Search Results (328)

European beech is a species of both ecological and economic relevance in Europe. However, its high sensitivity to drought poses a significant risk amid increasing climate extremes. This study aimed to evaluate the physiological and spectral responses of beech to drought stress, combining in situ leaf-level measurements with hyperspectral remote sensing data. We set up the experiment in an Alpine European beech forest in northern Italy, which included three water treatments: control, water stress, and irrigation. Physiological data (i.e., leaf gas exchange and chlorophyll content), alongside airborne hyperspectral remote sensing data, were collected from 20 to 29 July 2022 during a compound drought and heatwave (CDHW) event. Water-stressed trees exhibited significantly reduced photosynthetic rates, lower photosystem II efficiency, and higher non-photochemical quenching, indicating impaired photosynthetic performance. Water-stressed beech exhibited up to 70% reduced photosynthesis and 35% lower leaf chlorophyll content under severe drought conditions. Hyperspectral vegetation indices, particularly the RENDVI, CIRE, and SPRI, successfully detected stress status. This exploratory study, based on an intensive analysis of four trees, demonstrates the feasibility of integrating physiological measurements with hyperspectral remote sensing to detect drought-stress signatures in European beech at the individual-tree level, establishing a methodological framework for more extensive future research. Full article

We integrate the dynamic event synchronization (DES) method to analyze temporal synchronization between regions with the frequent pattern growth (FP-Growth) pattern to extract significant spatial associations. The European Centre for Medium-Range Weather Forecasts ECMWF Reanalysis version 5 reanalysis data were partitioned into two 30-year intervals (1965–1994 and 1995–2024). First, inter-regional heatwave synchrony was measured using DES, and prevalent spatial associations were derived through the FP-Growth pattern. Comparative results show that the later interval yields twice as many association rules, a 34% decline in short-range linkages, and an 8% increase in long-range teleconnections—evidence of a transition from localized clustering toward transcontinental-scale heatwave synchronization. Full article

Power distribution systems face increasing threats from high-impact, low-probability (HILP) events caused by extreme weather conditions such as floods, typhoons, droughts, and heatwaves. These events often lead to power outages worldwide, highlighting the need for effective strategies to mitigate their impact. This work proposes an emergency response strategy that integrates network reconfiguration (NR) with the deployment of mobile emergency generators (MEGs) to enhance system resilience. The objective is to maximize power supply availability following HILP events. To achieve this, mixed-integer quadratic constraint programming (MIQCP) is used to optimize MEG deployment and network restoration. Additionally, improved quantitative resilience metrics are introduced to assess system degradation, pre-recovery, and recovery phases, enabling continuous resilience measurement and informed decision-making. Furthermore, an optimal capacity deployment strategy (OCDS) is proposed to ensure that MEGs are deployed with suitable capacities based on the specific needs of outage-affected areas. The effectiveness of the proposed strategy is demonstrated through tests on the IEEE 118 bus system. The results show a significant improvement of up to 100% in system resilience, reducing power outages and accelerating restoration. The findings confirm that integrating NR with optimized MEG deployment enhances service restoration, providing an effective approach for utilities to manage power disruptions. Full article

Accurate forecasting of heatwaves is critical for ensuring the safe operation of electricity grids. Focusing on the complex terrain of Sichuan, China, this study investigates the optimization of spectral nudging parameters within the Weather Research and Forecasting (WRF) model to improve predictions of heatwave events. To overcome the subjectivity inherent in the traditional selection of the spectral nudging cutoff wavenumber, we propose an objective method based on power-spectrum energy diagnostics of the background field. This method determines an optimal domain-specific cutoff wavenumber. A series of sensitivity experiments were designed for a significant heatwave event that affected the Sichuan electricity grid in August 2019. These experiments evaluated the impact of different spectral nudging configurations, which considered varying domain sizes and forecast lead times, on correcting large-scale circulation drift and enhancing near-surface air temperature forecasts. The results demonstrate the following: (1) For a smaller domain or a longer forecast lead time, spectral nudging effectively compensates for circulation drift induced by weakening lateral boundary constraints, significantly improving the forecast of heatwave intensity and spatial extent, representing a compensatory effect. (2) For a larger domain that already adequately resolves large-scale circulation evolution, spectral nudging can over-constrain the model’s internal dynamical processes, thereby degrading forecast performance, an outcome termed the over-constraint effect. (3) The proposed energy-threshold method provides an objective, physics-based strategy for identifying dominant large-scale waves and optimizing the spectral nudging cutoff wavenumber. This work offers practical insights for the operational application of spectral nudging over complex terrain to advance extreme temperature forecasting. Full article

Global climate change is intensifying extreme weather events such as floods and heatwaves, posing serious threats to lake ecosystems. The Huayanghe Lakes experienced a catastrophic flood in 2020 and a prolonged heatwave in 2022, providing an opportunity to compare zooplankton responses to contrasting extreme climate events. Based on summer water quality and zooplankton data collected from the Huayanghe Lakes during 2020–2023, this study used 2021 and 2023 as reference years to examine the summer zooplankton community state during the post-event period following extreme climate events. In 2020, 43 species belonging to 14 families and 25 genera were recorded, dominated by rotifers such as Polyarthra euryptera and Trichocerca spp., with a mean density of 239.26 ind./L. In contrast, 34 species from 12 families and 21 genera were identified in 2022, with dominant taxa including Diurella rousseoeti, Trichocerca cylindrica and Thermocyclops hyalinus, resulting in a lower mean density of 149.17 ind./L. Zooplankton density and species richness were higher during flood conditions but declined under prolonged heatwave conditions. Mantel correlation analysis identified water transparency as the primary environmental factor shaping zooplankton communities. Overall, zooplankton responded more strongly to flooding than to sustained heatwaves, indicating that different extreme climate events amplify the regulatory roles of distinct environmental drivers. Full article

Climate change-induced extreme weather events increasingly threaten public health, with a particularly acute impact on the mental well-being of urban populations. This study evaluates regional disparities in mental health outcomes associated with climate-induced extreme weather in urban environments, where social and infrastructural vulnerabilities exacerbate environmental stressors. We synthesized data from cohort and cross-sectional studies using both traditional frequentist and Bayesian meta-analytic frameworks to assess the mental health sequelae of extreme weather events (e.g., heatwaves, floods, droughts, and storms). The traditional meta-analysis indicated a significant increase in the odds of adverse mental health outcomes (OR = 1.32, 95% CI: 1.07–1.57). However, this global estimate was characterized by extreme heterogeneity (I² = 95.8%), indicating that the risk is not uniform but highly context-dependent. Subgroup analyses revealed that this risk is concentrated in specific regions; the strongest associations were observed in Africa (OR = 2.23) and Europe (OR = 2.26). Conversely, the Bayesian analysis yielded a conservative estimate, suggesting a slight reduction in odds (mean OR = 0.92, 95% CrI: 0.87–0.98). This divergence is driven by the Bayesian model’s shrinkage of high-magnitude outliers toward the high-precision data observed in resilient, high-income settings (e.g., USA). Given the extreme heterogeneity observed (I² = 95.8%), we caution against interpreting either pooled estimate as a universal effect size. Instead, the regional subgroup findings—particularly the consistently elevated risks in Africa and Europe—offer more stable and policy-relevant conclusions. These findings emphasize urgent, context-specific interventions in urban areas facing compounded climate social risks. Full article

Rural self-constructed homes in China’s cold-temperate regions often exhibit poor energy performance due to limited budgets and substandard construction, leading to a high reliance on active systems and low climate resilience. This study assesses four passive cooling strategies, nighttime natural ventilation (NNV), envelope retrofitting (ER), window shading (WS), and window-to-wall ratio adjustment (WWR), under 2040–2080 representative future climate conditions using energy simulation, multi-objective optimization, sensitivity analysis, and life-cycle cost assessment. Combined measures (COM) cut annual cooling demand by ~43% and representative peak cooling loads by ~50%. NNV alone delivers ~37% cooling reduction with rapid payback, while ER primarily mitigates heating demand. WS provides moderate cooling but slightly increases winter energy use, and WWR has minimal impact. Economic and sensitivity analyses indicate that COM and NNV are robust and cost-effective, making them the most suitable strategies for low-energy, climate-resilient retrofits in cold-climate rural residences. Since statistically extreme heat events are not explicitly modeled, the findings reflect relative performance under representative climatic conditions rather than guaranteed resilience under extreme heatwaves. Full article

The IPCC has emphasised the increasing impacts of climate change across multiple sectors, including cultural heritage. In response, UNESCO launched the Policy Document on Climate Action for World Heritage in 2023, offering guidance on mitigation strategies for historic sites. Cultural heritage faces risks not only from sudden catastrophic events—such as floods, droughts, and wildfires—but also from the gradual deterioration of buildings and artefacts due to shifting environmental conditions. Climate change further affects the indoor microclimate of heritage sites, including museums, archives, and libraries, which are critical to the long-term preservation of cultural assets. Heritage, including heritage buildings and both tangible and intangible heritages, are subject to changes; therefore, their conservation should be assessed to identify sustainable approaches. This study investigates how climate change and microclimate alterations impact the conservation of historic buildings without modern climate control, using the Malatestiana Library—a UNESCO Memory of the World site—as a case study. The library has preserved a remarkably stable indoor environment for centuries, without the introduction of heating, cooling, or major restorations. A monitoring campaign during the summer of 2024 assessed the effects of extreme heat events on the library’s microclimate, comparing two internal spaces to examine the attic’s role in mitigating thermal stress. Data from the 2024 heatwave are also compared with similar data collected in 2013. Results show a marked shift toward a more tropical indoor climate over the past decade, signalling new threats to the preservation of historic materials. These findings highlight the urgent need for adaptive conservation strategies to address the evolving challenges posed by climate change. Full article

Heatwaves pose increasing risks to human health and socio-economic systems, yet their spatiotemporal organization and underlying synergistic mechanisms remain insufficiently understood, particularly with respect to daytime and nighttime processes. Using a dual identification framework combining absolute and relative temperature thresholds, this study systematically investigates the spatiotemporal evolution of daytime and nighttime heatwaves across China during 1961–2022. A complex network approach is further introduced to characterize the interannual co-variability and interdecadal structural evolution of heatwave activity from a system-level perspective. Results reveal a pronounced interdecadal transition in the early 1990s, accompanied by a fundamental reorganization of heatwave co-occurrence networks. Heatwave frequency exhibits a clear post-transition desynchronization, characterized by a sharp decline in network connectivity and fragmented local clustering, indicating a shift from large-scale, circulation-dominated coherence toward increasingly localized and heterogeneous heatwave occurrences. In contrast, heatwave duration shows an opposite evolution, with significantly enhanced spatial synchronization after the transition. Degree centrality and clustering coefficients increase markedly, and high-connectivity cores expand from coastal regions into inland areas, including North, Central, and Northwest China. This coexistence of desynchronized heatwave occurrence and strongly synchronized persistence suggests an emerging high-risk regime in which heatwaves occur more randomly but, once initiated, tend to persist coherently across large regions. Furthermore, a dual-layer network analysis reveals previously undocumented cross-temporal coupling between daytime and nighttime heatwaves, with pronounced regional differences. The middle and lower reaches of the Yangtze River are more strongly influenced by local processes, whereas northern China is increasingly governed by large-scale circulation control and enhanced regional clustering after the transition. These findings demonstrate that complex network analysis provides a powerful framework for uncovering hidden structural changes in extreme heat events and offer new insights into the evolving risks of compound and persistent heatwaves under climate change. Full article

Extreme weather events, particularly marine heatwaves (MHWs), increasingly threaten aquaculture systems worldwide by impairing animal physiology and economical sustainability. This showcases the need to develop nutritional approaches that enhance animal performance under sub-optimal conditions. This study evaluated the effects of dietary supplementation with the brown macroalga Laminaria digitata (whole dried powder or extract) on the antioxidant status, digestive activity, and lipid metabolism of juvenile Sparus aurata exposed to a simulated MHW. Fish were fed four diets (control, 0.3% extract, and 0.3% or 1.5% powder) for 30 days before being exposed to a category III Mediterranean MHW. Under optimal temperature, macroalgae supplementation reduced oxidative status (lower catalase activity). The powder-feeds decreased lipid peroxidation, while the extract-feed elicited the opposite. All supplemented diets reduced proteolytic activity, and the extract-feed also decreased amylase activity. The MHW impaired gastrointestinal antioxidant defenses and liver lipid metabolism, decreasing catalase and glutathione S-transferase activities, as well as ΣPUFA n-6, 16:1 n-7, and 18:2 n-6 levels. The 0.3% powder-feed mitigated MHW-induced reductions in antioxidant activity, while both 0.3%-diets prevented thermal stress-related alterations on fatty acid profile. Overall, L. digitata powder at 0.3% was most effective at enhancing thermal stress resilience, supporting its value as a functional aquafeed ingredient. Full article

Compound drought and heatwave (CDHW) events pose a rising threat to global water security and ecosystem stability. While their increased frequency under global warming is recognized, their spatiotemporal evolution and subsequent cascading impacts on hydrological processes in monsoonal lake basins remain poorly quantified. This study investigates the characteristics and hydrological impacts of CDHW in the Poyang Lake Basin, China’s largest freshwater lake, from 1981 to 2016. Using a daily rolling-window approach with the Standardized Precipitation Index (SPI) and Standardized Temperature Index (STI), we identified CDHW events and characterized them with metrics of frequency, severity, and intensity. Event coincidence analysis (ECA) was employed to quantify the trigger relationship between CDHW and subsequent hydrological droughts (streamflow and lake water level). Our results reveal a paradigmatic shift in the CDHW regime post-2000, marked by statistically significant increases in all three metrics and a fundamental alteration in their statistical distributions. ECA demonstrated that intensified CDHW events significantly enhance hydrological drought risk, primarily through a robust and increasing lagged influence at seasonal timescales (peaking at 40–90 days). Decomposition of compound events attributes this protracted impact predominantly to the heatwave component, which imposes prolonged hydrological stress, in contrast to the more immediate but rapidly decaying influence of drought alone. This study highlights the necessity of integrating compound extremes and their non-stationary, lagged impacts into water resource management and climate adaptation strategies for monsoonal basins. Full article

This study analyzes the relationship between fires and climate extremes in the Caatinga biome from 2012 to 2023 by integrating Fire Radiative Power (FRP) from VIIRS (S-NPP and NOAA-20), Vapor Pressure Deficit (VPD) and air temperature from ERA5, drought indices (SPI-1 and SPI-6), and heatwave events from the Xavier database. Daily percentiles of maximum (CTX90pct) and minimum (CTN90pct) temperatures were used to characterize heatwaves. Spatial and temporal dynamics of fire patterns were identified using the HDBSCAN algorithm, an unsupervised Machine Learning clustering method applied in three-dimensional space (latitude, longitude, and time). A marked seasonality was observed, with fire activity peaking from August to November, especially in October, when FRP reached ~1000 MW/h. The years 2015, 2019, 2021, and 2023 exhibited the highest fire intensities. A statistically significant upward trend in cluster frequency was detected (+1094.96 events/year; p < 0.001). Cross-correlations revealed that precipitation deficits (SPI) preceded FRP peaks by about four months, while VPD and air temperature exerted immediate positive effects. FRP correlated positively with heatwave frequency (r = 0.62) and negatively with SPI (r = −0.69). These findings highlight the high vulnerability of the Caatinga to compound drought and heat events, indicating that fire management strategies should account for both antecedent drought conditions, monitored through SPI, and real-time atmospheric dryness, measured by VPD, to effectively mitigate fire risks. Full article

The water sustainability in Chihuahua City is challenged by rapid urbanization, population growth, industrial expansion, and climate variability. This study examines how these factors impact water demand by analyzing six decades of local precipitation, extreme temperature, demographic, and water consumption data. Statistical methods (time series and gamma distribution with R-package) and spatial analysis using Landsat and Spot satellite imagery were employed. Chihuahua’s urban area grew at an average annual rate of 7.4% from 1992 to 2020. Minimum and maximum temperatures have increased by 0.07 °C and 0.05 °C per year, respectively, leading to more frequent heatwaves over the past 30 years. Since the 1990s, there has been a noticeable trend towards more frequent extreme precipitation events coinciding with a sustained rise in extreme temperatures. Urban expansion and rising temperatures have increased water consumption by approximately 40% per °C over the past 30 years, accelerating the depletion of groundwater reserves in the city’s three main aquifers. These trends highlight the urgent need for integrated urban planning and climate-adaptation measures to reduce vulnerability and ensure long-term water security for Chihuahua. Full article

The Japanese chub mackerel (Scomber japonicus) is a small pelagic economically important fish species in the northwest Pacific Ocean, and its abundance and distribution are influenced by water temperature changes. In recent years, frequent marine heatwaves (MHWs), defined as prolonged anomalously warm sea surface temperature events, in this region have significantly impacted marine ecosystems and fishery resources. The effects of MHWs on Japanese chub mackerel remain poorly understood. This study analyzed the relationship between Japanese chub mackerel abundance and MHW characteristics in the northwest Pacific Ocean from 2014 to 2021. It includes comparative analyses on the spatiotemporal patterns of catch per unit effort (CPUE) and MHWs, an exploration of CPUE distribution under varying MHW intensities and durations, and an assessment of the relationship between MHW characteristics and CPUE using a Generalized Additive Model (GAM) approach. Additionally, CPUE variations before, during, and after MHWs in 2016, 2018, and 2021 across different regions are measured. Results reveal significant interannual variability in MHWs, with increasing trends in the frequency, intensity, and duration of MHWs. As the frequency, intensity, and duration of MHWs increased, the abundance of Japanese chub mackerel decreased, particularly in years with higher intensity and longer lasting MHWs. The study concludes that MHWs negatively impact Japanese chub mackerel, highlighting the urgent need for climate-adaptive fishing and management strategies. Full article

The West African Sahel suffered an unprecedented hot season during spring 2024 especially marked by noticeable heatwave episodes in the urban context of Burkina Faso’s capital, Ouagadougou, where significant impacts were reported. These heat events are analyzed to link hazards with impacts and improve early warning systems in the under-recognized Sahel context. Using observational data from the Burkina Faso National Meteorological Agency and the European reanalysis, ERA5, anomalies of both daily maximum (Tmax) and minimum (Tmin) temperatures were analyzed. The results show that, during the first half of 2024, monthly Tmax and Tmin anomalies were highly positive compared to the reference period 1991–2020. A total of four daytime and one nighttime heatwave events were detected. The longest daytime heatwave lasted six days with observed Tmax reaching 44.5 °C. The unique nighttime heatwave was at least twice as long as the longest daytime heatwave, persisting 13 days between late April and early May. In addition, the heat was not evenly distributed spatially as some districts were significantly hotter than the rest of the city, suggesting possible urban/local effects. These results underscore the occurrence of exceptional heat in 2024 and the need for efforts towards heatwave risk mapping and management in African cities. Full article