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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]

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]

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]

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]

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]

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]

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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.)

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]

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]

This paper presents a synthesis of the main characteristics of precipitation in the State of Rio de Janeiro (Brazil) based on extreme rainfall indicators. Daily precipitation data are derived from 56 rainfall stations during the second half of the twentieth century and the 2000s. Eight indices related to extreme precipitation were analyzed. The Mann–Kendall nonparametric test and the Sen's Curvature were employed to evaluate the significance and magnitude of trends. The primary climatological aspects and identified trends throughout the last decades are discussed, besides the hydrometeorological impacts associated with them. Lower values of annual total precipitation are recorded in northern Rio de Janeiro (around 800 mm) and higher in the southern State (up to 2,200 mm). The Serra do Mar affects the frequency of heavy precipitation, and the areas near the sea and high relief present the highest values of consecutive days with expressive rainfall (more than 150 mm in 5 days). These areas also showed a high concentration of flood and landslides events. Most of Rio de Janeiro exhibits precipitation intensity of about 13 mm/day. The maximum number of consecutive dry days shows a gradient from the coast (about 30 days) to the State's interior (around 50 days). Regarding trends, there is a growth of accumulated extreme precipitation in various stations near the ocean. The extreme rainfall in 24 h displays an increase in most Rio de Janeiro (+ 1 to + 5 mm/decade). The consecutive dry and rainy days present similar signs of decreasing trends, suggesting irregularly distributed precipitation in the State. This study is especially relevant for decision-makers who need detailed information in the short and long term to prevent natural hazards like floods and landslides and the related impacts in the environmental and socioeconomic sectors of the Rio de Janeiro. [ABSTRACT FROM AUTHOR]

The Yangtze River Economic Belt (YREB) is an important strategic area in China. However, frequent extreme precipitation events have caused great economic losses and human casualties in this region. In this article, we explore the spatial and temporal links between extreme precipitation events and Sunspot Number (SSN), El Niño Southern Oscillation (ENSO), Arctic Oscillation (AO) and Pacific Decadal Oscillation (PDO) in this important economic belt. According to the research findings, all of the extreme precipitation indices (EPIs) except for consecutive dry days (CDD) and consecutive wet days (CWD) showed an upward trend in the YREB over the 59 years. The spatial distributions of very wet days (R95p), extremely wet days (R99p), max 1-day precipitation amount (Rx1day) and max 5-day precipitation amount (Rx5day) had similar distribution patterns, showing decreasing trends from east to west. The EPIs generally had a 2–4-year band, suggesting stronger and more elusive changes. The wavelet coherence (WTC) spectra suggested that SSN, ENSO, AO, and PDO have different effects on extreme precipitation events during different time periods. Before 1985, the SSN, ENSO, AO, PDO and extreme precipitation events shared similar oscillation periods, but after 1985, their oscillation periods were no longer consistent with each other. In addition, solar activity and the AO mainly had negative correlations with extreme precipitation events, while the ENSO and PDO had predominantly positive correlations with the EPIs. This paper provides a reference for national economic strategic planning and natural resource management in the YREB. [ABSTRACT FROM AUTHOR]

Concurrent compound dry and hot events (CDHEs) amplified more damange on the ecosystems and human society than individual extremes. Under climate change, compound dry and hot events become more frequent on a global scale. This paper proposes a mathematical method to quantitatively attribute changes of CDHEs to changes of precipitation, change in temperature and change in the dependence between precipitation and temperature. The attribution is achieved by formulating the total differential equation of the return period of CDHEs among Meta-gaussian model. A case study of China is devised based on monthly precipitation and temperature data during the period from 1921 to 2020 for 80 major river basins. It is found that temperature is the main driving factor of increases in CDHEs for 49 major river basins in China, except for the upper and middle reaches of the Yangtze River. In West China, precipitation changes drove the increase in CDHEs in 18 river basins (23%), particularly in parts of North Xinjiang, Qinghai and Gansu. On the other hand, dependence between precipitation and temperature dominated changes of CDHEs in 13 river basins (16%) of China with other factors, including parts of South China, East China and Northwestern China. Furthermore, changes in both the mean and spread of precipitation and temperature can also contribute to changes in CDHEs. [ABSTRACT FROM AUTHOR]

For those involved in planning for regional and local scale changes in future climate, there is a requirement for climate information to be available in a context more usually associated with meteorological timescales. Here we combine a tool used in numerical weather prediction, the 30 weather patterns produced by the Met Office, which are already applied operationally to numerical weather prediction models, to assess changes in the UK Climate Projections (UKCP) Global ensemble. Through assessing projected changes in the frequency of the weather patterns at the end of the 21st Century, we determine that future changes in large-scale circulation tend towards an increase in winter of weather patterns associated with cyclonic and westerly wind conditions at the expense of more anticyclonic, settled/blocked weather patterns. In summer, the results indicate a shift towards an increase in dry settled weather types with a corresponding reduction in the wet and windy weather types. Climatologically this suggests a shift towards warmer, wetter winters and warmer, drier summers; which is consistent with the headline findings from the UK Climate Projections 2018. This paper represents the first evaluation of weather patterns analysis within UKCP Global. It provides a detailed assessment of the changes in these weather patterns through the 21st Century and how uncertainty in emissions, structural and perturbed parameters affects these results. We show that the use of these weather patterns in tandem with the UKCP projections is useful for future work investigating changes in a range of weather-related climate features such as extreme precipitation. [ABSTRACT FROM AUTHOR]

Quantitative and qualitative knowledge about the potential impacts of climate change on extreme hydrological events is crucial for water resource management and extreme risk management under climate change. This has theoretical and realistic implications to study and couple the climate system with hydrologic processes, to understand the system and solve related problems in water resources and extreme hydrology, such as decision making, plan management, environmental protection, and ecological balance. This paper reviews recent studies investigating climate change impact on hydrological extremes using a perspective of the integrated modeling framework comprising climate change scenarios, climate models, bias correction methods, hydrological modeling (model structure and parameterization), and reducible uncertainty arising from these sources characterized by a paucity of knowledge. The available research outcomes show the extreme high flows are likely to increase under climate change in the most parts of Europe, Asia, and the USA, but greatly vary and decrease in Africa and Latin America, which is highly variable and uncertain in space and time. Each component in integrated modeling has an important role in shifting and producing uncertainty in projected extreme flow. Among them, the climate model's discrepancy and hydrological models' structure are the more dominant source of uncertainty in projection of extreme high and low (or mean) flow in most of the regions, respectively. However, the quality of input data and hydrological model structures are the most dominant source of uncertainty in Africa, Latin America, and some parts of Asia. This indicated that these regions have strong hydrological cycle and higher physiographic heterogeneity. We believe that our existing knowledge and skills need to be improved and transformed into an accurate mathematical and physical representation, to minimize the uncertainty due to the effect of choices in the methodology chain. So, disentangling the aggregated uncertainty in the cascade modeling chain can be done by using variances, which can help understand the interaction effect and identify their contribution to the projected extreme flow. This comprehensive review can help modelers to identify and reduce uncertainty in projecting hydrological extremes and policy makers for full awareness of the various uncertainties to make a robust decision for water resources management under climate change. Article Highlights: This study provides a comprehensive review on reducing uncertainty in projecting hydrological extremes from the perspective of an integrated modeling framework Existing knowledge and skills need to be improved and transformed into an accurate mathematical representation The impact of climate change on hydrological extremes is highly variable and uncertain in space and time Uncertainties of the integrated modeling framework can be reduced by decomposing the aggregated uncertainty using variance analysis and/or the modeling chain [ABSTRACT FROM AUTHOR]

Different geographical zones have regional heterogeneity in underlying earth surface structure and microclimate which result in different evolution trends and their response to climate change varies in extreme rainfalls in these zones. In the Guizhou province of China, there are complex landforms, which lead to spatial redistribution of rainfall, frequent extreme rainfall, and disasters high risk of geologic disasters. Research on extreme climate in Guizhou mostly paid attention to its spatio-temporal characteristics and modeling, but lack of analysis on its characteristics of extreme rainfall variability and response to temperature changes under different subsurface conditions. This study investigated the characteristics of the extreme rainfall spatiotemporal and recurrence periods in Guizhou province and discussed the relationship between the response of extreme rainfall to temperature change. Daily rainfall data from 1990 to 2020 and 2021–2100 at 31 meteorological observation stations throughout the province were collected to calculate extreme precipitation. This research had the following results. (1) Both historical and future periods show an upward trend in extreme rainfall in Guizhou province, with a spatial distribution pattern of "high in the south and low in the north, high in the east and low in the west" and "high in the southeast and low in the northwest", respectively; the spatial distribution of extreme rainfall under each recurrence period is consistent with the non-recurrence period. (2) Both historical and future periods show an upward trend in temperature in Guizhou province, with a spatial distribution consistent with that of the extreme rainfall in the corresponding period. (3) The change in extreme rainfall intensity with increasing temperature is almost always greater than the C–C rate for different periods and underlying earth surface structure; Extreme rainfall has a Hook response structure to temperature change, and the climate response structure shifts to the right with climate warming. The results of the study can provide a basis for decision-making on regional disaster prevention and mitigation in the context of temperature change. [ABSTRACT FROM AUTHOR]

Changing climatic conditions threaten forest ecosystems. Drought, disease and infestation, are leading to forest die-offs which cause substantial economic and ecological losses. In central Europe, this is especially relevant for commercially important coniferous tree species. This study uses climate envelope exceedance (CEE) to approximate species risk under different future climate scenarios. To achieve this, we used current species presence-absence and historical climate data, coupled with future climate scenarios from various Earth System Models. Climate scenarios tended towards drier and warmer conditions, causing strong CEEs especially for spruce. However, we show that annual averages of temperature and precipitation obscure climate extremes. Including climate extremes reveals a broader increase in CEEs across all tree species. Our study shows that the consideration of climate extremes, which cannot be adequately reflected in annual averages, leads to a different assessment of the risk of forests and thus the options for adapting to climate change. [ABSTRACT FROM AUTHOR]

Devising effective strategies to retard the negative impacts of extreme climatic events on water security in general and environmental water balance in specific is imperative, especially in semi-arid rural-Western-India, where climate change has markedly increased water scarcity in domestic and agricultural sectors. This exploratory research thus aimed at investigating the water budget against mismanagement of available water resources for remote-marginalized villages in rural-Nashik (West-India). Investigation entailed visual interpretation of LULC analysis (2008–2017) using fine-scale Google Earth imageries, rainfall-runoff analysis using SCS-CN method, determining the supply-demand potential of water storage structures using field-experimentations and PRA tools, and estimation of season-wise water-budget using hydrological (water-balance) equations. Results identified agriculture as the major land-use (~ 78%) followed by hilly regions (~ 16%) and water bodies (~ 3%). Surface runoff was found as the dominating hydrological phenomenon (33–89% of monsoonal rainfall) followed by surface storage (6–36% of annual rainfall) and groundwater flow (4–82% of annual rainfall). Deforestation over hills for firewood, which reduced forest cover by 52%, was observed as the primary concern for soil erosion, thereby siltation of water bodies and higher runoff against percolation. Erratic rainfall patterns (departure range − 42 to 83% during 1998–2017) coupled with sub-graded irrigational systems confined the agricultural practices to one season [South–West monsoon (June–September)]. High unmet drinking water demand (73% to 98%) forced women communities to fetch water by walking 4.5 ± 1.5 km. Considering the urgent response to collectively combat water-budget imbalance, integrated water security plans were proposed using decentralized participatory watershed development approaches. [ABSTRACT FROM AUTHOR]

Regional Climate Models (RCMs) provide climate information required for evaluating vulnerability, impacts, and adaptation at finer scales than their global driving models. As they explicitly resolve the basic conservation and state equations, they solve physics with more detail, conserving teleconnection of larger scales provided by Global Climate Models (GCMs). In South America (SA), the regional simulations have been historically evaluated principally on climatological aspects, but the representativeness of extremes still needs a more profound assessment. This study aims to analyze three RCMs (RegCM4-7, REMO2015, and Eta) driven by different GCMs in SA, focusing on their capacity to reproduce extreme historical indices of daily precipitation and temperature. The indices of maximum consecutive 5 days precipitation (Rx5day), Consecutive Dry Days (CDD), daily maximum and minimum annual temperature (TXx and TNn, respectively) were evaluated regarding the historical spatio-temporal variability and trends. Furthermore, their projections for the 2071–2099 period, under the Representative Concentration Pathway 8.5 scenario, were analyzed. The historical behavior of RCMs (1981–2005) was compared with two gridded products: Climate Prediction Center (CPC) and agrometeorological indicators derived from the fifth generation of global reanalysis produced by the ECMWF (AgERA5), previously compared with records from meteorological stations to evaluate them. The results show that the highest differences within the gridded products and stations were observed in the regions with more scarce surface stations (North and West of SA) and with complex topography (The Andes Cordillera), being more pronounced in the precipitation-based indices. We found that RCMs generally show more agreement in the spatial variability than in the inter-annual variability for all the indices and SA regions. When analyzing the observed trends, all models better reproduced the long-term variability of extreme temperature indices than those of rainfall. More disagreement was observed for Rx5day and CDD indices trends, including substantial spatial heterogeneities in both magnitude and sign of tendency. Climate change projections exhibited significant agreement to warmer conditions in TXx and TNn, but precipitation signals differed between RCMs and the driving GCM within each regional model. Maximum dry spells are expected to increase in almost all SA regions, whereas the climate change signals in extreme precipitation events are more consistent over southeastern SA (northern and southwestern SA), with positive (negative) changes by the end of the century. [ABSTRACT FROM AUTHOR]

During the crucial stage of the energy transition for combating extreme climate changes, it has been frequently discussed: Whether clean and fossil energies are substitutes or complements? To answer this question, we first analyze the correlations of some main clean and fossil energy markets in 2015–2022. After identifying and measuring the volatility spillovers in these energy markets, the original sequence is decomposed into three subsequences in each time-frequency to accurately capture the temporal relations in the short or long term. Furthermore, we select three periods when global climate change issues occurred frequently for the event analysis, then explore the linkages between the energy markets when experiencing climate uncertainties from different time dimensions. We find that the close interactions between clean energy markets are mainly presented in the long term. Meanwhile, even though the spillover effects between the oil market and others are not obvious in the original sequence, significant spillovers could be observed in the selected periods. Therefore, we can infer that the frequently-occurred climate change issues could be one of the reasons that trigger the volatility spillovers between the oil and other energy markets. As climate uncertainties increase, different reactions between the energy markets can be seen in the short term, while a synchronized trend is also easily observed in the long term. Hence, we conclude that these energies could be substitutes in the short term, while complements in the long run. The above analytic results could be helpful for policymakers and investors to cope with the market fluctuations that are brought by climate issues. [ABSTRACT FROM AUTHOR]

Climate change and atmospheric deposition of nitrogen (N) and sulfur (S) impact the health and productivity of forests. Here, we explored the potential impacts of these environmental stressors on ecosystem services provided by future forests in the contiguous U.S. We found that all stand-level services benefitted (+ 2.6 to 8.1%) from reductions in N+S deposition, largely attributable to positive responses to reduced S that offset the net negative effects of lower N levels. Sawtimber responded positively (+ 0.5 to 0.6%) to some climate change, but negatively (− 2.4 to − 3.8%) to the most extreme scenarios. Aboveground carbon (C) sequestration and forest diversity were negatively impacted by all modelled changes in climate. Notably, the most extreme climate scenario eliminated gains in all three services achieved through reduced deposition. As individual tree species responded differently to climate change and atmospheric deposition, associated services unique to each species increased or decreased under future scenarios. Our results suggest that climate change should be considered when evaluating the benefits of N and S air pollution policies on the services provided by U.S. forests. [ABSTRACT FROM AUTHOR]

Climate change is affecting the global hydrological cycle, causing drastic changes in precipitation patterns. Extreme climatic events are becoming more frequent and intense than in the past, leading to water-level fluctuations and affecting aquatic ecosystems. Semiarid regions are very susceptible to changing climate. We analyzed a 10 years dataset from a tropical semiarid reservoir during extreme hydrological events (heavy rains and prolonged drought), and evaluated phytoplankton functional responses to environmental conditions. We found, as hypothesized, that phytoplankton functional structure change in a temporal scale due to water–volume fluctuation induced by the rainfall pattern. Depth and inorganic material acted as environmental filters selecting phytoplankton groups. High water level seems to improve water quality and low water level worsen it. Colonial and filamentous cyanobacteria dominate the wet period; however, it may have a critical threshold during severe periods of drought, which will lead to dominance of groups well adapted to low light conditions and with mixotrophic metabolism. Phytoplankton functional approaches can simplify phytoplankton identification and reflect better the environmental conditions than the taxonomic approach. Therefore, these approaches can help to understand the shifts in aquatic ecosystems under extreme hydrological events and predict functional response of phytoplankton being an important tool to water management and conservation. [ABSTRACT FROM AUTHOR]

Background: Treeline ecotones of Mediterranean ecoregions have been affected by the increasing intensity and severity of droughts. Even though the effect of droughts on forest dynamics has been widely documented, knowledge is relatively scarce of how extreme climate episodes affect the hydraulic structure and, therefore, the physiology of woody plants. The Mediterranean Andes have experienced an uninterrupted period of drought since 2010, including an extremely dry year in 2019 with approximately 80% rainfall deficit. Here, we investigated shifts in wood anatomical and physiological traits of Kageneckia angustifolia, an endemic treeline species, in response to this drought period. Methods: We evaluated the xylem plasticity of three K. angustifolia populations across their natural distribution (31–35° SL) based on anatomical (vessel structure and distribution) and physiological (intrinsic water-use efficiency) variables in the tree rings. We focused on the period 2000–2020 that corresponds to before the megadrought (2000–2007), (ii) megadrought (2008–2018) and (iii) hyperdrought (2019–2020). The variables were annualized and analyzed by linear mixed-effects models. Results: Our results provide insights to the anatomical and physiological mechanisms underlying the resilience of treeline forests to persistent droughts in central Chile. We found that the extreme drought in 2019–2020 triggered shifts in vessel size and frequency that increased hydraulic safety. These significant shifts in vessel traits occurred in parallel with a decrease in pit aperture area and an increase in water-use efficiency, further increasing the resilience of K. angustifolia to extreme drought stress. Conclusions: Our results revealed coordinated shifts in vessel size and frequency and water-use efficiency in response to the megadrought, thereby reducing vulnerability to hydraulic failure. The apparent resilience of K. angustifolia to extreme droughts suggests that this adaptation to drought stress may increase its ability to tolerate novel climatic conditions of treeline environments of the Mediterranean Andes, although it is not clear whether these adaptations will be sufficient to persist in scenarios that predict intensification of climate stress. Finally, our results provide empirical evidence that integrating wood anatomical and physiological traits facilitates the understanding of resilience mechanisms that treeline forests develop in the face of increasing drought stress. [ABSTRACT FROM AUTHOR]

Agriculture-based livelihoods, dominant in rural areas of developing countries, have been facing the challenges to cope up with climate change and extreme climatic events. Therefore, livelihood analysis along with vulnerability to climate change is an important aspect to address the climate change issues. Present research was contemplated to assess the livelihood status of dominant farm livelihood groups and their vulnerability in both coastal and non-coastal ecosystems of Odisha, an Indian state that suffers from climate-induced natural disasters. It also aimed to delineate livelihood assets determining climatic vulnerability of farm households. Sustainable livelihood framework was followed in analysing differential level of physical, social, human, financial and natural assets covering a random sample of 200 farm households representing three dominant farm livelihood groups, viz. farmers cultivating crops, rearing livestock and farmers occupied with both crop + livestock farming. The farmers under study were the beneficiaries of national innovations in climate-resilient agriculture programme launched by Indian council of agricultural research since 2011. Both crop and livestock farmers belonged to similar level of livelihood with no significant differences. Farmers engaged in crop + livestock farming had overall livelihood status at above average level and social assets contributing highest to it. However, farmers engaged in crop + livestock farming significantly differed from both crop and livestock farmers with livelihood status index values of 51.73 and 62.72 in coastal and non-coastal districts, respectively. The livelihood indicators delineated as determinants of vulnerability of farm households to climate change would help in climate policy advocacy regarding institutional innovations. Climate smart technological and institutional innovations, partnership between the stakeholders and diversified livelihood options provide farm households better resilience to climate change as reflected from lower vulnerability index values in coastal regions. This calls for policy advocacy to designing and deploying climate smart socio-technical innovations bundling in terms of both technological and institutional innovations through good partnership to provide farm households diversified livelihood options and better insulation against the vulnerability to climate change in a specific agro-ecosystem. Government support in terms of financial assistance, subsidies, insurance, extension advisories and adequate institutional infrastructure would enable farmers to adopting climate smart agriculture innovations, building sustainable livelihoods and improving resilience to climate change impacts. [ABSTRACT FROM AUTHOR]

This research examined the influence of perceived child mortality risk on the fertility choices of married women in Bangladesh. Employing a cross-sectional survey conducted in four rural areas, categorized as either vulnerable or not vulnerable to extreme climate events, a total of 759 married women were surveyed through simple random sampling, while 25 women were selected for in-depth interviews through judgment sampling. The findings indicate that women in climate-vulnerable regions express a greater desire for additional children compared to those in non-vulnerable areas. Furthermore, women who perceive increased child mortality risk and have experienced past child loss show a stronger tendency towards wanting more offspring. The qualitative insights from the interviews shed light on the underlying motivations driving these preferences, emphasizing the significance of child replacement and seeking security against potential child loss. These empirical findings provide valuable insights into the complex dynamics between perceptions of child mortality and reproductive decision-making among women in Bangladesh. The implications of this study are crucial for policymakers and practitioners, as they can guide the development of targeted interventions and policies to address reproductive health challenges in climate-vulnerable areas. By acknowledging women's perspectives and considering contextual factors, these strategies can effectively address the reproductive implications of climate vulnerability, empowering women to make informed decisions about their fertility and promoting improved reproductive outcomes and overall well-being in vulnerable communities. [ABSTRACT FROM AUTHOR]

Interpreting changes in climate extremes indices and related large-scale teleconnection factors is critical to addressing intensified climate change. The spatiotemporal trend in SU25 (summer days) and ID0 (icing days), as well as the contribution rates of large-scale circulation factors, were investigated using daily maximum temperature data from 93 stations in the Shandong Peninsula and 8 metrics of large-scale teleconnections from 1961 to 2017. The results showed that SU25 increased significantly while ID0 decreased significantly in the Shandong Peninsula during the study period. SU25 ranged from 66.3 to 155.1 days and gradually declined from inland to coast. ID0 ranged from 4.7 to 24.8 days and decreased roughly from north to south. SU25 had a significant negative correlation with longitude, while the trend of SU25 had a significant positive correlation with longitude. ID0 had a significant positive correlation with both latitude and longitude, while the trend of ID0 had a significant negative correlation with both latitude and longitude. The abrupt years of SU25 were concentrated in 1965, 1976, 1977, 1994, 2007, and 2012, respectively. The change point of ID0 at each station was most concentrated in 1970, 1972, 1986, and 1988, respectively. In the future, SU25 in most stations will continue to increase, while ID0 in almost all the stations will decrease. The Atlantic Multidecadal Oscillation (AMO) was the most important factor influencing SU25 change. Both the Arctic Oscillation (AO) and AMO made significant contributions to the ID0 change. The combined results of the two factors were usually greater than the results of the single circulation factor, and the contributions to SU25 and ID0 were mostly nonlinear enhancement. [ABSTRACT FROM AUTHOR]

Most studies projecting human survivability limits to extreme heat with climate change use a 35 °C wet-bulb temperature (Tw) threshold without integrating variations in human physiology. This study applies physiological and biophysical principles for young and older adults, in sun or shade, to improve current estimates of survivability and introduce liveability (maximum safe, sustained activity) under current and future climates. Our physiology-based survival limits show a vast underestimation of risks by the 35 °C Tw model in hot-dry conditions. Updated survivability limits correspond to Tw~25.8–34.1 °C (young) and ~21.9–33.7 °C (old)—0.9–13.1 °C lower than Tw = 35 °C. For older female adults, estimates are ~7.2–13.1 °C lower than 35 °C in dry conditions. Liveability declines with sun exposure and humidity, yet most dramatically with age (2.5–3.0 METs lower for older adults). Reductions in safe activity for younger and older adults between the present and future indicate a stronger impact from aging than warming. Research examining the ability to survive or safely live under extreme heat often oversimplifies human exposure and responses. Here, the authors apply a physiology-based approach for young and older adults to improve survivability estimates and introduce liveability in current and future climates. [ABSTRACT FROM AUTHOR]

Climate change and global urbanization have often been anticipated to increase future population exposure (frequency and intensity) to extreme weather over the coming decades. Here we examine how changes in urban land extent, population, and climate will respectively and collectively affect spatial patterns of future population exposures to climate extremes (including hot days, cold days, heavy rainfalls, and severe thunderstorm environments) across the continental U.S. at the end of the 21st century. Different from common impressions, we find that urban land patterns can sometimes reduce rather than increase population exposures to climate extremes, even heat extremes, and that spatial patterns instead of total quantities of urban land are more influential to population exposures. Our findings lead to preliminary suggestions for embedding long-term climate resilience in urban and regional land-use system designs, and strongly motivate searches for optimal spatial urban land patterns that can robustly moderate population exposures to climate extremes throughout the 21st century. Considering changes in urban land extent, population, and climate over the 21st century, the authors find spatial urban land patterns can reduce rather than increase population exposures to climate extremes, even heat extremes, at regional scales. [ABSTRACT FROM AUTHOR]

Based on the ERA5 reanalysis dataset, we analyzed the changes in extreme climate indices on the MP from 1981 to 2020, and the relationship between the extreme climate indices and atmospheric circulation indices. The results showed that (1) for temperature, (a) in terms of hot events, the inter-annual variation trends of summer days, warm days, and warm nights have significantly increased across the entire MP, with the central region experiencing a higher probability of extreme hot events. The inter-decadal variation of extreme hot indices showed a considerable increase from the period of 1991 to 2000 to the period of 2001 to 2010. (b) In terms of cold events, a substantial decrease in extreme cold events was revealed, with a great decrease from the period of 1981 to 1990 to the period of 1991 to 2000. (2) For precipitation, there was a decrease in extreme wet indices from 1981 to 2020. The simple precipitation intensity index (SDII) and total precipitation in wet days (PRCPTOT) exhibited a significant descending trend in the northern and northeastern MP. Decadal variations showed a decrease in extreme precipitation events, with a significant decline observed between the period of 1991 to 2000 and the period of 2001 to 2010. (3) For the relationship between the extreme climate indices and atmospheric circulation indices, extreme temperature indices are likely influenced by polar vortices, with the Asian polar vortex area index (APVAI) negatively correlated with extreme hot indices and the Asian polar vortex intensity index (APVII) positively/negatively correlated with most extreme hot and cold indices. Asian zonal circulation index (AZCI) showed significant correlations with most extreme hot and cold indices. Extreme precipitation indices only showed significant negative correlations with the Atlantic Meridional mode (AMM). [ABSTRACT FROM AUTHOR]

Droughts and heat waves are currently recognized as two of the most serious threats associated with climate changes. Drought is characterized by prolonged dry periods, low precipitation, and high temperature, while heat wave refers to an extended period of exceptionally high temperature, surpassing the region's average for that time of year. There is a close relationship between droughts and heat waves, as both are often caused by similar weather patterns and can exacerbate each other's impacts. Therefore, it is crucial to monitor and quantify both droughts and heat waves jointly at a regional level in order to develop sustainable policies and effectively manage water resources. This article develops a new index, the standardized composite index for climate extremes (SCICE), for joint monitoring and probabilistic quantification of extreme climate events at regional level. The procedure of SCICE is mainly based on the joint standardization of standardized precipitation index (SPI) and standardized temperature index (STI). In the application of SCICE, results reveal that the long-term probabilities of the joint occurrence of dry and hot events are significantly greater than those of wet and cold events. Furthermore, the outcomes of the comparative assessment support the validity of using SCICE as a compact statistical approach in regional drought analysis. In summation, the study demonstrates the capability of SCICE to effectively characterize and assess the joint monitoring of drought and heat waves at a regional level, providing a comprehensive approach to understanding the joint impact of climate extremes. [ABSTRACT FROM AUTHOR]

Efforts to diagnose the risks of a changing climate often rely on downscaled and bias-corrected climate information, making it important to understand the uncertainties and potential biases of this approach. Here, we perform a variance decomposition to partition uncertainty in global climate projections and quantify the relative importance of downscaling and bias-correction. We analyze simple climate metrics such as annual temperature and precipitation averages, as well as several indices of climate extremes. We find that downscaling and bias-correction often contribute substantial uncertainty to local decision-relevant climate outcomes, though our results are strongly heterogeneous across space, time, and climate metrics. Our results can provide guidance to impact modelers and decision-makers regarding the uncertainties associated with downscaling and bias-correction when performing local-scale analyses, as neglecting to account for these uncertainties may risk overconfidence relative to the full range of possible climate futures. [ABSTRACT FROM AUTHOR]

Understanding the spatiotemporal variations in climate extremes indices, as well as the influencing factors, is critical to the scientific response to climate change. The temporal and spatial variations of SU25 (annual count of days when daily maximum temperature > 25 °C) were discussed in this study, based on daily maximum temperature data from 2398 meteorological stations in China from 1961 to 2017. The contributions of associated large-scale circulation factors to SU25 were quantitatively assessed by using the geographical detector method (GMD). The overall spatial distribution of SU25 was marked by a considerable increase from north to south. The SU25 increased significantly over time, with the national SU25 increasing at a rate of 2.5 days/decade. The Tibet Plateau (TP) had the slowest growth rate, with an average increase rate of 1.4 days/decade. The Hurst values of SU25 in all the subregions were generally high, indicating that most stations of SU25 would continue to increase in the future. Except for TP, the tipping years of other subregions were concentrated in the 1990s, and SU25 increased after the years. Among the large-scale circulation factors affecting SU25 in each subregion, Atlantic Multidecadal Oscillation (AMO) played a major role in SU25 variability. As a whole, the result of the pairwise interaction of each circulation factor was mainly nonlinear enhancement. The joint contributions of multiple factors to SU25 were larger than the contribution of each individual factor. [ABSTRACT FROM AUTHOR]

Pesticides are among the pollutants present in aquatic bodies. Climate change is expected to favor the growth, multiplication, persistence, and range expansion of most serious agricultural pests. In addition, due to climate change and land degradation, pest species may become more abundant, with consequent losses in agricultural production and, thus, pesticide use is likely to intensify. Temperature variations and thermal extremes caused by climate change may have profound implications for pesticide toxicity in aquatic organisms. Using a meta-analytic technique to the peer-reviewed literature, we evaluated the impacts of warming and pesticides in isolation and combination on the biological responses of freshwater biota (microalgae, invertebrates and vertebrates). Meta-analysis of the dataset showed that the association between pesticides and temperature showed more negative effects on the fitness and physiological regulation of organisms than on the isolated effects of variables. In contrast, the independent effect of pesticides affected negatively only the fitness measurements, while molecular responses were positively influenced by temperature, and physiological regulation was negatively influenced by temperature increase. Microalgae and invertebrates were the groups most negatively affected by the interaction of pesticides (atrazine, avermectin – imidacloprid, chlorpyrifos) and temperature (25 °C, 30 °C). Additional studies should consider other factors relevant to climate events in freshwater that can presumably interact with chemicals, to make more exact generalizations about chemical contamination and climate change. [ABSTRACT FROM AUTHOR]

Climate and extreme hydrometeorological studies are required to reduce risk and vulnerabilities. This study uses different cumulus and microphysics schemes in Weather Research and Forecasting (WRF) model to simulate heavy rainfall events and Cyclone Sidr in Bangladesh, where many extreme events occur. Results show that WRF can capture the cyclone track, intensity, and landfall position. In addition, regionalization and an ensemble method through Bayesian regression model (BRM) are used to improve WRF rainfall simulations. Although regionalization can improve results of the experiments with different schemes, BRM leads to the best performance. To consider uncertainties and evaluate hazards, a probabilistic framework and proper indices based on distributions are used. Spatiotemporal precipitation distributions are used to develop the flash flood index (FFI) to compare the intensity of heavy rainfall events. Results show a large FFI over the central and southeast divisions that indicates the areas prone to the flash flood hazards and high-level risk. We use standardized precipitation index (SPI) in 6- and 12-month time scales based on monthly precipitation of ACCESS-CM2 in 2015–2100 under two scenarios (SSP-126 and 585) to evaluate long-term precipitation changes and drought/flood tendency. In addition, the probability distributions of the precipitation and wind speed are used in reliability analysis of the infrastructure. Target reliability indices determine the proper design rainfall (105 mm d−1) and wind speed (60 m s−1) that leads to a safe design of infrastructure. This study provides an integrated analysis of extreme hydrometeorological events, which is crucial for sustainable adaptation and mitigation plans. [ABSTRACT FROM AUTHOR]

This study examined the impact of climate change on climate extreme indices in the Kaduna River basin, Nigeria. Large-scale atmospheric variables derived from the Global Climate Model (GCM), Coupled Model Intercomparison Project Phase 5 (CMIP5) (CanESM2) were used to develop a high-resolution climate using a Statistical Down Scaling Model. The adapted Caussinus-Mestre algorithm for homogenizing networks of temperature series and multivariate bias correction based on an N-dimension probability function were used to homogenize and correct the climate data, respectively. Fifteen climate extreme indices were computed using RClimdex. The coefficient of variance, Kruskal–Wallis test, and the modified Mann–Kendall test were used to assess the variation and trends. Wavelet analysis was used to determine the periodicities of the indices (1980–2020). The findings revealed a significant warming trend with low variability of temperature indices. The moderate variability with an insignificant decreasing trend was found for rainfall indices. Similarly, the future climate indices indicate a continuing positive trend in the temperature extreme indices. The majority of climate indices have a periodicity of less than or equal to 10 years for high frequency, except for PRCPTOT, R10MM, R20MM, Rx5day, SDII, TN90p, and TX90p for temperature indices. The findings conclude that the periodicity pattern of climate extreme indices is related to atmospheric phenomena (such as quasi-biennial oscillation, QBO), which indicate the impact of climate change. As a result, this can serve as an early warning for possible extreme event occurrences in the basin. The CMIP6 should be used to compare with the results of this study to provide a detailed assessment of the current implication of climate change on the catchment. [ABSTRACT FROM AUTHOR]

As a consequence of global warming, extreme weather events have become much more common in many countries. Extreme weather events negatively impact on mortal social and environmental issues, and recognizing the dynamical aspects of extreme weather is absolutely essential for forecasting and mitigating the implications of extreme weather occurrences on people and the planet. This research looked at the variations in space and time of 11 extreme precipitation indices and 16 extreme temperature indices in the Liaohe River Basin within Jilin Province and their associations with normalized-difference vegetation index (NDVI) and atmospheric circulation indices were evaluated. The results showed that: (1) The extreme warmth index showed a growing pattern and the extreme coldness index showed a declining tendency. The average consecutive dry days and consecutive wet days (CWD) indices showed a slow decreasing trend, and all other extreme precipitation indices showed a slowly intensifying trend. (2) There was a favorable connection between the NDVI and the extreme climate index, and most of the NDVI showed a significant correlation with the extreme temperature index, which shows that the dominant factor causing changes in the NDVI is extreme temperature. (3) The Arctic Oscillation index has a significant effect on extreme low temperatures. The Pacific Decadal Oscillation (PDO) has a large influence on extremely high temperatures. The CWD index in the extreme precipitation index had significant negative and positive correlations with the Southern Oscillation index and the PDO index, respectively. The results of the study contribute to further understanding and forecasting of extreme weather events in the Liaohe River Basin of Jilin Province and provide insights for appropriate measures to reduce the social and environmental impacts associated with extreme weather events in the study area. [ABSTRACT FROM AUTHOR]

Under the global warming, it is particularly important to explore the response of extreme climate to global climate change over the arid regions. Based on daily temperature (maximum, minimum, and average) and precipitation data from meteorological stations in Xinjiang, China, we analyzed the spatiotemporal characteristics of extreme temperature and extreme precipitation events via combining thin plate smoothing spline function interpolation, Sen's slope, and Mann–Kendall test. Our results showed that during 1960–2019, the extreme low temperature index of frost days (FD), icing days (ID), cold days (TX10p), cold nights (TN10p), and cold speel duration index (CSDI) all showed the downward trend to varying degrees, and the extreme high temperature index of summer days (SD25), warm days (TX90p), warm night (TN90p), and warm speel duration index (WSDI) all showed an upward trend to varying degrees, and the extreme low temperature index of high altitude mountains decreases more than that of the basin and plains. In addition, all the extreme temperature indices are closely related to the annual average temperature in Xinjiang (R > 0.6). Among the extreme precipitation indices, except for the consecutive dry days (CDD), the other extreme precipitation indices showed increasing trends to different degrees, but the changes in extreme precipitation in Xinjiang were mainly manifested by the increase of heavy precipitation in a short period (the increase of heavy precipitation and extreme heavy precipitation was the largest, 44.8 mm/10a and 17.6 mm/10a, respectively) and spatially concentrated in the Ili River and Altai Mountains in northern Xinjiang. Meanwhile, annual precipitation was positively correlated with the extreme precipitation index (R > 0.4), except for the CDD. This study provides theoretical support for the prevention and control of natural disasters in the dry zone. [ABSTRACT FROM AUTHOR]

Projections of future streamflow extremes are subjected to various sources of uncertainties. Uncertainties arising from different stages in the modelling process of extremes contribute to the overall uncertainty in the final estimates. In this study, some important sources of uncertainties that occur in the modelling chain for projection of future extremes are analysed. The contribution of climate models, hydrological models, representative concentration pathways (RCPs) and the parameters of the extreme value distribution to the overall uncertainty in the streamflow return levels of the Chaliyar river basin in Kerala, India, was quantified using analysis of variance. 5, 10, 25, and 50-year return levels for the near (2021–2050) and far (2070–2099) future periods were computed. Results of the study indicate that the median values of return levels for the near (0.6–13.5%) and far (21.5–37.3%) future periods are higher than the corresponding values for the observed data. Also the uncertainty ranges of the return levels in the near (2–2.4 times) and far (3–3.7 times) future for different return periods are higher compared to that of the observed. The contribution to uncertainties in the return levels from climate models, parameters of the extreme value distribution employed and hydrological models is higher than that from the RCPs. The contribution of parameter uncertainty increases with the return period and that of the climate models reduces with the return period for the two future periods considered in this study, indicating that parameter uncertainty is an important source of uncertainty and has to be considered while predicting the future extremes. The contribution to uncertainty by the hydrological models and by the RCPs does not exhibit much variation for different return periods in both the future time periods considered. Understanding the uncertainties in future extremes would help to devise proper adaptation strategies to mitigate the probable impacts of climate change. [ABSTRACT FROM AUTHOR]

A warming climate cause changes in regional climate and climate extremes. However, understanding how future warming can affect the arid climate and drought in Asia is still unclear. Global warming (GW) impacts on shifts in arid regions and change patterns of drought in the Asia region are investigated using the shared socioeconomic pathway 5–8.5 of the Coupled Model Intercomparison Project Phase 6. The variations in the arid region are explored under potential GW targets above preindustrial levels (+ 0.66 °C for the reference period and + 1.5 °C, + 2.5 °C, + 3.0 °C for future periods). We examine changes in precipitation and temperature indices related to drought, the drought patterns corresponding to consistent arid zones and arid-wet shifting zones based on GW scenarios. The results indicate that warming climates influence temperature and precipitation, and consequently alter climate distribution toward an expansion of the arid region. Due to shifts in climate zones, arid regions may expand by 2.6% relative to the reference climate in response to 3.0 °C of warming. Changes in precipitation indices contribute to the spatial patterns and magnitude of drought changes. Future drought features induced by meteorological conditions exhibit different behaviors according to arid-wet shifts and drought events. Especially, drought features throughout Asia are likely to be aggravated in terms of both severity and frequency in response to a greater degree of GW, especially in arid regions and regarding extreme droughts. This study provides valuable information on the relationship between regional climate and drought features in a world affected by GW. [ABSTRACT FROM AUTHOR]

Aims and background: Groundwater-dependent minerotrophic fens are globally threatened biodiversity hotspots. The supply of groundwater keeps their soil thermally stable and mitigates climatic extremes by thermal buffering. This stability has been shown to influence species composition variation at the between-site scale but has not been studied at the within-site scale. Methods: A total of 19 calcareous fens in the Western Carpathians were sampled for bryophytes, vascular plants, and terrestrial snails with three plots at each site along a watertable gradient, i.e. from the most waterlogged (plot A) through intermediately waterlogged (plot B) to the most terrestrial (plot C) areas. Temperature dataloggers were buried in each plot, and climate variables were derived from the climate database. Results: Water table depth and soil temperature were the most important factors influencing species composition. Significant differences were found between spring source area (A) and fen margin (C) plots for all taxa groups studied. Soil temperature played a significant role at the site level only for bryophytes and vascular plants. However, a large overlap between water table depth and soil temperature for bryophytes also suggests a synergistic effect of these two factors. Conclusion: Soil temperature plays an important role in promoting compositional variation of vegetation on the within-site scale (i.e. a pure effect of soil temperature) in groundwater-dependent mires, as we show here for the first time. This is essential in the light of ongoing climate change. Conservation measures should primarily focus on bryophytes as they are the most temperature-sensitive organisms and important ecosystem engineers. [ABSTRACT FROM AUTHOR]

Drought is an extreme climatic event that mostly occurs as a result of low rainfall, which leads to lack of water in various agro-ecological conditions of Pakistan. The condition could be further exacerbated by the prevailing dry weather. Therefore, accurate, timely, and efficient drought monitoring is crucial to ensure that its adverse effects are mitigated. In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) and TRMM-based data were used together with remote sensing techniques to improve drought mitigation and disaster risk reduction strategies. In order to monitor drought mitigation and disaster risk reduction strategies in Pakistan, the crop water stress index (CWSI), vegetation condition index (VCI), normalized vegetation supply water index (NVSWI), vegetation health index (VHI), and temperature vegetation drought index (TVDI) were chosen as the instrument. Due to low rainfall and significantly low vegetation, CWSI, NDVI, TVDI, and VHI are useful in characterizing drought mitigation strategies in Pakistan. Monthly NDVI, NAP, NVSWI, TVDI, VCI, and VHI values and heat map analysis show that Pakistan suffered from drought in years 2001, 2002, and 2006. Seasonal CWSI, NDVI, VHI, and TVDI confirmed that Pakistan was affected by severe drought in 2001, which continued and led to severe drought in 2002 and 2006. We generate spatial correlation coefficients between NDVI and NVSWI, VCI, and VHI, and NVSWI and VCI and VHI, while the VCI and VHI values are significantly positively correlated. CWSI, NDVI, VHI, and TVDI show positive signs of effective climate change drought mitigation and disaster risk reduction strategies in Pakistan. Thus, these drought indices have been confirmed to be a complete drought monitoring indicator and reduce the risk of drought in Pakistan. [ABSTRACT FROM AUTHOR]

Extreme climate events disrupt the stable, established interactions among the components of the socio-economic and environmental systems. The disruptions affect reaching the targets defined by the United Nations Sustainable Development Goals 1, 2, 6, and 7 that aim at ending poverty and hunger and ensuring access to clean water, sanitation, and affordable energy. We have semantically modeled the interactions of climate change events with the components of the food, water, and energy systems in the 'Sustainable Development and Climate' (SDC) ontology. The domain ontology formalizes the impacts of the events on the implementations of the actions, plans, strategies, and policies that are described by the targets of the selected goals. To ensure interoperability with other ontologies, our ontology extends classes and properties of the top-level Basic Formal Ontology, mid-level Common Core Ontologies, and other upper-level ontologies. The publicly-available SDC ontology facilitates automated discovery, management, integration, and reasoning of the indicator data of the selected goals by reusing the extensive resources of the Common Core Ontologies for data and information modeling. The SDC knowledge model allows government agencies to identify the consequences of their planned actions on people, resources, and the environment in their country, and assess the impacts of the current climate change on the successful implementation of the requirements for goals 1, 2, 6, and 7. [ABSTRACT FROM AUTHOR]

Fir species have been threatened by extreme weather and climate conditions in many parts of the Mediterranean Basin. However, there are almost no studies focused on the mortality of Taurus fir in the Eastern Mediterranean basin and Turkey. This study aims to quantify the mortality pattern of Taurus fir stands in Hadim Forest Enterprise from 1971 to 2016 and to assess this pattern considering the long-term trends and fluctuations in the observed climate data. To this end, spatiotemporal changes in forest cover were analyzed using historical stand type maps in GIS. Statistical and graphical time-series analyses were performed on observed climate data. As a result, rapid areal losses were detected in pure fir stands, even though the annual rate of forestation is 0.5% for the entire forest. More than half of the stands transformed into pure or mixed stands dominated by black pine. Both fir stands and the entire forest became much more fragmented and drought-induced deadwood remarkably increased in almost all fir stands. Regarding the climatic analyses, statistically significant increased trends (p < 0.01) were detected particularly in annual, summer, and autumn mean and average maximum and minimum air temperatures of the Hadim station; strong decreased trends were observed in all relative humidity series; and rapid warming in the surrounding region along Hadim was observed. In addition, series of the Aridity Index and the Standardized Precipitation-Evapotranspiration Index revealed that more arid conditions and significant droughts have dominated the study district since the 1990s. This period has been characterized mostly by long-term agricultural and hydrological droughts. We conclude that selective tree mortality events in the Hadim's forests are likely caused by adverse impacts of observed climate variations and long-term droughts in the sub-region. [ABSTRACT FROM AUTHOR]

The present study intends to assess the climatic controls on the streamflow and its impacts on the changing form of hydrological extremes in the Jhelum basin. The study entails robust statistical analysis of the observed hydroclimatic data (1980–2016) using the standard procedures of trend and abrupt change point detection, flood frequency analysis (FFA), and streamflow drought index (SDI). The coupled impact of rising temperatures (0.024 °C/year) and diminishing precipitation (− 5.71 mm/year) is yielding substantial decreases in the streamflow of the Jhelum basin. The other manifestations of changing climatic regimes are the increasing trends in the spring season (March-May) streamflow and the concurrence of abrupt change points in the streamflow data with climatic variables. The climate change signals are well evident over the hydrological extremes, reflected in an enhanced occurrence of droughts through the latter half of the examined period. Moreover, the flood frequency estimates show that the magnitude of the peak discharges about different return periods has increased significantly during 1986–2016 compared to 1956–1985 estimates. The magnitude of 100-year recurrence interval flood has increased by 10.54–79.58% during 1986–2016. The current study calls for the inclusive restructuring of water management practices to offset the impacts of changing hydrological extremes in the basin. [ABSTRACT FROM AUTHOR]

Europe witnessed a strong increase in climate variability and enhanced climate-induced extreme events, such as hot drought periods, mega heat waves, and persistent flooding and flash floods. Intensified land degradation, land use, and landcover changes further amplified the pressure on the environmental system functionalities and fuelled climate change feedbacks. On the other hand, global satellite observations detected a positive spectral greening trend—most likely as a response to rising atmospheric CO2 concentrations and global warming. But which are the engines behind such shifts in surface reflectance patterns, vegetation response to global climate changes, or anomalies in the environmental control mechanisms? This article compares long-term environmental variables (1948–2021) to recent vegetation index data (Normalized Difference Vegetation Index (NDVI), 2001–2021) and presents regional trends in climate variability and vegetation response across Europe. Results show that positive trends in vegetation response, temperature, rainfall, and soil moisture are accompanied by a strong increase in climate anomalies over large parts of Europe. Vegetation dynamics are strongly coupled to increased temperature and enhanced soil moisture during winter and the early growing season in the northern latitudes. Simultaneously, temperature, precipitation, and soil moisture anomalies are strongly increasing. Such a strong amplification in climate variability across Europe further enhances the vulnerability of vegetation cover during extreme events. [ABSTRACT FROM AUTHOR]

With the continued strengthening of global climate change, various extreme climate events have become increasingly prominent. Typhoons are the most disastrous weather event that cause severe losses to the economy, agriculture, transportation, communication, and ecosystem in coastal regions. The super typhoon Sarika that hit Hainan Island on October 18, 2016, lasted for 15 h, and it was the most severe typhoon that hit this island in October since 1970. The coastal land of Hainan Island experienced gales with an average speed of 35 m/s. In this study, we evaluated the impact of the super typhoon Sarika on vegetation by performing normalized difference vegetative index (NDVI) difference analysis using MODIS multi-temporal images acquired before and after the typhoon. The assessment of typhoons depends on the land-use types and landscape topography of slope, aspect, and altitude. The results indicated that the super typhoon Sarika seriously hit forestry, agriculture, shrubs, plantations, and orchards on Hainan Island. Overall, 79% of vegetation exhibited a negative change, whereas only 21% of vegetation exhibited a positive change in NDVI after the super typhoon Sarika. Agriculture was most severely impacted by the typhoon, where more than 81% of areas exhibited a decrease in NDVI, followed by plantations and orchards, where 77% of areas exhibited a decrease in NDVI. Additionally, the impact of the typhoon on vegetation was affected by the degree of NDVI decrease with the altitude, slope, and aspect. In conclusion, vegetation damage is associated with land cover types, altitude, aspect, and slope. NDVI decreased more in low-altitude plain and coastal areas than in higher altitude montane forest areas. [ABSTRACT FROM AUTHOR]

Emergency shelters are often designed to be of temporary nature but end up adopting a more permanent nature in becoming informal settlements. On one hand, these settlements suffer from the conflicts and environmental pressures. On the other hand, they also bear the inadequacies of services and facilities. This adds to the vulnerability of the refugee population to climatic extremes and environmental extremes along with a low quality of life. The present study aims to identify the pressures both environmental and socio-economic on a refugee camp in the Dalhamyie settlement in Bekaa, Lebanon and design a resilient model which address both internal and external risks. We propose a master plan as a suggested guideline representing a preliminary design umbrella plan that may be updated and altered depending on the population of the community, the site's limitations, and the general availability of resources. To help the local refugees become more resilient and self-sufficient in times of crisis, recommendations are here presented are not strict structural plans but rather a strategic, data-driven collection of actions. With the increasing mental stress that refugees experience, the idea of resilience at all levels is needed to lessen and reinforce the constant environmental, physical, and economic threat that they are subjected to. Residential zoning has been detailed out with respect to the form, structure and assembling of components along with cluster planning within the settlement. Recommendations are not a rigid structural plan but a strategic, data driven set of actions that can be implemented by the local refugee community in order to achieve greater resilience and self-sustainability during crisis situations. Such model is applicable with modifications for other emergency settlements also with varying risk factors. The proposed model addresses the challenges and the multiple risks that the people are exposed to present a framework that can lead to better quality of life in temporary settlements. With more climate refugees, conflict driven refugees and internal refugees, absence of such models was a gap and the authors have tried to build the same through one case study. [ABSTRACT FROM AUTHOR]

Global warming has altered the thermodynamic and dynamic environments of climate systems, affecting the biogeochemical processes between the geosphere and atmosphere, which has significant impacts on precipitation extremes and the terrestrial carbon budget of ecosystems. Existing studies have reported a hook structure for precipitation extreme-temperature relationships but have rarely examined the underlying physical mechanisms. Previous studies have also failed to quantify the impact of precipitation on ecosystem productivity, hindering the assessment of future extreme climatic hazards and potential ecosystem risks. To reveal the thermodynamic driving mechanisms for the formation of global precipitation extremes and ecohydrological effects, this study utilizes over ten multisource datasets (i.e., satellite, reanalysis, climate model, land surface model, machine learning reconstruction, and flux tower measurements). We first assess the response of water-heat-carbon flux to precipitation extremes and explain the underlying physical mechanisms behind the hook structures in terms of atmospheric thermodynamics and dynamics. Based on outputs from five global climate models (GCMs) under ISIMIP3b, we project future changes in the hook structures as well as their impacts on precipitation extremes. Finally, we discuss the impact of precipitation on the terrestrial carbon budget by using outputs from the CLM4.5 model. The results show that precipitation extremes are usually accompanied by strong exchanges of water and heat and demonstrate a nonlinear relationship between precipitation and ecosystem productivity. The intensity (duration) of extreme precipitation is intensifying (decreasing) over most areas of the globe, whereas three-dimensional precipitation events are becoming more concentrated. Atmospheric dynamics play a key role in shaping the hook structure. The structure is not stable; it shifts under climate change and is projected to result in a 10–10% intensification in precipitation by the end of this century. Moderate levels of precipitation contribute to carbon assimilation in ecosystems, and the response of the carbon budget to precipitation is relatively stable under climate change. [ABSTRACT FROM AUTHOR]

The overlap region between the eastern fringe of the Asian westerly region and the temperate continental-monsoon climate transition zone is sensitive to climate changes and is characterized by fragile ecosystems. Uncovering the long-term historical climate variability patterns in this region is necessary. A standardized tree-ring width chronology was constructed based on the tree-ring samples collected from four representative tree species in four typical areas in the overlap region, and the 203- to 343-year annual mean minimum temperature series in the overlap region were reconstructed. The reconstructed series overlapped well with extreme climate events and low-temperature periods recorded in historical data. Therefore, the reconstructed model is stable and reliable. As suggested by the reconstructed series, the annual average minimum temperature in the overlap region changes sharply from east to west, and the periodicity change in the overlap region shows a trend of gradually weakening from the east and west ends to the middle. In the nineteenth century, the high-latitude area was in the high-temperature period, and the entire overlap region experienced significant low-temperature periods lasting 20–45 years until the 1950s. The western part had an earlier low-temperature period start time, a longer cooling duration, and a slower cooling rate than the central part. The overlap region experienced a significant warming period in approximately the last half-century, with temperatures increasing faster in the western and eastern parts than in the central part. The temperature variability in the overlap region was more intense in the last two centuries, with shorter periodicities and a larger proportion of cold periods. The central and western parts of the Asian westerly region, the mid- to high-latitude regions of the transition zone, and the overlap region experienced significant low-temperature periods or drastic cooling trends (the Little Ice Age) in the first half of the nineteenth century and significant warming trends afterwards due to global warming. The influences of these changes may have been exacerbated by the westerly circulation. The results of this study provide new insights into the use of dendroclimatology to extract temperature series in the Asian westerly region and the transition zone and a reference for research on global climate change. [ABSTRACT FROM AUTHOR]

The study area of Cala Gonone in NE Sardinia (Italy) consists of a wide terraced re-entrance/valley crowned inland by carbonate hills and, near the coast bounded laterally and partly floored by thin basaltic lava lying over carbonate bedrock. In this re-entrance, several inland alluvial fans (500 m length by 700 m wide) have developed, and a local ~ 30 m high, about 10 m wide (thick), 400 m long scarp body-remnant of semi-consolidated alluvial fan deposits is exposed along the coast. The fans experience depositional events mostly developed during the late Pleistocene. They although nowadays dormant may be reactivated by major rainstorms during strong climate changes. In these last few decades, the touristic village of Cala Gonone has been rapidly expanding over the mid to lower parts of two coalescing alluvial fans (Stadium and Gustui) and along the coastal marine scarp edge (Palmasera alluvial fan system). The village thus may become exposed to natural hazards if extreme climatic conditions may re-occur. Moreover, rock falls and the instability of the costal scarp due to wave erosion may add addition hazards for habitations built near the scarp crest and visitors to the frontal replenished beach. As commonly occurring elsewhere since antiquity, the risk perception of such events is low because of the centennial, millennial of longer recurrence. Such perception does not negate the hazards but a long event recurrence may be accepted as a reasonable risk for the human's activity. Nevertheless, serious consideration should be given to potential problems and plan and build for amelioration and defense. The evidence of what environmentally did and could still happen in the Cala Gonone and similar other area is in part clearly imprinted on the landscape: geology, geomorphology, and relative details in the stratigraphy and sedimentology of the deposits. [ABSTRACT FROM AUTHOR]