornamented plumage. Overall, responses to extreme events are difficult to predict from responses to long-term climate change, and responses to one event, such as the 2021 snowstorms, may not predict responses to a future extreme event. [ABSTRACT FROM AUTHOR]

Although an extensive body of research examines the implications of climate change for various aspects of human health, little conceptual or empirical work has focused on how climate change may affect addiction recovery. This paper addresses this gap by identifying probable pathways through which climate change may impact recovery, drawing on environmental, public health, and recovery research. Applying the theory of recovery capital, I outline the potential effects of climate change on social, physical, human, and cultural recovery domains. For example, in the domain of social capital, extreme weather and climate-related displacement are likely to make it more challenging for people in recovery to attend social events and support groups, though the use of digital support services may partially mitigate negative impacts. I synthesize this research in a model of probable pathways through which climate change will affect recovery capital and recovery outcomes, highlighting the ways in which marginalization related to factors such as race, income, and age is likely to shape the magnitude of effects. Building from this model, I discuss research implications, including the need for qualitative studies that examine how people engage as resilient actors pursuing recovery in the face of this ongoing global crisis, as well as quantitative studies that test hypotheses about the specific links between climate change and recovery capital. This paper concludes with implications for practice at individual, organizational, and societal levels, describing actions that service providers and people in recovery can take to build recovery capital while pursuing climate justice activism. [ABSTRACT FROM AUTHOR]

Atmospheric blocking is a phenomenon that can lead to extreme weather events over a large region, yet its causes are not fully understood. Global climate models show limitations in representing Northern Hemisphere blocking, especially its frequency, and decadal variability in Greenland blocking in summer in the recent decades. In this study we evaluate the ability of high-resolution (HighResMIP) Earth System Models (ESMs) to simulate summer blocking over the Greenland area, using different but complementary methods to describe the characteristics of blocking. We find that the HighResMIP ensemble can reproduce the spatial pattern of Greenland blocking events, albeit with systematic biases, and capture the relative frequencies of the main blocking patterns: namely the wave breaking structure, North Atlantic ridge, and omega-type blocking. However, the HighResMIP ensemble fails to simulate the observed temporal variations of Greenland blocking index (GB2) and the extremely high values of daily GB2 observed in recent decades. In addition, we do not find clearly superior representation of blocking features from higher-resolution in HighResMIP models compared with lower-resolution models. We also find large sea surface temperature (SST) biases over the North Atlantic and seas surrounding Greenland, and biases in moisture transport over the North Atlantic toward Greenland, especially over the western flank of blocking areas, which might together contribute to model biases in the representation of blocking magnitude. [ABSTRACT FROM AUTHOR]

This study built truck productivity prediction models incorporating real-site weather conditions at varying temporal resolutions. The best models were combined with SHapley Additive exPlanations to offer quantitative and qualitative analysis for input variables' effect on the model outputs. The results showed that mining engineers can make more accurate predictions of truck productivity at the weekly resolution compared with other resolutions. The three most influential input parameters were haul distance, empty speed, and ambient temperature. Extreme weather, such as strong wind speed, heavy precipitation, and extreme relative humidity, had a certain effect on truck-shovel allocation. Meanwhile, a unified graphical user interface was developed to predict mine truck productivity. [ABSTRACT FROM AUTHOR]

Increasing frequency of extreme weather events threatens the livelihoods of low‐income farm households due to the heavy dependence on rain‐fed agriculture coupled with the under‐developed formal markets for risk management products. Thus, crop diversification is one of the widely used ex ante adaptation strategies to hedge against weather risk exposure. In this study, we use survey data from the northern Savanna zone of Ghana merged with historical weather data to shed light on the heterogeneous impact of crop diversification on farm net returns and risk exposure. We employ the dose response function and instrumental variable techniques to address potential endogeneity concerns. Overall, our findings show that crop diversification is a welfare‐enhancing strategy that significantly increases farm net returns, lowers the probability of crop failure, and thus decreases downside risk exposure. Notably, our dose‐response function analysis demonstrates that the positive benefits of crop diversification are particularly pronounced at lower intensities, reaching an optimal threshold. Beyond this point, the incremental advantages tend to diminish, suggesting the importance of carefully considering the optimal level of diversification for maximum benefits. The results further underscore the significant impact of both access to agricultural extension services and fertilizer usage on the adoption of crop diversification. [ABSTRACT FROM AUTHOR]

Traditional mid‐term electricity forecasting models rely on calendar and meteorological information such as temperature and wind speed to achieve high performance. However depending on such variables has drawbacks, as they may not be informative enough during extreme weather. While ubiquitous, textual sources of information are hardly included in prediction algorithms for time series, despite the relevant information they may contain. In this work, we propose to leverage openly accessible weather reports for electricity demand and meteorological time series prediction problems. Our experiments on French and British load data show that the considered textual sources allow to improve overall accuracy of the reference model, particularly during extreme weather events such as storms or abnormal temperatures. Additionally, we apply our approach to the problem of imputation of missing values in meteorological time series, and we show that our text‐based approach beats standard methods. Furthermore, the influence of words on the time series' predictions can be interpreted for the considered encoding schemes of the text, leading to a greater confidence in our results. [ABSTRACT FROM AUTHOR]

We offer a perspective on the major challenges that are confronting the management of reproduction in sheep and cattle in Australia and New Zealand, over the next two decades. An important context is the dominance of grazing systems in which large flocks or herds are managed over large areas where it is challenging to manage reproduction with precision. Consequently, the variable forage supply usually dominates reproductive outcomes, a problem that will be exacerbated by global heating. Thus, in extensive grazing systems, there is a great need for technological solutions to improve the management of nutrition. Global heating will also exert direct effects on reproductive function. Therefore, for the foreseeable future, reproduction will remain a focus for industry. In addition, as the industries develop, we foresee continued societal pressure to reduce medication, mitigate environmental damage, and improve animal well-being. Management solutions for extensive grazing systems must involve minimal interventions with the animals and be applicable to diverse genotypes and environments. Clearly, genetics and breeding will be at the heart of solutions and elegant strategies will be needed that focus on developing animals that are robust, if perhaps a little less productive. A high rate of genetic gain is the main reason for pursuing reproductive technologies, but highly advanced reproductive technology is not likely to be the best fit in extensive management systems. Even for AI, the simplest technology, uptake is limited and lateral thinking is needed to find ways to improve the rates of genetic gain. We conclude that there are many opportunities for improving reproductive performance in sheep and cattle in Australia and New Zealand. As we gain deeper understanding of the processes involved, we should be able to make progress in fertility and fecundity, embryo survival, and postnatal survival. Improvements in reproductive performance will increase productivity, and should also be associated with significantly improved animal well-being and a reduction in methane emissions intensity. To capture these benefits, the development of new management options will require lateral thinking about reproductive technology for extensive grazing systems, and a transdisciplinary approach that brings together the systems biology of grazing animals with an understanding of the barriers to adoption by farmers. • The context for management of reproduction is large flocks or herds grazing over large areas. • Nutrition-reproduction is key – feed supply is variable, becoming more so with climate change. • Extreme weather events caused by climate change might directly affect reproduction. • Reproduction is an industry focus, but transdisciplinary problem-solving will be needed. • Intensive ART not likely for genetic strategies so lateral thinking is needed. [ABSTRACT FROM AUTHOR]

In extremely cold regions with frequent extreme weather conditions, coupled factors make concrete corrosion by garbage landfill leachate become more complicated. Although previous studies have characterized the effects of individual factors, the mechanisms of coupled effects under specific conditions require further research. Therefore, this study analyzed the individual and coupled effects of landfill leachate, salt solution, and freeze–thaw cycles. The corrosion mechanism of landfill leachate was explained by analyzing the mechanical properties, surface morphology, and microstructure of the concrete. The individual factor tests showed that landfill leachate affected the performance of concrete more significantly than salt solution in the short term. In the immersion tests, the strength of concrete specimens corroded by landfill leachate was always minimized throughout the process, and the compressive and flexural strengths of concrete in landfill leachate decreased by 6.40% and 7.83%, respectively. In the coupled tests, freeze–thaw cycles amplified the effect of landfill leachate on concrete, exhibiting more severe damage than that with only landfill leachate. After four test cycles, the compressive strength of the concrete in the coupled test group decreased by 22.5%, 19.7%, and 31.3% and the flexural strength decreased by 40.2%, 26.7%, and 46.3%, respectively. Through surface morphology and microstructure analyses, we found that the inorganic salt ions in the landfill leachate reacted to form expansive ettringite and gypsum, which initially optimized the internal structure of the concrete but caused severe damage in the later stage. Concrete corrosion by landfill leachate was significantly enhanced under the influence of freeze–thaw cycles. The experimental results of this study provide basic data and theoretical support for designing and protecting concrete buildings in extremely cold environments. Practical Applications: The deterioration of concrete buildings in landfills by landfill leachate corrosion has received widespread attention, and this problem is pronounced in cold regions. This study selected landfill leachate, salt solution, and freeze–thaw cycles as the corrosion conditions for the concrete corrosion test under one-factor conditions. At the same time, landfill leachate and salt solution were coupled with freeze–thaw cycles for the concrete corrosion test. The severity of concrete damage was compared by the changes in mechanical properties and microscopic morphology of the concrete during the test. The results of the one-factor corrosion test showed that the landfill leachate would cause more damage to the concrete in the short term. Meanwhile, the coupled-factor corrosion test results showed that freeze–thaw cycles amplify concrete corrosion by landfill leachate, resulting in a significant reduction in the mechanical properties of concrete and damage to the internal structure. In addition, the study characterized the mechanism of action of landfill leachate corrosion on concrete. This could also provide theoretical support for constructing and protecting concrete structures in landfills in cold regions. [ABSTRACT FROM AUTHOR]

Subsidized insurance against extreme weather events improves affordability among households in at‐risk areas but it can weaken the risk signal via property prices. Leveraging a granular data set of all property transactions and flood events in England, we study the effects of a reinsurance scheme that lowers insurance premiums for at‐risk properties. We document that the introduction of this scheme increases prices and transaction volumes of flood‐prone properties. This fully offsets the negative direct effects of flooding on property prices, with high‐income areas and high‐value properties benefiting relatively more. Our findings speak to the debate on climate adaptation policies and their consequences for wealth distribution. [ABSTRACT FROM AUTHOR]

One of society's most pressing challenges in the twenty-first century is that of climate change. In fact, climate change is seen as the most defining issue of our time as we are witness to an anthropogenic perturbation in geology and earth sciences of global scale. To move forward in this new era, solutions will be sought to both mitigate the effects of climate change (e.g., reduce greenhouse gasses) as well as adapt and build resilience (e.g., improve infrastructure and agriculture to resist damage from extreme weather or floods). The immediacy of the needed solutions dictates that the response must use the full force of society's current knowledge base, science, technology, and innovation. Nanotechnology, an enabling technology that has matured over the past few decades and now considered for general-purpose and mass use, is ideal for addressing climate change and its impacts. To position nanotechnology to address such complex challenges, this Perspective integrates collective insights from a broad range of viewpoints and presents recommendations for how research can be motivated and scoped, organized, and implemented to achieve beneficial outcomes and innovations in the most efficient ways. While this Perspective was created with a focus on the research landscape within the United States, the findings are also relevant in other international contexts. Research that can effectively advance nanotechnology solutions will be use-inspired basic research, incorporate systems-level thinking, apply a convergence research approach, engage stakeholders, and require advanced nanotechnology infrastructure. By illuminating this compelling and complex research topic, this Perspective aims to direct, inform, and accelerate needed actions in the research community to advance nanotechnology solutions for addressing climate change. [ABSTRACT FROM AUTHOR]

Climate change has caused devastating extreme weather in East and South Asia during the summer of 2022. The Ooty muon telescope records short-term variations in muon intensity during major thunderstorms, termed thunderstorm-induced muon events (TIMEs). As part of the GRAPES-3 experiment, the telescope detects approximately 370 billion muons every summer. Its excellent angular resolution validates the TIMEs with small directional variations. In the summer of 2022, the telescope detected 18 TIMEs, compared to eight in the previous summer. A sudden increase in TIMEs is possibly a harbinger of climate change. [ABSTRACT FROM AUTHOR]

Wicked problems of climate change, extreme weather events, pandemics, and rising inequality are pushing businesses to explore the next frontiers of resilience, innovation, and sustainability. Although previous studies have examined diverse aspects of resilience, innovation, and sustainability independently, attempts to integrate all three are limited. Further, in the literature, there is a growing need to adopt an interdisciplinary approach to regeneration for solving wicked problems. We aim to address this gap by combining a systematic literature review with practice review methodology to unearth evidence and research themes that integrate resilience, innovation, sustainability, circularity, and regeneration. In this paper, we present 10 cases, including diverse businesses and Net Zero Cities that have adopted business practices for regenerative, sustainable, and circular value creation. In doing so, we extend the discourse on sustainable or circular business models by proposing a definition of regenerative innovation and developing four archetypes of regenerative innovation (urban transformation innovation, technological innovation, responsible innovation, and business model innovation). We draw from the theoretical lens of socio-ecological systems to present nature as the key stakeholder for regenerative businesses. We make novel contributions to theory, practice, and policy by highlighting a new system-based paradigm of regenerative innovation for future resilient products and services. [ABSTRACT FROM AUTHOR]

The output of photovoltaic power stations is significantly affected by environmental factors, leading to intermittent and fluctuating power generation. With the increasing frequency of extreme weather events due to global warming, photovoltaic power stations may experience drastic reductions in power generation or even complete shutdowns during such conditions. The integration of these stations on a large scale into the power grid could potentially pose challenges to system stability. To address this issue, in this study, we propose a network architecture based on VMD-KELM for predicting the power output of photovoltaic power plants during severe weather events. Initially, a grey relational analysis is conducted to identify key environmental factors influencing photovoltaic power generation. Subsequently, GMM clustering is utilized to classify meteorological data points based on their probabilities within different Gaussian distributions, enabling comprehensive meteorological clustering and extraction of significant extreme weather data. The data are decomposed using VMD to Fourier transform, followed by smoothing processing and signal reconstruction using KELM to forecast photovoltaic power output under major extreme weather conditions. The proposed prediction scheme is validated by establishing three prediction models, and the predicted photovoltaic output under four major extreme weather conditions is analyzed to assess the impact of severe weather on photovoltaic power station output. The experimental results show that the photovoltaic power output under conditions of dust storms, thunderstorms, solid hail precipitation, and snowstorms is reduced by 68.84%, 42.70%, 61.86%, and 49.92%, respectively, compared to that under clear day conditions. The photovoltaic power prediction accuracies, in descending order, are dust storms, solid hail precipitation, thunderstorms, and snowstorms. [ABSTRACT FROM AUTHOR]

In the Earth's general circulation, polar jets act as baroclinic pumps of angular momentum and heat. Reanalysis datasets indicate that shear changes near jets induce upward displacements of the jet cores, suggesting a weakening thermodynamic pumping over the last 50 years. From secondary flow theory, a well‐established principle in fluid dynamics, an increased frequency of heatwaves and persistent winter storms is expected. The ageostrophic wind shear between 700 and 50 hPa indicates the strength of this secondary circulation. The weakening tendency during the reanalysis period also exists in multimodel simulations under the RCP8.5 emissions scenario for the 21st century. The reduction between the periods 2005–2025 and 2081–2100 reaches 18%, 5.3% and 19%, respectively, for the North America, Mid‐Europe and East Asia sectors of the Northern Hemisphere polar jet. Within this background, cold‐surge events are the result of synergic co‐working of several factors. The occurrence trend for transitional season winter extreme events also is examined. The winter extremes seemingly have larger temperature drops. However, in a warming climate, they emerge more rapidly from extreme cold states. The storm tracks, especially over North America, have equatorward extensions, indicating that winter storms can reach lower latitudes. Due to the temperature‐dependence of air viscosity, secondary flows decrease more slowly than the main zonal flow. This imposes an important adjustment to the traditional polar amplification effects on midlatitude winter extremes. During a warmer winter (the primary manifestation of a warmer climate), spatially uniform positive trends in cold extreme events are not expected. There are, however, regions experiencing more winter extremes. These regions show consistent patterns in both the reanalysis period and the remainder of the 21st century. [ABSTRACT FROM AUTHOR]

ABSTRACT Climate change and associated risks of extreme weather has led to growing interest in drought‐tolerant species such as lucerne (Medicago sativa L.), tall fescue (Festuca arundinacea Schreb.) and cocksfoot (Dactylis glomerata L.) in mixed grass‐legume forage production in North‐Western Europe. Lucerne and grasses have distinct nutritive value that can be combined when grown in mixtures. The extent of a ‘net mixture effect’ (NE) on the nutritive value, that is the deviations of the mixture quality from the expected one derived from the pure stands, has not been studied in any depth and requires further investigation in the context of climate change. The present study was conducted at four sites during two main cropping years with the aim of comparing potentially drought‐tolerant mixtures against pure stands. With significant sward type × site × year interactions, nutritive value of the mixed swards often differed significantly from pure stands, ranging intermediate between the component pure stand nutritive value. The concentration of water‐soluble carbohydrate (WSC) did not differ between mixtures and lucerne pure stands. Significant NE were found, with larger measured concentrations in mixtures compared to those predicted, for neutral and acid detergent fibre and the crude protein:WSC ratio. The concentrations of WSC and metabolizable energy were smaller than expected. The NE was not influenced by sward type or species number, except for WSC at a few sites. The results show that improved knowledge of positive mixing effects could be used to specifically enhance the nutritive value in grasses‐lucerne mixtures irrespective of sward diversity. [ABSTRACT FROM AUTHOR]

Climate change poses an unprecedented challenge to human development. Despite recent efforts by organizations like the IPCC to integrate social perspectives, the article contends that a more substantial contribution from social scientists is essential. This article argues for the integration of social scientific perspectives, particularly within the realm of health, to comprehend climate change as both a consequence and a driver of social change and human behavior. It highlights the necessity of acknowledging the interplay between socioeconomic systems, capitalist expansion, and environmental degradation, particularly emphasizing the impact of climate change on health. By reframing climate change as contingent on social phenomena, new avenues for understanding and addressing the issue emerge. The article proposes a shift from a narrow focus on direct health impacts of extreme weather events to a broader consideration of subtler yet equally detrimental effects on health, such as reduced food and water availability, increased infections, mental health concerns, displacement, and migration. Furthermore, it advocates for embracing an expanded conception of health, integrating planetary health principles that underscore the interconnectedness of ecosystems and human well-being. In addition, the article contends that existing frameworks still lack adequate incorporation of postcolonial perspectives, necessitating a deeper examination of historical legacies of conquest and exploitation. By adopting an assemblage model that acknowledges the complex interplay of historical continuums and global inequalities, this article offers a critical appraisal of current interpretations of climate change and health. It emphasizes the imperative of rehabilitating planetary health as a prerequisite for human well-being while acknowledging and addressing the enduring impacts of colonialism and colonial logics of conquest on land, bodies, and histories. [ABSTRACT FROM AUTHOR]

Arctic Oscillation (AO) is the dominant mode of atmospheric circulation in the extratropical Northern Hemisphere regions. The spatial pattern of the AO Arctic center affects the extent of polar cold air outbreaks southward. However, the underlying nature and causes of its interdecadal variation remain unclear. Utilizing ERA5 reanalysis data, this study identifies two distinct spatial patterns of the wintertime AO Arctic center through the K‐means clustering method, which alternate over different decade periods. The Double‐trough pattern generates a tripolar temperature pattern of "cold Arctic‐warm Eurasia‐cold Tibetan Plateau" through a Rossby wave train during 1960–1997/2013–2024. While the Single‐trough pattern leads to a dipolar temperature pattern in 1998–2012. Furthermore, interdecadal variations in North Atlantic sea surface temperature meridional gradient act as an influencing factor in shaping the spatial pattern of the AO Arctic center. This research aids the understanding and prediction of climate anomalies using AO signals within various decadal contexts. Plain Language Summary: Arctic Oscillation (AO) is a key extratropical atmospheric variability mode in the Northern Hemisphere, significantly influencing weather and climate anomalies in the mid‐latitudes. The shape of AO's trough in the Arctic center governs the southward advancement of Arctic cold air. Using the K‐means clustering method, the spatial patterns of the wintertime AO Arctic center are primarily divided into two distinct categories, which alternate across different decades. Specifically, from 1960 to 1997 and 2013 to 2024, the AO Arctic center exhibits dual troughs over the Ural Mountains and North America, resulting in a distribution of "cold Arctic‐warm Eurasia‐cold Tibetan Plateau." However, during the period from 1998 to 2012, only the North American trough is present, and its temperature connection with Eurasia weakens. Notably, interdecadal variations in the AO Arctic center are affected by North Atlantic sea surface temperature meridional gradient. This study enhances our understanding of the physical significance of AO and assists us in better utilizing it to predict winter weather and climate anomalies. Key Points: The AO Arctic center shows two spatial patterns alternating between Double‐ and Single‐trough configurations on an interdecadal timescaleThe two spatial patterns of the AO Arctic center are modulated by the interdecadal variations of North Atlantic SST meridional gradientThe Double‐trough pattern of the AO Arctic center can cause a unique tripolar pattern of "cold Arctic‐warm Eurasia‐cold Tibetan Plateau" [ABSTRACT FROM AUTHOR]

Solar power will become the largest renewable energy source, contributing to global carbon neutrality. In addition to the well‐recognized temporal intermittency of solar energy supply, the local energy demand to cope with extreme weathers can further stress the energy grid; both the supply and demand can be greatly influenced by future climate change. Here, we redefine solar drought events by considering supply demand imbalance in solar power. Observation and multi‐model simulations reveal an anthropogenic exacerbation of global solar drought frequency in the past three decades. Moreover, compared to the pathway SSP2‐4.5, the carbon neutrality pathway SSP1‐2.6 can mitigate the increasing frequency and severity of solar droughts by 60% and 63% in the 2090s, respectively. Our study suggests a co‐benefit of solar energy stability and security toward carbon neutrality, especially in developing nations where the local supply demand imbalance is a major issue. Plain Language Summary: Solar power is a key renewable source to support the formidable target of carbon neutrality in the coming decades. However, the supply and demand of solar power are both influenced by future climate change. To our knowledge, no studies have provided an integrated perspective of both the supply and the demand side and the potential imbalance lasting for 3 days due to the more impactful compound events. In this study, we first develop an index (SDI) to describe the dynamic changes of Supply Demand Imbalance relationship in solar power and then quantify the potential risk of solar droughts at the global scale. Based on observation and simulations, we reveal an anthropogenic exacerbation of global solar drought frequency in the past three decades. Furthermore, we project notable regional inequality in the possible energy imbalance and highlight the mitigating effect of the carbon neutrality policy on increasing frequency and severity of solar droughts toward the end of the 21st century. Key Points: The frequency of global solar droughts shows large spatial heterogeneityGHG forcing dominates the increasing solar droughts worldwide in the past three decadesThe increasing frequency and severity of solar droughts can be greatly mitigated by a carbon neutrality policy toward the end of the 21st century [ABSTRACT FROM AUTHOR]

ABSTRACT Warm fronts often trigger significant weather changes, which also play a role in many extreme weather incidents. Therefore, it is crucial to understand the location and characteristics of warm fronts to accurately forecast weather changes. However, warm fronts are more difficult to identify than cold fronts on average, since the gradients can be weaker and shallower. This paper proposes a new objective method for identifying warm fronts in the Eurasia region using ERA‐5 hourly reanalysis data. The method uses the appropriate thermal front parameter and warm advection threshold to identify the potential warm frontal zone, then determines the corresponding warm boundary according to the predominant wind direction within the frontal zone, and finally locates the warm front line along the warm boundary. In various weather processes, the location and shape of the objective warm front correspond well with the distribution of weather systems and meteorological elements, indicating the effectiveness of the method. Meanwhile, the high agreement between objective and manual warm fronts further supports the reliability of the method. Furthermore, this method is applied to the long‐term datasets covering Eurasia, enabling an exploration of the climatological characteristics of warm fronts in the region. The study reveals distinct seasonal patterns in warm front frequency, with the highest frequency occurring during winter and the lowest during summer. Warm fronts are notably active in Europe, the Siberian Plain, the Northeast China Plain extending to the Western Pacific during winter, spring, and autumn. The dataset of warm fronts produced by this method proves valuable for climate change research. [ABSTRACT FROM AUTHOR]

Low production potential of arid regions heightens vulnerability of farms to market shocks and extreme weather events. Here we examine African smallholder farmer perceptions of climate change, including perceived (intended) and actual adaptation strategies. We invoke survey questionnaires, focus group discussions, interviews and meteorological data to compare smallholder perceptions with actual weather events realised. We showed that most communities perceived climate change through the lens of perturbations to rainfall and temperature. Perceived increases in precipitation, indicated by 62% of respondents, and increased temperature, indicated by 77% of participants, aligned well with evidence shown by meteorological data. Around 88% of respondents identified prolonged drought as the most frequent extreme weather, followed by unseasonal rainfall (86% of respondents). Diversification of pasture fodder species and access to technology enabling timely weather forecasts were preferred actual and intended adaptation strategies, respectively. Recurrent and prolonged drought, spurious seasonal weather patterns, and lack of access to timely weather prognostics were the primary constraints to adoption of practices aimed at climate change adaptation. While farm size and practitioner experience were not associated with adaptive capacity, awareness of climate change impact potential and household income significantly influenced the rate and extent of adoption. We revealed a marked influence of gender in adaptation to the changing climate, with households where males made decisions exhibiting 76% adoption, compared with 34% of households adopting climate adaptations where decisions were made by females. Taken together, our study narrates critical roles of knowledge, finances, and gender in enabling or inhibiting adaptation to the climate crisis. [ABSTRACT FROM AUTHOR]

Globally, increasing occurrences of forest fires are major threats to the ecosystem. The rich forests in the Himalayas also suffer from high incidents of forest fires in the pre‐monsoon summer months, March to June. Research studies are limited in identifying the meteorological factors governing the spatiotemporal distribution of forest fires. Using three satellite‐based data sets of monthly burned area (BA) for March to June, we found higher BA in the Eastern Himalayas (EH) compared to the Central (CH) and Western Himalayas (WH). Using statistical methods, we found Vapor Pressure Deficit (VPD) to be the most dominating variable controlling BA in the Himalayas. Precipitation, soil moisture and temperature, with their relative variability, control VPD that governs the interannual and intraseasonal variations of BA. Our results imply that a good forecast of VPD will facilitate alert generation for the Himalayan forest fires. Plain Language Summary: The Intergovernmental Panel on Climate Change's sixth assessment report warns of a substantial rise in global forest fires due to climate change. This threatens biodiversity, pollution, soil erosion, human health, and exacerbates global warming. In India, 54.4% of forests are fire‐prone, with the Himalayas, a critical biodiversity hotspot, hosting 13% of the nation's forests. Forest fires here can significantly impact global and regional socio‐economies. While global literature discusses meteorological factors influencing forest fires, the Himalayan region remains underexplored in this context. The present study, the first of its kind, focuses on the Himalayas during peak fire months (March–June) and finds an increasing trend in burnt areas over the Himalayas. The eastern Himalayas were found to be more prone to forest fires, which peak in March–April because of a substantial number of dry days. We found that precipitation, temperature, and soil moisture govern the variability of vapor pressure deficit (VPD), which controls BA. Emphasizing VPD as the primary driver of Himalayan forest fires, the study highlights the necessity for extensive monitoring to develop effective management and mitigation strategies in this unique biodiversity hotspot. Key Points: The spatial extent of the forest burned area is increasing across the entire HimalayasThe Eastern Himalayas show a higher forest burned area than the western and central HimalayasVapor pressure deficit governs the interannual and intraseasonal variations in the forest fire extent [ABSTRACT FROM AUTHOR]

To cope with the increasingly serious electromagnetic pollution, the demand for electromagnetic interference (EMI) shielding materials with low electromagnetic wave reflection ability has become urgent. Controlling electrical components, magnetic components, and designing the EMI material structure can effectively improve electromagnetic shielding performance, but this remains a significant challenge. Besides, extreme cold weather conditions also do considerable potential damage to the normal work of outdoor electronic equipment. Integrated light‐to‐heat conversion capability on electromagnetic shielding materials can further improve the stability and reliability of the equipment. Herein, the novel bilayer aerogels composed of zeolitic imidazolate frameworks derived hollow CoNi carbon nanocage/MXene Ti3C2Tx/nanocellulose (BZMN) are prepared by a two‐step freezing method. BZMN aerogels exhibit good EMI shielding effectiveness (SE) with low reflection coefficient (R coefficients): 35.1 dB (R coefficient = 0.28) and 21.2 dB (R coefficient = 0.25). The unique structures of bilayer aerogels demonstrate the ability to absorb more electromagnetic waves through interfacial polarization and multiple scattering. The green shielding index (gs) of BZMN aerogels can reach 2.88. Moreover, BZMN aerogels show remarkable and unique light‐to‐heat conversion performance on different surfaces. Under 2.0 sun intensity, temperatures can reach 109.3 °C in the upper layer and 102.3 °C in the lower layer. Under 0.8 W cm−2 near‐infrared (NIR) laser intensity, the temperatures can rise to 234.1 °C in the upper layer and 167.4 °C in the lower layer. In addition, the size and shape of BZMN aerogels can be customized according to the mold. These features present BZMN aerogels as advanced potential low reflection EMI shielding device candidates, useful for future telecommunication and electronic equipment protection. [ABSTRACT FROM AUTHOR]

Mangroves protect coasts from extreme weather and erosion but can be destroyed by climate change and harvesting. However, there is no consistent formulation of protective capacity that integrates key factors such as area, width, height, and health. Here, we quantified and analyzed a process-based measure of mangrove coastal protection index (MCPI) incorporating cross-shore width, canopy height, and the normalized difference vegetation index (health index). Width/area generally declined at low rates but width increases in some regions reduced MCPI. Cluster exchange network analysis from 2007 to 2019 showed an 800% increase in mangrove forests with characteristically low height, width, and MCPI. Globally, this suggests a 25% decrease in MCPI from 2007 to 2019, primarily from height/biomass change, compared to a 2% decrease in area. Relatively sheltered low-latitude high mangrove strands (>20 m) of high-MCPI appear to be resilient to destruction from cyclones. In contrast, our results highlight an alarming, widespread decline in low MCPI, particularly along coasts exposed to deep water, possibly in concert with human destruction, cyclones, and intensifying oceanic boundary currents. This study assesses the protective capacity of mangroves by incorporating their width, height, and health. It reveals that while mangrove area remained relatively stable, the coastal protection capacity declined by 25% from 2007 to 2019 due to significant decreases in height and biomass. This decline poses risks for coastal regions, particularly those vulnerable to climate change and human activities. These findings underscore the urgent need for enhanced conservation efforts to preserve mangrove ecosystems and their protective functions. [ABSTRACT FROM AUTHOR]

Background: Frontline clinics - primary care clinics that predominantly serve low-income and socially disadvantaged communities - are facing increasing impacts from climate-related extreme events. This study evaluated staff perspectives at frontline clinics on the health risks of climate change, the impacts of extreme events on their clinics and patients, and their motivators to improve climate resiliency. Methods: A national, cross-sectional survey was conducted of staff working at frontline clinics including administrators, case workers, and providers across the United States. Survey questions assessed clinic and respondent attributes, knowledge of health risks of climate change, preferences for climate change educational and operational resources, and clinic and patient climate impacts and resilience. The survey was distributed electronically to a convenience sample of primary care clinics and to the National Association of Community Health Centers (NACHC) and National Association of Free and Charitable Clinics (NAFC) listservs. Data was collected from September to November of 2021. Respondents were current staff who consented to the survey. Responses were collected via Qualtrics, and the statistical analysis was completed using Stata. Results: A total of 430 surveys were completed representing clinics in 43 states. Most (82.0%) respondents reported human activities were causing climate change. Over half (52.8%) of respondents reported an operational disruption to their clinic from extreme events in the past 3 years, and another 54.4% had plans in place to address risks from extreme events. The most useful resources identified to improve operational resilience were checklists and planning guidance. Over half (52.0%) of respondents reported they were motivated to use these resources to improve clinic preparedness. Most (84.4%) providers and case workers reported that climate change impacted patient health, however only 36.2% discussed health risks with patients, with barriers including more pressing topics and time available. Another 55.7% of respondents reported they were motivated to learn ways to help patients prepare for extreme events. Conclusions: Climate-related extreme events were reported to impact patient health and disrupt frontline clinic operations. Overcoming gaps in knowledge about climate change impacts on health and providing climate educational resources can engender motivation to improve clinic and patient resilience to climate change. [ABSTRACT FROM AUTHOR]

The escalating severity and frequency of extreme weather conditions, such as typhoons and thunderstorms, exacerbate the failure risk of transmission lines. In this study, a series of wind tunnel tests were conducted to investigate the rain-wind-induced vibrations (RWIVs) on an overhead transmission conductor. First, a conductor sectional model was fabricated to accurately represent the physical appearance and material of the prototype conductor. Then, experimental wind-rain conditions were simulated to investigate the impact of rainfall on the cross-wind buffeting vibration of the conductor, with attempts made to reproduce the phenomenon of RWIVs. Meanwhile, section model vibration tests were conducted on the conductor model with an artificial rivulet to investigate the effects of rivulet position, dynamic characteristics, mass, and wind yaw angle. Finally, high-frequency force balance (HFFB) tests were performed on the same conductor model, and the mechanism of the RWIVs was discussed from the viewpoint of galloping. The results indicated that the presence of rainfall slightly decreased the in-plane vibrations of the conductor when no RWIVs occurred. Due to the interference from the spiral aluminum wires on the conductor surface, this type of conductor is less susceptible to RWIV compared to smooth cables. The conductor model with an artificial rivulet exhibited significant vibrations at position angles 휃 = 48∘–60∘, essentially corresponding to negative Den Hartog coefficients. [ABSTRACT FROM AUTHOR]

Background: Extreme weather is a recognised risk factor for stillbirth and preterm birth, disrupts women's access to healthcare during pregnancy and childbirth, and negatively affects the care of newborns. Reliable and accessible heat and weather warning systems are key in alerting individuals to undertake protective measures. There is a notable gap in understanding how women and caregivers in rural East Africa perceive and utilize weather information. We investigated community members' heat and weather warning information-seeking behaviour, identified available sources, assessed their reliability and utility, and examined their influence on behaviour. Settings: Our research was conducted in rural Kilifi County in Kenya's coastal region. The area experiences temperatures exceeding 23°C throughout the year, with extended periods of extreme temperatures [> 40°C] and long and severe droughts. Methods: We conducted in-depth interviews [IDI] with pregnant and postpartum women [n = 21] and held six focus group discussions [FGDs] involving mothers-in-law and community health volunteers [CHVs]. The data were analysed in NVivo 12 using both inductive and deductive approaches. Results: We found significant gaps concerning pregnant and post-partum women, and their caregivers, having timely access to weather forecasts and heat information from health or meteorological authorities. Information on heat and weather warnings is disseminated through various channels, including television, radio, mobile phones, and word of mouth, which are facilitated by community influencers such as CHVs and local chiefs. Indigenous methods of weather forecasting, such as cloud observation, consulting local "rainmakers", and studying the behavioural patterns of amphibians, are employed in conjunction with warnings from the Kenyan Meteorological Department (KMD). Barriers to accessing weather information include the cost of television and smartphones and a lack of segmented information in local languages. Conclusions: National and county meteorological services need to enhance public participation, communication, and the delivery of heat and weather information to guide community-level response measures and individual behaviour change. They should also collaborate with health professionals to address heat risks for vulnerable groups. Further research is needed to empower indigenous weather predictors with modern weather information and revise national policies to deliver tailored messages to vulnerable populations like pregnant and postpartum women. [ABSTRACT FROM AUTHOR]

The article "ArboItaly: Leveraging open data for enhanced arbovirus surveillance in Italy" discusses the importance of arboviruses, such as West Nile, chikungunya, and dengue, and their impact on public health. It highlights the need for robust public data and genomic surveillance systems to monitor and respond to these diseases effectively. The creation of ArboItaly, a centralized repository for arboviral disease surveillance in Italy, aims to consolidate epidemiological data and facilitate targeted control measures. The article emphasizes the significance of international collaboration and information sharing to address the evolving threat of arboviruses globally, especially in the context of climate change and increasing disease transmission risks. [Extracted from the article]

Climate change's effect on agriculture is a severe problem in every society, particularly in West Africa. The rising temperatures and extreme weather events have significant implications for food security. In this study, we examine the effects of CO2 emissions, agricultural advancements, and food availability on economic growth in West Africa from 1990 to 2020, using a panel ARDL approach with data from 14 countries. The analysis evaluates both long- and short-term effects, with the Dynamic Fixed Effects (DFE) estimator chosen as the most robust model. Results show no significant link between CO2 emissions and economic growth, while agriculture plays a key role, and food availability has mixed effects. The findings underscore the importance of sustainable agriculture and food security in promoting economic resilience in West Africa, offering insights for policymakers. [ABSTRACT FROM AUTHOR]

Flash droughts are rapidly developing extreme weather events with sudden onset and quick intensification. Global prediction of flash droughts at sub‐seasonal time scales remains a great challenge. Current state‐of‐the‐art dynamic models subject to large errors and demonstrate low skills in global flash drought prediction. Here, we develop a machine learning‐based framework that uses meteorological forecasts as inputs to predict global root‐zone soil moisture and flash droughts from 1 day to 2 week lead times. The results indicate that 33% and 24% global flash drought onset and termination events can be correctly predicted by machine learning at 7 day lead time, versus 19% and 11% fractions by state‐of‐the‐art dynamic model. The developed machine learning model demonstrates substantial improvements over dynamic model in global soil moisture prediction, and thus enhances global flash drought forecasting skills in space and time. The presented framework may benefit global flash drought prediction and early warning at sub‐seasonal scales. Plain Language Summary: Global flash drought risks are prevailing currently and will continue to be an important concern under climate change. Skillful prediction of global flash drought onset and termination events can provide critical early warning information for agricultural preparations and water resources management. However, current weather forecasting models suffer from large errors in root‐zone soil moisture and flash drought predictions. Here, we develop a machine learning‐based framework that could predict 33% and 24% global flash drought onset and termination events at 7 day lead time, better than the state‐of‐the‐art dynamic model. The machine learning‐based framework can reduce soil moisture prediction errors in dynamic coupled models and thus enhances global flash drought prediction skills. The proposed machine learning forecasting approach may provide scientific advances for flash drought early warning at global scales. Key Points: Machine learning is used for global flash drought prediction up to 2 week lead time33% and 24% global flash drought onset and termination events can be correctly predicted at 7 day lead timeMachine learning improves global flash drought prediction over dynamic model [ABSTRACT FROM AUTHOR]