Extreme Climate Research Articles (Page 1)

Impacts of extreme climate change on terrestrial ecosystem carbon storage in China.

This study investigates the viability and potential of the Earth-Air Heat Exchanger (EAHE) low-enthalpy geothermal system for greenhouse climate control in arid regions, specifically addressing the prevalent challenge of limited meteorological data. Our approach integrates ERA5-Land data with a subsurface soil temperature model, enabling accurate EAHE design and performance prediction in data-scarce environments like Bahariya Oasis, Egypt. The research confirmed the significant thermal stability of the subsurface soil, establishing its potential as a consistent heat source/sink. Initial simulations highlighted effective winter heating but revealed a need for enhanced summer cooling. We demonstrated that optimizing the EAHE system by increasing airflow successfully maintained greenhouse temperatures within near-optimal ranges (below 35[Formula: see text]C in summer, above 20[Formula: see text]C in winter) throughout the year. This achievement validates EAHE's effectiveness for dual heating and cooling in extreme climates. This work provides a robust, data-driven methodology for designing and implementing sustainable, climate-controlled greenhouses in challenging arid zones.

Abstract Using German crop farm data from the EU Farm Accountancy Data Network for 2004–2020, we investigate how weather and climate extremes interact with farm-level inefficiency, accounting for policy. We use a four-component stochastic production frontier model to disentangle farm heterogeneity from persistent and transient inefficiency, and explicitly address economic and econometric endogeneity. We select weather-related determinants of inefficiency using panel random forests. We find that losses associated with one climate extreme day range from 0.15 to 26.31 Euro/hectare. Water-related extremes appear less detrimental than temperature-related extremes. Our results suggest that efficiency can be underestimated if agro-climatic conditions are not acknowledged.

Extreme climate events like droughts and floods are creating urgent challenges for sectors such as Agriculture or water management. Effective adaptation requires stakeholder collaboration, supported by stakeholder analysis (SA) methods, which are still evolving in environmental management. We briefly reviewed examples of recent existing systematic evidence syntheses on SA across different domains. This highlighted several SA challenges, including the lack of transparent, common methods—particularly for climate-induced extreme events—and weak links between SA results and policy or practice. We then present a case study that illustrates these challenges and suggests ways to address them. Cooperating with a local network organisation, the Living Lab Schouwen-Duiveland (LAB), we conducted a case study on the island of Schouwen-Duiveland (NL), which is trying to adapt to drought. Applying a novel stakeholder analysis method, the “Rings of involvement”, which enables the visualisation of stakeholders’ levels of affectedness regarding the issue, we were able to identify and categorise the stakeholder network in a systematic manner. We identified stakeholder groups, such as “Implementers”, who are not yet in the network but likely hold key practical knowledge to address local-regional climate adaptation. This calls for a better institutionalisation of and a more dynamic approach to SA in the local climate change adaptation practices. Based on our case study, we suggest that future studies could explore under which conditions a network organisation (such as the LAB) acts as a dynamic platform for facilitating stakeholder knowledge co-production.

Drought is a major stressor affecting tree physiology and is expected to intensify under climate extremes. Stems, partly due to their photosynthetic capacity, tend to be more drought-resilient than leaves. This study aimed to assess stem photosynthetic and its impact on carbon balance in leafless stems under drought conditions. Severe drought caused a marked decline in stem and root water potential (Ψ) and reduced stem water vapor conductance (gtw) by about 40%. Despite this, stems retained the capacity for active gas exchange: though with reduced stem CO2 efflux (ECO2) and enhanced CO2 refixation, which increased from about 40% under control conditions to ~55%–60% after drought, accompanied by a twofold increase in intrinsic water use efficiency (iWUE). Chlorophyll a fluorescence and pigment analyses indicated that the integrity of photosystem II (PSII) was preserved under drought, supporting sustained corticular photosynthesis. Concentrations of chloride, malate, and citrate in the xylem sap did not change significantly under drought, indicating a high capacity of stems to maintain homeostasis. Stable isotope analyses revealed drought-induced shifts in δ13C, consistent with altered carbon allocation following leaf abscission. These results confirm that stem photosynthesis and CO2 reassimilation contribute significantly to stem metabolic resilience, mitigating drought-induced carbon losses and helping to preserve plant survival.

The current global warming, which has been going on since the mid-70s of the last century, has been confirmed by numerous factual observations. A decrease in edaphic moisture should inevitably cause the replacement of forest-steppe vegetation by northern steppe vegetation, and the latter by dry steppe vegetation. At the same time, dark-gray forest soils and ordinary chernozems still remain in the position of northern relics during this short period. However, due to the increased humification of organic matter, the predominant type of humus changes from humate-fulvate to fulvate-humate. The successional trend in boreal phytocoenoses includes the replacement of oak and/or pine by spruce, with a decrease in forest density, as well as the nemoralization of the ground cover. On the Main Landscape Boundary of the Russian Plain, a three-dimensional local phytocoenotic ecotone is developing to a certain extent, with the strengthening of the boreal vegetation type in the tree layer and sub-boreal types in the undergrowth and ground cover. The increase in the range of inter-annual fluctuations in temperatures and precipitation over the last century indicates a clear increase in climate extremes. The frequency of extreme weather increases -- abnormally cold and abnormally warm, as well as excessively humid and extremely dry. All this contributes to the development of steppe ecosystems and has an extremely unfavorable effect on the state of oak groves, causing waves of their mass drying out even at the northern borders of their habitats. In general, on the territory of the Eastern European sub-continent, the “savannization” of mesophilic broad-leaved forests should begin, with their merging with a mosaic complex of sparse forests, meadows and steppes of the typical forest-steppe.

Geographic patterns of diversity in any group of plants are the result of the interplay of environmental conditions and the evolutionary dynamics of the respective plant group. Here, the geographic distribution of current mean diversification rates (MDR) is explored at the genus level for ferns and relate it to climatic conditions and regional species richness. It is found that MDR is highest at tropical latitudes and in humid and hot environments, and is influenced primarily by current climate (rather than historical climate change), by precipitation-related variables (rather than temperature-related ones), and roughly equally by climate extremes and seasonality. Furthermore, a positive relationship between MDR and fern species density is found, with the latter being more strongly directly influenced by MDR than by climate, and all of the above-mentioned patterns differ among longitudinal segments. Critically, the relationship between MDR and climate shifts across longitude, revealing region-specific diversification drivers. This study shows that diversification rates provide complementary information on the evolutionary history of ferns compared to species richness and phylogenetic diversity, and that highly diverse regional fern assemblages appear to be centers of ferns belonging to rapidly diversifying lineages.

Spatio-temporal patterns of extreme climate events have been extensively studied, yet two questions remain underexplored: Do such events occur regularly, and how do regularity patterns change under global warming? We address these questions by investigating dominant periods in crop failure, heatwave, and wildfire data. Here, we show that under pre-industrial conditions dominant periods emerge in 28% of cropland exposed to crop failure and 10% of wildfire-affected areas, likely related to climatic oscillations such as the El Niño-Southern Oscillation, while heatwaves occur irregularly. The number of dominant periods increases by 2-13% during the transition from the pre-industrial era to the anthropocene. In the anthropocene, the occurrence of extreme events shifts towards monotonic growth, replacing previous natural regularity patterns. Linearly de-trended projections reveal an additional shift towards smaller dominant periods due to climate change. These shifts in regularity are crucial for adaptation planning, and our method offers an additional approach for studying extreme events.

The operation of modern power networks is increasingly exposed to overlapping climate extremes and volatile system conditions, making it essential to adopt scheduling approaches that are resilient as well as economical. In this study, a two-stage stochastic formulation is advanced, where indicators of system adaptability are embedded directly into the optimization process. The objective integrates standard operating expenses—generation, reserve allocation, imports, responsive demand, and fuel resources—with a Conditional Value-at-Risk component that reflects exposure to rare but damaging contingencies, such as extreme heat, severe cold, drought-related hydro scarcity, solar output suppression from wildfire smoke, and supply chain interruptions. Key adaptability dimensions, including storage cycling depth, activation speed of demand response, and resource ramping behavior, are modeled through nonlinear operational constraints. A stylized test system of 30 interconnected areas with a 46 GW demand peak is employed, with more than 2000 climate-informed scenarios compressed to 240 using distribution-preserving reduction techniques. The results indicate that incorporating risk-sensitive policies reduces expected unserved demand by more than 80% during compound disruptions, while the increase in cost remains within 12–15% of baseline planning. Pronounced spatiotemporal differences emerge: evening reserve margins fall below 6% without adaptability provisions, yet risk-adjusted scheduling sustains 10–12% margins. Transmission utilization curves further show that CVaR-based dispatch prevents extreme flows, though modest renewable curtailment arises in outer zones. Moreover, adaptability provisions promote shallower storage cycles, maintain an emergency reserve of 2–3 GWh, and accelerate the mobilization of demand-side response by over 25 min in high-stress cases. These findings confirm that combining stochastic uncertainty modeling with explicit adaptability metrics yields measurable gains in reliability, providing a structured direction for resilient system design under escalating multi-hazard risks.

ObjectiveTo characterise and quantify the mortality risks for a range of causes after tropical cyclones in nine countries and territories.DesignTwo stage, time series study.SettingNine countries or territories (Australia, Brazil, Canada, South Korea, Mexico, New Zealand, the Philippines, Taiwan, and Thailand), covering tropical, subtropical, and extra-tropical regions.ParticipantsGeneral populations living in regions with tropical cyclones in the nine countries or territories, 2000-19.Main outcomes measuresExcess mortality risk of cardiovascular diseases, respiratory diseases, infectious diseases, injuries, neuropsychiatric disorders, renal diseases, digestive diseases, diabetes, and neoplasms as the leading cause of death. Wind speed and rainfall profiles were quantified with a physics based tropical cyclone field model.Results14.8 million deaths and 217 tropical cyclone events in communities from the nine countries or territories were included in the analysis. Mortality risks from various causes consistently increased after tropical cyclones, with peaks occurring within the first two weeks after the cyclone, followed by a rapid decline. During the first two weeks after a tropical cyclone, the highest increases were seen in mortality from renal diseases and injuries, with a cumulative relative risk of 1.92 (95% confidence interval (CI) 1.63 to 2.26) and 1.21 (1.12 to 1.30), respectively, for each additional tropical cyclone day. Relatively more modest risks were found for mortality from diabetes (cumulative relative risk 1.15, 95% CI 1.08 to 1.21), neuropsychiatric disorders (1.12, 1.05 to 1.19), infectious diseases (1.11, 1.05 to 1.17), digestive diseases (1.06, 1.02 to 1.09), respiratory diseases (1.04, 1.00 to 1.08), cardiovascular diseases (1.02, 1.01 to 1.04), and neoplasms (1.02, 1.00 to 1.04). Mortality risks were substantially higher in communities with greater levels of deprivation and in those with historically fewer tropical cyclones, especially for renal, infectious, and digestive diseases, as well as for diabetes. Rainfall related to tropical cyclones had a more consistent increasing exposure-response relation with mortality risks, particularly for deaths related to respiratory, cardiovascular, and infectious diseases.ConclusionsAfter tropical cyclones, mortality risk increased variably for different causes, populations, and regions. Integrating epidemiological evidence into the development of management systems for climate extremes is urgently needed, particularly in regions with higher levels of deprivation and in those with historically fewer tropical cyclones. These measures are necessary to improve the adaptive capacity in responding to the growing risks and shifting activity of tropical cyclones in a warming climate.

The increasing frequency of global extreme climate events has heightened the need to understand the mechanisms through which desert ecosystems respond to altered precipitation patterns. This includes elucidating how arbuscular mycorrhizal fungi (AMF) drive these responses by regulating key soil processes and shaping microbial community dynamics. We therefore conducted an in situ experiment involving increased precipitation and AMF suppression, and phospholipid fatty acid (PLFA) was employed to reveal the changes in soil microbial community. Results showed that increased precipitation significantly promoted the growth of soil AMF and Actinobacteria (Act). Increased precipitation significantly changed soil microbial community structure and promoted soil microbial community diversity, but it posed neutral effects on soil microbial community biomass. AMF suppression clearly inhibited AM fungal growth but increased the growth of Act and Gram-positive bacteria (G+) and posed limited effects on Gram-negative bacteria (G−), leading to an increased G+/G− ratio. Notably, AMF suppression posed slight effects on the biomass, diversity, and structure of soil microbial community. Random forest analysis revealed that soil ammonium nitrogen (NH4+-N), microbial biomass nitrogen (MBN), and soil organic carbon (SOC) were the main factors influencing different soil microbes, and soil Act and G+ were the main factors influencing plant community diversity, but AMF were the primary factor influencing plant community biomass. More importantly, structural equation modeling (SEM) results further confirmed that increased precipitation and AMF significantly altered plant community diversity by influencing soil AM fungi and increased plant community biomass by promoting soil AM fungal growth. In conclusion, our results demonstrate that increased precipitation enhances plant community productivity and diversity in desert ecosystems primarily by stimulating the growth of arbuscular mycorrhizal fungi, which function as a key biological pathway mediating the ecosystem’s response to climate change.

The frequency, intensity, and duration of extreme climate events will probably increase in various areas in the 21st century. This trend is especially critical for the western Tianshan Mountains, which are highly sensitive to climate variability. Here, we used tree core samples of Picea schrenkiana Fisch. & C.A.Mey. (P. schrenkiana) from the Kashi River Basin to establish standardized earlywood and latewood density chronologies, analyze correlations between the density chronologies and extreme climate indices, and explore the response of tree-ring density to climate and altitudinal variation. Earlywood and latewood densities were significantly correlated with major climatic indices: positively with warm nights (TN90p; June–August), Max Tmin (TNx; June–August), and Min Tmin (TNn; July), and negatively correlated with cold nights (TN10p; June–September). The climate has undergone significant changes particularly in minimum temperatures, and the sensitivity of tree-ring density to major extreme climate indices (TN90p, TNx, TNn, and TN10p) strengthened significantly in sample sites below 1900 m and above 2200 m during 1980–2015 and 1974–2009, respectively, reflecting the vulnerability of mid–high-altitude forests to drought stress. Combined with teleconnection analysis, the positive phase of the AMO is synergistic with the negative phase of NAO/AO, which aggravates the response of tree growth to drought. These results indicate that changes in extreme climate indices primarily exacerbate drought stress in the region’s vulnerable mountain ecosystems, suggesting that future forest management plans should accordingly strengthen their focus on P. schrenkiana.

Abstract Heat vulnerability is a critical issue for cities under climate change, especially in socially precarious contexts and extreme climates such as deserts. The Iquique–Alto Hospicio conurbation in northern Chile represents a distinctive case study due to its marked altitudinal contrasts and rapid urban expansion. This research focuses on assessing the Surface Urban Heat Island (SUHI) at its peak expression, during summer nighttime conditions, in order to spatialize heat vulnerability. A multi-scalar workflow was applied, beginning with long-term multitemporal analysis of land surface temperature (LST) at moderate resolution (2002–2023) and extending to high-reslution downscaling for five recent years (2019–2023) using bilinear resampling combined with robust regression techniques. A Heat Vulnerability Index (HVI) was then developed through principal component analysis (four components, ~74% variance explained), complemented by a spatial cluster analysis based on Anselin’s Local Moran’s I, which delineated statistically significant hot-spots in Iquique’s historic core and in recently formalized social-housing districts on the Alto Hospicio plateau, as well as cold-spots along the affluent coastal seafront. The results confirm the presence of a strong nocturnal summer SUHI, largely coinciding with the most densely populated areas characterized by low-rise housing and limited green space. The Local Climate Zone Compact low-rise and lightweight built forms were identified as the most vulnerable to heat. The study concludes that effective strategies should promote less dense building typologies while incorporating urban infrastructures that act as climate refuges across the conurbation. More broadly, the approach offers a transferable template for climate-resilient planning in data-scarce, arid coastal cities worldwide.

Mongolia has extremely fragile ecosystems and rich vegetation resources in arid and semi-arid zones. It is highly affected by extreme climatic events and is important in the global carbon cycle. In global warming, it is important to study its vegetation changes for ecological security. In this paper, based on the gross primary productivity (GPP) data with daily maximum temperature, daily minimum temperature and daily precipitation data of Mongolia from 2000 to 2023, the characteristics of spatial and temporal changes in GPP and its response to climate extremes were analyzed by using Sen Slope + Mann-Kendall trend analysis, MK mutation test, Pearson's correlation analysis method, and structural equation modeling (SEM). The main findings of the study are as follows: (1) GPP shows an overall increasing trend, especially in the northern Mongolia, with 61% of the study area experiencing significant growth. (2) Extreme temperature indices (SU, TNx, TNn) and precipitation index R20 are increasing at most stations, while R95P and SDII are declining. (3) Extreme precipitation indices generally support GPP, though they suppress it in Western Mongolia. R20 is identified as the primary driver of vegetation growth. (4) TNx and SU inhibit GPP, except in North Mongolia, where warmer summers enhance productivity. R20 and R95P have opposing effects on GPP, highlighting the dual role of precipitation type and intensity.

Since 1990, Dhaka has experienced rapid, unplanned urban expansion, profoundly altering land-use patterns and intensifying local climate extremes in one of the world’s most densely populated megacities. This study aims to quantify three decades of land use and land cover (LULC) changes and evaluate their associated impacts on land surface temperature (LST), near-surface air temperature, and rainfall, with a view to informing climate-resilient urban planning. Landsat 5 TM (1990) and Landsat 9 OLI-2/TIRS-2 (2022) imagery were analyzed using ArcGIS and ERDAS Imagine to classify built-up areas, vegetation, bare land, and water, achieving high accuracy (κ = 0.93). LST was estimated using radiometric calibration, NDVI-based emissivity correction, and the mono-window algorithm, while long-term climate data from the Bangladesh Meteorological Department supported trend analysis. Findings reveal a 41.15% increase in built-up area, largely at the expense of vegetation (–31.02%), resulting in a 4.87 °C rise in peak LST and a 71 mm increase in annual rainfall. Strong positive correlations (|r| ≥ 0.99) show that each 1% gain in built-up land adds approximately 0.12 °C to LST and enhances convective precipitation, whereas vegetation loss exerts a cooling and drying effect. These dynamics are exacerbating urban-heat-island intensity, disrupting seasonal rainfall, and increasing flash-flood and health risks. To counteract these effects, the study recommends vertical urban densification, conservation of wetlands and green belts, and integration of green–blue infrastructure alongside high-resolution remote sensing and climate modeling for adaptive urban policy and planning. Jagannath University Journal of Life and Earth Sciences, 10 (2): 153-177 (December 2024)

ABSTRACT The relocation process and exposure to climatic extremes directly influence the resilience of climate migrants. This study assessed the impact of a government-led relocation program on migrant resilience in Khurushkul Ashrayan Prokolpo, Cox’s Bazar, using data from 251 randomly selected households. Household resilience was measured with the ARC-D toolkit, and findings were validated through focus group discussions and field observations. Resilience scores decreased from 76.37 to 70.99 after relocation, indicating reduced adaptive capacity against cyclones, coastal flooding, and salinity intrusion. Qualitative data revealed unequal aid distribution, limited volunteerism, and weak community cohesion. Quantitative analyses showed resilience was higher among males (M = 2.44, SD = 0.40), adults aged 26–40 (M = 2.42, SD = 0.40), and tourism workers (M = 2.58, SD = 0.36), and lower among females and fishermen. Regression results confirmed that gender (β = –0.164, p = 0.006), occupation (β = 0.148, p = 0.015), and water access (β = 0.196, p = 0.001) significantly influenced resilience. The findings highlight that physical relocation alone cannot ensure resilience without essential services, inclusive governance, and sustainable livelihoods, emphasizing the need for integrated and equitable relocation planning in climate-vulnerable coastal region.

ABSTRACT Driven by escalating environmental degradation and extreme climate events, the 21st-century global economy now places sustainability at its core. Researchers, policymakers, global institutions and environmentalists worldwide are urging a shift to environmentally friendly waste management practices to ease environmental pressure. Although sustainable practices have emerged in key sectors like construction to reduce their harmful impacts, many remain ineffective, particularly in developing countries. This study analyses global construction and demolition waste management methods and proposes a suitable model for developing countries, using South Africa as a case study. This was carried out using a systematic literature review, semi-structured interviews, and questionnaires, with epistemic communities in the construction and environment sector. The study found that while most construction and demolition waste management approaches are highly effective in developed countries, they are less effective and less applicable in developing countries. It is argued that methods from developed countries cannot be directly applied in developing countries like South Africa and must be adapted to local economic and technological contexts. To enhance construction and demolition waste management in South Africa, a hybrid approach combining circular economy and industrial ecology is proposed as an effective solution.

Tourism has emerged as a critical economic pillar for many island communities worldwide, transforming their socio-economic structure and land use strategies. However, intensifying typhoons and other extreme climate events pose escalating risks to these communities, demanding adaptive transformations in disaster knowledge systems and risk management strategies. Local disaster knowledge (LDK), as a place-based knowledge system, plays an essential role in shaping adaptive responses and enhancing resilience within these communities. This study investigates the structure and dynamic adaptation paths of local disaster knowledge amid the shift toward tourism-based communities. Using a qualitative approach, this study conducted an in-depth case study on Shengsi Island, China. The findings reveal that LDK exhibits a three-layered structure: deep-intermediate-surface layers. Beliefs constitute the deep core, while social cohesion, risk knowledge and perception form the middle mediating layer. The surface practical layer encompasses early warning systems, anticipatory measures, structural measures, and livelihood adaptation strategies. The interaction among the three layers constitutes the endogenous dynamics driving knowledge adaptation, while macro-level disaster governance and tourism development act as exogenous drivers. Together, these mechanisms facilitate two adaptive pathways: policy-guided structural transformation and tourism-led practical adaptation. This study advances theoretical understanding of LDK by exploring its dynamics in transforming communities, with a framework that can be extrapolated to other disaster risk contexts. It also provides policy-relevant insights for developing disaster resilience and sustainable land use policies in island communities experiencing tourism transformation.

Under global climate change, the rising frequency of extreme weather events profoundly affects ecosystem carbon cycles. However, in the ecologically fragile dry-hot valleys of Southwest China, the response of carbon source-sink dynamics to these extremes remains unclear, which hinders effective regional carbon management. This study investigates the Nu River dry-hot valley, using the Google Earth Engine platform to process multi-source remote sensing and meteorological data from 2001–2024. We established a framework of 15 extreme climate indices and applied Sen-Mann-Kendall trend analysis, Pearson correlation, and threshold regression models to explore the spatiotemporal evolution of carbon dynamics and their non-linear response to extreme climate. Our results show that: (1) The region’s carbon sink capacity displayed a fluctuating but overall increasing trend with significant spatial heterogeneity; areas of substantial increase were concentrated in the southern, low-altitude zones. (2) Extreme climate events triggered non-linear carbon cycle responses by altering hydrothermal conditions. The synergy of high temperatures and intense, short-duration precipitation weakened the carbon sink, whereas dispersed rainfall alleviated drought stress and enhanced carbon fixation. (3) Both extreme temperature and precipitation indices showed clear regulatory thresholds, above which their effects were significantly amplified; this reveals that the carbon cycle in the dry-hot valley is highly sensitive to extreme events and exhibits distinct threshold-driven responses. This research provides a theoretical basis for the mechanisms regulating carbon flux in dry-hot ecosystems under a variable climate and offers crucial scientific support for optimising regional pathways to carbon neutrality and implementing climate-adaptive management.

Current research on net ecosystem productivity (NEP) still lacks sufficient attention to the impacts of extreme climate events, particularly in understanding the interactive response mechanisms of carbon sinks under extreme climate conditions. This study investigated the spatiotemporal dynamics of NEP and its interactive mechanisms in Dongying, China, from 2001 to 2023 under extreme climate conditions. Using trend slope estimation, geographical detector, and XGBoost methods, we systematically revealed the responses of NEP to the factors including climatic changes, human activities, vegetation growth status, and topographic features. The results indicated that NEP exhibited an overall fluctuating yet increasing trend during 2001–2023. The normalized difference vegetation index (NDVI, for vegetation growth status) and the digital elevation model (DEM, for terrain features) were identified as the dominant factors influencing the spatial heterogeneity of NEP. However, extreme precipitation and high temperature events significantly diminished the positive contribution of the NDVI to NEP, while simultaneously amplifying the negative influence of the DEM on NEP. These two concurrent changes superimposed on each other, especially after 2017, further constrained the potential for carbon sequestration. Furthermore, a lag effect was observed in the response mechanisms of NEP to factors under the influence of precipitation and high-temperature climates. These findings highlight the critical and complex role of extreme climate in reorganizing the contributions of factors and intensifying pressure on the carbon sequestration capacity of ecosystems.