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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]

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]

On 20 July 2021, an extreme rainstorm battered Zhengzhou in China's Henan Province, killing 302 people, including 14 individuals who drowned in a subway tunnel and 6 who drowned in a road tunnel. As the global climate warms, extreme weather events similar to the Zhengzhou flood will become more frequent, with increasingly catastrophic consequences for society. Taking a case study-based approach by focusing on the record-breaking Zhengzhou flood, this paper examines the governance capacity of inland cities in North China for managing extreme precipitation and flooding events from the perspective of the flood risk management process. Based on in-depth case analysis, our paper hypothesizes that inland cities in North China still have low risk perceptions of extreme weather events, which was manifested in insufficient pre-disaster preparation and prevention, poor risk communication, and slow emergency response. Accordingly, it is recommended that inland cities update their risk perceptions of extreme rainfall and flooding events, which are no longer low-probability, high-impact "black swans", but turning into high-probability, high-impact "gray rhinos." In particular, cities must make sufficient preparation for extreme weather events by revising contingency plans and strengthening their implementation, improving risk communication of meteorological warnings, and synchronizing emergency response with meteorological warnings. [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]

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]

This paper compares the ideas contained in the main papers published on climate change since World War II to arrive at a suggested consensus of our present knowledge regarding climatic changes and their causes. Atmospheric carbon dioxide is only suggested as a cause in one theory, which, despite its wide acceptance by Politicians, the media, and the Public, ignores the findings in other studies, including the ideas found in the Milankovitch Cycles. It also does not explain the well-known NASA map of the changes between the global 1951–1978 and the 2010–2019 mean annual temperatures. The other theories by Oceanographers, Earth scientists, and Geographers fit together to indicate that the variations in climate are the result of differential solar heating of the Earth, resulting in a series of processes redistributing the heat to produce a more uniform range of climates around the surface of the Earth. Key factors are the shape of the Earth and the Milankovitch Cycles, the distribution of land and water bodies, the differences between heating land and water, ocean currents and gateways, air masses, and hurricanes. Low atmospheric carbon dioxide levels during cold events could result in too little of this gas to support photosynthesis in plants, resulting in the extermination of most life on Earth as we know it. The 23 ka Milankovitch cycle has begun to reduce the winter insolation received at the surface of the atmosphere in the mid-latitudes of the Northern Hemisphere starting in 2020. This results in extreme weather as the winter insolation reaching the surface of the atmosphere in the higher latitudes of the Northern Hemisphere decreases while the summer air temperatures increase. It heralds the start of the next glaciation. A brief outline is given of some of the climatic changes and consequences that may be expected in western Canada during the next 11.5 ka. [ABSTRACT FROM AUTHOR]

Many parts of the world are experiencing extreme weather events, energy poverty, food insecurity, and lack of access to basic healthcare. Moreover, concerns over socioeconomic, gender, and racial inequalities are growing. These socially relevant issues are ripe for analysis and improvement using an operations management lens. In this paper, we review some of the relevant research advancements made in the last decade, and identify future research directions on these important topics. In particular, we focus on papers related to sustainable planet (renewable energy, environmentally and socially responsible operations, regulation‐driven operations), agriculture, and public health. For future research directions, we discuss the role of innovative business models and disruptive technologies, such as artificial intelligence (AI) and blockchain, in addressing these pressing issues. [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]

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]

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]

The Tibetan Plateau (TP) vegetation plays an important role in the local ecosystem, which responds significantly to climate change and can affect local and large-scale weather and climate anomalies. However, little attention has been paid to its year-to-year variation. In this paper, using two NDVI datasets (GIMMS and MODIS) originated from satellite remote sensing, the variability characteristics of NDVI over the TP on the interannual time scale and associated local climatic factors were investigated. The results show that two primary patterns of NDVI governed TP during the main growing season (June–September, JJAS) for the period 1982–2020. The first one is a uniform pattern, with a consistent spatial variation over the entire TP, and the second is a dipole pattern, with an out-of-phase spatial variation of NDVI between the northern and southern TP. Interannual variations of the different climatic factors regulate the NDVI variability over the different regions of the TP. The interannual variability of the uniform NDVI pattern is mainly affected by the two local climatic factors, the preceding May–August precipitation and simultaneous JJAS sunshine duration. Specifically, NDVIs over the southern and eastern TP have a more significant response to the preceding precipitation and simultaneous sunshine duration, respectively. The variability of the dipole NDVI pattern is primarily modulated by the preceding May–August precipitation and simultaneous surface air temperature, ground surface temperature, and sunshine duration. However, NDVIs over the northern and southern TP have different degrees of response to the four climatic factors, with the most significant response being to preceding precipitation. The combined effect of these factors contributes to the formation of the interannual variability in the uniform and dipole patterns. This paper may shed light on deeply understanding the reasons for the inconsistency in variations of vegetation over the different regions of the TP under climate change. In addition to the effect of local climatic factors that this study focuses on, the influence of external climatic factors on the variability of the TP NDVI deserves further research in the future. [ABSTRACT FROM AUTHOR]

This paper aims to assess the level of credit risk (from the perspective of default risk) among Polish households associated with the physical risks of climate change. In order to determine the potential impact of the physical risk of climate change on household credit risk, we conducted CAWI interviews with 1,006 borrowers residing in different Polish voivodeships (to account for heterogeneity of credit exposures to extreme weather events). According to these respondents, wildfires and storms in Poland are the greatest source of physical risk of climate change. In the event of a wildfire or storm, approximately 13% of borrowers would not be able to repay their loans while not being insured, which potentially increases banks' credit risk and exposes banks to losses. However, we find that households underestimate the credit risk that could arise from a drought. [ABSTRACT FROM AUTHOR]

Purpose: The interconnections between climate change and health are well studied. However, there is a perceived need for studies that examine how responses to health hazards (e.g. cardiovascular diseases, ozone layer effects, allergens, mental health and vector-borne diseases) may assist in reducing their impacts. The purpose of this paper is to review the evidence on health responses to climate hazards and list some measures to address them. Design/methodology/approach: A mixed literature review, bibliometric analysis and an original online survey were undertaken on 140 participants from 55 countries spread across all geographical regions. Findings: The bibliometric analysis identified that most climate-related health hazards are associated with extreme weather events. However, only one-third of the investigated papers specifically analysed the connections between climate change and health hazards, revealing a thematic gap. Also, although Africa is highly affected by climate change, only 5% of the assessed studies focused on this continent. Many respondents to the survey indicated "heat distress" as a significant vulnerability. The survey also identified social determinants relevant to climate-induced health vulnerabilities, such as socioeconomic and environmental factors, infrastructure and pre-existing health conditions. Most respondents agree that policies and regulations are the most effective adaptation tools to address the public health hazards triggered by climate change. This paper presents some suggestions for optimising public health responses to health hazards associated with climate change, such as the inclusion of climate-related components in public health policies, setting up monitoring systems to assess the extent to which specific climate events may pose a health threat, establishing plans to cope with the health implications of heatwaves, increased measures to protect vulnerable groups and education and awareness-raising initiatives to reduce the overall vulnerability of the population to climate-related health hazards. These measures may assist the ongoing global efforts to understand better – and cope with – the impacts of climate change on health. Originality/value: The combination of a literature review, bibliometric analysis and an original world survey identified and presented a wide range of responses. [ABSTRACT FROM AUTHOR]

The sub-tropical, flat, peninsular region of Florida is subject to a unique climate with extreme weather events that impact agriculture, public health, and management of natural resources. Meteorological data at high temporal resolutions especially in tropical latitudes are essential to understand diurnal and semi-diurnal variations of climate, which are considered as the fundamental modes of climate variations of our Earth system. However, many meteorological datasets contain gaps that limit their use for validation of models and further detailed observational analysis. The objective of this paper is to apply a set of data gap filling strategies to develop a gap-free dataset with 15-minute observations for the sub-tropical region of Florida. Using data from the Florida Automated Weather Network (FAWN), methods of linear interpolation, trend continuation, reference to external sources, and nearest station substitution were applied to fill the data gaps depending on the extent of the gap. The outcome of this study provides continuous, publicly accessible surface meteorological observations for 30 FAWN stations at 15-minute intervals for years 2005–2020. [ABSTRACT FROM AUTHOR]

This review article delves into the multifaceted relationship between climate change, air quality, and respiratory health, placing a special focus on the process of particle deposition in the lungs. We discuss the capability of climate change to intensify air pollution and alter particulate matter physicochemical properties such as size, dispersion, and chemical composition. These alterations play a significant role in influencing the deposition of particles in the lungs, leading to consequential respiratory health effects. The review paper provides a broad exploration of climate change's direct and indirect role in modifying particulate air pollution features and its interaction with other air pollutants, which may change the ability of particle deposition in the lungs. In conclusion, climate change may play an important role in regulating particle deposition in the lungs by changing physicochemistry of particulate air pollution, therefore, increasing the risk of respiratory disease development. Climate change influences particle deposition in the lungs by modifying the physicochemical properties of particulate air pollution, thereby escalating the risk of respiratory disease development. It is crucial for healthcare providers to educate patients about the relationship between climate change and respiratory health. People with conditions such as asthma, COPD, and allergies must understand how changes in weather, air pollution, and allergens can exacerbate their symptoms. Instruction on understanding air quality indices and pollen predictions, along with recommendations on adapting everyday activities and medication regimens in response, is essential. [ABSTRACT FROM AUTHOR]

Accurate prediction of storm surges is crucial for mitigating the impact of extreme weather events. This paper introduces the Bidirectional Attention-based Long Short-Term Memory (LSTM) Storm Surge Architecture, BALSSA, addressing limitations in traditional physical models. By leveraging machine learning techniques and extensive historical and real-time data, BALSSA significantly enhances prediction accuracy. Utilizing a bidirectional attention-based LSTM framework, it captures complex, non-linear relationships and long-term dependencies, improving the accuracy of storm surge predictions. The enhanced model, D-BALSSA, further amplifies predictive capability through a doubled bidirectional attention-based structure. Training and evaluation involve a comprehensive dataset from over 70 typhoon incidents in Macao between 2017 and 2022. The results showcase the outstanding performance of BALSSA, delivering highly accurate storm surge forecasts with a lead time of up to 72 h. Notably, the model exhibits a low Mean Absolute Error (MAE) of 0.0287 m and Root Mean Squared Error (RMSE) of 0.0357 m, crucial indicators measuring the accuracy of storm surge predictions in water level anomalies. These metrics comprehensively evaluate the model's accuracy within the specified timeframe, enabling timely evacuation and early warnings for effective disaster mitigation. An adaptive system, integrating real-time alerts, tropical cyclone (TC) chaser, and prospective visualizations of meteorological and tidal measurements, enhances BALSSA's capabilities for improved storm surge prediction. Positioned as a comprehensive tool for risk management, BALSSA supports decision makers, civil protection agencies, and governments involved in disaster preparedness and response. By leveraging advanced machine learning techniques and extensive data, BALSSA enables precise and timely predictions, empowering coastal communities to proactively prepare and respond to extreme weather events. This enhanced accuracy strengthens the resilience of coastal communities and protects lives and infrastructure from the escalating threats of climate change. [ABSTRACT FROM AUTHOR]

Time‐lapse cameras have been widely used as a tool to monitor the timing of seasonal vegetation growth. These simple, relatively inexpensive systems can provide high‐frequency observations of leaf development and demography which are critical data sets needed to characterize plant phenology from species to landscapes. This is important for understanding how plants are responding to global changes, as well as for validating satellite‐derived phenology products.However, in remote regions including the high‐latitude Arctic, deploying time‐lapse cameras could be challenging. The remoteness and lack of widespread power and telecommunications infrastructure limit options for the installation, maintenance and retrieval of data and equipment, and make it difficult for cameras to survive in extreme weather (e.g. long cold winters). To improve our understanding of Arctic phenology, new technologies are required to address these challenges.Here, we present a novel, low‐power, compact, lightweight time‐lapse camera system, called power‐interval camera automation module (PiCAM). The PiCAM was designed with explicit consideration to simplify deployment (i.e. without a need for external power supplies) of camera systems and to address the challenges of camera survival in harsh Arctic environments. In this paper, we describe the design, setup and technical details of the PiCAM and provide a roadmap for how to build and operate these systems. As proof of concept, we deployed 26 PiCAMs at three low‐Arctic tundra sites on the Seward Peninsula, Alaska in early August 2021 for characterizing Arctic plant phenology.Of the 26 PiCAMs, 70% remained active at the point of our revisit in late July 2022 despite the extreme winter temperatures they experienced (< −30°C, heavy snow cover). We extracted key plant phenology metrics from the PiCAMs and captured strong differences across key Arctic plant species. We showed that the PiCAM has the potential to be widely used for monitoring plant phenology across the broader Arctic region, addressing the need for ground‐based understanding of Arctic phenological diversity to develop knowledge of plant response to climate change and to validate remote sensing products. [ABSTRACT FROM AUTHOR]

With climate change, more intense weather phenomena can be expected, including pressure drops related to the arrival of an atmospheric front. Such drops of pressure are the main reason for gas emissions from closed mines to the surface, and a closed, empty mine shaft is the most likely route of this emission. Among the gases emitted, the most important are carbon dioxide and methane, creating a twofold problem—greenhouse gas emissions and gas hazards. The work presented in this paper simulated the spread of the mentioned gases near such an abandoned shaft for four variants: model validation, the most dangerous situations found during measurements with or without wind, and a forecast variant for a possible future pressure drop. It was found that a momentary CO2 emission of 0.69 m3/s and a momentary CH4 emission of 0.29 m3/s are possible, which for one hour of the appropriate drop would give hypothetically 2484 m3 CO2 and 1044 m3 CH4. In terms of gas hazards, the area that should be monitored and protected may exceed 25 m from a closed shaft in the absence of wind influence. The wind spreads the emitted gases to distances exceeding 50 m but dilutes them significantly. [ABSTRACT FROM AUTHOR]

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Climate dictates the critical aspects of human environmental conditions. The frequency and intensity of extreme weather conditions due to human-induced climate change have alarmingly increased. Consequently, climate change directly affects environmental sustainability and human mortality in the short term and creates prolonged and complicated long-term indirect grave risks. This paper examines three-level environmental impact risks associated with climate change on human mortality. It proposes a conceptual framework for developing an empirical event-based human mortality database related to climate change and communication strategies to enhance global environmental adaptation, resilience, and sustainability. [ABSTRACT FROM AUTHOR]

Small fishing harbours substantially contribute to coastal economies as they support not only fishing but also tourism activities. They are located at the land–sea interface and are considered vulnerable infrastructure affected by the increased human activities but also by the impacts of climate change, including rising sea levels and extreme weather events. In this paper, the 16 existing fishing shelters of Cyprus are used as a case study to develop a complex vulnerability index for assessing the shelters' vulnerability. The index incorporates physical, environmental, technical and socioeconomic variables, which are quantified and scored to denote the current state of vulnerability. The results are validated through on-site visits, questionnaires answered by local fishermen and targeted interviews with representatives of the port authorities. Furthermore, climate change projections are taken into account for the physical variables to evaluate the impact of climate change on vulnerability changes. The study highlights the complex interactions between a variety of factors characterising the fishing shelters and driving vulnerability. The proposed index can assist decisionmakers with prioritising interventions, allocating funding and designing adaptation pathways that reduce the shelters' vulnerability while increasing their resilience. [ABSTRACT FROM AUTHOR]

Vineyards are agroecosystems of great importance in the Niagara Region, Ontario (Canada). Due to its microclimate, this region is projected to be impacted by climate change with temperature increases, changes in precipitation patterns in all seasons, and greater frequency of extreme weather events. The aim of this review paper is to summarize which seasonal changes are expected to occur in the Niagara Region and assess how such changes are likely to affect the main components of the vineyard ecosystem (i.e., soil, vines, invertebrates, and pathogens). It is expected that by 2080 the region will experience an increase in temperature in all four seasons; an increase in precipitation during the fall, winter, and spring; and a decrease in precipitation during summer months. Impacts of the projected changes will likely lead to vine water stress, yield loss, increases in incidents of diseases, increases in the spread of new pests, and changes in grape quality ultimately resulting in lower wine quality and/or production. Current management practices will need to be better understood and adaptive strategies introduced to enhance grape growers' ability to minimize these impacts. [ABSTRACT FROM AUTHOR]

Background: Climate variability influences the population dynamics of the Aedes aegypti mosquito that transmits the viruses that cause dengue, chikungunya and Zika. In recent years these diseases have grown considerably. Dengue is now the fastest-growing mosquito-transmitted disease worldwide, putting 40 per cent of the global population at risk. With no effective antiviral treatments or vaccines widely available, controlling mosquito population remains one of the most effective ways to prevent epidemics. This paper analyses the temporal and spatial dynamics of dengue in Mexico during 2000–2020 and that of chikungunya and Zika since they first appeared in the country in 2014 and 2015, respectively. This study aims to evaluate how seasonal climatological variability affects the potential risk of transmission of these mosquito-borne diseases. Mexico is among the world's most endemic countries in terms of dengue. Given its high incidence of other mosquito-borne diseases and its size and wide range of climates, it is a good case study. Methods: We estimate the recently proposed mosquito-borne viral suitability index P, which measures the transmission potential of mosquito-borne pathogens. This index mathematically models how humidity, temperature and precipitation affect the number of new infections generated by a single infected adult female mosquito in a host population. We estimate this suitability index across all Mexico, at small-area level, on a daily basis during 2000–2020. Results: We find that the index P predicted risk transmission is strongly correlated with the areas and seasons with a high incidence of dengue within the country. This correlation is also high enough for chikungunya and Zika in Mexico. We also show the index P is sensitive to seasonal climatological variability, including extreme weather shocks. Conclusions: The paper shows the dynamics of dengue, chikungunya and Zika in Mexico are strongly associated with seasonal climatological variability and the index P. This potential risk of transmission index, therefore, is a valuable tool for surveillance for mosquito-borne diseases, particularly in settings with varied climates and limited entomological capacity. [ABSTRACT FROM AUTHOR]

Wildfires are natural occurrences of the forests’ ecosystems and vital for the renewal of biomes and survival of some plant species. Studies indicate that in recent times, in many parts of the world, the frequency, extent, and austerity of wildfires have been escalating and occurring in places where they rarely occurred before. Several reports indicate that the environment is gradually warming up and is associated with severe droughts that could be responsible for such wildfire escalations. The humans’ role in climate change is vastly debated. Whereas some scientists believe that the current rise in atmospheric temperature is due to the changes in solar activities and is a part of natural climate cycle where humans have no accountabilities, the others disagree and suggest that the rise in atmospheric temperatures is aided by anthropogenic activities. Regardless of the scientific opinions on the mechanism of climate change, shifting climatic conditions are evidenced and supported by many scientific studies. This paper reports on some brutal wildfire activities in 2021 that severely impacted various parts of the world where extreme weather conditions were reported and where drought and environmental temperature surpassed all previous records. [ABSTRACT FROM AUTHOR]

The impact of climate change on the physical environment, ecosystems, and human societies is increasingly recognized as the most important global challenge. Climate change may alter, among others, the thermal environment, the occurrence of extreme weather events, and the human exposure to physical, chemical, and biological pollutants, thus affecting human health with several potential outcomes. The impact of climate change on occupational health and safety has been receiving increasing attention in last years. In the European Union, the health and safety of workers is under the rule of Directive 89/391 and its daughters. In a changing climate, compliance with all requirements of the existing EU regulation entails an additional effort to implement preventive and protective measures. A central role in workers' health protection is played by proper workers' information and training, which is partly in charge of the occupational physicians. This paper provides a basic proposal on topics related to climate change to update workers' information and training and to integrate the curricula of occupational physicians. Importantly, suitable information and training may contribute to promoting workers' health and to implement adaptation measures, which are part of the individual, societal, and global responses to climate change. [ABSTRACT FROM AUTHOR]

Featured Application: The application of this research in agriculture is related to the rapid progression of climate change, which has drastic effects on crops. We can build an accurate and robust model that can help identify the optimum planting day to maximise the crop yield, based on the weather forecast and meteorological conditions of the region. This can support farmers in their agricultural activity planning and help minimise the impact of weather anomalies. Machine learning is often used to predict crop yield based on the sowing date and weather parameters in non-irrigated crops. In the context of climate change, regression algorithms can help identify correlations and plan agricultural activities to maximise production. In the case of sunflower crops, we identified datasets that are not very large and have many missing values, generating a low-performance regression model. In this paper, our aim is to study and compare several approaches for missing-value imputation in order to improve our regression model. In our experiments, we compare nine imputation methods, using mean values, similar values, interpolation (linear, spline, pad), and prediction (linear regression, random forest, extreme gradient boosting regressor, and histogram gradient boosting regression). We also employ four unsupervised outlier removal algorithms and their influence on the regression model: isolation forest, minimum covariance determinant, local outlier factor and OneClass-SVM. After preprocessing, the obtained datasets are used to build regression models using the extreme gradient boosting regressor and histogram gradient boosting regression, and their performance is compared. The evaluation of the models shows an increased R 2 from 0.723 when removing instances with missing data, to 0.938 for imputation using Random Forest prediction and OneClass-SVM-based outlier removal. [ABSTRACT FROM AUTHOR]

Countering climate impacts by increasing resilience is a pivotal issue in scientific debate, in which the awareness of the risks of extreme weather phenomena is growing. Cities have been revealed to be increasingly unsuited to the changing climate and vulnerable to it due to their settlement patterns, constructive practices and living habits. Scientifically addressing the issue of climate-proof design requires the development of knowledge models and processes capable of managing the complexity of information needed to guide the transformation of the built environment. In this paper, a model for assessing climate resilience scenarios for the heatwave phenomenon is proposed by implementing a database of technical climate-proof solutions for climate adaptation and mitigation aimed at increasing the indoor comfort and reducing the CO2 emissions of buildings. The model is implemented through a GIS-based framework and was tested on the city of Naples (Italy), measuring the reduction in the heatwave impact/risks determined by the selected climate-proof solutions. The test results show the effectiveness of the climate-proof solutions applied to the built environment through an increase in climate resilience. The framework provides support for planning climatic resilience design strategies at the building scale. It could be applied in future local climate adaptation plans or as a knowledge resource to achieve resilient built environments. [ABSTRACT FROM AUTHOR]

Achieving a good level of resilience to extreme events caused by severe weather conditions is a major target for operators in modern power systems due to the increasing frequency and intensity of extreme weather phenomena. Moreover, regulatory authorities are pushing transmission and distribution operators to prepare resilience plans suitably supported by Cost–Benefit Analyses (CBAs). In this context, this paper proposes a CBA framework based on Optimization via Simulation (OvS) for the selection of the optimal portfolio of resilience enhancement measures. Starting from a comprehensive set of candidate grid hardening and operational measures, the optimal mix is identified by applying a novel two-step procedure based on an efficient application of the generalized pattern search heuristic technique. Risk indicators for the CBA are quantified, accounting for probabilistic models of climate changes. Moreover, the potential cascading outages due to multiple component failures provoked by extreme events are simulated on selected scenarios. The examples carried out on an IEEE test system show the effectiveness of the approach in identifying the best portfolio of resilience enhancement measures depending on climate change projections and costs of the measures, while the application to the model of a large portion of the Italian EHV transmission system demonstrates the practicability of the approach in real-world studies to support operators in different power system management phases, from planning to operation. [ABSTRACT FROM AUTHOR]

With global warming, the frequency, intensity, and period of extreme climates in more areas will probably increase in the twenty first century. However, the impact of climate extremes on forest vulnerability and the mechanisms by which forests adapt to climate extremes are not clear. The eastern Tianshan Mountains, set within the arid and dry region of Central Asia, is very sensitive to climate change. In this paper, the response of Picea schrenkiana and Larix sibirica to climate fluctuations and their stability were analyzed by Pearson's correlation based on the observation of interannual change rates of climate indexes in different periods. Additionally, their ecological adaptability to future climate change was explored by regression analysis of climate factors and a selection of master control factors using the Lasso model. We found that the climate has undergone significant changes, especially the temperature, from 1958 to 2012. Around 1985, various extreme climate indexes had obvious abrupt changes. The research results suggested that: (1) the responses of the two tree species to extreme climate changed significantly after the change in temperature; (2) Schrenk spruce was more sensitive than Siberian larch to extreme climate change; and (3) the resistance of Siberian larch was higher than that of Schrenk spruce when faced with climate disturbance events. These results indicate that extreme climate changes will significantly interfere with the trees radial growth. At the same time, scientific management and maintenance measures are taken for different extreme weather events and different tree species. [ABSTRACT FROM AUTHOR]

This paper presents a multidisciplinary approach to understand the impacts of temperature increase on the retention of particulate pollutants, such as heavy metals and microplastics, by the road pavement material. A soil with a particle size distribution similar to road dust was selected. A Wheel Tracking device was used to assess the permanent deformation behavior of prismatic specimens and the retention of the dust, at controlled temperatures of 40 °C and 60 °C, likely to occur on pavement in the future. The soil representing road pollutants was placed at the top of the slabs prior to the Wheel Tracking Test (WTT), based on the European Standard EN 12697-22:2020. After the WTT, two common methods were used, in order to evaluate the soil retention (pollution accumulation) on road pavement. The results confirm that the viscoelastic behavior of bituminous mixtures under increased temperatures can contribute to particle retention at the pavement. Future studies are needed to understand the phenomena, the retention characteristics by different bituminous mixtures, and the efficiency of pollutants capture. The work opens the opportunity to develop innovative road pavement bituminous mixtures that can reduce the discharge of road particulate pollutants, and have increased resilience and sustainability in extreme weather conditions. [ABSTRACT FROM AUTHOR]

"Changes of the Coastal Zones Due to Climate Change" is a research article that explores the relationship between coastal climate change and sea dynamics. The article highlights the vulnerability of coastal areas to environmental shifts such as rising sea levels and extreme weather events. It discusses various research papers that investigate the impacts of climate change on coastal ecosystems, shoreline changes, and storm surge inundation. The article also emphasizes the importance of understanding waves and storm surges to develop effective strategies for coastal flooding mitigation. Additionally, it explores the potential for renewable offshore energy exploitation and ecosystem-based solutions for climate change adaptation in coastal areas. The research findings contribute to a comprehensive understanding of coastal climate dynamics and provide valuable insights for policymakers, researchers, and stakeholders in developing adaptation strategies and fostering resilience in the face of climate change. [Extracted from the article]

Fishers' local knowledge and their perceptions of climate change are increasingly recognized by researchers and international institutions. However, in India, limited regional studies are available to understand the fishers' local knowledge, and a crucial question which largely remained unaddressed has been how fishers perceive the relevance of their local knowledge systems in the face of climate change. Provided this background, this paper aims to explore the fishermen's local knowledge and their climate perceptions in the face of climate change. This paper has employed the data that were obtained by in-depth interviews and focus-group discussions with the small-scale fishermen of three highly vulnerable fishing villages of Nagapattinam district, Tamil Nadu. The marine fishers across this coast were the victims of the 2004 Indian Ocean Tsunami disaster, several major cyclones, and various weather and climate events for over the last four decades. Key results show (1) fishermen perceive multiple aberrations and anomalies in the weather and climate patterns for over the previous three to four decades, particularly after the 2004 Indian Ocean Tsunami disaster. (2) The next finding is contrary to the conventional understandings, in which we have found that the fishermen are increasingly felt and experienced that their local knowledge is no longer adequately relevant in the face of climate change. Thus, for promoting the adaptive capacity of fishers, this paper has suggested that fishermen's perceptions and their expectations should be appropriately recognized and there is a strong need to provide scientific assistance to the fishermen through proper channels to respond to climate change impacts. [ABSTRACT FROM AUTHOR]

According to reports from international institutions such as Intergovernmental Panel on Climate Change, United Nations Development Programme, and the World Bank, the impacts of climate change will continue affecting the Least Developed Countries (LDC) for the coming years and the less resilient countries, defined by the climate vulnerability index (CVI), will be the most vulnerable. The CVI relates the Exposure and Adaptive Capacity for a specific Hazard, offering feasible supports for decision-makers in identifying country-specific needs to adapt to climate change. However, even with this scenario, the LDCs are still unable to cope with the impact of extreme events. Therefore, the main question is, which part of Adaptive Capacity needs more effort to deal with extreme weather events? To address this issue, this paper discusses the governance role in the CVI definition, suggesting an alternative approach to assess climate vulnerability. Overall, we propose a tool, taking into account four main components: Exposure, Sensitivity, Adaptive Capacity, and Governance. In this case, the Governance component represents organizations, policies, and qualified human resources that could improve the planning and management of a specific system. More specifically, we explicitly considered the Governance component in the climate vulnerability function by adding specific indicators. As a study case, we consider Mozambique, a highly vulnerable country to the adverse impact of climate change. The results have shown that by adding the Governance component to assess climate vulnerability, the function becomes more sensitive. In conclusion, Governance is accepted as a powerful component in the CVI definition. [ABSTRACT FROM AUTHOR]

Agriculture is widely recognized as a solution to food insecurity and poverty, especially in rural areas. However, 75% of the world's poor live in rural areas, and agriculture is the primary source of their livelihood. One may wonder if the observed correlation between agriculture and poverty also suggests causation. If that is the case, then what such causal relationship might exist? Is agriculture a vehicle for poverty alleviation or a source of poverty trap? The role of climate change is rather undisputed: associated extreme weather phenomena cause severe negative impacts on agriculture, exacerbating rural poverty. However, climate-smart agriculture (CSA) is acclaimed to potentially reverse the situation by eliminating poverty and food insecurity. Against this backdrop, the paper investigates whether smallholder farmers who adopt CSA could achieve food security and better income. This aim was approached through three key research objectives (i) to examine the effects of climate change on smallholder farmers, (ii) to examine the extent to which smallholder farmers adopt CSA and the barriers to adoption, and (iii) to investigate empirically the effects of CSA practices in terms of food security and poverty alleviation. The Upper West and Upper East regions in Ghana were selected purposively for the case study, and the data collected were analyzed using inferential and descriptive techniques. The results revealed no statistically significant positive relationship between the adoption of CSA with food security and income. Poor socioeconomic and market conditions marred the expected positive effects of CSA, hence the need for the provision of agricultural infrastructures and inputs as well as the creation of market for commodities. [ABSTRACT FROM AUTHOR]

Coastal regions in Southwest Europe have experienced major interventions and transformations of the territory with unprecedented urban development, primarily related to growing tourism activity. The coast is the place where marine and terrestrial processes converge, making it highly vulnerable to the effects of climate change. However, the lack of information on the frequency of these extreme weather events and their impacts on the coast hampers an accurate analysis of the consequences of global change. This paper provides a detailed analysis of the extreme weather events (EWE) that have affected the Atlantic and Mediterranean coasts of Southwest Europe during the period from 1 January 2009 to 28 February 2020, as well as a quantification of their impacts: fatalities, injuries and economic damage. Official sources from France, Portugal and Spain were consulted, along with technical reports, scientific articles, etc., to generate a unified database. A total of 95 significant extreme events have caused 168 fatalities, 137 injuries and almost €4000 M in direct economic losses. Cyclone Xynthia (February 2010) on the French Atlantic coast stands out, having caused 47 fatalities, 79 injuries and substantial economic losses valued at €3000 M. The study shows a slight upward trend in the number of events recorded, especially during the last three years of the analysis, as well as in human losses and damages. The results reveal a higher exposure of the Mediterranean coast of Southwest Europe when compared to the Atlantic, especially the Spanish Mediterranean coast, with 61% of the fatalities recorded there during the study period. This is primarily due to a model of exponential tourism growth on the Mediterranean coast, with an enormous urban and infrastructure development during the last decades. Traditionally, the Mediterranean coast is less prepared to reduce the effects of marine storms, extreme events that are becoming more frequent and virulent in the context of climate and global change. This work highlights the need to create a continuous monitoring system–at the European level–of the impacts of extreme weather events on the coast, where 40% of the European population is concentrated. This observatory should serve as a source of information for risk mitigation policies (predictive, preventive and corrective), as well as for emergency management during disasters. [ABSTRACT FROM AUTHOR]

Weather and climate extremes such as heat waves, droughts and floods are projected to become more frequent and intense in several regions. There is compelling evidence indicating that changes in climate and its extremes over time influence the living conditions of society and the surrounding environment across the globe. This study applies max-stable models to capture the spatio–temporal extremes with dependence. The objective was to analyse the risk of drought caused by extremely high temperatures and deficient rainfall. Hopkin's statistic was used to assess the clustering tendency before using the agglomerative method of hierarchical clustering to cluster the study area into n = 3 temperature clusters and n = 3 precipitation clusters. For the precipitation and temperature data, the values of Hopkin's statistic were 0.7317 and 0.8446, respectively, which shows that both are significantly clusterable. Various max-stable process models were then fitted to each cluster of each variable, and the Schlather model with several covariance functions was found to be a good fit on both datasets compared to the Smith model with the Gaussian covariance function. The modelling approach presented in this paper could be useful to hydrologists, meteorologists and climatologists, including decision-makers in the agricultural sector, in enhancing their understanding of the behaviour of drought caused by extremely high temperatures and low rainfall. The modelling of these compound extremes could also assist in assessing the impact of climate change. It can be seen from this study that the size, including the topography of the location (cluster/region), provides important information about the strength of the extremal dependence. [ABSTRACT FROM AUTHOR]

Millions of local communities in southern Africa depend on forest ecosystems and the goods and services they provide for their livelihoods. This paper aims to assess the socio-economic benefits of forest goods and services in a changing climate by focusing on the forest products of Colophospermum mopane (C. mopane) in the Kunene and Omusati regions in northern Namibia. We used C. mopane product data from 2011 to 2021. Our analyses showed that local communities harvested five main products from C. mopane, namely firewood, poles, droppers, rafters, and roots. Firewood and poles were the primary C. mopane products harvested by local communities, mainly for subsistence use. Our results suggest that C. mopane potentially continues to the provision of goods and services for the livelihood of local communities, despite the changing climate in northern Namibia. We propose future studies in predictive analysis focus on extreme weather events, such as forest fires, droughts, floods, and other climate-related hazards that affect goods and services provided by forest ecosystems in the northern regions and the entire country. [ABSTRACT FROM AUTHOR]

Current climate projections for Southern Africa indicate an increase in the incidence of extreme weather events in the future. Even though South Africa does not rank among the highest on the world multi-hazard index list, the country is prone to multiple climate-related extreme events which pose substantial human and ecological impacts. Consequently, such climate extremes have serious negative effects on regional water resources, public health, biodiversity, food security, natural systems, and infrastructure. The main aim of this study is to review the literature on climate-change-induced weather events and the implications for urban water resource management in South Africa particularly focusing on QwaQwa. The study reviewed 122 documents which include books, peer-reviewed articles, conference papers, newspaper articles, institutional and government reports, and one news broadcast video. Findings revealed that QwaQwa experiences increasing water challenges as demand for water increases and both quantity and quality decrease to critical levels. This study, therefore, provides preliminary suggestions of strategies to build resilience in this climate change context, such as investment in climate-resilient water infrastructure, effective and transparent management of public resources with accountability, strengthening resilience through addressing poverty and marginalisation, nature-based solutions, and education and awareness. Furthermore, conducting hazard, exposure, and resilience analyses is necessary in order to inform the development of relevant disaster risk reduction strategies. The findings contribute to the literature on climate change impacts on water resource planning in South Africa and similar climate change contexts. The findings could; therefore, be valuable to researchers and applied practitioners such as policymakers, water resource management professionals, and urban planners. [ABSTRACT FROM AUTHOR]

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This paper presents a research study of expected precipitation extremes across the Gandaki Province, Nepal. The study used five indices to assess extreme precipitation under climate change. Precipitation output of two Global Climate Models (GCMs) of Coupled Model Intercomparison Project Phase Six (CMIP6) were used to characterize the future precipitation extremes during the rainfall season from June to September (JJAS) and overall days of the year. To characterize extreme precipitation events, we used daily precipitation under the SSP2–4.5 and SSP5–8.5 scenarios from the Beijing Climate Center and China Meteorological Administration, China; and Meteorological Research Institute (MRI), Japan. Considering large uncertainties with GCM outputs and different downscaling (including bias correction) methods, direct use of GCM outputs were made to find change in precipitation pattern for future climate. For 5-, 10-, 20-, 50-, and 100-year return periods, observed and projected 24 h and 72 h annual maximum time series were used to calculate the return level. The result showed an increase in simple daily intensity index (SDII) in the near future (2021–2040) and far future (2081–2100), with respect to the base-year (1995–2014). Similarly, heavy precipitation days (R50 mm), very heavy precipitation days (R100 mm), annual daily maximum precipitation (RX1day), and annual three-day maximum precipitation (RX3day) indices demonstrated an increase in extreme precipitation toward the end of the 21st century. A comparison of R50 mm and R100 mm values showed an extensive (22.6% and 63.8%) increase in extreme precipitation days in the near future and far future. Excessive precipitation was forecasted over Kaski, Nawalparasi East, Syangja, and the western half of the Tanahun region. The expected increase in extreme precipitation may pose a severe threat to the long-term viability of social infrastructure, as well as environmental health. The findings of these studies will provide an opportunity to better understand the origins of severe events and the ability of CMIP6 model outputs to estimate anticipated changes. More research into the underlying physical factors that modulate the occurrence of extreme incidences expected for relevant policies is suggested. [ABSTRACT FROM AUTHOR]

In an effort to improve their quality of life and battle poverty, many urban residents are turning to agriculture as an alternative source of income, employment, and food security. However, climate-related hazards such as heatwaves, floods, and droughts have had an effect on urban agriculture. The purpose of this study was to determine how climate change-related hazards affected the urban livestock industry in Masvingo City. These researchers administered a structured questionnaire on urban livestock farmers, the results of which were triangulated with in-depth interviews with livestock stakeholders. The results show that the urban livestock industry is significantly impacted by climate-related hazards. Farmers lose livestock to diseases, poor pastures, and extreme weather conditions. Furthermore, the hazards badly affect the storage and distribution of livestock products, the labour supply and productivity, and the profitability of livestock enterprises. This study contributes to the body of knowledge on the urban livestock industry and climate change-related hazards. The results are significant to policy makers and livestock stakeholders to understand climate change effects on the urban livestock sector so as to formulate mitigation, adaptation, and coping strategies against any adverse effects. This paper is a foundation for future studies and these researchers suggest that future studies be on location-specific adaptation strategies. [ABSTRACT FROM AUTHOR]

Starting from the relationship between urban planning and mobility management, TeMA has gradually expanded the view of the covered topics, always remaining in the groove of rigorous scientific in-depth analysis. This section of the Journal, Review Notes, is the expression of a continuous updating of emerging topics concerning relationships between urban planning, mobility and environment, through a collection of short scientific papers written by young researchers. The Review Notes are made of four parts. Each section examines a specific aspect of the broader information storage within the main interests of TeMA Journal. In particular, the Urban planning literature review section aims at presenting recent books and journals, within global scientific panorama, on selected topics and issues. This contribution aims at delving into the most severe effects due to storms and droughts and presenting three interesting and significant scientific books and journal that present effective adaptation strategies to limit climate crisis and improve Mediterranean resilience towards more frequent and severe storm surges and droughts. The third contribution of the Review Notes for TeMA vo. 15 highlights the need for integrated action to address the climate crisis in the Mediterranean region, bringing together the strengths and weaknesses of its shores, despite social, economic and political differences. Moreover, the extreme weather events that are occurring throughout Europe, from the south to the north, show how the Mediterranean area is particularly sensitive to climate change-related events. [ABSTRACT FROM AUTHOR]