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As the global community faces the escalating challenges posed by climate change, there is an increasing need for innovative tools that enhance public awareness and understanding of the complex and dynamic nature of environmental shifts. This paper introduces a Climate Change Visualization Awareness System (CCVAS), designed to bridge the gap between scientific data and public comprehension through immersive and accessible visualizations. Leveraging cutting-edge technologies, including augmented reality, interactive mapping, and data analytics, CCVAS provides users with real-time and historical insights into key climate indicators such as temperature variations, sea level rise, and extreme weather events. The CCVAS employs a user-centric approach, tailoring information to diverse audiences and promoting engagement through intuitive interfaces. Community engagement features facilitate collaborative efforts among users, enabling the sharing of experiences, knowledge, and initiatives aimed at addressing climate change challenges at the local and global levels. Users will be able to participate in discussions, organize events, and access community-driven resources within the CCVAS platform. Personalized user profiles enable individuals to customize their climate change experience within CCVAS, tailoring content and visualizations to their specific interests, expertise, and geographical locations. By providing personalized recommendations, alerts, and action plans based on user preferences and behavior, CCVAS will empower individuals to take meaningful steps towards climate resilience and sustainability in their daily lives. This paper outlines the architecture, functionality, and potential applications of the Climate Change Visualization Awareness System. [ABSTRACT FROM AUTHOR]

This paper employs an innovative event study methodology to demonstrate the impact of climate change on the NASDAQ index from the unique perspective of extreme weather events. This is achieved through the application of the event study methodology to a total of 526 biological, climatic, geological, hydrological, and meteorological disasters of climate change occurring in the U.S. during the period of 2000–2019. The results of the study demonstrate that: ① it can be generally observed that the five dimensions of climate change have a significant impact on stock returns. ② Empirical evidence indicates that the impact of different climate change dimensions on the return rate of stocks from NASDAQ stocks varies. In contrast, the biological and hydrological dimensions have a significantly negative impact on the return rate of stocks from the NASDAQ index, while the climate dimension has a significantly positive impact on the return rate of stocks from the NASDAQ index. ③ From the perspective of time, the impact of the five dimensions of climate change on the stock yield exhibits certain non-linear characteristics. This can be observed in the phenomenon of shock reversal, which occurs before and after the event. [ABSTRACT FROM AUTHOR]

The existing body of research into the environmental and socio-economic benefits of green infrastructure supports the case for it to be positioned as a form of critical infrastructure, particularly in urban settings. It is broadly recognized that extreme weather and climate change pose significant risks to critical infrastructure systems linked to the provision of services, including electricity, water, communications, and transport, and consequently risk assessments and associated adaptation strategies are common practice. However, although green infrastructure is also at risk from extreme weather and climate change, threatening the realization of benefits that it can deliver in urban settings, associated risks to green infrastructure are not widely understood or assessed in practice. This paper discusses the status of existing research on this topic and uses this as a foundation for a Greater Manchester (UK) case study that assesses the risk of low water availability to grassed areas, which represent a key element of the city-region's green infrastructure. In doing so, the paper demonstrates how risks linked to extreme weather and climate change can be assessed spatially to inform green infrastructure planning. In summary, this paper aims to raise awareness of extreme weather and climate change risk to urban green infrastructure, present an empirical case study and associated methodological approach on this topic, and ultimately support efforts to enhance the resilience of urban green infrastructure to extreme weather and climate change. [ABSTRACT FROM AUTHOR]

Climate change is a financial risk to companies, and those that disregard this will have to deal with losses due to extreme weather events, new regulations, or the disruption of the supply chain. Companies must disclose climate-related financial implications to enable informed decision-making by investors and other stakeholders. Any indifference or disregard for climate-related disclosures will harm the investors who may trade based on insufficient information and prices of securities that do not account for climate risks. In India, disclosures are mandated for companies under the Companies Act 2013 and various Securities and Exchange Board of India Regulations. This paper will explore the adequacy of the current disclosure regime concerning climate change and argue that, although information regarding climate risks falls within the ambit of the current set of mandated disclosures, it is insufficient. The paper concludes by making a case for mandatory climate disclosures under the Companies Act. [ABSTRACT FROM AUTHOR]

Purpose: Social housing offers occupants comfort, safety and protection against extreme weather conditions. However, social housing occupants in various regions of Nigeria face various challenges. This paper aims to use a quantitative approach to examine the factors that contribute to the challenges faced by occupants in social housing within a semi-arid climate of Nigeria. Design/methodology/approach: An exploratory cross-sectional survey was used to administer 1,032 copies of structured questionnaires to occupants of social housing in Maiduguri, one of the largest urban centers of the semi-arid climate in Nigeria. A total of 955 responses were retrieved, giving a response rate of 92.5%. The statistical model used in analyzing data was relative importance indices and factor analysis. Findings: The results show that poor quality of FM services provided, poor maintenance of building components, damage to materials and valuables in the Harmattan period and housekeeping problems due to dust deposition in doors, while the poor response to occupants' complaints/reports is the least among the occupants' challenges in order of importance. Moreover, the results of the factor analysis further established that inadequate FM services and poor environmental conditions are the two factors contributing to the occupants' challenges in social housing within the semi-arid climate of Nigeria. Originality/value: This paper seeks to examine the factors contributing to social housing occupants' challenges in the semi-arid climate of Nigeria. The paper should inform policymakers, academics and professionals. [ABSTRACT FROM AUTHOR]

In this paper, we investigated Cold Air Outbreaks (CAOs) in Hungary using temperature data from ten weather stations located near populous Hungarian cities. Our main motivation for performing this research was the fact that in this rapidly changing climate, these events continue to represent a threat to infrastructure and human life, such as the outbreaks experienced in early 2021 (e.g., Texas, USA) and late 2022 (Winter Storm Elliott). In addition, no comprehensive study of CAOs in Hungary has been conducted using station data. The definition of CAO used in this paper is that the daily mean temperature had to be in the lower 10th percentile of the daily climatology for five consecutive days, and we allowed a maximum two-day gap between periods matching the criteria above, after which we merged events together. We found that the number of CAOs in Hungary decreased considerably in recent decades (due to increasing mean temperatures), and the climates of the investigated stations became increasingly homogenous. Developing our understanding of CAOs around the world is important because, due to climate change, their seasonal distribution may change in a way that negatively impacts our life and economy. [ABSTRACT FROM AUTHOR]

Electric power systems face heightened risks from climate change, on top of existing challenges like aging infrastructure, regulatory shifts, and cybersecurity threats. This paper explores how advanced technologies, including smart grids, artificial intelligence (AI), and machine learning, (ML), enhance the resilience of power systems against climate-driven extreme weather events. Drawing insights from resilience theory, the paper presents a state-of-the-art review of the literature on power system resilience, highlighting the escalating vulnerabilities of energy systems to weather-related disruptions. Although utilities currently use technologies like automated meter reading and advanced metering infrastructure to collect vital grid performance data, the lack of strategic collaboration often impedes effective data governance and sharing, thus undermining efficient responses to climate threats. The paper underscores the significance of distributed energy resources, long-duration energy storage, microgrids, and demand-side management. It further illustrates how AI and ML optimize smart grids to support these strategies. Proactive integration of smart grids with advanced technologies could significantly reduce climate-related costs compared to non-adaptive methods. Such proactive grid resilience strategies not only climate-proof energy infrastructure against climatic changes but also herald a modern, placed-based industrial transformation. Climate change exacerbates challenges in our energy systems, from aging infrastructure and a constantly shifting regulatory environment to cybersecurity risks and diversifying energy portfolios. Addressing these issues requires strategic investment in modern infrastructure, particularly smart grids enhanced by advanced technologies like artificial intelligence (AI) and machine learning (ML). These technologies are vital for enhancing power system resilience against climate impacts. Automated systems such as automated meter infrastructure (AMI) and supervisory control and data acquisition (SCADA) provide real-time data crucial for managing extreme weather events. AI and ML contribute to predictive maintenance, preventing failures and blackouts. They also forecast grid loads during severe weather, facilitating proactive power distribution management to prevent blackouts. This comprehensive improvement in situational awareness promotes economic growth in the energy sector and supports sustainable, climate-resilient transformation. AI and ML not only improve energy distribution and efficiency but also promote conservation efforts and ensure reliable energy amidst a changing climate. Collaboration among utility managers, regulators, and governments is key, focusing on data access, verification, and adaptability. Strategies should be tailored to each utility's unique challenges. Moreover, establishing technical standards is critical for enhancing power grid resilience against climate-induced extreme weather events. [ABSTRACT FROM AUTHOR]

Climate change poses a formidable threat to food security in India, a country with a population of over 1.3 billion people heavily dependent on agriculture for their livelihoods. This paper provides an overview of the challenges and potential solutions for addressing the intersection of climate change and food security in India. The impact of climate change, such as altered precipitation patterns, extreme weather events, rising temperatures, and changing pest and disease dynamics, have profound consequences for Indian agriculture, exacerbating the already existing vulnerabilities within the food system, from smallholder farmers to the overall supply chain. The consequences of a disrupted food supply extend to issues of malnutrition, hunger, and socio-economic instability. This paper explores various facets of this complex issue such as the specific challenges faced by Indian agriculture due to climate change and the resultant threats to food security, ongoing efforts and potential solutions, including the adoption of climateresilient crop varieties, precision agriculture, and sustainable water management practices, to mitigate these challenges, and the necessity of policy intervention to enhance climate resilience within Indian agriculture. [ABSTRACT FROM AUTHOR]

Temperate forests are particularly exposed to climate change and the associated increase in weather extremes. Droughts, storms, late frosts, floods, heavy snowfalls, or changing climatic conditions such as rising temperatures or more erratic precipitation are having an increasing impact on forests. There is an urgent need to better assess the impacts of climate change and extreme weather events (EWEs) on temperate forests. Remote sensing can be used to map forests at multiple spatial, temporal, and spectral resolutions at low cost. Different approaches to forest change assessment offer promising methods for a broad analysis of the impacts of climate change and EWEs. In this review, we examine the potential of Earth observation for assessing the impacts of climate change and EWEs in temperate forests by reviewing 126 scientific papers published between 1 January 2014 and 31 January 2024. This study provides a comprehensive overview of the sensors utilized, the spatial and temporal resolution of the studies, their spatial distribution, and their thematic focus on the various abiotic drivers and the resulting forest responses. The analysis indicates that multispectral, non-high-resolution timeseries were employed most frequently. A predominant proportion of the studies examine the impact of droughts. In all instances of EWEs, dieback is the most prevailing response, whereas in studies on changing trends, phenology shifts account for the largest share of forest response categories. The detailed analysis of in-depth forest differentiation implies that area-wide studies have so far barely distinguished the effects of different abiotic drivers at the species level. [ABSTRACT FROM AUTHOR]

Context: This paper introduces the special issue of Pacific Conservation Biology devoted to the natural history of Two Peoples Bay Nature Reserve on the south coast of Western Australia. Methods: This paper provides the background to the special issue. Key results: Two Peoples Bay Nature Reserve was gazetted in 1967 for the conservation of the native biota, including two species; the Djimaalap/noisy scrub-bird (Atrichornis clamosus) and Ngilgaitch/Gilbert's potoroo (Potorous gilbertii), both believed extinct for over 100 years before being rediscovered on the Reserve. The Reserve is 4774.7 ha in area, with wetlands, heathlands, granite outcrops, sand dunes, beaches, cliffs, and islands. Since it was established, mean annual rainfall has decreased by 16.8%, mean annual maximum temperature has increased by 0.2°C, and mean annual minimum temperature has increased by 0.7°C. Conclusions: The paper poses the question: what do the changes of drier winters, hotter summers, and more extreme weather events mean for managers of conservation areas such as Two Peoples Bay? Implications: Changing climate will pose problems for the managers of Two Peoples Bay Nature Reserve in ensuring the conservation of the Djimaalap/noisy scrub-bird and Ngilgaitch/Gilbert's potoroo. Two Peoples Bay Nature Reserve comprises ~5000 ha of wetlands, heathlands, granite outcrops, sand dunes, beaches, cliffs, and islands. Two species, the Djimaalap/noisy scrub-bird and Ngilgaitch/Gilbert's potoroo, were believed extinct for over 100 years before being rediscovered on the Reserve. Since the Reserve was established in 1967, rainfall has decreased, while minimum and maximum temperatures have increased. We ask what the climate change means for managers of conservation areas such as Two Peoples Bay. This article belongs to the Collection The Natural History of Two Peoples Bay Nature Reserve, Western Australia. [ABSTRACT FROM AUTHOR]

The far-reaching effects of climate change are among the leading global concerns today. The impacts of changing climate manifest in rising global temperatures (on land and in the ocean), escalating destructive extreme weather events, increasing biodiversity loss, shifting biomes, growing food insecurity, greater health risks (physical and mental), and involuntary migration of people, among other interconnected factors. The complexity of these problems individually and collectively is receiving extensive consideration in research and public arenas. Concerns about the influences of climate change have been increasing since the 1950s and through the last half of the twentieth century scientific understanding reached a consensus of the causes and numerous negative outcomes. The impacts have become clear in the first decades of the twenty-first century. Researchers in many disciplines are cautioning that the world is rapidly reaching a tipping point in the overall health of the planet, after which recovery will be very difficult. In addition, decision makers are grappling with how to evaluate multiple and sometimes competing calls for action and to decide how to address the issues best. In both research and decision-making settings, grey literature has been a prominent information genre about the multifaceted aspects of climate. Large quantities of grey literature on climate and climate change subjects have been produced. Academic institutions, governmental and intergovernmental bodies, non-governmental organizations, professional associations, think tanks, and news media have turned out grey literature ranging from brochures to hefty technical reports. These materials have been generated in print and digital formats to fulfil a suite of roles: 1) to report research findings, 2) to compile and synthesize literature on research and professional practice, 3) to inform policymakers and the public, 4) to advocate for policy development, 5) to implement policy, 6) to promote change in professional and individual practice, 7) to educate; 8) to broker information and promote networking, and 9) to counter misinformation. In this paper we draw on research about decision making in public policy and management practice about coastal and marine environments to illustrate how grey literature on climate subjects has been deployed in delivering on these roles. Grey literature is widely used in many decision-making contexts. Recognizing its numerous roles can inform citizens, managers, planners, and policy- and decision-makers in addressing the climate challenges facing society today. [ABSTRACT FROM AUTHOR]

Geosites are windows into the geological past, which may be recorded in rocks and their properties, the fossil content, and landform produced by processes no longer operating. Since the histories of sedimentation, life, and landscape evolution are to a certain extent controlled by climatic conditions, some geosites may be used as illustrations of various themes linked to the issue of climate change. In this paper, a coherent systematic framework is proposed for how to look at geosites through the lens of climate change. Four major aspects of relevance are recognized: (i) geosites providing evidence of changing climatic conditions in the past; (ii) geosites providing evidence of an environment different than that of today at the place; (iii) geosites providing evidence of extreme weather events; and (iv) dynamic geosites, subject to change as a response to ongoing climate change. The use of geosites to raise awareness and educate the public about climate change faces various interpretation challenges. In particular, linking with ongoing climate change requires caution and balanced presentation as most geosites record changes which occurred without any anthropogenic component. The preferred focus should be on environmental instability in general rather than on any specific reasons for change. [ABSTRACT FROM AUTHOR]

In light of the challenges posed by climate change and rural revitalization, high-quality construction in rural areas is facing significant obstacles from rainstorm flooding. This study adopts a regional disaster system analysis framework and examines the characteristics of rural rainstorm flooding disasters, including the instability of the breeding environment, the hazard characteristics, and the vulnerability of the exposure. Using this framework, we explore the various causes of rainstorm flooding in rural China, assess the effectiveness of responses to these disasters, and examine the differences between urban and rural responses. Our analysis reveals that the increase in rainstorm flooding in rural China is a complex result of multiple factors, including increased risk, instability, and vulnerability. While rural areas have made some progress in monitoring and responding to rainstorm flooding disasters, they remain weaker than cities in terms of governance and disaster management systems. To address these challenges, we recommend increased attention to rural flood control and disaster reduction, stronger preparation for disaster prevention and reduction plans, enhanced rural disaster infrastructure defense, increased financial support for water conservancy projects, and stronger professional emergency response teams, disaster relief equipment, and materials. Additionally, we recommend strengthening disaster prevention and reduction education and publicity among rural residents to promote the ability to self-rescue and mutual rescue. The disastrous impact of climate change and resulting extreme weather events on rural areas has become increasingly evident in recent years. China's vast rural areas have been particularly affected by frequent rainstorm flooding disasters. This paper identifies the increase in rainstorms, the instability of the disaster breeding environment in rural areas, and the increased vulnerability of exposures in these areas as the main reasons behind the intensification of rural rainstorm flooding. To mitigate the impact of these disasters, attention should be paid to natural disaster risk management, normalized flood control, and disaster reduction in rural areas. This requires overall coordination of rural disaster prevention and reduction planning, emphasis on improving the defense capacity of rural areas, increasing financial support for defensive water conservancy projects, promoting the construction of professional emergency rescue teams in rural areas, scientifically distributing flood prevention and disaster relief equipment and materials, strengthening publicity and education on disaster prevention and reduction, and enhancing rural disaster prevention awareness and self-rescue and mutual rescue capabilities. [ABSTRACT FROM AUTHOR]

Atmospheric rivers (ARs) significantly impact the hydrological cycle and associated extremes in western continental regions. Recent studies suggest ARs also influence water resources and extremes in continental interiors. AR detection tools indicate that AR conditions are relatively frequent in areas east of the Rocky Mountains. The origin of these ARs, whether from synoptic‐scale waves or mesoscale processes, is unclear. This study uses meteorological composite maps and transects of AR conditions during the four seasons. The analysis reveals that ARs east of the Rockies are associated with long‐wave, baroclinic Rossby waves. This result demonstrates that eastern North American ARs are dynamically similar to their western coastal counterparts, though mechanisms for vertical moisture flux differ between the two. These findings provide a foundation for understanding future climate change and ARs in this region and offer new methods for evaluating climate model simulations. Plain Language Summary: Atmospheric rivers (ARs) are a weather pattern that brings high amounts of atmospheric water and winds in a relatively narrow region. ARs are typically considered a "west coast" phenomenon, largely because the majority of the scientific research on ARs has focused on ARs in western coastal regions: particularly the western United States (US). ARs occur in continental interiors, but there has been some debate about whether these ARs represent the same type of weather as those in western coastal regions. This paper uses two objective methods for identifying ARs and finds times when ARs are present in three locations in the eastern half of the US: Norman, OK, Bloomington, IN, and Washington, DC. Examination of weather conditions during these AR times shows remarkable similarity to conditions associated with west coast ARs. This gives strong evidence that ARs do occur in the eastern half of the US. This result is important because it suggests that ARs may be important for water resources and extreme weather in the eastern half of the US, just as they are in the western US. This result also suggests that ARs may be important for water resources and extremes in other continental interiors. Key Points: Atmospheric rivers (ARs) east of the Rockies are associated with baroclinic wavesWestern coastal ARs and eastern/midwest ARs are dynamically similarSynoptic‐scale uplift, combined with convective instability, provide efficient mechanisms for generating precipitation [ABSTRACT FROM AUTHOR]

Climate change is a pressing global concern with far-reaching implications and its impact on soil properties is a critical aspect that warrants comprehensive investigation. This abstract delves into the multifaceted effects of climate change on soil, highlighting the intricate relationships between climate patterns and soil characteristics. Rising temperatures associated with climate change contribute to increased evaporation rates, leading to changes in soil moisture levels. These alterations can influence soil structure, affecting porosity, compaction and water retention capacity. Additionally, shifting precipitation patterns may result in changes to soil erosion and sedimentation rates, impacting nutrient cycling and the overall fertility of the soil. The increase in extreme weather events, such as floods and droughts, intensifies soil erosion and nutrient loss. Changes in temperature and precipitation also influence microbial activity and diversity in the soil, impacting crucial processes like decomposition and nutrient mineralization. These alterations in microbial communities can further cascade into shifts in soil organic matter content and nutrient availability. Furthermore, the interaction between climate change and soil properties extends to the realm of soil carbon sequestration. Altered conditions may affect the balance between carbon inputs and outputs, influencing the capacity of soils to act as carbon sinks. Understanding these complex dynamics is imperative for sustainable land management practices and developing strategies to mitigate the adverse effects of climate change on soil properties. This review paper throws light on the complex interplay between climate change and soil properties underscoring the need for interdisciplinary research to unravel the intricacies of this relationship. Such knowledge is indispensable for formulating effective adaptation and mitigation strategies to safeguard soil health, ensuring the resilience of ecosystems and global food security in the face of ongoing climate challenges. [ABSTRACT FROM AUTHOR]

Agriculture is weather dependent, and changes in climate can have a drastic impact on our ability to feed, fuel, and clothe the world's population. Climate change is causing more frequent and unprecedented extreme weather events that are already negatively affecting agriculture. We need to assess the effects of extreme temperatures and rainfall on agriculture. Patterns of short‐term extreme weather events, such as elevated temperatures, flooding, and strong winds, are not predictable enough to design field experiments around. Process‐based crop and soil simulation models allow us to explore new management options and thus provide whole‐system‐based knowledge and management guides for different locations over variable climate conditions. By using crop simulation models, researchers can test different adaptation strategies and assess their effectiveness in reducing the impacts of climate change on agricultural production. In this paper, we discuss the development of crop models and how they have been used to assess the effects of a changing climate on agricultural productivity and propose methods for agriculture to adapt to those changes. We describe potential applications of crop models to assess regional issues such as irrigation demand, greenhouse gas emissions, and policy decisions. Better understanding of how weather and climate forecasts at various scales are provided and the reliability of these forecasts is important for using crop models as a planning tool. Different approaches for simulating long‐term climate change impacts on crop yield and seasonal yield forecasting are discussed. The use of ensemble models to better assess climate change impacts is also discussed. Core Ideas: Assessment of climate change impacts on agriculture requires a systems approach.Agriculture is weather dependent, and changes in climate can have a drastic impact on food production.Crop models can extend the results of physical experiments to better assess long‐term climate change effects on agriculture.Crop models are critical in assessing climate change impacts and developing adaptation and mitigation strategies. [ABSTRACT FROM AUTHOR]

The stochastic synthesis of extreme, rare climate scenarios is vital for risk and resilience models aware of climate change, directly impacting society in different sectors. However, creating high-quality variations of under-represented samples remains a challenge for several generative models. This paper investigates quantizing reconstruction losses for helping variational autoencoders (VAE) better synthesize extreme weather fields from conventional historical training sets. Building on the classical VAE formulation using reconstruction and latent space regularization losses, we propose various histogram-based penalties to the reconstruction loss that explicitly reinforces the model to synthesize under-represented values better. We evaluate our work using precipitation weather fields, where models usually strive to synthesize well extreme precipitation samples. We demonstrate that bringing histogram awareness to the reconstruction loss improves standard VAE performance substantially, especially for extreme weather events. [ABSTRACT FROM AUTHOR]

Climatic and geographic factors characterizing local conditions, as well as the ecological state of the external environment, have a direct effect on human health, morbidity, and life expectancy. The paper considers the basic concepts of medical ecology, a pathogenetic role of environmental atmospheric pollution in the development of environmentally induced and environmentally dependent diseases associated with exposure to meteorological factors. In addition to the major hygienic risk factors affecting the public health (a level of air, water, and soil pollution), the levels of acoustic and electromagnetic background, the type of human nutrition, architectural and planning conditions of human life are of significant importance. Global climate warming causes numerous environmental changes, primarily an increase in surface air temperature, which in turn entails global changes in weather conditions that lead to various weather anomalies. Human health is directly dependent on environmental conditions and a degree of adaptation to them. The paper highlights the issues of diagnosing environmentally induced diseases and measures to counteract their spread. Based on the system diagnosis using physiological indicators of human health and the integration of the adaptation and nosological approaches, a hardware-software complex has been developed and introduced into medical practice. Corrective technologies of regenerative medicine that are used for ecologically dependent pathologies are described. Their application in the process of the complex sanatorium and resort treatment is most effective. [ABSTRACT FROM AUTHOR]

The urgency of addressing housing challenges in low-income areas is increasing due to widening socio-economic inequalities and the worsening impact of natural disasters. Saint Martin, a small Caribbean island, is struggling to provide affordable housing amidst hurricanes, floods, and heat waves. As a result, there has been a rise in self-organized housing units, which are built incrementally and are susceptible to risks. The main challenge is to balance durability, functionality, and esthetic appeal over time. Inspired by St. Martin's self-organized units, this article explores housing considerations in low-income, hazard-prone contexts by emphasizing their temporalities. Integrating insights from a formative study, including a literature review and ethnographic research, the paper draws on Stewart Brand's "Layers of Change" and the concept of "Flow". The study identifies layers within self-organized units corresponding to durability, functionality, and esthetic appeal. It delves into their connection with building activities over time, unveiling the temporalities of housing considerations. This exploration leads to the proposition of "Designing for a Flow" as a novel design approach. Offering practical insights within a concise framework, the study provides nuanced perspectives on mitigating housing challenges in low-income and hazard-prone contexts. [ABSTRACT FROM AUTHOR]

Climate extremes are threatening transportation infrastructures and hence require new methods to address their vulnerability and improve their resilience. However, existing studies have yet to examine the climate impacts on transportation networks systematically rather than independently assessing the infrastructures at a component level. Therefore, it is crucial to configure alternative shipping routes from a systematic perspective to reduce climate vulnerabilities and optimise the resilience of the whole shipping network. This paper aims to assess the global shipping network focusing on climate resilience by a methodology that combines climate risk indicators, centrality analysis and ship routing optimisation. The methodology is designed for overviewing the climate vulnerability of the current and future scenarios for comparison. First, a multi-centrality assessment defines the global shipping hubs and network vulnerabilities. Secondly, a shipping model is built for finding the optimal shipping route between ports, considering the port disruption days caused by climate change (e.g. extreme weather) based on the climate vulnerability analysis result from the first step. It contributes to a new framework combining the global and local seaport climate vulnerabilities. Furthermore, it recommends changing shipping routes by a foreseeable increase in port disruptions caused by extreme weather for climate adaptation. [ABSTRACT FROM AUTHOR]

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.

Southeast Asia’s coastal communities are the frontliners of climate change impacts. Traditional livelihoods and fish landings are already declining due to changes in sea temperatures and increasingly frequent extreme weather. A human security lens should be used to examine the consequences of climate change impacts on the marginalised communities that suffer directly from it. This study adapts a 2001 Intergovernmental Panel on Climate Change vulnerability assessment for human and food security and assessment of potential conflicts, merging it with a tool to assess community resilience and adaptability to threats, as a framework to analyse the predicament of Malaysia’s artisanal fishermen. A case study based on 16 years of ethnographic and participant observation in a fishing community that depends on the maritime boundary between Malaysia and Singapore is used to illustrate the above. This paper demonstrates how local knowledge and experience in overcoming change should be used for better climate change adaptation policies and implementation. [ABSTRACT FROM AUTHOR]

Soil moisture is an essential climate variable of the Earth system. Understanding its spatiotemporal dynamics is essential for predicting weather patterns and climate variability, monitoring and mitigating the effects and occurrence of droughts and floods, improving irrigation in agricultural areas, and sustainably managing water resources. Here we review in depth how soils can remember information on soil moisture anomalies over time, as embedded in the concept of soil moisture memory (SMM). We explain the mechanisms underlying SMM and explore its external and internal drivers; we also discuss the impacts of SMM on different land surface processes, focusing on soil‐plant‐atmosphere coupling. We explore the spatiotemporal variability, seasonality, locality, and depth‐dependence of SMM and provide insights into both improving its characterization in land surface models and using satellite observations to quantify it. Finally, we offer guidance for further research on SMM. Plain Language Summary: Our review paper takes an in‐depth look at soil moisture memory, which is how soil records its moisture history over time and space. Analogous to human psychology, which seeks to understand how a person's/society's memory influences his/her present and future behavior, understanding soil moisture memory encourages consideration of how such memory determines present state and might determine future behavior of soils exposed to environmental disturbances. Soil moisture memory can be affected by a variety of factors, both external (e.g., weather extremes) and internal (soil's unique properties). It affects everything from the air to the way our landscapes respond to disasters like droughts, wildfires, and floods. We also studied how this phenomenon affects the balance of water and energy in our environment, the health of our plants, and even how it communicates with the atmosphere. We show how it can change depending on where you are on the planet, the time of year, and how deep you dig into the soil. We offer scientists insights into how weather and land surface models can become more accurate by accounting for soil moisture memory. Its understanding not only helps us predict and manage our environment, but also provides opportunities for exciting scientific discoveries. Key Points: Atmospheric forcings, land use and management, and soil processes and mechanisms explain how and why soil moisture memory emerges in ecosystemsNonlocality of moisture memory, its spread across different regions, and its interaction with large‐scale climate phenomena are underexploredFurther advances in land surface models and closer integration of model simulations and observations are needed to better characterize moisture memory [ABSTRACT FROM AUTHOR]

This document provides a summary of a hackathon event organized by the Ministry of Justice (MoJ) and Aon, a reinsurance company, to explore the social impacts of climate change. The hackathon focused on developing consistent scenarios for future climate risk, understanding uncertainties in European windstorm modeling, and providing real-time context for extreme weather events. The teams developed tools and methodologies to assess the severity and potential impact of extreme events on insured losses. The collaboration between the MoJ, Aon, and participants from various institutions aims to further research and develop papers and grant proposals in these areas. [Extracted from the article]

This systematic review examines current evidence on the association between extreme weather and child, early, and forced marriage (CEFM). Studies published in English between 1990 and 2022 were identified through ten databases, and independently screened for inclusion followed by data extraction, quality assessment, and narrative synthesis. Of the 20 studies included, CEFM was a major theme in the qualitative studies; quantitative and mixed-method studies noted a positive association between extreme weather and CEFM. Limitations include reporting bias, non-representative samples, and limited geographic coverage. Health professionals and social workers must recognize the complexities surrounding CEFM and extreme weather, which will worsen amid climate change. [ABSTRACT FROM AUTHOR]

This perspective paper presents a conceptual, theoretical framework of the weather as a determinant of mental health for farmers. This model proposes that the effects of extreme weather events have interacting and cumulative effects for farmers, who are dependent on the land. [ABSTRACT FROM AUTHOR]

This study summarizes the media coverage of climate change in Pakistan. Pakistan is among the most climate-vulnerable countries, which leaves a long-lasting impression on the already crippling economy along with other issues. Climate communication is a crucial need of this hour. Media needs to play an important part in guiding people about their role in climate preservation to lessen the impacts. Various studies have been done on this issue to learn the media's role in climate change awareness in Pakistan. This research implies systematic literature review using studies from the last 15 years i.e., 2009 to 2023. The study concludes that Pakistani media did not have sufficient coverage of climate issues due to various issues like illiteracy, lack of infrastructure for reporting, lower rating and editorial preferences. It is recommended that media needs to design special programs and dedicate more time to climate reporting. [ABSTRACT FROM AUTHOR]

Climate change (CC) is a complex phenomenon that has the potential to significantly alter marine, terrestrial, and freshwater ecosystems worldwide. Global warming of 2°C is expected to be exceeded during the 21st century, and the frequency of extreme weather events, including floods, storms, droughts, extreme temperatures, and wildfires, has intensified globally over recent decades, differently affecting areas of the world. How CC may impact multiple food safety hazards is increasingly evident, with mycotoxin contamination in particular gaining in prominence. Research focusing on CC effects on mycotoxin contamination in edible crops has developed considerably throughout the years. Therefore, we conducted a comprehensive literature search to collect available studies in the scientific literature published between 2000 and 2023. The selected papers highlighted how warmer temperatures are enabling the migration, introduction, and mounting abundance of thermophilic and thermotolerant fungal species, including those producing mycotoxins. Certain mycotoxigenic fungal species, such as Aspergillus flavus and Fusarium graminearum, are expected to readily acclimatize to new conditions and could become more aggressive pathogens. Furthermore, abiotic stress factors resulting from CC are expected to weaken the resistance of host crops, rendering them more vulnerable to fungal disease outbreaks. Changed interactions of mycotoxigenic fungi are likewise expected, with the effect of influencing the prevalence and co‐occurrence of mycotoxins in the future. Looking ahead, future research should focus on improving predictive modeling, expanding research into different pathosystems, and facilitating the application of effective strategies to mitigate the impact of CC. [ABSTRACT FROM AUTHOR]

This paper investigates the relationship between extreme temperature and online complaints to local government officials. We show that the number of complaints significantly increases by 11.1% on extremely hot days relative to the benchmark temperature. Such effect is most pronounced on the day of extreme weather conditions and muted immediately after the extreme weather day. Among all the complaint areas, we find that 28.6% of the increase in complaints on hot days is related to public service, 42.8% to urban construction, 21.4% to noise, and 7.2% to safety. Moreover, we reveal that the primary motivators of increased complaints on hot days are not likely to be psychological factors; instead, the complaints are more likely to be associated with inadequate provision of public facilities to cope with extreme weather and inadequate management of other environmental disamenities caused by extreme temperature. [ABSTRACT FROM AUTHOR]

This paper highlights the role of climate change as a persistent, systemic, long-term inflationary driver. The inflationary impacts of climate change have been commonly overlooked in the economic literature. As global temperatures rise and extreme weather events become more frequent and severe, the inflationary effects of climate change will only intensify. These effects could be further exacerbated by the considerable pricing power of the corporate sector. As a persistent inflationary driver, climate change poses a serious threat to central banks' ability to maintain price stability mandates. The traditional tools of monetary policy will be ineffective in curbing climate change-induced price pressures. Further, growth-based Green New Deal and related fiscal policies will be ineffective at mitigating climate change and reducing its inflationary impacts. Unless degrowth solutions are sought, climate change and its price effects will only intensify over time. [ABSTRACT FROM AUTHOR]

The global temperature has been increasing resulting in climate change. This negatively impacts planetary health that disproportionately affects the most vulnerable among us, especially children. Extreme weather events, such as hurricanes, tornadoes, wildfires, flooding, and heatwaves, are becoming more frequent and severe, posing a significant threat to our patients' health, safety, and security. Concurrently, shifts in environmental exposures, including air pollution, allergens, pathogenic vectors, and microplastics, further exacerbate the risks faced by children. In this paper, we provide an overview of pediatric illnesses that are becoming more prevalent and severe because of extreme weather events, global temperature increases, and shifts in environmental exposures. As members of pediatric health care teams, it is crucial for pediatric radiologists to be knowledgeable about the impacts of climate change on our patients, and continue to advocate for safe, healthier environments for our patients. [ABSTRACT FROM AUTHOR]

The existing body of research into the environmental and socio-economic benefits of green infrastructure supports the case for it to be positioned as a form of critical infrastructure, particularly in urban settings. It is broadly recognized that extreme weather and climate change pose significant risks to critical infrastructure systems linked to the provision of services, including electricity, water, communications, and transport, and consequently risk assessments and associated adaptation strategies are common practice. However, although green infrastructure is also at risk from extreme weather and climate change, threatening the realization of benefits that it can deliver in urban settings, associated risks to green infrastructure are not widely understood or assessed in practice. This paper discusses the status of existing research on this topic and uses this as a foundation for a Greater Manchester (UK) case study that assesses the risk of low water availability to grassed areas, which represent a key element of the city-region’s green infrastructure. In doing so, the paper demonstrates how risks linked to extreme weather and climate change can be assessed spatially to inform green infrastructure planning. In summary, this paper aims to raise awareness of extreme weather and climate change risk to urban green infrastructure, present an empirical case study and associated methodological approach on this topic, and ultimately support efforts to enhance the resilience of urban green infrastructure to extreme weather and climate change.

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.

The document titled "A Short Supplemental Reading List for The Environment: Issues in Justice, Conflict and Peacebuilding" is a compilation of various resources related to the environment and its intersection with justice, conflict, and peacebuilding. The list includes sources such as reports, articles, and policy briefs from organizations like the United Nations, the Institute for Economics and Peace, and the Environmental Law Institute. Topics covered include climate change, environmental justice, and the impact of environmental stressors on peace. The list aims to provide library patrons with additional sources for research on these specific topics. [Extracted from the article]

Climate change exhibits a clear trend of escalating frequency and intensity of extreme weather events, posing heightened risks to drainage systems along the existing road networks. However, very few studies to date have investigated the consequences of projected future changes in rainfall on main road drainage and the resulting risk of road flooding. The work presented in this paper builds on the limited research by introducing a probabilistic model for assessing the impact of climate change on road drainage systems, incorporating climate uncertainty and drainage system variation. The probabilistic scenario-based model and associated framework offer a practical and innovative method for estimating the impact of short-duration storms under future climates for 2071–2100, in the absence of fine-resolution spatio-temporal data. The model also facilitates the assessment of the effectiveness of a climate adaptation strategy. An illustrative case-study of a road drainage system located in the south of Ireland is presented. It was found that the probability of road flooding during intense rainfall is projected to surpass the current acceptable limits set by Irish standards. Assessment of a proactive climate adaptation strategy implemented in 2015 indicated it may need to be adjusted to further reduce climate change impacts and optimise adaptation costs. • Climate change can impact extreme rainfall patterns, and resulting road flooding. • A flooding model is developed incorporating climate and drainage system uncertainty. • A quantitative climate risk analysis framework is proposed for road drainage. • The effectiveness of a climate adaptation strategy adopted in Ireland is quantified. [ABSTRACT FROM AUTHOR]

Across recent years, there has been a growing prevalence of extreme weather events throughout the United States, posing significant challenges to the reliable and resilient operation of power systems. Specifically, summer droughts threaten to severely reduce available generation capacity to meet regional electricity demand, potentially leading to power outages. This underscores the importance of accurate resource adequacy (RA) assessment to ensure the reliable operation of the nation's energy infrastructure. Accurately evaluating the usable capacity of regional generation fleets is a challenging undertaking due to the intricate interactions between power systems and hydro-climatic systems. This paper proposes a systematic and analytical framework to evaluate the impacts of extreme summer drought events on the available capacity of various generating technologies, incorporating both meteorological and hydrologic factors. The framework provides detailed plant-level capacity derating models for hydroelectric, thermoelectric, and renewable power plants, facilitating evaluations with high temporal and spatial resolution. The application of the proposed impact assessment framework to the 2025 generation fleet of the real-world power system within the PJM and SERC regions of the United States yields insightful results. By analyzing the daily usable capacity of 6,055 at-risk generators across the study region, it shows that the summer capacity deration is most significant for hydroelectric and once-through thermal power plants, followed by recirculating thermal power plants and combustion turbines. In the event of the recurrence of the 2007 southeastern summer drought event in the near future, the generation fleet could experience a substantial reduction in available capacity, estimated at approximately 8.5 GW, compared to typical summer conditions. The sensitivity analysis reveals that the usable capacity of the generation fleet would suffer an even more significant decrease under conditions of increasingly severe summer droughts. The proposed approach and the findings of this study provide valuable methodologies and insights, empowering stakeholders to bolster the resilience of power systems against the potentially devastating effects of future extreme drought events. [Display omitted] • A systematic summer droughts generating capacity assessment framework is developed. • Capacity derating models for various generation technologies are presented. • The impacts of summer droughts on generating fleet in PJM and SERC are studied. • Impact of extreme summer drought on usable capacity of generators is significant. [ABSTRACT FROM AUTHOR]

• An innovative conceptual model for assessing flood risk. • The FVI increases flood risk by 33 %, while FAI reduces flood risk by 45 %. • PD, DVP and DFS are important responsibilities for urban flood risk. • Reducing socioeconomic disparities among cities is essential for flood risk assessment. Risk assessment and adaptation have become key focuses in the examination of urban flooding risk. In recent decades, global climate change has resulted in a high incidence of extreme weather events, notably flooding. This study introduces a spatial multi-indicator model developed for assessing flood risk at the urban agglomeration scale. A crucial addition to the model is the incorporation of an adaptive capacity within the IPCC risk framework. The model systematically considers various flood risk indicators related to the economic, social, and geographic environments of the central and southern Liaoning urban agglomeration (CSLN). It generates a spatial distribution map of integrated flood risk for multiple scenario combinations. Furthermore, the intricate relationship between different risk indicators and flood risk was analyzed using correlation analysis and the Light Gradient Boosting Machine model (Light GBM). The findings reveal notable variations in flood risk under different scenarios. The inclusion of vulnerability indicators increased flood risk by 33 %, while the subsequent inclusion of adaptive indicators decreased flood risk by 45 %. Dense populations and assets contribute to high flood risk, while adaptive capacity significantly mitigates urban flood risk. The framework adopted in this paper can be applied to other areas where urban agglomeration-scale flood risk assessment is needed, and can contribute to advancing scientific research on flood forecasting and mitigation. [ABSTRACT FROM AUTHOR]

The intensification of global climate change has led to a widespread consensus on carbon reduction, with the power industry being the principal contributor to carbon emissions necessitating an inevitable transition of its energy structure. Concomitantly, the escalating frequency of natural disasters caused by extreme weather presents formidable challenges to both secure power supply and the low-carbon transition of the power system. To fulfill the developmental requirements of a low-carbon power system and address the carbon emission risks imposed by natural disasters, this paper proposes a bi-level model for generation expansion planning (GEP) that incorporates constraints on the carbon emission trajectory and the influence of natural disasters. The planning-level model optimizes investment costs of various generation technologies and energy storage (ES), as well as the overall operational expenses over the planning period, with an objective to minimize them. It incorporates carbon emission trajectory constraints and policy constraints, such as carbon peaking, carbon neutrality and renewable energy (RE) penetration rates, in order to optimize the planning installed capacity of power sources. The operational-level model aims to minimize typical daily operating costs while also simulating power unit outputs in routine and disaster scenarios. A case study is conducted in a disaster-prone province in southern China to analyze the power generation expansion planning and the trajectory of carbon emissions from 2020 to 2060 under different scenarios. The simulation results show that compared to thermal power, the planning scheme mainly focused on RE with ES is better suited to achieve the goal of a low-carbon transition of the power grid. Moreover, after considering natural disasters, the cost and carbon emissions of power system planning are higher, and the risk of carbon emissions increases with the severity of disasters. • A multi-time scale bi-level low-carbon GEP model is proposed. • Natural disaster scenarios and low-carbon policy constraints are considered in the GEP model. • Carbon emission trajectory of the planned power system is estimated and introduced as a constraint into the GEP model. • Evaluation indicators that comprehensively consider low-carbon performance and economic feasibility are proposed. [ABSTRACT FROM AUTHOR]

Climate change poses significant challenges to agricultural systems in the Mediterranean region, with Italy being significantly affected. This literature scoping review aims to examine existing research on the impact of climate change on yield and income on the three agri-food value chains in Italy: viticulture, fruit and vegetables, and dairy cattle. By analysing the available literature, this study seeks to outline the pros and cons, knowledge gaps, and potential areas for future research. A systematic search of scientific databases was conducted to identify relevant articles published between 2000 and 2022. The search terms included climate change, agriculture, Italy, yield, income, and related keywords. Articles were screened based on predetermined inclusion and exclusion criteria, resulting in a final selection of studies. Quantitative information was collected and organized into descriptive tables. The review encompassed 44 studies that investigated the impact of climate change on yield and income in various agricultural sectors across different regions of Italy. The findings indicate that climate change is already impacting crop productivity and income levels, with increased temperature, changes in precipitation patterns, and extreme weather events being identified as the primary drivers. Additionally, disparities were observed between different agricultural regions, crops, and farming systems, highlighting the need for location-specific and crop-specific assessments. The scoping review provides a prospective overview of the existing literature on climate change impacts on yield and income within the Italian agriculture system. It underscores the urgency for targeted adaptation strategies to minimize the negative consequences of climate change. Further research should focus on understanding the complex interactions between climate change, agricultural practices, socio-economic factors, and policy interventions to develop context-specific solutions for sustainable agriculture in Italy. [ABSTRACT FROM AUTHOR]

Semiarid regions play a pivotal role in global ecosystem and environmental governance. Changing environment (climate and land use variation) has led to the disruption of hydrology in semi-arid regions and ecological degradation in some area. Understanding their hydrological response to changing environments is crucial for ecological rehabilitation and optimal water resource allocation. This research, conducted in a Chinese semiarid watershed, integrates multi-field models about hydrology, meteorology and geography to investigate hydrological processes in typical hydrological years. The results indicate that the climate in this region is drying, and the likelihood of extreme weather events is increasing with global warming. Projecting changes from 2010 to 2060, 9.21% of grassland converting to 5.63% of forest and 3.58% of gully built-up land. As a result, the flood peak increases by 22.99% in typical drought years, while it decreases by 36.77% in normal years. Based on our analysis of the rainfallrunoff process in typical drought and normal years, we identify two distinct effects: the "local rainfall-runoff effect" and the "global rainfall-runoff effect", respectively. However, in typical wet years, the streamflow state is primarily controlled by intense and concentrated precipitation. This research provides insights into the effect of ecological restoration and typical climate variations on hydrological cycle in semiarid regions, thus contributing to more informed decision-making in environmental management and water resource planning. [ABSTRACT FROM AUTHOR]

Extreme weather events have led to widespread yield losses and significant global economic damage in recent decades. African agriculture is particularly vulnerable due to its harsh environments and limited adaptation capacity. This systematic review analyzes 96 articles from Web of Science, Science Direct, and Google Scholar, focusing on biophysical studies related to maize in Africa and worldwide. We investigated the observed and projected extreme weather events in Africa, their impacts on maize production, and the approaches used to assess these effects. Our analysis reveals that drought, heatwaves, and floods are major threats to African maize production, impacting yields, suitable cultivation areas, and farmers' livelihoods. While studies have employed various methods, including field experiments, statistical models, and process-based modeling, African research is often limited by data gaps and technological constraints. We identify three main gaps: (i) lack of reliable long-term experimental and empirical data, (ii) limited access to advanced climate change adaptation technologies, and (iii) insufficient knowledge about specific extreme weather patterns and their interactions with management regimes. This review highlights the urgent need for targeted research in Africa to improve understanding of extreme weather impacts and formulate effective adaptation strategies. We advocate for focused research on data collection, technology transfer, and integration of local knowledge with new technologies to bolster maize resilience and food security in Africa. [ABSTRACT FROM AUTHOR]

Agro-meteorological disasters are a significant cause of crop yield reduction. Northeast China is a major base for commodity grain production and is also highly sensitive to climate change. Early frost is one of the most significant meteorological disasters in Northeast China. The typical weather system serves as the primary meteorological cause of the occurrence of early frost. The Northeast Cold Vortex is a cyclonic system of certain intensity located in Northeast China, which has the potential to induce severe weather conditions such as extreme low temperatures and intense convection. Despite extensive research on the first occurrence of frost in Northeast China, the evolutionary characteristics under the combined influence of climate change and the Northeast Cold Vortex remain unclear. This limitation hinders the development of effective monitoring and early warning systems for early frost, as well as the formulation of disaster prevention and mitigation plans for crop production. Therefore, this study aims to objectively document the occurrence of early frost in maize crops in Northeast China from 1961 to 2021 under the influence of the Northeast Cold Vortex. It seeks to unveil the climatic characteristics and evolutionary patterns of early frost events in maize crops within this region, considering the impact of the Northeast Cold Vortex. Additionally, it endeavors to analyze the factors contributing to varying degrees of early frost caused by the Northeast Cold Vortex. The results showed that the occurrence of both early frost and frost influenced by the Northeast Cold Vortex exhibited a declining trend. Furthermore, there was also a decreasing proportion of initial frost attributed to the Northeast Cold Vortex, with a decline rate of 2% per decade, indicating a diminishing dominance of initial frost caused by this weather system. The onset date for the early frost under the influence of the Northeast Cold Vortex progressively advanced from southeast to northwest, occurring 4 days earlier than during the period from 1961 to 1990 between 1991 and 2021. While early frost displayed an increasing spatial distribution from southeast to northwest, it is noteworthy that the majority concentration of the Northeast Cold Vortex was observed in central regions, highlighting its predominant role in causing early frost in Northeast China. [ABSTRACT FROM AUTHOR]

The climate crisis poses a grave threat to numerous small island developing states (SIDS), intensifying risks from extreme weather events and sea level rise (SLR). This vulnerability heightens the dangers of coastal erosion, chronic water quality degradation, and dwindling coastal resources, demanding global attention. The resultant loss of ecological persistence, functional services, and ecosystem resilience jeopardizes protection against wave action and SLR, endangering coastal habitats' economic value, food security, infrastructure, and livelihoods. Implementing integrated strategies is imperative. A thorough discussion of available strategies and best management practices for coastal ecosystem restoration is presented in the context of SIDS needs, threats, and major constraints. Solutions must encompass enhanced green infrastructure restoration (coral reefs, seagrass meadows, mangroves/wetlands, urban shorelines), sustainable development practices, circular economy principles, and the adoption of ecological restoration policies. This requires securing creative and sustainable funding, promoting green job creation, and fostering local stakeholder engagement. Tailored to each island's reality, solutions must overcome numerous socio-economic, logistical, and political obstacles. Despite challenges, timely opportunities exist for coastal habitat restoration and climate change adaptation policies. Integrated strategies spanning disciplines and stakeholders necessitate significant political will. [ABSTRACT FROM AUTHOR]

Background: Extreme weather events like heatwaves and fine particulate matter (PM2.5) have a synergistic effect on mortality, but research on the synergistic effect of cold waves and PM2.5 on outpatient visits for respiratory disease, especially at high altitudes in climate change-sensitive areas, is lacking. Methods: we collected time-series data on meteorological, air pollution, and outpatient visits for respiratory disease in Xining. We examined the associations between cold waves, PM2.5, and outpatient visits for respiratory disease using a time-stratified case-crossover approach and distributional lag nonlinear modeling. Our analysis also calculated the relative excess odds due to interaction (REOI), proportion attributable to interaction (AP), and synergy index (S). We additionally analyzed cold waves over time to verify climate change. Results: Under different definitions of cold waves, the odds ratio for the correlation between cold waves and outpatient visits for respiratory disease ranged from 0.95 (95% CI: 0.86, 1.05) to 1.58 (1.47, 1.70). Exposure to PM2.5 was significantly associated with an increase in outpatient visits for respiratory disease. We found that cold waves can synergize with PM2.5 to increase outpatient visits for respiratory disease (REOI > 0, AP > 0, S > 1), decreasing with stricter definitions of cold waves and longer durations. Cold waves' independent effect decreased over time, but their interaction effect persisted. From 8.1 to 21.8% of outpatient visits were due to cold waves and high-level PM2.5. People aged 0–14 and ≥ 65 were more susceptible to cold waves and PM2.5, with a significant interaction for those aged 15–64 and ≥ 65. Conclusion: Our study fills the gap on how extreme weather and PM2.5 synergistically affect respiratory disease outpatient visits in high-altitude regions. The synergy of cold waves and PM2.5 increases outpatient visits for respiratory disease, especially in the elderly. Cold wave warnings and PM2.5 reduction have major public health benefits. [ABSTRACT FROM AUTHOR]

The vulnerability of corn yield to high temperature and insufficient rainfall in the US mid-west is widely acknowledged. The impact of extreme weather and genetic development on corn yield is less well known. One of the main reasons is that the multicollinearity in the variables can lead to confounding results. Here we model the impact of climate and genetic development by employing an elastic net regression model to address the multicollinearity issue. This allows us to develop a more robust multiple regression model with higher predictive accuracy. Using granular data for Iowa from 1981-2018, we find that corn yield is vulnerable to high mean summer temperatures particularly in July, a widening diurnal temperature range in June and dry summer conditions (due to extremely low rainfall) from June-August. We find that overall climate impact reduced average annual yield by 0.7%. We also find that genetic development which led to earlier planting dates, widening duration of the reproductive interval, higher growing degree day accumulation and larger net planted area had a beneficial impact on the Iowa corn yield during 1981-2018 resulting in an average annual yield improvement of 1.8% per annum. This provides a basis for optimism that these genetic developments and management practices will continue to adapt and improve in the future to counter the impact of climate change on corn yield. We have also modelled the impact of future climate change using the latest climate projections from the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR6). These climate projections show that the average temperature during the growing season (MayO-October) will increase by 2.4-2.9 °C by mid-century while the average spring temperature (March and April) will increase by a relatively slower 1.9-2.3 °C by mid-century. Additionally, climate projections show that both temperature and rainfall will also become more extreme in the future with the changes varying from spring to summer. Our results show that, just due to climate change alone in Iowa corn yield will decline between 1.4-1.7% per annum until mid-century (or 1.2-2.1% per annum until the late twenty first century). [ABSTRACT FROM AUTHOR]