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• Staying can be an alternate climate change adaptation strategy. • Staying and mobility are re-imagined with ideas of resilience and evolution. • Four key research areas linking climate change, staying and resilience. • Historical context and translocal networks shape immobility. • Equity and governance identify population differentials and choice of im(mobility). This paper brings work on mobility and 'staying' together with theoretical ideas of resilience to consider responses to climate change. To date, the majority of work that has explored the impacts of climate change on human populations has taken a migration-centred perspective, with an emphasis on mobility as a key response in crises, including extreme climatic events and civil conflict. However, evidence suggests that people may alternatively – and pro-actively – adopt a different approach involving "staying" as a climate change adaptation strategy. This is important as recent evolutionary approaches to resilience have highlighted how resilience is an on-going process of adaptation which emphasises the temporal, fluid and open-ended aspects of individuals' experiences and practices in shaping everyday lives. In turn, this means that individuals' experiences and practices can lead to different strategies of staying (as well as moving) in the face of climate change. Consequently, the paper highlights four key areas where more research is required in order to explore the links between climate change, 'staying' and resilience. These include the importance of historical context in disentangling and contextualising the "multicausal" nature of individuals' mobility decisions; translocal networks in shaping mobility or immobility; the influence of equity, diversity and gendered social expectations on staying; and the importance of governance responses in facilitating resilience, adaptation and subsequent decisions by individuals to stay or move. [ABSTRACT FROM AUTHOR]

Land degradation, desertification and tree mortality related to global climate change have been in the spotlight of remote sensing research in recent decades since extreme climatic events could affect the composition, structure, and biogeography of forests. However, the complexity of tree mortality processes requires a holistic approach. Herein, we present the first global assessment and a historical perspective of forest tree mortality by reviewing both remote sensing and meteorological ground-based studies. We compiled 254 papers on tree mortality that make use of remotely sensed products, meteorological ground-based monitoring, and climatic drivers, focusing on their spatial and temporal patterns and the methods applied while highlighting research gaps. Our core results indicate that international publications on tree mortality are on the increase, with the main hotspots being North America (39%) and Europe (26%). Wetness indicators appear as the barometer in explaining tree mortality at a local scale, while vegetation indicators derived from multispectral optical sensors are promising for large-scale assessments. We observed that almost all of the studies we reviewed were based on less than 25 years of data and were at the local scale. Longer timeframes and regional scale investigations that will include multiple tree species analysis could have a significant impact on future research. [ABSTRACT FROM AUTHOR]

Weather extremes have been responsible for widespread economic damage at global scale in the last decades. Agriculture alone absorbed 26% of the overall impact caused by natural hazards in low- and middle-income countries and even in high-income countries yield losses due to extreme weather are relevant. Vulnerability curves are traditionally used to quickly estimate the damage due to extreme events. This study maps the articles published from January 2000 to May 2022 implementing crop vulnerability curves to weather-related extreme events and climate change. Fifty-two articles have been identified through the use of Scopus, Web of Science, Google Scholar and the references of the selected papers. The selected papers have been analysed to determine for which extreme events vulnerability curves have been proposed, which crops have been studied, which explanatory variables have been used to create the curves, which functions are used to develop vulnerability curves and the number of parameters on which the proposed functions rely. Comparisons among the vulnerability curves for the various extremes are proposed, as well as indications of the main drawback of the developed vulnerability curves. Finally, areas where further research is needed are proposed together with recommendations on which elements should be included in vulnerability curve development. [ABSTRACT FROM AUTHOR]

This article is a response to comments made by researchers from the Universidad de Sevilla regarding a paper on extending climate justice to animals. The authors of the response agree with the commenters that the Iberian Lynx population has increased due to conservation efforts, but they clarify that their paper was not intended as a critique of these measures. The purpose of their paper is to discuss how to help wild animals cope with climate change, using the Iberian Lynx as an illustrative case. They argue that while the population has increased, the species is still at risk of extinction due to climate change. The authors also address the commenters' mention of the lack of originality in their proposed conservation measures, stating that their intention was to examine the moral implications of intervention strategies. Overall, the authors emphasize the importance of climate justice for animals, including the Iberian Lynx. [Extracted from the article]

Cities, and in particular those in coastal low-lying areas, are becoming increasingly susceptible to climate change, the impact of which is worsened by the tendency for population concentration in these areas. Therefore, comprehensive early warning systems are necessary to minimize harm from extreme climate events on communities. Ideally, such a system would allow all stakeholders to acquire accurate up-to-date information and respond effectively. This paper presents a systematic review that highlights the significance, potential, and future directions of 3D city modelling, early warning systems, and digital twins in the creation of technology for building climate resilience through the effective management of smart cities. In total, 68 papers were identified through the PRISMA approach. A total of 37 case studies were included, among which (n = 10) define the framework for a digital twin technology, (n = 14) involve the design of 3D virtual city models, and (n = 13) entail the generation of early warning alerts using the real-time sensor data. This review concludes that the bidirectional flow of data between a digital model and the real physical environment is an emerging concept for enhancing climate resilience. However, the research is primarily in the phase of theoretical concepts and discussion, and numerous research gaps remain regarding the implementation and use of a bidirectional data flow in a true digital twin. Nonetheless, ongoing innovative research projects are exploring the potential of digital twin technology to address the challenges faced by communities in vulnerable areas, which will hopefully lead to practical solutions for enhancing climate resilience in the near future. [ABSTRACT FROM AUTHOR]

The increasing intensity and frequency of extreme climate events have made improving the adaptability to extreme climate events a strategic imperative for manufacturing companies. This paper investigates whether manufacturing enterprises increase green technology innovation affected by different extreme climate events. Based on panel data of Chinese listed manufacturing enterprises, we show that extreme precipitation events can positively promote green technology innovation, yet extreme temperature events do not. Heterogeneity analyses suggest that the effect of extreme precipitation events on green technology innovation is more significant for non-state-owned enterprises, poor performance enterprises, and high R&D intensity enterprises than other enterprises. Furthermore, the facilitating effect of extreme precipitation events on green technology innovation is merely temporary. [ABSTRACT FROM AUTHOR]

Climate change is expected to increase the global occurrence and intensity of heatwaves, extreme precipitation, and flash droughts. However, it is not well understood how the compound heatwave, extreme precipitation, and flash drought events will likely change, and how global population, agriculture, and forest will likely be exposed to these compound events under future climate change scenarios. This research uses eight CMIP6 climate models to assess the current and future global compound climate extreme events, as well as population, agriculture, and forestry exposures to these events, under two climate scenarios, Shared Socioeconomic Pathways (SSP), SSP1‐2.6 and SSP5‐8.5 for three time periods: early‐, mid‐, and late‐ 21st century. Climate extremes are derived for heatwaves, extreme precipitation, and flash droughts using locational‐dependent thresholds. We find that compound heatwaves and flash drought events result in the largest increases in exposure of populations, agriculture, and forest lands, under SSP5‐8.5 late‐century projections of sequential heatwaves and flash droughts. Late‐century projections of sequential heatwaves and flash droughts show hot spots of exposure increases in population exposure greater than 50 million person‐events in China, India, and Europe; increases in agriculture land exposures greater than 90 thousand km2‐events in China, South America, and Oceania; and increase in forest land exposure greater than 120 thousand km2‐events in Oceania and South America regions when compared to the historical period. The findings from this study can be potentially useful for informing global climate adaptations. Plain Language Summary: There is lacking an understanding of how the compound heatwave, extreme precipitation, and flash drought events will likely change, and how global population, agriculture, and forest will likely be exposed to these compound events under future climate change scenarios. This paper presents a comprehensive assessment of the current and future global compound climate extreme events and population, agriculture, and forestry exposures to these events under two climate scenarios. We find that compound heatwaves and flash drought events have the largest increases in exposure of populations, agriculture, and forest lands, under a high emission scenario for late‐century projections of sequential heatwaves and flash droughts. The results revealed hot spot regions of exposure to sequential heatwaves and flash droughts and consistent increases in population, agriculture, and forest land exposures for late‐century projections. The findings from this study can potentially be useful for informing global climate adaptations. Key Points: Global compound flash drought, heat wave, and extreme precipitation are projected to increase by the end of the centuryThere are significant model agreements of compound heatwave and flash drought events compared to the other compound eventsExposures of populations, agriculture, and forestry lands to sequential heatwaves and flash droughts show the largest increases [ABSTRACT FROM AUTHOR]

Purpose: This research paper aims to empirically explore how stock market investors' perceptions are affected by extreme climatic events like El Nino and floods in Malaysia. Design/methodology/approach: This study uses structural equation modelling (SEM) to analyse the empirical data gathered through a questionnaire survey involving 273 individual investors from Bursa Malaysia between January and June 2019. Findings: Results reveal that companies' efforts, especially for agriculture and plantation-based industries, to adapt to climate change risk at the production, business and stock market levels significantly impact investors' behaviour and investment decisions. Moreover, stock market investors' climate change knowledge shows a significant moderating effect on corporate climate change adaptation initiatives and investors' decisions to invest in Malaysian agricultural and plantation industry stocks. Practical implications: This research has significant implications for practice and policy, as it measures the stock market investors' level of awareness about climate change events and explores the companies' strategies to reduce climatic risks to their business model. Social implications: This study shows the way to adjust the climate change information in the stock market investment decision to improve market efficiency and sustainable stock exchanges initiative. Originality/value: To the best of the authors' knowledge, this paper is the pioneer one to provide a comprehensive link between climate change events and business performances at production level, business level and stock market levels by drawing inferences from empirical data on investors' behaviours. This study also added value in investment theories and financial literature by observing the climate change as an important factor to determine the investors' decisions in the stock market. [ABSTRACT FROM AUTHOR]

Settlements operate across a wide range of densities and do so for every socio-economic mode of life from those based on hunter-gatherer economies to those which are based on industrial production. Human beings also live across a range of residential densities from very high to very low. Why they do so is a function of many factors, especially differing socio-cultural ways of managing interaction and communication and the associated social and political practices of the communities. Settlement forms are seen as a derivative of many factors because they are. But they are not thereby an epiphenomenon - especially as they become larger, more durable, and bulkier. That gives them inertia and, as a consequence, they become an agency in their own right which produces outcomes with consequences for the communities, which inhabit them. They are not a neutral background. Instead, their materiality, their sizes, and their densities have an impact on the viability of social life. This paper considers the outcomes generated by the regional networks of low-density, urban settlements larger than 100 sq km in extent. The implications of what happened to agrarian-based low-density urban settlements, like Greater Angkor and the Classic Maya settlements, such as Caracol, are of consequence for the risk faced by the regional networks of present-day, low-density urban giants - the megalopoleis and desa-kota. A further perspective is provided by placing these great cities of the past and the present in the larger context of the trajectories and outcomes of smaller low-density settlements over the previous six millennia. The concern is the implications for the viability of low-density urbanism in contexts of the rapid, extreme climate change we are now beginning to experience. The implications are ominous, yet the past also indicates that social and cultural systems are robust, that human beings can survive, and that they retain and continue to remake their social traditions as they adjust to seriously changing circumstances. [ABSTRACT FROM AUTHOR]

Pacific Islands, many relatively remote and small, have been occupied by people for more than 3000 years during which time they experienced climate‐driven environmental changes (both slow and rapid onset) that challenged human survival and led to the evolution of place‐based coping strategies expressed through traditional knowledge (TK). In today's globalized Pacific Islands region, into which western worldviews and global adaptation strategies have made significant inroads, most plans for coping with climate‐changed futures are founded in science‐based understandings of the world that undervalue and sideline TK. Many such plans have proved difficult to implement as a consequence. This paper reviews the nature of extant Pacific TK for coping with climate change, something that includes TK for anticipating climate change (including climate variability and climate extremes) as well as ancillary TK associated with food and water security, traditional ecological knowledge, environmental conservation, and settlement and house construction that represent coping strategies. Much of this TK can be demonstrated as being effective with precedents in other (traditional) contexts and a compelling plausible scientific basis. This study demonstrates that Pacific Islands TK for coping with climate change has value and, especially because of its place‐based nature, should be central to future climate‐change adaptation strategies to enhance their uptake, effectiveness and sustainability. To this end, this paper proposes specific ways forward to optimize the utility of TK and ensure it has a realistic role in sustaining Pacific Island communities into the future. This article is categorized under:Climate, History, Society, Culture > Ideas and KnowledgePaleoclimates and Current Trends > Modern Climate ChangeAssessing Impacts of Climate Change > Observed Impacts of Climate Change [ABSTRACT FROM AUTHOR]

The Canadian Prairies are associated with high natural hydroclimatic variability including the frequent periodic occurrence of droughts and pluvials. These extremes carry various risks including significant damage to the economy, environment and society. The well-documented level of damage necessitates further risk assessment and planned reductions to vulnerability, particularly in light of a warming climate. A logical starting point involves awareness and information about the changing characteristics of such climate extremes. We focus on the compound occurrence of droughts and pluvials as the risks from this type of event are magnified compared to the hydroclimatic extremes in isolation. Compound droughts and pluvials (CDP) are drought and pluvial events that occur in close succession in time or in close proximity in area. Also, research on CDP is limited even for the worldwide literature. Therefore, the purposes of this paper are to synthesize recent literature concerning the risks of CDP, and to provide examples of past occurrences, with a focus on the Canadian Prairies. Since literature from the Prairies is limited, global work is also reviewed. That literature indicates increasing concern and interest in CDP. Relationships between drought and pluvials are also characterized using the SPEI Global Monitor for the Prairies, emphasizing the recent past. Research mostly considers drought and pluvials as separate events in the Prairies, but is integrated here to characterize the relationships of these extremes. The spatiotemporal patterns showed that several of the extreme to record pluvials were found to be closely associated with extreme droughts in the Prairies. The intensities of the extremes and their dry to wet boundaries were described. This is the first research to explore the concept of and to provide examples of CDP for the Prairies and for Canada. Examples of CDP provide insights into the regional hydroclimatic variability. Furthermore, most literature on future projections strongly suggests that this variability is likely to increase, mainly driven by anthropogenic climate change. Therefore, improved methods to characterize and to quantify CDP are required. These findings suggest means of decreasing vulnerability and associated damages. Although the study area is the Canadian Prairies, the work is relevant to other regions that are becoming more vulnerable to increasing risks of and vulnerabilities to such compound extremes. [ABSTRACT FROM AUTHOR]

Oil refineries are among industrial installations that are vulnerable to climate extreme events, whose frequency and intensity have been increasing over the last decades. Building resilience in resources to withstand climate-related hazards and to recover fast at low human and material cost, for changing climate conditions, is required. In this paper, we present an action research effort for the design of a viable decentralized climate-resilience-providing virtual organization in an oil refinery in Greece using the Viable System Model. The VIPLAN method was employed for the methodological design of a distributed Climate Resilience Providing Organisation for the case of a refinery facility in Greece. The paper presents the process and the results of this effort. [ABSTRACT FROM AUTHOR]

Annual maxima of daily precipitation sums can be typically described well with a stationary generalized extreme value (GEV) distribution. In many regions of the world, such a description does also work well for monthly maxima for a given month of the year. However, the description of seasonal and interannual variations requires the use of non-stationary models. Therefore, in this paper we propose a non-stationary modeling strategy applied to long time series from rain gauges in Germany. Seasonal variations in the GEV parameters are modeled with a series of harmonic functions and interannual variations with higher-order orthogonal polynomials. By including interactions between the terms, we allow for the seasonal cycle to change with time. Frequently, the shape parameter ξ of the GEV is estimated as a constant value also in otherwise instationary models. Here, we allow for seasonal–interannual variations and find that this is beneficial. A suitable model for each time series is selected with a stepwise forward regression method using the Bayesian information criterion (BIC). A cross-validated verification with the quantile skill score (QSS) and its decomposition reveals a performance gain of seasonally–interannually varying return levels with respect to a model allowing for seasonal variations only. Some evidence can be found that the impact of climate change on extreme precipitation in Germany can be detected, whereas changes are regionally very different. In general, an increase in return levels is more prevalent than a decrease. The median of the extreme precipitation distribution (2-year return level) generally increases during spring and autumn and is shifted to later times in the year; heavy precipitation (100-year return level) rises mainly in summer and occurs earlier in the year. [ABSTRACT FROM AUTHOR]

Average monthly air temperatures in Bosnia and Herzegovina (BiH) exhibit a notable rise during summer, ranging from 0.4 to 0.8 °C per decade, while precipitation experiences a significant decrease of up to 8 mm per decade. Climate models, across various RCP scenarios, project an increase in air temperature, that is most pronounced in the summer season. Additionally, there is a projected frequency and intensity of heavy precipitation during autumn. In BiH, agricultural production faces substantial risks, including droughts, spring and autumn frosts, hail, and floods. Recent years have witnessed extreme hydrological events, notably the 2012 drought and the 2014 floods. Strategic documents highlight the critical importance of addressing floods and droughts for agriculture, as well as their implications for the environment, households, and industry. To assess the severity of extreme hydrological events and their impact on agriculture, with a specific emphasis on autumn and summer in Bosnia and Herzegovina, average and peak values of the Standardized precipitation evapotranspiration index (SPEI) were calculated separately for the periods 1961-1990 and 1991-2020, focusing on October and August. Compared to the reference climatic period the current climate is characterized by shifts between intense wet and dry periods, with very few years exhibiting stable and expected weather conditions. Identified as extremely wet and flood-prone years, SPEI2 October values for 1974 (2.42), 1996 (2.13), 2001 (2.24), and 2014 (2.05) stand out, with only one extremely dry year in 1985 (-2.21). SPEI2 August indicates extremely dry years, notably 2012 (-2.35) and 2017 (-2.25). [ABSTRACT FROM AUTHOR]

Wildfires are becoming more frequent due to the global climate change. Large amounts of greenhouse gases emitted by wildfires can lead to increases in extreme climate events. Accurately estimating the greenhouse gas carbon dioxide (CO2) emissions from wildfires is important for mitigation of climate change. In this paper, we develop a novel method to estimate wildfire CO2 emissions from the relationship between local CO2 emissions and XCO2 anomalies. Our method uses the WRF-Chem assimilation system from OCO-2 XCO2 retrievals which coupled with Data Assimilation Research Testbed (DART). To validate our results, we conducted three experiments evaluating the wildfire CO2 emissions over the conterminous United States. The four-month average wildfire emissions from July to October in 2015∼2018 were estimated at 4.408 Tg C, 1.784 Tg C, 1.514 Tg C and 2.873 Tg C, respectively. Compared to the average of established inventories CT2019B, FINNv1.5 and GFASv1.2 fire emissions, our estimates fall within one standard deviation, except for 2017 due to lacking of OCO-2 XCO2 retrievals. These results suggest that the regional carbon assimilation system, such as WRF-Chem/DART, using OCO-2 XCO2 retrievals has a great potential for accurately tracking regional wildfire emissions. [ABSTRACT FROM AUTHOR]

Changes in the frequency of temperature extremes are often attributed to global warming. The recent availability of near‐surface temperature data records from reference networks, such as the U.S. Climate Reference Network (USCRN), enables the quantification of measurement uncertainties. Within an activity of the Copernicus Climate Change Service, the estimation of the measurement uncertainty has been provided for USCRN temperature data, using metadata made available by the National Oceanic and Atmospheric Administration (NOAA). In this paper, four climate extreme indices (Frost Days, Summer Days, Ice Days, Tropical Nights) and the related uncertainties are calculated for the period 2006–2020 from the USCRN data set and compared with traditional indices. Moreover, the asymmetric USCRN measurement uncertainties are propagated to estimate the uncertainties of climate indices. The comparison shows expanded uncertainties homogeneously distributed with the latitude and typically within 15 days per year for Frost Days and within 10 days for Ice Days, while smaller uncertainties are estimated for Summer Days and Tropical Nights, with values typically within six to seven days per year. Positive uncertainties are typically larger than negative ones for all the indices. The values of Frost and Ice Days with the related uncertainties for USCRN have also been compared with the corresponding values calculated from reanalyses data, showing differences typically within 60 days for median values, quite often smaller than USCRN and inconsistent within the related uncertainties, Overall, the results show that USCRN measurement uncertainties increase confidence in the estimation of climate extreme indices and decisions for adaptation. Plain Language Summary: The relationship between the intensity and frequency of extremes and climate change as well as their attribution to human activities is fundamental for improving the assessment of risk and the elaboration of adaptation strategies. Temperature extremes are often reported and estimated using observations or model data using indices, which are widely adopted in the research community and by decision‐makers. However, the number of temperature extremes is quantified assuming input observations as perfect, whereas these are always affected by uncertainties due to instrumental noise and systematic effects that cannot be always properly accounted for. This also implies that climate extreme indices may under or over‐represent the number of temperature extremes. The advent of reference measurement networks, as well as the overall increase in observational data quality due to recent technological improvements, allows us to quantify measurement uncertainties in detail. In this paper, temperature extremes over the US are estimated from near‐surface temperature measurements provided by the USCRN network in the period 2006–2020 with related uncertainties. The use of uncertainty illustrates the range of values that climate extreme indices may assume. Possible sources of uncertainties and comparisons with data from atmospheric reanalysis are also discussed. Key Points: An extensive assessment of uncertainties for four climate extreme indices is provided using reference near‐surface temperaturesEstimate uncertainties of climate indices for reanalysis validation and quantification of extremes by propagating measurement uncertaintiesUSCRN traceable measurements with quantified uncertainties increase confidence in estimating extreme indices and decisions for adaptation [ABSTRACT FROM AUTHOR]

The Tibetan Plateau is a driver and amplifier of global climate change. The increased frequency and scale of landslides in this area are one of the manifestations of extreme climate change. Studying the trigger of landslides is of great value to the research, protection, and management of engineering geology and climatic environmental changes. However, to our knowledge, there is no efficient, convenient and intelligent method to recognize the trigger of landslides in the Tibetan Plateau. Therefore, a new high-efficiency and high-precision deep learning algorithm has been proposed in this study to analyze the landslides triggers. Specifically, this paper proposes a novel lightweight neural network landslide classification method (MNTL) based on MobileNet-V2 and transfer learning. Mobilenet-V2 requires few parameters and few floating-point operations per second. Furthermore, it is integrated with transfer learning to improve the representation learning ability of the model. The proposed method was applied to classify landslides induced by rainfall and thawing effect. The method required only 30 samples of each class, and it converged quickly in just 3 min and achieved a 94% forecast accuracy. Compared with six state-of-the-art deep learning classification methods—specifically, VGG-16, VGG-19, ResNet-50, ResNet-101, Inception, and MobileNet-V2, the proposed method exhibited competitive advantages in terms of convergence speed and generalization capability. MNTL can be embedded into the mobile terminal, which is conducive to the rapid application of landslide-related research results at a small cost. More importantly, the work in this paper could serve as a potential basis for advancing research on the correlation between landslide hazards and climate change in southeast Tibet. [ABSTRACT FROM AUTHOR]

Flood events have caused huge disasters with regard to human life and economic development, especially short-term flood events that have occurred in recent years. Gravity Recovery and Climate Experiment (GRACE) satellites can directly detect the spatiotemporal characteristics of terrestrial water storage anomalies (TWSA), which play an important role in capturing flood signals. However, the monthly resolution of GRACE-derived TWSA limits its application in monitoring sub-monthly flood events. Therefore, this paper first reconstructs the daily TWSA based on a statistical model with near real-time precipitation and temperature as input variables, and then three daily flood monitoring indexes are developed based on the reconstructed TWSA. Furthermore, these indexes are employed to evaluate the temporal and spatial characteristics of the 2016 short-term flood event in the Haihe River basin (HRB), including the flood potential index (FPI), water storage deficit index (WSDI), and combined climate deviation index (CCDI). In contrast to previous studies, the temporal resolution of TWSA-based indexes is improved from the monthly scale to the daily scale, which largely improves the temporal characterization of flood monitoring. Results demonstrate that (1) among ten kinds of "Temperature-Precipitation" combinations, the reconstructed TWSA based on CN05.1-CN05.1 match well with the GRACE TWSA, as well as publicly available daily TWSA datasets with a Nash-Sutcliffe efficiency coefficient (NSE) of 0.96 and 0.52 ~ 0.81 respectively. (2) The short-term flood characteristics can be better characterized by the reconstructed daily TWSA based on CN05.1-CN05.1, reaching the peak of 216.19 mm on July 20 in the flood center. Additionally, the spatial characteristics of the equivalent water height (EWH) are detected to evolve from southwest to northeast during the short-term flood. (3) FPI, WSDI, and CCDI are proven to be effective in monitoring flood events in the HRB, which validates the reliability of the reconstructed daily TWSA. Moreover, compared to the 56% and 66% coverage of damage quantified by FPI and CCDI, the 45% damage coverage of the flood mapped by WSDI is more consistent with the governmental reports within the HRB. This paper is expected to provide a valuable reference for the assessment of short-term events caused by extreme climate change. [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]

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]

Against the background of growing concern about climate change, this study attempts to examine the impact of US climate policy uncertainty on exchange rate volatility. Specifically, this paper explores whether climate policy changes and their extreme observations, as well as the short-term asymmetry of exchange rate volatility, can help predict future exchange rate volatilities. The in-sample estimation results show that the uncertainty of US climate policy significantly affects the volatility of the US exchange rate, and extreme positive shocks of climate policy uncertainty have a greater impact on the exchange rate than extreme negative shocks of the same magnitude. In addition, we find significant asymmetries in the short-term components of exchange rate volatility, especially in the USD-CNY exchange rate and the USD-EUR exchange rate. Multiple out-of-sample forecasting tests show that models incorporating extreme values of climate policy uncertainty exhibit superior forecasting performance. Notably, the predictive performance of these models tends to be stronger during periods of low volatility and relatively weak during periods of high volatility. This paper provides valuable insights for stakeholders to make informed decisions and optimize strategies in the face of uncertain climate policies. [ABSTRACT FROM AUTHOR]

Quantifying the extent of change in climatic and hydrological variables in the past and the future is essential for climate change-resilient development, especially in the climate change sensitive region of Nepal. This paper analyzed future climatic trends and extremes, historical hydrological extremes and their linkage with historical precipitation extremes, and discussed the impacts of climate change on various sectors in the less-studied Small and Medium-sized Eastern River Basins (SMERB) of Nepal. Applying an ensemble of five Coupled Model Intercomparison Project phase 6 (CMIP6) global climate models (GCMs), we evaluated 10 precipitation and 13 temperature extreme indices using Climpact2 for the historical (1979–2020), near-future (2021–2045), mid-future (2046–2070) and far-future (2071–2100) under two Shared Socioeconomic Pathway (SSP), SSP245 and SSP585. Hydrological extreme indices were assessed using Indicators of Hydrologic Alteration tool. Projected climate revealed significant increase (9–73%) in annual and seasonal rainfall except winter; frequent intense rainfall extremes but prolonged dry spells; significant increasing minimum and maximum temperature trends (0.4–5 °C); rise in extreme heat events; increasing minimum and maximum discharge extreme trends in most hydrological stations; as well as strong association between maximum 1 day precipitation (Rx1day) and 1 day max flow for all stations. Growing dry periods but intense rainfall in few wet days, coupled with warming pattern all-over SMERB with frequent extreme events indicate high risk for future climate-related disasters. The harsher climate will potentially have damaging implications, especially in climate-induced disasters, food security, and water and sanitation infrastructure. [ABSTRACT FROM AUTHOR]

Since the droughts of the 1970s–1980s, populations in the Sahel region have opted for a mass exodus to more humid urban or rural centers. Migrations or exoduses have accelerated in recent decades due to environmental degradation and unfavorable climatic conditions. Insufficient harvests are the main reason for migration for the majority of migrants in the Sahelian areas. Migration is a major adaptation strategy to cope with extreme climatic conditions, thus requiring quantification in the destination area. The aim of this paper is to propose a metapopulation model to approximate reality by identifying the transition from one socioeconomic vulnerability group to another, from a less favorable area to favorable area in terms of natural resources, depending on the strategies, policies, and climate variability. The model was used to analyze the dynamics of socioeconomic vulnerability to study the impact of migration on the dynamics of socioeconomic vulnerability. The developed mathematical model was analyzed. Up to 2050, simulations applied to the Tougou village in northern Burkina Faso show that migration has a positive impact on the socioeconomic vulnerability of the destination area, thereby reducing the vulnerability of the population by 10% when resources are increased by up to 30%. [ABSTRACT FROM AUTHOR]

Wildfire risk is greatest during high winds after sustained periods of dry and hot conditions. This paper is a statistical extreme-event risk attribution study that aims to answer whether extreme wildfire seasons are more likely now than under past climate. This requires modeling temporal dependence at extreme levels. We propose the use of transformed-linear time series models, which are constructed similarly to traditional autoregressive–moving-average (ARMA) models while having a dependence structure that is tied to a widely used framework for extremes (regular variation). We fit the models to the extreme values of the seasonally adjusted fire weather index (FWI) time series to capture the dependence in the upper tail for past and present climate. We simulate 10 000 fire seasons from each fitted model and compare the proportion of simulated high-risk fire seasons to quantify the increase in risk. Our method suggests that the risk of experiencing an extreme wildfire season in Grand Lake, Colorado, under current climate has increased dramatically relative to the risk under the climate of the mid-twentieth century. Our method also finds some evidence of increased risk of extreme wildfire seasons in Quincy, California, but large uncertainties do not allow us to reject a null hypothesis of no change. [ABSTRACT FROM AUTHOR]

According to numerous reports, the year 2023 is considered the hottest year on record, as a series of natural disasters have struck especially in countries bordering the Mediterranean Sea. These calamities, such as vegetation fires and floods like the recent ones in Greece, are not just a localised threat, but one that goes beyond the perimeter of countries bordering the Mediterranean Sea, as these uncommon occurrences of nature are also being observed in other parts of the world. Considering that this sort of threat is highly unpredictable and requires specific measures, this paper aims to assess the effects of the recent natural disasters in Southern Europe and to identify measures taken by Greece to counter and mitigate the effects of the mentioned calamities. [ABSTRACT FROM AUTHOR]

Extreme climate change is an existential threat to humanity and infrastructure development. At the same time, the construction and operation of carbon-intense public–private partnership (PPP) infrastructure such as road transport, water, public houses, energy supply and sanitation unleash most of the greenhouse gas emissions that impacts negatively on the climate. Increasingly, there is a heightened interests in the development and financing of climate-smart PPP solutions to promote resilient and sustainable public infrastructures. Therefore, this article aims at identifying the critical solutions to the provision of climate-smart PPP infrastructure projects together with the driving factors and challenges of its implementation in public facilities. The paper utilized a systematic literature review method where data were sourced from prominent academic databases of Scopus, Web of Science, Google Scholar, and PubMed. The outcomes of the review demonstrate that the adoption of climate finance, renewable energy, and maintaining resilient infrastructures are prominent solutions to attain low-carbon infrastructure development. Key drivers such as the global call to reduce huge emissions from construction projects and transition to sustainable green construction management account for the shift toward climate-smart PPP projects. The barriers identified include poor and unconcerted practice and policy directions to resolve emission problems in the construction industry. The outcomes of this article provide incentives for the development and management of climate-smart public projects. Researchers can harness the results to investigate and develop adaptation and mitigation strategies for low-carbon PPP projects. [ABSTRACT FROM AUTHOR]

This paper's aim is to provide clear basic explanation of the relationship between human health and climate change. It focuses on global warming, connecting it with the greenhouse effect and describing various effects the global warming has already had on human health. After the disclosure of other threats connected to climate change, the paper studies the history of it according to the Anthropocene concept theory. It also uses the perspective of weather extremes to explain climate change in the past and its connection to human health. Furthermore, this article focuses on the air pollution and its impact on the health of human population. Lastly, it touches on the topic of health inequalities and provides collected data and numbers for the future of climate change and human health. [ABSTRACT FROM AUTHOR]

This paper aims to measure the tail‐risk dependence between climate change and commodity futures markets. We utilize Morgan Stanley Capital International Climate Change Index (CCI) to serve as a proxy indicator of the stock market climate change for examining the tail‐risk spillover effect among 16 major commodity futures. Using GARCH–Copula–CoVaR framework, we show that extreme climate change has a significant tail‐risk spillover effect on commodity futures markets, in which agricultural and energy futures are affected by climate change most. We then adopt the copula‐based generalized autoregressive conditional heteroskedasticity (GARCH) model to compute the optimal hedge ratio among each pair of CCI with commodity futures, which performs well economic advantages for all 16 commodities. Compared with hedging against commodity index, CCI has a more significant hedging effect on metal and energy subindex futures. Therefore, we finally suggest an effective hedging portfolio composed of CCI and subindex futures in a significant economic sense. [ABSTRACT FROM AUTHOR]

Global warming and rare weather caused by climate change continue to affect ecosystems, human health, and economic systems, which pose serious climate risk challenges for humanity. To address and adapt to climate change risks and to facilitate the process of achieving carbon peaking and carbon-neutral targets, the financial industry has become more concerned about the information spillover effects of extreme climate events on green financial products. Therefore, this paper adopts the Southern Oscillation Index (SOI) to describe climate change and investigates the influence of the SOI on the volatility of the NASDAQ OMX Green Economy Index (OMX-GEI) under a variant of the Double Asymmetric GARCH-MIDAS (DA-GM-X) model. The results show that the SOI provides relevant information for OMX-GEI volatility forecasting and the DA-GM-X model yields outstanding forecasting performance in statistical and economic terms. This conclusion indicates that considering SOI and its asymmetry changes can significantly improve the prediction accuracy of econometric models. Also, several robustness tests confirm our findings. Overall, the findings of this paper suggest that to achieve the two-carbon goal and combat climate change, governments should pay more attention to policy formulation that combines environment, climate, health, energy, and economy, and actively promote green, low-carbon, and sustainable energy development globally. [ABSTRACT FROM AUTHOR]

Among several devastating natural hazards, flooding is a common and serious threat to society causing huge loss of lives, properties, and infrastructure throughout the world. The intensity and frequency of this extreme weather event are expected to increase due to significant changes in the present‐day climate and land use and land cover (LULC) pattern. India has a very systematic and organized structural program and policies but lacks proper implementations, and adverse effect of climate change and the extreme event goes on in society. This paper is an analysis of floods in India and hazards due to climate change and LULC change patterns. Three models, namely "Eco‐biogeography‐based optimization (EBO), Random forest (RF), and Support vector machine (SVM)" were used to obtain the final output to prepare a "Flood susceptibility map". The result was validated through the "Receiver operating characteristics (ROC)" with "Area under curve (AUC)" values. The future rainfall scenario has been estimated by considering the "General circulation models" through different "shared socioeconomic pathways (SSPs)". The values of AUC are 0.915 (EBO), 0.887 (RF), and 0.869 (SVM), respectively. After consideration of different SSPs, the result shows that there is an increasing tendency of flood hazards in the projected period. Among all the employed modelling approaches, the EBO model has notable potential in delineating the possible flood‐prone regions for effective flood planning and management. Decision‐makers can benefit from country‐specific information and regional planner to implement sustainable and long‐term measures to overcome this type of hazardous situation. [ABSTRACT FROM AUTHOR]

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Basin ecohydrological processes are essential for informing policymaking and social development in response to growing environmental problems. In this paper, we review watershed ecohydrology, focusing on the interaction between watershed ecological and hydrological processes. Climate change and human activities are the most important factors influencing water quantity and quality, and there is a need to integrate watershed socioeconomic activities into the paradigm of watershed ecohydrological process studies. Then, we propose a new framework for integrated watershed management. It includes (1) data collection: building an integrated observation network; (2) theoretical basis: attribution analysis; (3) integrated modeling: medium- and long-term prediction of ecohydrological processes by human–nature interactions; and (4) policy orientation. The paper was a potential solution to overcome challenges in the context of frequent climate extremes and rapid land-use change. [ABSTRACT FROM AUTHOR]

Hydro-hazards are increasing in frequency due to climate change which has inspired a cultural change in Flood Risk Management (FRM). Uncertainty associated with climate change has resulted in a shift towards flood resilience as it helps deal with unexpected climatic perturbations that impact extreme flows. The concept of resilience has increased in popularity, leading to a multitude of definitions, measurements and applications. This paper systematically reviews the FRM literature to provide clarity on the differing perspectives of resilience and how they influence successful implementation of the concept. Our analysis assesses where FRM is positioned within three pre-defined interdisciplinary understandings of resilience. The polysemic nature of resilience has produced a multitude of different perspectives that prevent successful operationalisation. Resilience is interdisciplinary; therefore it requires integration between top-down and bottom-up FRM approaches, as well as a more holistic approach to the interdependence between temporal and spatial scales. [ABSTRACT FROM AUTHOR]

Sub-Saharan Africa, of which Kenya is part, is considered the most vulnerable region to climate change impacts due to its dependence on rain-fed agriculture and natural resources. Since the rural livelihood systems in Kenya are expected to bear some of the worst effects of climate change, it is imperative to assess rural households' vulnerability to climate change impacts to facilitate the development of adaptation strategies. Therefore, this paper determines the level and sources of households' livelihood vulnerability to climate variability in the Migori River watershed, Kenya. The Livelihood Vulnerability Index (LVI) framed within the Intergovernmental Panel on Climate Change (IPCC) vulnerability framework (LVI-IPCC) was applied. A cross-sectional household survey conducted on 318 randomly selected households was used to assess how vulnerability differs across three watershed zones, upstream, midstream, and downstream. The LVI-IPCC scores were −0.047, −0.003, and 0.008 for the upstream, midstream, and downstream zones, respectively, with significant differences noted in the scores (ANOVA, p < 0.05). Findings indicate that while the livelihoods in all three zones showed moderate vulnerability to environmental and socio-economic stressors, there are notable variations between them. The downstream households exhibit the highest vulnerability, attributed to their lower adaptive capacity, increased exposure, and heightened sensitivity. Conversely, the upstream households demonstrate the least vulnerability compared to the other zones, owing to their lower sensitivity and exposure, as well as better adaptive capacity. Policy recommendations for reducing households' exposure to climate risks and for strengthening their adaptive capacity are discussed. [ABSTRACT FROM AUTHOR]

Rodents are one of the most abundant and diverse groups of mammals in arid zones. Their population and community dynamics are closely linked to climatic factors and pulses of primary productivity activation. In the future, climatic conditions in arid ecosystems could become more extreme as a consequence of climate change, which could affect the species that inhabit these regions. In this paper, we review the literature on the ecological response of rodents in the world's arid zones, at the population and community levels, to climatological factors (temperature and precipitation), climatic events and the possible impact of climate change. We used the PRISMA protocol to systematically search the literature, and the “vote‐counting” method to count positive, null or negative responses of the rodents. At the population level, rodent density and abundance responded positively to precipitation, while biomass responded negatively and reproduction responded positively to increasing temperature. At the community level, rodent density, biomass and diversity increased after rainfall. El Niño events were positively related to rodent population increases. In contrast, intense storms affected the survival of some species. Rodents with physiological adaptations suited to living in arid areas, for example, the heteromyids, responded positively to precipitation and could suffer fewer negative ecological consequences in the future when exposed to increased temperature and changes in precipitation. [ABSTRACT FROM AUTHOR]

Recent years have witnessed climate change characterized by increasingly frequent extreme precipitation events, and the assumption of stationarity in traditional frequency analyses is gradually being questioned. In terms of the current research status in China, there is a lack of thorough investigations on the linkage between extreme precipitation and climate change. This paper aims to determine the dominant climate indices as well as the corresponding significant time scales and periods affecting extreme precipitation over China for dynamic assessments of the upcoming rainstorm risk. Correlations between 15 climate indices and precipitation extremes, as well as the correlations among climate indices, are fully explored to identify potential predictors for non-stationary modeling. Then, 21 non-stationary generalized extreme value (GEV) models are constructed, and the optimal covariates as well as their lag times with extreme precipitation at 769 stations are ascertained in a Bayesian framework. Finally, a complete predictive process is developed, and the national rainstorm risk under non-stationary conditions is assessed. The results indicate that precipitation extremes remain stationary only at 74 stations (less than 10%). WPI is dominant in modeling the variability in precipitation extremes for nearly 22% of the total stations, ranking first among all the climate indices. The predominant time scale affecting extreme precipitation at the majority of stations is 3 months. Ignoring the non-stationarity of extreme precipitation inevitably leads to misperceptions of rainstorm risks, and the spatial distribution of the maximum case of the design rainstorms under non-stationary conditions differs remarkably from that under stationary conditions. Our findings have important implications for the in-depth understanding of the real drivers of extreme precipitation non-stationary and enable advanced predictions of rainstorm risks for mitigating subsequent disasters. [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]

The uncertainty of climate change's impacts hinders adaptation actions, particularly micro-scale urban design interventions. This paper proposes a sixfold urban design framework to assess and enhance the resilience of urban form to climate change, where urban form refers to the patterns of streets, buildings, and land uses. The framework is then applied to Long Bay in Negril, Jamaica–a coastal area that incorporates the complex interactions between urbanization and a highly vulnerable socio-ecological system to climate change-related hazards, primarily sea-level rise. Empirical evidence from 19 in-depth interviews with planning and design professionals and development actors, in situ observations, and morphological analyses reveal that Long Bay's current adaptation strategies heavily rely on bounce-back resilience measures that predominantly consider the impacts of extreme climatic events rather than slow-onset ones. Such strategies abet current tourism-driven development patterns while overlooking Long Bay's inherent abilities for generative transformation and incremental changes to meet climatic uncertainty. Instead, this study's findings highlight how generative urban form transformation would better equip Long Bay to cope with future uncertainty–climatic or other. [ABSTRACT FROM AUTHOR]

The wine sector faces important challenges related to sustainability issues and the impact of climate change. More frequent extreme climate conditions (high temperatures coupled with severe drought periods) have become a matter of concern for the wine sector of typically dry and warm regions, such as the Mediterranean European countries. Soil is a natural resource crucial to sustaining the equilibrium of ecosystems, economic growth and people's prosperity worldwide. In viticulture, soils have a great influence on crop performance (growth, yield and berry composition) and wine quality, as the soil is a central component of the terroir. Soil temperature (ST) affects multiple physical, chemical and biological processes occurring in the soil as well as in plants growing on it. Moreover, the impact of ST is stronger in row crops such as grapevine, since it favors soil exposition to radiation and favors evapotranspiration. The role of ST on crop performance remains poorly described, especially under more extreme climatic conditions. Therefore, a better understanding of the impact of ST in vineyards (vine plants, weeds, microbiota) can help to better manage and predict vineyards' performance, plant-soil relations and soil microbiome under more extreme climate conditions. In addition, soil and plant thermal data can be integrated into Decision Support Systems (DSS) to support vineyard management. In this paper, the role of ST in Mediterranean vineyards is reviewed namely in terms of its effect on vines' ecophysiological and agronomical performance and its relation with soil properties and soil management strategies. The potential use of imaging approaches, e.g. thermography, is discussed as an alternative or complementary tool to assess ST and vertical canopy temperature profiles/gradients in vineyards. Soil management strategies to mitigate the negative impact of climate change, optimize ST variation and crop thermal microclimate (leaf and berry) are proposed and discussed, with emphasis on Mediterranean systems. [ABSTRACT FROM AUTHOR]

Simple Summary: Anthropogenic climate change is one of the greatest threats to biodiversity. Extreme temperature events associated with longer-term climate change are increasing in frequency, duration and intensity. The effects of climatic extremes on ectotherms, such as insects, have been well-studied in recent years. However, the effects of extreme temperatures on other arthropod groups, such as spiders, has received much less attention. Spiders are important organisms as predators in natural and agricultural ecosystems. In this paper, we describe spider responses to extreme temperatures and highlight the most important knowledge gaps that urgently need to be filled to better understand how vulnerable spiders are to climate change and climatic extremes. Unlike insects, traits such as body size and niche breadth may differ markedly in male and female spiders. Therefore, we argue that research needs to address the effects of heat exposure on the physiology, behavior and ecology of male and female spiders across multiple taxa. Observed declines in some terrestrial insects have been widely reported in recent years, with climate change, along with other anthropogenic threats, being implicated. Longer-term data on trends in spider abundance, where available, may also shed possible light on the role of climate change. Climatic extremes, such as heat waves, are increasing in frequency, intensity and duration under anthropogenic climate change. These extreme events pose a great threat to many organisms, and especially ectotherms, which are susceptible to high temperatures. In nature, many ectotherms, such as insects, may seek cooler microclimates and 'ride out´ extreme temperatures, especially when these are transient and unpredictable. However, some ectotherms, such as web-building spiders, may be more prone to heat-related mortality than more motile organisms. Adult females in many spider families are sedentary and build webs in micro-habitats where they spend their entire lives. Under extreme heat, they may be limited in their ability to move vertically or horizontally to find cooler microhabitats. Males, on the other hand, are often nomadic, have broader spatial distributions, and thus might be better able to escape exposure to heat. However, life-history traits in spiders such as the relative body size of males and females and spatial ecology also vary across different taxonomic groups based on their phylogeny. This may make different species or families more or less susceptible to heat waves and exposure to very high temperatures. Selection to extreme temperatures may drive adaptive responses in female physiology, morphology or web site selection in species that build small or exposed webs. Male spiders may be better able to avoid heat-related stress than females by seeking refuge under objects such as bark or rocks with cooler microclimates. Here, we discuss these aspects in detail and propose research focusing on male and female spider behavior and reproduction across different taxa exposed to temperature extremes. [ABSTRACT FROM AUTHOR]

Summary 1: The first text explores power imbalances in market structures, showing how smallholders and traders are at a disadvantage due to the bargaining power of downstream buyers and product differentiation. It challenges the notion that traditional food systems are inefficient by revealing that supermarkets associated with retailers produce more waste compared to traditional markets.Summary 2: The second text focuses on the aftermath of the Beirut Harbour explosion in 2020, highlighting the role of civil society in rebuilding the city when centralized governmental efforts were lacking. It discusses how participating in the rebuilding process created new forms of solidarity and encounters that helped people find solace and reorient themselves.Summary 3: The third text examines the significance of forests for food security in Sangthong District, Laos. It finds that forest food plays a crucial role in the food security of the population, particularly for lower wealth groups. The study also emphasizes the negative impact of deforestation and forest degradation on food security and suggests integrating forests into food security strategies.Summary 4: The fourth text discusses the impact of climate change on archaeological sites in the Arctic. It highlights the vulnerability of these sites to permafrost thaw, increased vegetation, and coastal erosion. The text calls for further research and methodologies to assess the environmental threats posed by climate change on archaeological remains. [Extracted from the article]

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]

Enhancing community capacity towards resilience is key to reducing climate disaster risk, especially in Black immigrant communities in Canada. While there are many extreme climate change events occurring, such as hailstorms, floods, snowstorms, forest fires, droughts, and heat waves in western Canada, there is no known study that has explored resilience within sub‐Saharan African immigrant communities to climate disaster risks in western Canada. All these extreme climate change events have devastated Black populations threatening their ability to cope with disaster risks. Following a decolonial phenomenology methodological framework research approach; our study explores sub‐Saharan African immigrant communities' adaptation strategies to address climate disaster risk in western Canada. In this research, our main purpose was to investigate whether community resilience strategies implemented by the two provinces (Saskatchewan and Alberta) meet the unique needs of sub‐Saharan African Immigrants. By exploring local communities' perspectives on climate change, we highlighted the relevance of inclusivity in climate capacity building to reduce disaster risk and cope with climate change‐related disasters in the localities. Our findings revealed that personal experiences with climate change risks significantly influenced communities' strength and resilience and contributed to their resilience strategies. We view this paper as a first step in developing a community‐led climate change resilience research agenda that will have a practical application for the community in the face of climate change in Canada. [ABSTRACT FROM AUTHOR]

Emerging economies (EMEs) often ignore effective mitigation strategies for persistent climate changes to prioritise growth acceleration. This paper shows that they cannot sustain their economic growth due to the adverse impact of temperature rise on total factor productivity (TFP). Using a standard growth model, it demonstrates how temperature rise and variation for growing carbon emissions reduce capital productivity along with the damage to ecosystem services and labour productivity, adversely impacting total factor productivity (TFP) of an individual economy. A cross-sectional augmented auto-regressive distributed lag model (CS-ARDL), which addresses the issues of endogeneity, heterogeneity and cross-sectional dependence with stochastic trends, has been applied to 21 EMEs over the period from 1990 to 2018 and reveals a strong negative impact of temperature rise on total factor productivity. Although EMEs have heterogeneous impacts across the countries depending upon their climatic zones and income levels, one degree increase in temperature, on average, has decreased the TFP by approximately 3.22 per cent. It is much higher in the extreme climatic zones and less developed economies. • Temperature rise and its variation for raising carbon emission reduce capital productivity along with ecosystem services and labour productivity, adversely impacting total factor productivity (TFP). • The cross-sectional augmented auto-regressive distributed lag model (CS-ARDL), which addresses endogeneity, cross-sectional dependence and heterogeneity, has been applied to 21 emerging markets and developing economies for 1990 to 2018 and reveals a strong negative impact of temperature rise on total factor productivity. • One-degree increase in temperature, on average, reduces the TFP by approximately 3 per cent. • The temperature rise has heterogeneous and non-linear impacts on TFP across countries in geo-climatic locations. • Two extre-climatic zones are worse-affected than the moderate-climatic region. [ABSTRACT FROM AUTHOR]

This paper investigates how variations in sediment supply, grain size distribution and climate change affect channel morphology and flood inundation in the Nakkhu River, Kathmandu, Nepal. Climate change‐induced extreme rainfall is expected to increase flood intensity and frequency, causing severe flooding in the Kathmandu basin. The upper reaches of the Nakkhu River are susceptible to landslides and have been impacted by large‐scale sand mining. We simulate potential erosion and deposition scenarios along a 14 km reach of the Nakkhu River using the landscape evolution model CAESAR‐Lisflood with a 10 m digital elevation model, field‐derived sediment grain size data, daily discharge records and flood forecast models. In a series of numerical experiments, we compare riverbed profiles, cross‐sections, flood extent and flow depths for three scenarios (1.2‐, 85‐ and 1000‐year return period floods). For each scenario, the model is first run without sediment transport and then with sediment transport for three grain size distributions (GSDs) (observed average, finer and coarser). In all cases, the inclusion of sediment led to predicted floods of a larger extent than estimated without sediment. The sediment grain size distribution was found to have a significant influence on predicted river morphology and flood inundation, especially for lower magnitude, higher probability flood events. The results emphasise the importance of including sediment transport in hydrological models when predicting flood inundation in sediment‐rich rivers such as those in and around the Himalaya. [ABSTRACT FROM AUTHOR]

Since land use/cover change profoundly impacts climate change and global warming has become an irreversible trend in the Anthropocene, there have been numerous global studies on the impact of climate change on vegetation growth (VG). However, the effects of climate extremes on the growth and direction of various vegetation types need to be better investigated, especially in the climate transition zones. In this paper, we examined the effect of diurnal warming on the growth of various types of vegetation in China's north–south transition zone. Based on the daily observation data of 92 meteorological stations in the Qinling-Daba (Qinba) mountainous area from 1982 to 2015, coupled with the Normalized Difference Vegetation Index (NDVI) and data on the type of vegetation. This research examined the temporal changes in the highest and lowest temperatures during the last 33 years using trend analysis. Second-order correlation analysis was used to investigate vegetation NDVI response characteristics to diurnal warming and to examine the effect of diurnal warming on the growth of different vegetation types. Our results showed that maximum temperature (Tmax) and minimum temperature (Tmin) showed an obvious upward trend, with the daytime temperature increase rate 1.2 times that at night, but failing the t-test. In addition, diurnal warming promoted vegetation growth, with NDVI associated positively correlated with Tmax at approximately 91.2% of the sites and 3492 rasters and with Tmin at roughly 53.25% of the sites and 2864 rasters. Spatial significance analysis showed an apparent difference, but few areas passed the t-test. Furthermore, daytime warming enhanced the growth of grasses, shrubs, deciduous broad-leaved forests, crops, and conifers, while the effect of nighttime warming on VG had a positive effect only on the growth of evergreen broad-leaved forest vegetation. These findings reveal the mechanisms of the impact of climate extremes on VG under global change, particularly the extent to which different vegetation types in climatic transitional zones respond to climate extremes. [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]