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Increasing temperatures cause the weather to become more severe. Studying how heatwaves (HWs) impact individual heat exposure and susceptibility is vital for building climate change mitigation and adaptation measures. So, this study explores the impact of HWs on individual heat exposure and susceptibility. The assessment was based on the highly complex topographic region contribution to HWs in the Republic of Armenia (RA) using data from 16 meteorological stations for the extended warm season (May–September). We developed a regional HW catchment program to estimate the HW indices' responses to climatic change and to present them in terms of topography changes. The Mann–Kendall (MK) test was used to determine the statistical significance of the trends for 10 distinct HW indicators using linear and exponential trends along with graphical interpretations. This study reveals a large‐scale, significant increasing trend in annual maximum temperatures (Tmax) and observed HWs over the period 1955–2019. The rising temperature is accompanied by an increase in HW indices, particularly at low altitudes up to 1250 m above sea level (ASL), where the main population centres and national crop production are concentrated. According to our classification, the above‐mentioned areas have faced extreme and severe increases in HW intensity, covering more than 60% of the country's territory. Moreover, not only the intensity and frequency have been identified but the HW period extension as well. This extreme increase has been found in the low‐lying highly populated and intensively cultivated areas, such as in the Ararat valley. These results have implications for future climate assessments, adaptation strategies, agriculture and public health in Armenia. The development of targeted mitigation measures and adaptation strategies informed by these findings is essential for addressing the escalating challenges posed by HWs in the region. [ABSTRACT FROM AUTHOR]

According to national climate resilience projections, the coastal area of Bolaang Mongondow has experienced an increase in wave height of around 1 meter. It is in the top priority category with high potential hazards and vulnerability or risk of climate change disasters. The rise of the global sea level affects the increase in coastal submergence and erosion and increases the frequency of overtopping of coastal buildings. This research aimed to analyze the extent of the physical vulnerability of coastal Bolaang Mongondow related to the climate change impacts. The coastal area of Bolaang Mongondow was chosen because it is a coastal area with varied lowlands that directly face the Sulawesi Sea (Pacific Ocean). The vulnerability assessment method used in this study was calculating the Coastal Vulnerability Index (CVI). Spatial data interpretation of the parameters of coastal geomorphology, elevation, coastal slope, shoreline change, sea level rise, tides, and significant wave height will contribute to the final vulnerability index value. The results showed that the weight of each analyzed variable varied, ranging from not vulnerable, moderate, vulnerable, and very vulnerable. The CVI assessment shows the less vulnerable category class in all analyzed coastal areas, with index values of 5.86 in Poigar District, 13.1 both in East Bolaang and Bolaang Districts, 14.6 in Lolak District, and 6.55 in Sangtombolang District. Thus, this research concludes that the physical condition of the Bolaang Mongondow coast is less vulnerable to the impacts of climate change. However, it is still threatened in several specific aspects. Although it has not considered socio-economic factors, the assessment of the physical vulnerability of the Bolaang Mongondow coastline produced in this study can be used to formulate targeted mitigation strategies and adaptation measures in the area. [ABSTRACT FROM AUTHOR]

This study evaluates the potential impacts of climate change on Bangladesh by analyzing 19 bioclimatic indicators based on temperature and precipitation. Data from 18 bias-corrected CMIP6 global climate models (GCMs) were used, covering four Shared Socioeconomic Pathways (SSPs)—SSP126, SSP245, SSP370, and SSP585—across three future timeframes: near-term (2015–2044), mid-term (2045–2074), and long-term (2075–2100). Under the high-emission SSP585 scenario, average temperatures are projected to rise by up to 3.76 °C, and annual precipitation could increase by 52.6%, reaching up to 3446.38 mm by the end of the century. The maximum temperature (Bio5) could reach 32.91 °C, while the minimum temperature (Bio6) might rise by 4.43 °C, particularly during winter. Precipitation seasonality (Bio15) is projected to increase by as much as 7.9% in the northwest, indicating heightened variability between wet and dry seasons. The diurnal temperature range (Bio2) is expected to decrease by up to − 1.3 °C, signifying reduced nighttime cooling, which could exacerbate heat stress. Significant reductions in temperature seasonality (Bio4) are forecast for the northeast, with notable declines in isothermality (Bio3) under SSP585, pointing to increased climatic extremes. These climatic shifts pose severe risks to agricultural productivity, water resource availability, and biodiversity, particularly in flood-prone regions. The findings highlight the need for urgent adaptation measures, including improved flood management systems, efficient water resource use, and climate-resilient agricultural practices. By providing robust region-specific projections, this study offers critical insights for policymakers and stakeholders to mitigate the adverse effects of climate change and safeguard environmental and economic sustainability in Bangladesh. [ABSTRACT FROM AUTHOR]

A comprehensive framework for climate change assessment is a prerequisite for managing multiple risks related to climate extremes, such as droughts, floods, or compound extreme events. It is also useful for addressing the diverging interests of stakeholders in finding regional adaptation solutions. Here, we design such a framework and a general methodology to assess the evolution of regional climate. Both mean values and extreme event characteristics of surface air temperature and soil moisture are analysed, including the likelihood of compound hot-dry, hot-wet, cold-dry, and cold-wet extreme conditions. These analyses are conducted for each month to investigate a variety of climate change impacts. The methodology is designed to be generic and easily applicable to any region of the world. It provides a foundational basis for initiating dialogue with local decision-makers, which will subsequently allow for further refinement of climatic impact-driver indices and analyses to produce tailored climate services. This work reports an application to Southwestern France, a region vulnerable to both floods and droughts with severe impacts on natural ecosystems and human societies. Drying and warming are expected throughout the year, with more pronounced effects in summer. This study highlights the complexity of designing adaptation solutions and the need for in-depth and comprehensive analyses of the evolution of local climate conditions. Specifically, Southwestern France is expected to experience an increase in drought frequency and intensity, while the region might still have to cope with the opposite phenomenon, floods. [ABSTRACT FROM AUTHOR]

Groundwater constitutes 99% of the Earth's liquid freshwater and is crucial for human health, economic development, and ecosystem sustainability. This study assesses groundwater sustainability in Denmark by employing a comprehensive hydrological model and a set of ensemble indicators. The paper describes the methodology and the results based on nine selected indicators. Three indicators focus on recharge capture and aquifer sustainability, one focuses on groundwater level and wetland capture, two focus on baseflow and drainage flow capture, and three focus on eco flow capture. Our findings highlight that while overall exploitable groundwater resources are estimated at 1.1 billion m3/year, significant regional disparities exist, with certain areas, notably Zealand, facing over-exploitation rates exceeding 250% of sustainable limits. The indicators developed not only provide a framework for assessing current groundwater resource limits, but also serve as a basis for future monitoring and adaptive management strategies. This research underscores the need for stakeholder engagement and integrated approaches to ensure the sustainability of groundwater resources in the face of growing anthropogenic pressures and climate change. Our work contributes to the ongoing discourse on sustainable water management and offers a robust methodology for assessing groundwater sustainability. [ABSTRACT FROM AUTHOR]

In this study, a CMIP6 ensemble of 26 GCMs and SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios from CanDCS-U6 is used to project drought conditions in the South Saskatchewan River Watershed. The near-current period (2015–2030) and two future periods (2041–2060 and 2071–2100) are analyzed based on the Standardized Precipitation Evapotranspiration Index (SPEI) at 1-, 3-, 6-, 12-, and 24-month timescales. Projections indicate a shift in average SPEI values from above zero (no drought) in the base period (1951–1990) to more negative values in the future. Results show an increase in drought severity and frequency under climate change conditions. The percentage of time with no drought conditions is projected to decline from 55–70% in the base period to 25–45% by 2071–2100. Severe and extreme droughts, rare in the base period (below 4%), are projected to increase to up to 19% by 2071–2100. The area experiencing drought is expected to expand from 36–49% (for different SPEI timescales) in the base period to up to 76% by 2071–2100. Drought frequency is projected to be higher under SSP1-2.6 and less frequent under SSP2-4.5. Results showed that longer SPEI timescales are associated with higher drought occurrence rates and severity. The spatial pattern of drought is also projected to significantly change, with higher frequencies expected in the eastern parts of the watershed under climate change. [ABSTRACT FROM AUTHOR]

Temperate rainforests are rare ecosystems globally; restricted to cool, moist conditions that are sensitive to a changing climate. Despite their crucial conservation importance, a global assessment of how temperate rainforests will be impacted by climate change is lacking. We calculated historical (1970–2000) climate conditions for the temperate rainforest biome using ERA5 reanalysis data for three key bioclimatic variables: warmest quarter temperature, annual precipitation and proportion of rainfall during warmest quarter. We used high‐spatial resolution climate projections for these variables to identify regions likely to become unsuitable for temperate rainforests under four future shared socioeconomic pathway (SSP) scenarios. We predict unmitigated climate change (SSP 5–8.5) would lead to a 68.3 (95% confidence interval (95 CI): 53.4–81.3)% loss in the existing temperate rainforest biome by 2100 at a global scale with some national‐level reductions exceeding 90%. Restricting global warming to <2°C (consistent with SSP 1–2.6), limits loss of global temperate rainforest biome to 9.7 (95 CI: 7.8–13.3)% by 2100 and is crucial to ensuring temperate rainforest persistence. Deforestation has resulted in loss of up to 43% of the current temperate rainforest biome with only 37% of primary forest remaining, and some regions like Europe with virtually none. Protection and restoration of the temperate rainforest biome, along with emissions reductions, are vital to its climate future. Plain Language Summary: Temperate rainforests are rare ecosystems found only in wet and cool regions, making them vulnerable to a warming climate. They are important to conserve because they host unique species and can store high amounts of carbon. We use global maps of forest cover and condition to assess how much temperate rainforest remains, and how much it has been impacted by human activity. We find that only 37% of the temperate rainforest area is still covered by primary forest. We use a map of existing temperate rainforests along with records of past weather conditions to estimate what climate conditions are needed for its survival. We then use estimates of future climate under four different scenarios of greenhouse gas emissions to see which areas of temperate rainforest will maintain these conditions up to 2100. We find that under the most pessimistic scenario, 68% of temperate rainforest will be lost, while under the most optimistic scenario, only 9% will be lost. Our study can aid temperate rainforest conservation by identifying the areas of temperate rainforest that are least/most vulnerable to climate change, and where there is potential to restore forest. Key Points: Temperate rainforests rely on a cool and moist climate biome that globally rare and vulnerable to climate changeUnmitigated climate change would lead to a loss of 68% of the temperate rainforest biome, but climate mitigation limits loss to 9%We identify historical, intact and potential temperate rainforest extent and climate change vulnerability to inform conservation efforts [ABSTRACT FROM AUTHOR]

Rice is a critical staple crop that feeds more than half of the world's population. Still, its production confronts various biotic risks, notably the severe bacterial blight disease produced by Xanthomonas oryzae. Understanding the possible effects of climate change on the geographic distribution of this virus is critical to ensuring food security. This work used ecological niche modeling and the Maxent algorithm to create future risk maps for the range of X. oryzae under several climate change scenarios between 2050 and 2070. The model was trained using 93 occurrence records of X. oryzae and five critical bioclimatic variables. It has an excellent predictive performance, with an AUC of 0.889. The results show that X. oryzae's potential geographic range and habitat suitability are expected to increase significantly under low (RCP2.6) and high (RCP8.5) emission scenarios. Key climatic drivers allowing this development include increased yearly precipitation, precipitation during the wettest quarter, and the wettest quarter's mean temperature. These findings are consistent with broader research revealing that climate change is allowing many plant diseases and other dangerous microbes to spread across the globe. Integrating these spatial predictions with data on host susceptibility, agricultural practices, and socioeconomic vulnerabilities can help to improve targeted surveillance, preventative, and management methods for reducing the growing threat of bacterial blight to rice production. Proactive, multidisciplinary efforts to manage the changing disease dynamics caused by climate change will be critical to assuring global food security in the future decades. [ABSTRACT FROM AUTHOR]

Global warming is shifting the thermal dynamics of lakes, with resulting climatic variability heavily affecting their mixing dynamics. We present a dual ensemble workflow coupling climate models with lake models. We used a large set of simulations across multiple domains, multi‐scenario, and multi GCM‐ RCM combinations from CORDEX data. We forced a set of multiple hydrodynamic lake models by these multiple climate simulations to explore climate change impacts on lakes. We also quantified the contributions from the different models to the overall uncertainty. We employed this workflow to investigate the effects of climate change on Lake Sevan (Armenia). We predicted for the end of the 21st century, under RCP 8.5, a sharp increase in surface temperature (4.3±0.7K) $(4.3\pm 0.7\,\mathrm{K})$ and substantial bottom warming (1.7±0.7K) $(1.7\pm 0.7\,\mathrm{K})$, longer stratification periods (+55 days) and disappearance of ice cover leading to a shift in mixing regime. Increased insufficient cooling during warmer winters points to the vulnerability of Lake Sevan to climate change. Our workflow leverages the strengths of multiple models at several levels of the model chain to provide a more robust projection and at the same time a better uncertainty estimate that accounts for the contributions of the different model levels to overall uncertainty. Although for specific variables, for example, summer bottom temperature, single lake models may perform better, the full ensemble provides a robust estimate of thermal dynamics that has a high transferability so that our workflow can be a blueprint for climate impact studies in other systems. Plain Language Summary: Lakes are threatened by climate change because of effects related to the increasing temperature, long stratification, and ice disappearance. One of the best tools to predict these effects on lakes is numerical modeling of lakes that benefit from climate modeling. Climate modeling is normally done globally or in the so‐called general circulation model (GCM) or more detailed simulations on regional levels (RCM) like the CORDEX data set. In this study, we used the CORDEX data, which employed several climate models from several regions (domains) for several climatic scenarios (emissions scenarios) to force multiple lake models. This approach gave us an extensive prediction about various possible outputs. We applied this approach to Lake Sevan (Armenia), a large mountain lake. Our study predicted for the worst‐case scenario, an increase of the surface temperature by almost 4.3 K by the end of the 21st century, 1.75 K for bottom temperature, a total disappearance of ice cover, and about 55 extra days of stratification, showing its vulnerability for climate change. This optimized workflow uses the strength of a wide variety of models on the climate and lake levels to better understand the impact of climate change and quantify the sources of uncertainty in the workflow. Key Points: Dual multi‐model ensemble of climate data and lake models is used for robust projections of climate change impactsVariance decomposition effectively identified the sources of uncertainty and contributions of different models to the overall uncertaintySignificant warming, longer stratification periods, and loss of ice cover are predicted for Lake Sevan by the end of the 21st century [ABSTRACT FROM AUTHOR]

Climate change impacts on the hydrology and water resources in East Africa require proper planning of regional adaptation measures. Past studies on the subject matter tended to focus on catchment instead of regional scale. To support actionable policy regarding regional planning of water resources management, this paper reviewed studies conducted in East Africa based on CMIP3, CMIP5, and CMIP6. Compared to the historical condition, temperature of East Africa over the mid- to late 21st century will increase by varying extents over the range 0.17-7°C with about 2.6°C on average. Future precipitation over East Africa will increase by 8.5% on average. Changes in discharge based on CMIP3, CMIP5, and CMIP6 will vary from -25.3 to +60.5%, -42.5 to 129%, and -23.4 to 69%, respectively. Ensemble means of the changes in discharge across the study area based on CMIP3, CMIP5, and CMIP6 will be by 25.2, 19.2, and 19.1%, respectively. Future peak river discharge across East Africa will increase by 8% on average. These results are important for planning regional climate change adaptation across East Africa. To support local or catchment adaptation, results of climate change impacts of temperature, precipitation and discharge of about 50 catchments across East Africa can be found summarized in this review paper. It is recommended that both regional and local policies or approaches should be considered for climate change adaptation to ensure a balanced, effective and sustainable framework for climate resilience in support of measures for tackling broad and specific needs cohesively. [ABSTRACT FROM AUTHOR]

Climate change is a major challenge for the global tourism sector, affecting destinations worldwide. Greece, known for its scenery and abundant cultural history, is particularly vulnerable to these impacts. Tourism is a key driver of Greece's economy, yet climate change threatens both natural environments and cultural sites. To evaluate the impacts of climate change on different types of Greek tourism (beach, sightseeing, winter tourism in mountainous areas), the widely used Holiday Climate Index (beach and urban versions) alongside three additional climatic indices customized for Greek climatic conditions, namely the Urban Climate Comfort Index, the Beach Utility Index, and the Mountainous Winter Climate Index were utilized for top tourist destinations of Greece. The results indicate that urban tourism may face challenges during peak summer months due to rising temperatures, but the shoulder seasons (April–May and September–October) will offer improved conditions, potentially extending the tourist season. For beach tourism, favorable conditions are expected to increase from April to October, with significant gains in June and September. Winter tourism in mountainous areas, especially snow-dependent activities like skiing, is at risk due to the declining snow availability. Overall, the study highlights both the challenges and opportunities posed by climate change for Greece's tourism sector. It emphasizes the importance of adaptation strategies, including infrastructural improvements and promoting alternative activities, to minimize negative impacts and enhance the future attractiveness of Greek tourism. [ABSTRACT FROM AUTHOR]

Social psychologists have conducted research relevant to environmental problems for many decades. However, the climate crisis presents a new problem with distinctive aspects and distinctive urgency. This paper reviews some of the principal ways in which social psychological research and theory have approached the topic, looking at perceptions, behaviour, and impacts linked to climate change. Each of these areas is becoming more sophisticated in acknowledging the diversity of experience among groups that vary in demographics and social roles. I close by identifying three important facets for future research: a focus on social justice, an effort to participate in interdisciplinary efforts, and an emphasis on maximizing our impact. [ABSTRACT FROM AUTHOR]

To help with preparedness efforts of Canadian public health and safety systems for adaptation to climate change, the humidity index (humidex) and three threshold‐based humidex indices (annual number of days with humidex greater than 30, 35 and 40) were computed for a multi‐model ensemble of climate change projections, over Canada. The ensemble consists of one run from each 19 Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate models and offers historical simulations starting in 1950 and future projections out to 2100 following Shared Socioeconomic Pathways (SSPs): SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5. Each ensemble member was bias‐adjusted and statistically downscaled using the Multivariate bias correction—N‐dimensional probability density function transform (MBCn) with hourly data from ERA5‐Land as the target dataset and following a method proposed by Diaconescu et al. (2023; International Journal of Climatology, 43, 837) to calculate humidex from daily climate model outputs. This paper details the steps for data production including evaluation of the target historical gridded data and selection of downscaling method and presents some of the resulting humidex projections at the end of the century. [ABSTRACT FROM AUTHOR]

Abstract To help with preparedness efforts of Canadian public health and safety systems for adaptation to climate change, the humidity index (humidex) and three threshold‐based humidex indices (annual number of days with humidex greater than 30, 35 and 40) were computed for a multi‐model ensemble of climate change projections, over Canada. The ensemble consists of one run from each 19 Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate models and offers historical simulations starting in 1950 and future projections out to 2100 following Shared Socioeconomic Pathways (SSPs): SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5. Each ensemble member was bias‐adjusted and statistically downscaled using the Multivariate bias correction—N‐dimensional probability density function transform (MBCn) with hourly data from ERA5‐Land as the target dataset and following a method proposed by Diaconescu et al. (2023; International Journal of Climatology, 43, 837) to calculate humidex from daily climate model outputs. This paper details the steps for data production including evaluation of the target historical gridded data and selection of downscaling method and presents some of the resulting humidex projections at the end of the century.

Dust and high cloud interactions are critical for climate change, primarily due to the dominant roles of high cloud in the greenhouse effect and the continental precipitation. Nonetheless, disentangling the specific impacts of dust from the overlying meteorology influence on high clouds presents great challenges. In this study, we construct a meteorological pattern that successfully reveal the intricate connection between high cloud distribution and atmospheric conditions. Through this strong bounded relationship, we find that dust exhibits notable controls over the facilitation or inhibition of ice particle growth contingent upon the prevailing meteorological fields. More dust can increase precipitation rate and shorten high cloud lifetime particularly under favorable meteorology. These findings underscore the crucial role of dust concentration in mitigating global warming for future climate change. Plain Language Summary: Dust particles in the atmosphere play a crucial role in the formation and dissipation of high clouds, which can significantly impact global climate and weather patterns. By analyzing satellite observations and climate model data, we discovered that dust can either enhance or suppress the growth of ice crystals, depending on the atmospheric conditions. In moist environments with favorable weather, increased dust leads to larger ice crystals and more precipitation, accelerating the life cycle of high clouds. Conversely, in dry conditions with unfavorable weather, excessive dust competes for limited moisture, resulting in smaller ice crystals, although it can still increase rainfall during the dissipation stage of high clouds. As climate change progresses and dust storms become more frequent, the increased presence of dust in the atmosphere may lead to more extreme weather events and potentially mitigate some of the warming effects caused by high clouds. Understanding these complex interactions between dust, high clouds, and weather conditions is essential for improving climate models and predicting future changes in Earth's water cycle and energy balance. Key Points: Extracted first principal component, highly correlated with high cloud fraction, isolating meteorological effects on cloudsDust facilitates ice crystal formation and precipitation, catalyzing cloud lifecycle and ultimately modifying radiative effectsIncreased dust accelerates high cloud lifecycle, causing more extreme weather and mitigating climate warming [ABSTRACT FROM AUTHOR]

Climate change is one of the greatest threats to cultural heritage. This work develops a climate change risk assessment (CCRA) methodology, assessing large portfolios of properties spread over a wide geographic area. Climate hazards, exposure and vulnerability metrics are identified, and results from two case studies presented to highlight the application of the national CCRA. How a national CCRA fits in a wider context is discussed along with improvements and further work. This method helps understand the impact of climate change across a large estate, supports investment prioritisation and climate informed decision making to increase heritage resilience. [ABSTRACT FROM AUTHOR]

Wheat rusts, including leaf, stripe, and stem rust, have been a threat to global food security due to their devastating impact on wheat yields. In recent years, significant strides have been made in understanding wheat rusts, focusing on disease spread mechanisms, the discovery of new host resistance genes, and the molecular basis of rust pathogenesis. This review summarizes the latest approaches and studies in wheat rust research that provide a comprehensive understanding of disease mechanisms and new insights into control strategies. Recent advances in genetic resistance using modern genomics techniques, as well as molecular mechanisms of rust pathogenesis and host resistance, are discussed. In addition, innovative management strategies, including the use of fungicides and biological control agents, are reviewed, highlighting their role in combating wheat rust. This review also emphasizes the impact of climate change on rust epidemiology and underscores the importance of developing resistant wheat varieties along with adaptive management practices. Finally, gaps in knowledge are identified and suggestions for future research are made. This review aims to inform researchers, agronomists, and policy makers, and to contribute to the development of more effective and sustainable wheat rust control strategies. [ABSTRACT FROM AUTHOR]

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This study uses a new dataset on gauge locations and catchments to assess the impact of 21st-century climate change on the hydrology of 221 high-mountain catchments in Central Asia. A steady-state stochastic soil moisture water balance model was employed to project changes in runoff and evaporation for 2011–2040, 2041–2070, and 2071–2100, compared to the baseline period of 1979–2011. Baseline climate data were sourced from CHELSA V21 climatology, providing daily temperature and precipitation for each subcatchment. Future projections used bias-corrected outputs from four General Circulation Models under four pathways/scenarios (SSP1 RCP 2.6, SSP2 RCP 4.5, SSP3 RCP 7.0, SSP5 RCP 8.5). Global datasets informed soil parameter distribution, and glacier ablation data were integrated to refine discharge modeling and validated against long-term catchment discharge data. The atmospheric models predict an increase in median precipitation between 5.5% to 10.1% and a rise in median temperatures by 1.9 °C to 5.6 °C by the end of the 21st century, depending on the scenario and relative to the baseline. Hydrological model projections for this period indicate increases in actual evaporation between 7.3% to 17.4% and changes in discharge between + 1.1% to –2.7% for the SSP1 RCP 2.6 and SSP5 RCP 8.5 scenarios, respectively. Under the most extreme climate scenario (SSP5-8.5), discharge increases of 3.8% and 5.0% are anticipated during the first and second future periods, followed by a decrease of -2.7% in the third period. Significant glacier wastage is expected in lower-lying runoff zones, with overall discharge reductions in parts of the Tien Shan, including the Naryn catchment. Conversely, high-elevation areas in the Gissar-Alay and Pamir mountains are projected to experience discharge increases, driven by enhanced glacier ablation and delayed peak water, among other things. Shifts in precipitation patterns suggest more extreme but less frequent events, potentially altering the hydroclimate risk landscape in the region. Our findings highlight varied hydrological responses to climate change throughout high-mountain Central Asia. These insights inform strategies for effective and sustainable water management at the national and transboundary levels and help guide local stakeholders. [ABSTRACT FROM AUTHOR]

Flooding is Aotearoa-New Zealand's most frequent natural hazard, and there is high confidence that climate change is making extreme rainfall events more frequent and intense. Additionally, there are significant development pressures which could both increase the number of people and assets at risk and the flood hazard. To date, there is no publicly available consistent approach to accurately determine flood risk on a national scale, nor for how this may be changing; although there is a growing legislative requirement to provide quality information over multiple spatial scales. This paper draws on empirical data to gain insights on how to best manage changing flood risks in Aotearoa-New Zealand from the perspective of centrally organised entities. Findings confirm the need for a nationally consistent approach to flood risk management, better understanding of Aotearoa's communities and their vulnerability to floods, equitable access to quality information and decision-support tools, and better understanding of the economic impacts on differing communities, regions and places. The paper concludes that to achieve a flood-resilient Aotearoa, flood governance needs to be reconfigured to achieve national consistency in flood risk management whilst enabling targeted variability at the local scale. [ABSTRACT FROM AUTHOR]

Climate change has profound impacts on forest ecosystem dynamics and could lead to the emergence of novel ecosystems via changes in species composition, forest structure, and potentially a complete loss of tree cover. Disturbances fundamentally shape those dynamics: the prevailing disturbance regime of a region determines the inherent variability of a system, and its climate‐mediated change could accelerate forest transformation. We used the individual‐based forest landscape and disturbance model iLand to investigate the resilience of three protected temperate forest landscapes on three continents—selected to represent a gradient from low to high disturbance activity—to changing climate and disturbance regimes. In scenarios of sustained strong global warming, natural disturbances increased across all landscapes regardless of projected changes in precipitation (up to a sevenfold increase in disturbance rate over the 180‐year simulation period). Forests in landscapes with historically high disturbance activity had a higher chance of remaining resilient in the future, retaining their structure and composition within the range of variability inherent to the system. However, the risk of regime shift and forest loss was also highest in these systems, suggesting forests may be vulnerable to abrupt change beyond a threshold of increasing disturbance activity. Resilience generally decreased with increasing severity of climate change. Novelty in tree species composition was more common than novelty in forest structure, especially under dry climate scenarios. Forests close to the upper tree line experienced high novelty in structure across all three study systems. Our results highlight common patterns and processes of forest change, while also underlining the diverse and context‐specific responses of temperate forest landscapes to climate change. Understanding past and future disturbance regimes can anticipate the magnitude and direction of forest change. Yet, even across a broad gradient of disturbance activity, we conclude that climate change mitigation is the most effective means of maintaining forest resilience. [ABSTRACT FROM AUTHOR]

The global increase in extreme weather and climate events may dramatically impact agriculture, food safety, and socioeconomic dynamics. The Mediterranean basin is already exposed to extreme climatic events, severely challenging viticulture, a pivotal Mediterranean agro–industry. This study aims to understand better how climate is expected to evolve in six viticulturally important Mediterranean regions in Portugal, Italy, Turkey and Morocco, using a 4–member ensemble of climatic model projections under Representative Concentration Pathways (RCP) 4.5 and 8.5 for 2041–2070, and using the 1981–2010 period as a baseline. By comparing the main specific challenges these locations will face, we comparatively define the best strategies to reduce the impacts of climate change at the national and regional levels. Projections show increases in overall temperatures, up to + 3.6°C than the historical baseline, whilst precipitation projections indicate decreases that could reach 36% of the overall annual precipitation. Biological effective degree days, consecutive dry days, growing season length, tropical nights, or very heavy precipitation days, also show challenging prospects for viticulture in these countries. A screening of the adaptative strategies already undertaken in the studied countries suggests that growers are taking reactive rather than preventive strategies. Moreover, the discussion of the most suitable strategies in this study is region–specific, i.e., prioritised by the specific needs of each location. The conclusions drawn herein may support local growers, improving their decision–making based on the most adequate adaptive strategies to their conditions, thus optimising their sustainable production under changing climates. [ABSTRACT FROM AUTHOR]

Significant increase in wintertime air temperature, especially the reduced cold extremes under climate change, might be beneficial to the winter survival of perennial crops. However, climate warming could result in less snowfall, reduced snow cover, as well as changes in climate conditions for fall hardening and winter thaws. How these changes might impact the risks of winter damages to overwintering crops, such as perennial forage crops requires a comprehensive assessment for proactively adapting to climate change in the agricultural sector, especially the beef and dairy industries. Based on the most up-to-date climate projections from a set of global climate models, we used a snow model and a suite of agroclimatic indices for perennial forage crops to assess potential changes in the risks of winter injury to perennial forage crops across Canada in the near-term (2030s), the mid-term (2050s), and the distant future (2070s). Our results show that the risk of exposure to extremely low temperatures (daily Tmin ≤ −15 °C) without snow protection is projected to decrease across Canada with improved conditions for fall hardening. However, winter thaws and rainfall are projected to increase, and this would increase the risk of winter injury due to loss of hardiness together with potential soil heaving and ice encasement. [ABSTRACT FROM AUTHOR]

Climate change restricts and alters the distribution range of plant species. Predicting potential distribution and population dynamics is crucial to understanding species' geographical distribution characteristics to harness their economic and ecological benefits. This study uses Dendrocalamus brandisii as the research subject, aiming to accurately reveal the impact of climate change on this plant. The findings offer important insights for developing practical conservation and utilization strategies, and guidance for future introduction and cultivation. The MaxEnt model was optimized using regularization multiplier (RM) and feature combination (FC) from the 'Kuenm' package in R language, coupled with ArcGIS for modeling 142 distribution points and 29 environmental factors of D. brandisii. This article explored the key environmental factors influencing the potential suitable regions for D. brandisii, and predicted trends in habitat changes under SSPs2.6 and SSPs8.5 climate scenarios for the current era, the 2050s, 2070s, and 2090s. (1) The results show that when FC = QPH and RM = 1, the AUC = 0.989, indicating that the model prediction is accurate with the lowest complexity and overfitting. The key environmental factors affecting its primary suitable distribution, determined by jackknife training gain and single-factor response curve, are the precipitation of warmest quarter (bio18), the temperature seasonality (bio4), the minimum average monthly radiation (uvb-4), and elevation (Elev), contributing 93.6% collectively. It was established that the optimal range for D. brandisii is precipitation of warmest quarter of between 657 and 999 mm, temperature seasonality from 351% to 442%, minimum average monthly radiation from 2420 to 2786 J/m2/day, at elevation from 1099 to 2217 m. (2) The current potential habitat distribution is somewhat fragmented, covering an area of 92.17 × 104 km2, mainly located in southwest, south, and southeast China, central Nepal, southern Bhutan, eastern India, northwestern Myanmar, northern Laos, and northern Vietnam. (3) In future periods, under different climate scenario models, the potential habitat of D. brandisii will change in varying degrees to become more fragmented, with its distribution center generally shifting westward. The SSP8.5 scenario is not as favorable for the growth of D. brandisii as the SSPs2.6. Central Nepal, southern Bhutan, and the southeastern coastal areas of China have the potential to become another significant cultivation region for D. brandisii. The results provide a scientific basis for the planning of priority planting locations for potential introduction of D. brandisii in consideration of its cultivation ranges. [ABSTRACT FROM AUTHOR]

This article discusses an innovative approach to science education focused on engaging students through authentic learning experiences and hands-on activities. It emphasizes the importance of linking classroom instruction with real-world science research practices, particularly in the context of coral reef ecosystems through an authentic learning opportunity. The article shares insights from piloting a coral reef ecosystem lesson with high school biology students, noting their enthusiastic engagement and skill development in data interpretation and communication. The lab activity is an opportunity for students to simulate underwater research techniques and analyze authentic data to assess the health of coral reef ecosystems. The article underscores the urgency of educating students about threats facing coral reefs, including climate change, pollution, and human activities. Whether we live near an ocean or far away it is important to help students understand how the ocean is connected to our daily lives. By integrating ocean literacy principles into the curriculum, educators can empower students to understand the interconnectedness of marine ecosystems and human behaviors, encouraging informed citizenship and environmental stewardship. This article advocates for transformative science education that cultivates critical thinking, scientific inquiry, and a deeper appreciation for the natural world. [ABSTRACT FROM AUTHOR]

Synthesizing the extensive and ever‐growing climate change literature is becoming increasingly challenging using conventional review processes, yet is crucial to understand key trends, including knowledge and policy related gaps, managing widespread impacts, and prioritizing future efforts. Here, we employ a systematic approach to interrogate ~130,000 international peer‐reviewed climate change articles published between 1990 and 2021. We examine the time–space evolution of research topics and international collaborations, providing insights into broad scale climate change research themes, how they are developed and/or are interconnected. Our analyses indicate that significant thematic adjustments have occurred over the past three decades. Whilst all major areas of climate research have grown in output metrics, there has been a relative shift from understanding the physical science basis toward evaluating climate change impacts, adaptation, and mitigation. There has also been a significant internationalization of climate research with the ratio of international over domestic research increasing from 0.05 in 1990 to nearly 0.60 in 2021. These findings reveal a growing need for collective and coupled adaptation‐mitigation actions to address climate change. The repeatable method and overall results presented herein can help to complement existing large‐scale literature assessments, such as future IPCC reports. This article is categorized under:Climate, History, Society, Culture > Disciplinary PerspectivesIntegrated Assessment of Climate Change > Methods of Integrated Assessment of Climate Change [ABSTRACT FROM AUTHOR]

Paleoclimate information has played an instrumental role in showing how fast climate can vary and how large these changes can be. It provided the first vivid demonstration of the relationships between atmospheric greenhouse gas concentrations and surface air temperatures, as well as striking representations of climate change impacts and possible feedbacks within the climate system, such as those associated with vegetation or ice sheet changes. Here, a short review of recent advances in paleoclimate studies is provided, with the objective of showing what this information on past climates and environments can bring to research on current and possible future climates. We advocate that (1) paleoclimatic and paleoenvironmental information can be leveraged for narratives about climate change, in particular at the local and regional levels, (2) paleoclimate data is essential for out-of-range tests of climate models, since future climates are also out of the range of recent climate information used for calibrating climate models, (3) paleoclimate data, in particular for the last millennia, is essential for taking multi-centennial and multi-millennial variability into account when describing trends related to anthropogenic forcings and attributing climate change signals, in particular for extreme and rare events, and (4) paleoclimates also provide extremely valuable information for initializing the slow components of climate models. In addition, we show how paleoclimate studies can be beneficial to put recent and future climate change into context and improve our knowledge on key processes. They can both benefit from and contribute to models and knowledge based on the study of recent and future climates.

The growing global demand for energy, water, and food presents a challenge to sustainable development. This challenge is further intensified by the expanding human population and the rapid pace of industrialization, which together exert intense pressure on these essential resources. Recent trends indicate a significant increase in energy usage, and it is expected that water and food requirements will also increase. Such pressures highlight the critical need to understand and manage the interconnected nature and associated risks, including cascading risks, within the energy, water, and food sectors. This study delves into the relationship between climate change risks and the Energy-Water-Food (EWF) nexus, assessing the diverse impacts of risk categories on distinct sectors. Furthermore, it expands on the concept of cascading risks, an area often overlooked, across two primary dimensions: hazards, which can evolve into cascading and compound hazards; and systems, where failures can propagate between interdependent systems or even within their own boundaries. Building on the reviewed concepts, a framework is proposed to quantify cascading performance within EWF nexus considering the dynamic interactions of the involved elements to reinforce their resilience.

This review article thoroughly examines the role of Species Distribution Models (SDMs) in plant conservation science, with a specific focus on applications within Iran. Commencing with an extensive methodological approach, involving an exhaustive search across reputable academic databases such as Scopus, Web of Science, and Google Scholar, the review synthesizes a comprehensive set of studies. It offers deep insights into SDM principles, challenges, and transformative applications. Addressing these challenges, the review explores contemporary data collection methods, including the use of remote sensing, drones, and citizen science, which enhance the precision and scope of SDMs. A detailed examination of various modelling algorithms and approaches, including MaxEnt, Random Forest, Bayesian models, and others, highlights their specific applications and contributions to plant conservation. The review also integrates climate change data and various scenarios into SDMs, showcasing case studies that illustrate SDMs' potential to predict shifts in plant distributions in response to changing climate conditions and overexploitation. Emphasizing the importance of spatial scale, the review discusses its critical impact on the accuracy of modelling and conservation planning. The article concludes by underlining the indispensable role of SDMs in advancing plant conservation efforts, offering tailored recommendations for researchers, policymakers, and conservation practitioners.

Extreme weather events are recognized as major drivers of crop yield losses, which threaten food security and farmers’ incomes. Given the increasing frequency and intensity of extreme weather under climate change, it is crucial to quantify the related future yield damages of important crops to inform prospective climate change adaptation planning. In this study, we present a statistical modeling approach to project the changes in crop yields under climate change for eight majorly cultivated field crops in Germany, estimating the impacts of nine types of extreme weather events. To select the most relevant predictors, we apply the least absolute shrinkage and selection operator (LASSO) regression to district-level yield data.The LASSO models select, on average, 62% of the features, which align with well-known biophysical impacts on crops, suggesting that different extremes at various growth stages are relevant for yield prediction. We project on average 2.5-times more severe impacts on summer crops than on winter crops. Under RCP8.5, crop yields experience a mean change from −2.53% to −8.63% in the far future (2069–98) for summer crops and from −0.80% to −2.88% for winter crops, without accounting for CO2 fertilization effects. Heat impacts are identified as the primary driver of yield losses across all crops for 2069–98, while shifting precipitation patterns exacerbate winter and spring waterlogging, and summer and fall drought.Our findings underscore the utility of LASSO regression in identifying relevant drivers for projecting changes in crop yields across multiple crops, crucial for guiding agricultural adaptation. While the present analysis can identify empirical relationships, replicating these findings in biophysical models could provide new insights into the underlying processes.

Abstract Temperate rainforests are rare ecosystems globally; restricted to cool, moist conditions that are sensitive to a changing climate. Despite their crucial conservation importance, a global assessment of how temperate rainforests will be impacted by climate change is lacking. We calculated historical (1970–2000) climate conditions for the temperate rainforest biome using ERA5 reanalysis data for three key bioclimatic variables: warmest quarter temperature, annual precipitation and proportion of rainfall during warmest quarter. We used high‐spatial resolution climate projections for these variables to identify regions likely to become unsuitable for temperate rainforests under four future shared socioeconomic pathway (SSP) scenarios. We predict unmitigated climate change (SSP 5–8.5) would lead to a 68.3 (95% confidence interval (95 CI): 53.4–81.3)% loss in the existing temperate rainforest biome by 2100 at a global scale with some national‐level reductions exceeding 90%. Restricting global warming to

Climate change impacts on the hydrology and water resources in East Africa require proper planning of regional adaptation measures. Past studies on the subject matter tended to focus on catchment instead of regional scale. To support actionable policy regarding regional planning of water resources management, this paper reviewed studies conducted in East Africa based on CMIP3, CMIP5, and CMIP6. Compared to the historical condition, temperature of East Africa over the mid- to late 21st century will increase by varying extents over the range 0.17–7°C with about 2.6°C on average. Future precipitation over East Africa will increase by 8.5% on average. Changes in discharge based on CMIP3, CMIP5, and CMIP6 will vary from −25.3 to +60.5%, −42.5 to 129%, and −23.4 to 69%, respectively. Ensemble means of the changes in discharge across the study area based on CMIP3, CMIP5, and CMIP6 will be by 25.2, 19.2, and 19.1%, respectively. Future peak river discharge across East Africa will increase by 8% on average. These results are important for planning regional climate change adaptation across East Africa. To support local or catchment adaptation, results of climate change impacts of temperature, precipitation and discharge of about 50 catchments across East Africa can be found summarized in this review paper. It is recommended that both regional and local policies or approaches should be considered for climate change adaptation to ensure a balanced, effective and sustainable framework for climate resilience in support of measures for tackling broad and specific needs cohesively.

Temperature increases are associated with an intensification of heavy sub‐daily extreme rainfall by approximately 7% per °C, in accordance with the Clausius‐Clapeyron (CC) relation. As a result of this intensification, there are concerns regarding the increased frequency and magnitude of floods in small to medium‐sized catchments. The high‐resolution two‐dimensional weather generator (WG), AWE‐GEN‐2d, offers an ideal tool to simulate the climate variables required to assess the catchment‐scale hydrological response at high resolution. However, it lacked an explicit representation of the relationship between temperature and precipitation that can mimic the CC relationship. Therefore, we introduce a newly revised version of the model, named AWE‐GEN‐2d‐CC, designed to mirror the observed CC scaling by conditioning the simulation of precipitation properties (intensity and area) on temperature. We demonstrate the model's efficacy in representing future extreme rainfall by simulating their potential impact on the hydrological response of a mountainous catchment in the Swiss Alps. Based on observations and future climate model projections, AWE‐GEN‐2d‐CC was used to generate large ensembles of present and end‐of‐century climate data at hourly and 2‐km resolutions, used subsequently as input to Topkapi‐ETH, a physically‐based, distributed hydrological model. The new version of the WG successfully mimics the CC scaling of heavy rainfall, leading to an intensification of short‐duration heavy rainfall in future climates, in contrast with the results obtained using the original model. This allows for a more realistic assessment of future rainfall impact on hydrological response, which, in the demonstration application, shows a modulated effect even for short durations. Plain Language Summary: As global temperatures continue to rise, so does the intensity of heavy rainfall, which can lead to increased flooding in small to medium‐sized areas. The challenge is predicting not only how heavy rainfall will intensify at a specific point, but also how it is distributed over a catchment area. The AWE‐GEN‐2d model proved to be an effective tool in this respect. We introduce a new version of that model, called AWE‐GEN‐2d‐CC, which explicitly considers the relationship between temperature and rainfall. We tested our model on a mountainous area in the Swiss Alps, using past observations and future climate model projections, and found that the model can successfully predict heavy rainfall intensification in the future, especially for short, intense bursts of rain. This improves the plausibility of the results compared to those obtained with the older version of the model. Despite the predicted increase in heavy rainfall, we found the effect on river flows in the catchment was less drastic. Our study highlights the importance of accurately modeling the impact of temperature on rainfall. In areas prone to high‐intensity storms, our model can assist stakeholders in preparing for future weather extremes. Key Points: A new version of the AWE‐GEN‐2d weather generator model is presentedThe new model explicitly simulates the temperature dependency of extreme precipitation, enabling a realistic simulation of future extremesA climate change hydrological impact study over an alpine catchment is presented [ABSTRACT FROM AUTHOR]

The research on the significant toxic weed Oxytropis glabra, which adversely affects the grazing industry and the ecological integrity of natural grasslands in the arid and semi-arid regions of northern China, aims to delineate its potential distribution amidst changing climate conditions. This analysis involves both current conditions (1970–2000) and future projections (2050s and 2070s) under four climate scenarios using an R-optimized MaxEnt model. The results indicate that the distribution of O. glabra was primarily influenced by the temperature of the coldest quarter (bio11, ranging from −12.04 to −0.07 °C), precipitation of the coldest quarter (bio19, 0 to 15.17 mm), and precipitation of the warmest quarter (bio18, 0 to 269.50 mm). Currently, the weed predominantly occupies parts of Xinjiang, Inner Mongolia, Gansu, Qinghai, Ningxia, and Tibet. Projections indicate that, across four future climate scenarios, the area of suitable habitats for O. glabra is expected to expand and shift toward higher latitudes and elevations. The research provides valuable information and a theoretical foundation for the management of O. glabra, alongside advancing grassland ecological research and grazing practices. [ABSTRACT FROM AUTHOR]

Submarine pipelines have become integral for transporting resources and drinking water across large bodies. Therefore, ensuring the stability and reliability of these submarine pipelines is crucial. Incorporating climate change impacts into the design of marine structures is paramount to assure their lifetime safety and serviceability. Deterministic design methods may not fully consider the uncertainties and risks related to climate change compared to risk-based design models. The latter approach considers the future risks and uncertainties linked to climate and environmental changes, thus ensuring infrastructure sustainability. This study pioneers a Hybrid 3D Hydrodynamic Monte Carlo Simulation (HMCS) Model to improve the reliability-based design of submarine pipelines, incorporating the effects of climate change. Current design approaches may follow deterministic methods, which may not systematically account for climate change's comprehensive uncertainties and risks. Similarly, traditional design codes often follow a deterministic approach, lacking in the comprehensive integration of dynamic environmental factors such as wind, waves, currents, and geotechnical conditions, and may not adequately handle the uncertainties, including the long-term effects of climate change. Nowadays, most countries are developing new design codes to modify the risk levels for climate change's effects, such as sea-level rises, changes in precipitation, or changes in the frequency/intensity of winds/storms/waves in coastal and marine designs. Our model may help these efforts by integrating a comprehensive risk-based approach, utilizing a 3D hydrodynamic model to correlate diverse environmental factors through Monte Carlo Simulations (MCS). The hybrid model can promise the sustainability of marine infrastructure by adapting to future environmental changes and uncertainties. Including such advanced methodologies in the design, codes are encouraged to reinforce the resilience of maritime structures in the climate change era. The present design codes should inevitably be reviewed according to climate change effects, and the hybrid risk-based design model proposed in this research should be included in codes to ensure the reliability of maritime structures. The HMCS model represents a significant advancement over existing risk models by incorporating comprehensive environmental factors, utilizing advanced simulation techniques, and explicitly addressing the impacts of climate change. This innovative approach ensures the development of more resilient and sustainable maritime infrastructure capable of withstanding future environmental uncertainties. [ABSTRACT FROM AUTHOR]

Climate-induced migration presents a growing challenge with significant humanitarian, social, and policy implications. This article examines the complex relationship between climate change and migration, exploring environmental impacts, socioeconomic consequences, and the different types of climate-induced migration, including internal displacement and cross-border migration. The article also highlights the current challenges in managing climate-induced displacement, such as legal and policy gaps, human rights and protection concerns, capacity constraints, and social integration and cultural challenges. The article emphasizes the importance of developing comprehensive policies and strategies to address climate-induced migration. It outlines potential approaches, such as enhancing global and regional frameworks, legally recognizing climate migrants, expanding support for regional and international cooperation, integrating climate-induced migration into national climate change and development plans, and investing in climate-resilient infrastructure and livelihoods. It also discusses case studies of successful policy responses to climate-induced migration and offers lessons learned and best practices. In conclusion, the article underscores the significance of proactive policy development, collaboration, and ongoing research and monitoring of climate-induced migration trends. By adopting best practices and learning from existing successes, policymakers can develop robust strategies to manage the growing challenge of climate-induced displacement and support vulnerable communities in the face of climate change. [ABSTRACT FROM AUTHOR]

Coastal dunes, formed and shaped by aeolian sediment transport, play a crucial role in ecosystem services and act as natural flood and coastal erosion defenses. This paper delves into theoretical equations and numerical models predicting sediment transport. Numerical models like cellular automata, XBeach-DUNA, the coastal dune model, and others are analyzed for their ability to simulate dune morphology, erosion processes, and vegetation impacts accurately. Evaluated are field observation and measurement techniques, such as sand traps, impact sensors, and optical sensors, for their precision in quantifying aeolian dynamics. Further examined is the effectiveness of vegetation and fencing in dune stabilization, noting species-specific responses and the influence of fence design on sediment accumulation. These tools offer insights into optimizing aeolian sediment management for coastal protection. By conducting a systematic review and connecting theoretical, empirical, and modeling findings, this study highlights the complex challenge of measuring and managing aeolian sediment transport and proposes integrated strategies for enhancing coastal dune resilience against the backdrop of climate change and erosion. This study's objectives to bridge gaps in current understanding are met, highlighting the need for a multidisciplinary approach to coastal dune management and conservation, especially combining wind- and wave-driven processes. [ABSTRACT FROM AUTHOR]

In this study, we enhance our understanding of the economic impacts of climate change on agriculture in Iran to provide further information for moving Iran's climate policy forward by linking farmland net revenue to novel climatic and non‐climatic variables. We take advantage of spatial panel econometrics to better circumvent omitted factors extraneous to the agricultural sector and to develop a more reliable and consistent model when data are inherently spatial. In contrast to conventional panel studies which relied on year‐to‐year weather observations, we exploit a hybrid approach to compromise between the disadvantages and advantages of longer‐term cross‐sectional analysis and shorter‐term panel models. We estimate the potential impacts of climate change on agriculture under several global warming scenarios based on the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6). We find that (I) farmlands' net revenues are projected to decline by 8%–19% and 14%–51% by 2050 and 2080; (II) the distributional impacts of climate change would highly depend on climate zones and geographical locations; (III) a few counties might benefit from climate changes; (IV) finally, failing to account for spatial spillovers when they are present leads to a misspecified model. [ABSTRACT FROM AUTHOR]

Advances in the field of extreme event attribution allow to estimate how anthropogenic global warming affects the odds of individual climate disasters, such as river floods. Extreme event attribution typically uses precipitation as proxy for flooding. However, hydrological processes and antecedent conditions make the relation between precipitation and floods highly nonlinear. In addition, hydrology acknowledges that changes in floods can be strongly driven by changes in land‐cover and by other human interventions in the hydrological system, such as irrigation and construction of dams. These drivers can either amplify, dampen or outweigh the effect of climate change on local flood occurrence. Neglecting these processes and drivers can lead to incorrect flood attribution. Including flooding explicitly, that is, using data and models of hydrology and hydrodynamics that can represent the relevant hydrological processes, will lead to more robust event attribution, and will account for the role of other drivers beyond climate change. Existing attempts are incomplete. We argue that the existing probabilistic framework for extreme event attribution can be extended to explicitly include floods for near‐natural cases, where flood occurrence was unlikely to be influenced by land‐cover change and human hydrological interventions. However, for the many cases where this assumption is not valid, a multi‐driver framework for conditional event attribution needs to be established. Explicit flood attribution will have to grapple with uncertainties from lack of observations and compounding from the many processes involved. Further, it requires collaboration between climatologists and hydrologists, and promises to better address the needs of flood risk management. This article is categorized under:Paleoclimates and Current Trends > Modern Climate ChangePaleoclimates and Current Trends > Detection and AttributionAssessing Impacts of Climate Change > Observed Impacts of Climate Change [ABSTRACT FROM AUTHOR]