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Fire plays a critical role in both the formation and degradation of ecosystems; however, there are still significant uncertainties in the estimation of burned areas (BAs). This study systematically evaluated the performance of ten global climate models (GCMs) in simulating global and regional BA during a historical period (1997–2014) using the Global Fire Emissions Database version 4.1s (GFED4s) satellite fire product. Then, six of the best models were combined using Bayesian Model Averaging (BMA) to predict future BA under three Shared Socioeconomic Pathways (SSPs). The results show that the NorESM2-LM model excelled in simulating both global annual and monthly BA among the GCMs. GFDL-ESM4 and UKESM1-0-LL of the GCMs had the highest Pearson's correlation coefficient (PCC), but they also exhibited the most significant overestimation of monthly BA variations. The BA fraction (BAF) for GCMs was over 90% for small fires (<1%). For small fires (2~10%), GFDL-ESM4(j) and UKESM1-0-LL(k) outperformed the other models. For medium fires (10–50%), CESM2-WACCM-FV2(e) was closest to GFED4s. There were large biases for all models for large fires (>50%). After evaluation and screening, six models (CESM2-WACCM-FV2, NorESM2-LM, CMCC-ESM2, CMCC-CM2-SR5, GFDL-ESM4, and UKESM1-0-LL) were selected for weighting in an optimal ensemble simulation using BMA. Based on the optimal ensemble, future projections indicated a continuous upward trend across all three SSPs from 2015 to 2100, except for a slight decrease in SSP126 between 2071 and 2100. It was found that as the emission scenarios intensify, the area experiencing a significant increase in BA will expand considerably in the future, with a generally high level of reliability in these projections across most regions. This study is crucial for understanding the impact of climate change on wildfires and for informing fire management policies in fire-prone areas in the future. [ABSTRACT FROM AUTHOR]

Understanding the evolutionary responses of anadromous salmon and trout to climate change is critical for effective conservation planning. In this study, we conducted a comprehensive review of literature published from 2010 to 2020 to synthesize current knowledge on climate impacts to these fish populations. Specifically, we focused on 199 papers that explored evolutionary processes in response to changing environmental conditions. Our analysis revealed several key themes, including the interwoven influences of climate and human activities on genetic variation, phenotypic traits, and population dynamics. We found that geographic patterns in genetic diversity are closely linked to climatic gradients, highlighting the importance to conservation strategies of variation in existing adaptive capacity. Additionally, temporal trends in phenology, maturation age, and fecundity indicate ongoing evolutionary and plastic responses to climate change. Importantly, human activities were identified as significant drivers of maladaptation in anadromous salmon and trout populations. We emphasize the need for targeted monitoring of specific evolutionary processes to mitigate the loss of genetic diversity and enhance adaptive capacity. Our study underscores the importance of identifying and protecting areas of high genetic diversity and rare genes, particularly in regions projected to experience rapid climatic shifts. In conclusion, our findings identify strengths and gaps in the research investigating the role of evolutionary dynamics in the face of climate change. By capitalizing on new tools for sequencing, genomic analysis, and automated field data collection, we can establish baselines for tracking evolutionary responses to climate change. Better integration of evolutionary processes into projections of future climate impacts will lead to more effective strategies to ensure the long‐term resilience of these iconic fish species and other wildlife. [ABSTRACT FROM AUTHOR]

Climate risk assessments must account for a wide range of possible futures, so scientists often use simulations made by numerous global climate models to explore potential changes in regional climates and their impacts. Some of the latest‐generation models have high effective climate sensitivities (EffCS). It has been argued these "hot" models are unrealistic and should therefore be excluded from analyses of climate change impacts. Whether this would improve regional impact assessments, or make them worse, is unclear. Here we show there is no universal relationship between EffCS and projected changes in a number of important climatic drivers of regional impacts. Analyzing heavy rainfall events, meteorological drought, and fire weather in different regions, we find little or no significant correlation with EffCS for most regions and climatic drivers. Even when a correlation is found, internal variability and processes unrelated to EffCS have similar effects on projected changes in the climatic drivers as EffCS. Model selection based solely on EffCS appears to be unjustified and may neglect realistic impacts, leading to an underestimation of climate risks. Plain Language Summary: Climate impact researchers often must decide which of the many available global climate models to use for their analyses. It has been suggested models with very high climate sensitivities should be excluded from impact analyses, because their global mean temperature projections are unrealistic. However, we show that projected future changes in climatic drivers of floods, droughts, and wildfires, across many regions of the world, are not correlated with model climate sensitivity. Regional impacts depend on numerous processes and phenomena many of which are unrelated to climate sensitivity. Excluding models solely on the basis of their climate sensitivity is thus not justified, and can lead to important impacts being ignored by policymakers, with serious consequences for society. Key Points: Future changes in climatic drivers of floods, droughts, and wildfires are generally not correlated with climate sensitivity in Sixth Coupled Model Intercomparison Project modelsModel selection for impacts solely based on climate sensitivity is not justified and may lead to an underestimation of climate risksModel internal variability plays an important role in future projections of climate impact drivers [ABSTRACT FROM AUTHOR]

Coastal zones are facing intensive ecological pressures and challenges, which could vary over a wide range of spatiotemporal scales. Our limited capability to understand and especially predict this variability can lead to the misinterpretation of coastal ecological resilience. Therefore, the assessment and prediction of ecological resilience are particularly important. In this study, a new approach based on the Pressure–State–Response model is developed to assess and predict pixel-scale multi-year ecological resilience (ER) and then applied to investigate the spatiotemporal variations of ER in the China's coastal zone (CCZ) in the past few decades and predict future ER trend under various scenarios. The results show that ER in the CCZ displayed a general spatial distribution pattern of "higher in the southern half and lower in the northern half" from 1995 to 2020. Over the 25-year period, ER exhibited a declining trend. Specifically, the eastern provinces experiencing the most significant decline. The ER levels across scenarios ranked from high to low as follows: SSP1-2.6 > SSP4-3.4 > SSP2-4.5 > SSP3-7.0 > SSP5-8.5. The assessment and prediction methods designed can be applied to ER studies in other coastal zones, making it a valuable approach for broader applications. [ABSTRACT FROM AUTHOR]

Snow conditions are changing rapidly across our planet, which has important implications for wildlife managers. In Alaska, USA, the later arrival of snow is challenging wildlife managers' ability to conduct aerial fall (autumn) moose (Alces alces) surveys. Complete snow cover is required to reliably detect and count moose using visual observation from an aircraft. With inadequate snow to help generate high‐quality moose survey data, it is difficult for managers to determine if they are effectively meeting population goals and optimizing hunting opportunities. We quantified past relationships and projected future trends between snow conditions and moose survey success across 7 different moose management areas in Alaska using 32 years (1987–2019) of moose survey data and modeled snow data. We found that modeled mean snow depth was 15 cm (SD = 11) when moose surveys were initiated, and snow depths were greater in years when surveys were completed compared to years when surveys were canceled. Further, we found that mean snow depth toward the beginning of the survey season (1 November) was the best predictor of whether a survey was completed in any given year. Based on modeled conditions, the trend in mean snow depth on 1 November declined from 1980 to 2020 in 5 out of 7 survey areas. These findings, coupled with future projections, indicated that by 2055, the delayed onset of adequate snow accumulation in the fall will prevent the completion of moose surveys over roughly 60% of Alaska's managed moose areas at this time of the year. Our findings can be used by wildlife managers to guide decisions related to the future reliability of aerial fall moose surveys and help to identify timelines for development of alternate measurement and monitoring methods. [ABSTRACT FROM AUTHOR]

Background: Ehrlichiosis and anaplasmosis are vector-borne bacterial diseases produced by intracellular rickettsial species of the genus Ehrlichia and Anaplasma. Ehrlichia canis and Anaplasma spp. (A. platys and A. phagocytophilum) have reported cases of zoonotic transmision and are the main bacterial agents of canine ehrlichiosis and anaplasmosis. They normally present an asymptomatic or mild course in domestic and wild animals with some lethal cases reported. The main vector of these diseases in Europe are the castor bean tick (Ixodes ricinus) and the brown dog tick (Rhipicephalus sanguineus), although only in the latter, the main host is the domestic dogs. The aim of this work is to apply an integrative approach to convert ecological niche models (ENMs) into potential transmission risk models and understand the relative contribution of the two potential vectors (R. sanguineus and I. ricinus) to spread both diseases in the Iberian Peninsula and Balearic Islands. Results: Two ENMs meeting all criteria were successfully generated for R. sanguineus and I. ricinus with human footprint being the most relevant explanatory variable. The novelty of the study lies in the combination of independent ENMs for both species to estimate the disease transmission risk of specific bacteria (E. canis, A. platys and A. phagocytophilum). Only the transmission risk maps that had higher contribution of R. sanguineus than I. ricinus showed relevant and positive significant correlations between risk and seroprevalence in either of the two species of bacteria (R ≥ 0.4; p < 0.05). Regarding Anaplasma spp., the map having 10% contribution of I. ricinus (10I) and 90% of R. sanguineus (90R) inferred 47.4% of infected dogs in very high-risk areas. In the case of E. canis, the model showing a proportion of 25I-75R showed better validation power (53.4% of infected dogs in very high-risk areas). Conclusion: The validation approach used in this study produced a good approximation to understand the relative contribution of the two tick species in bacterial disease transmission in dogs in the Iberian Peninsula and Balearic Islands. Rhipicephalus sanguineus appears as the main transmitter of both diseases in the study area (90% and 75% for anaplasmosis and ehrlichiosis respectively), in accordance with its higher abundance and host preference. This estimate may help veterinary staff, clinicians and owners to optimize the control of these diseases in certain vulnerable areas, and thus reduce the risk of infection in risk areas. [ABSTRACT FROM AUTHOR]

Due to growing water demands and changing hydro-meteorological variables brought on by climate change, drought is becoming an increasingly serious climate concern. The Al-Baha region of Saudi Arabia is the subject of this study because it is susceptible to both agricultural and meteorological droughts. This study investigates how climate change affects patterns of drought in Al-Baha by analyzing four drought indices (Agricultural Standardized Precipitation Index (aSPI), the Standardized Precipitation Index (SPI), the Rainfall Deficiency Index (RDI), and the Effective Reconnaissance Drought Index (eRDI)) for the years 1991–2022. Analysis of rainfall data was carried out to classify drought events according to their duration, frequency, and severity. Results showed that severe droughts occurred in 2009, 2010, 2012, 2016, and 2022, with 2010 being the worst year. Results also indicated a notable decrease in precipitation, which has resulted in extended dry spells. Several indices indicate that this tendency has significant ramifications for agriculture, particularly in areas where farming is a major economic activity. In addition, the possible occurrence of hydrological drought was also observed based on the negative values for the Reservoir Storage Index (RSI) in Al-Baha. Projections for the future under two Representative Concentration Pathways (RCPs) showed notable variations in temperature and precipitation. Both the RCP4.5 (low emission) and the RCP8.5 (high emission) projection scenarios indicate that drought conditions will likely worsen further. Depending on the emission scenario, it is projected to show a temperature increase of 1–2 °C, whereas the variability in precipitation projections indicates significant uncertainty, with a reduction change in the range of 1.2–27% between 2050 and 2100. The findings highlight the urgent need for proactive adaptation strategies, effective water resource management, and the development of sophisticated drought prediction tools. Addressing these challenges is crucial for sustaining agriculture and managing water scarcity in Saudi Arabia in the face of increasing drought risk. [ABSTRACT FROM AUTHOR]

Abstract Climate change has a significant impact on water resources, making it essential to re-evaluate water management strategies and incorporate climate scenarios in assessments. The Municipal Department of Aigeiros is located in the northern part of Greece. Water consumption is high in Aigeiros and the increased future temperatures projected during the summer period will create significant pressures on water resources. The water resources management study of the region is carried out using the simulations of the RCA4 Regional Climate Model (RCM) driven by the HadGEM-ES global climate model of the Met Office Hadley Centre (MOHC) under 3 different climate emission scenarios, namely RCP 2.6, RCP 4.5 and RCP 8.5. For the simulation of the urban water balance of Aigeiros, Komotini, Greece and the assessment of water demand and supply for three climate scenarios (RCP 2.6, 4.5, and 8.5) over a 30-year period, the Aquacycle software was used. The data used in the assessment included projected climatic conditions for the area (i.e., precipitation and evapotranspiration), domestic water consumption, and natural and spatial characteristics. The results indicate that drinking water demand is likely to increase in the coming decades for RCP 4.5 (1323 m3/d for 2041–2050) and RCP 8.5 (1330 m3/d for 2041–2050) scenarios compared to 2020 (1320 m3/d). However, simulations for water supply suggest an increase in groundwater recharge in the future, but also the potential for long drought periods during summer months in RCP 4.5 and RCP 8.5 scenarios. The simulation results show both the current situation and the climate scenarios and can be the reference basis for recording the different types of water consumption in urban areas. Therefore, it is possible to control and predict how much of the total consumption is due to the consumer usage profile within a household or to the irrigation needs of green areas in line with the climatic conditions, consumer behavior and technical parameters.

Transport energy demand (TED) forecasting is a crucial issue for countries like Turkey that are dependent on external resources. The accuracy and effectiveness of these forecasts are extremely important, especially for the strategies and plans to be developed. With this in mind, different forms of forecasting models were developed in the present study using the Walrus Optimizer (WO) and White Shark Optimizer (WSO) algorithms to estimate Turkey's energy consumption related to road and railway transportation modes. Additionally, another objective of this study was to examine the impacts of different transport modes on energy demand. To investigate the effect of demand distribution among transport modes on energy consumption, model parameters such as passenger-kilometers (P-km), freight-kilometers (F-km), carbon dioxide emissions (CO2), gross domestic product (GDP), and population (POP) were utilized in the development of the models. It was found that the WO algorithm outperformed the WSO algorithm and was the most suitable method for energy demand forecasting. All the developed models demonstrated a better performance level than those reported in previous studies, with the best performance achieved by the semi-quadratic model developed with the WO, showing a 0.95% MAPE value. Projections for energy demand up to the year 2035 were established based on two different scenarios: the current demand distribution among transport modes, and a demand shift from road to rail transportation. It is anticipated that the proposed energy demand models will serve as an important guide for effective planning and strategy development. Moreover, the findings suggest that a balanced distribution among transport modes will have a positive impact on transport energy and will result in lower energy requirements. [ABSTRACT FROM AUTHOR]

As urban expansion continues, the intensifying land surface temperature (LST) underscores the critical need for accurate predictions of future thermal environments. However, no study has investigated which method can most effectively and consistently predict the future LST. To address these gaps, our study employed four methods—the multiple linear regression (MLR), geographically weighted regression (GWR), random forest (RF), and artificial neural network (ANN) approach—to establish relationships between land use/cover and LST. Subsequently, we utilized these relationships established in 2006 to predict the LST for the years 2012 and 2018, validating these predictions against the observed data. Our results indicate that, in terms of fitting performance (R2 and RMSE), the methods rank as follows: RF > GWR > ANN > MLR. However, in terms of temporal stability, we observed a significant variation in predictive accuracy, with MLR > GWR > RF > ANN for the years 2012 and 2018. The predictions using MLR indicate that the future LST in 2050, under the SSP2 and SSP5 scenarios, is expected to increase by 1.8 ± 1.4 K and 2.1 ± 1.6 K, respectively, compared to 2018. This study emphasizes the importance of the MLR method in predicting the future LST and provides potential instructions for future heat mitigation. [ABSTRACT FROM AUTHOR]

Abstract Climate risk assessments must account for a wide range of possible futures, so scientists often use simulations made by numerous global climate models to explore potential changes in regional climates and their impacts. Some of the latest‐generation models have high effective climate sensitivities (EffCS). It has been argued these “hot” models are unrealistic and should therefore be excluded from analyses of climate change impacts. Whether this would improve regional impact assessments, or make them worse, is unclear. Here we show there is no universal relationship between EffCS and projected changes in a number of important climatic drivers of regional impacts. Analyzing heavy rainfall events, meteorological drought, and fire weather in different regions, we find little or no significant correlation with EffCS for most regions and climatic drivers. Even when a correlation is found, internal variability and processes unrelated to EffCS have similar effects on projected changes in the climatic drivers as EffCS. Model selection based solely on EffCS appears to be unjustified and may neglect realistic impacts, leading to an underestimation of climate risks.

Abstract Understanding the evolutionary responses of anadromous salmon and trout to climate change is critical for effective conservation planning. In this study, we conducted a comprehensive review of literature published from 2010 to 2020 to synthesize current knowledge on climate impacts to these fish populations. Specifically, we focused on 199 papers that explored evolutionary processes in response to changing environmental conditions. Our analysis revealed several key themes, including the interwoven influences of climate and human activities on genetic variation, phenotypic traits, and population dynamics. We found that geographic patterns in genetic diversity are closely linked to climatic gradients, highlighting the importance to conservation strategies of variation in existing adaptive capacity. Additionally, temporal trends in phenology, maturation age, and fecundity indicate ongoing evolutionary and plastic responses to climate change. Importantly, human activities were identified as significant drivers of maladaptation in anadromous salmon and trout populations. We emphasize the need for targeted monitoring of specific evolutionary processes to mitigate the loss of genetic diversity and enhance adaptive capacity. Our study underscores the importance of identifying and protecting areas of high genetic diversity and rare genes, particularly in regions projected to experience rapid climatic shifts. In conclusion, our findings identify strengths and gaps in the research investigating the role of evolutionary dynamics in the face of climate change. By capitalizing on new tools for sequencing, genomic analysis, and automated field data collection, we can establish baselines for tracking evolutionary responses to climate change. Better integration of evolutionary processes into projections of future climate impacts will lead to more effective strategies to ensure the long‐term resilience of these iconic fish species and other wildlife.

Climate conditions have a strong influence on the distribution of many natural communities; thus, the influence of global climate change may alter ecosystems. High-altitude wetlands in the Central Andes of Argentina (CAA) provide relevant ecosystem benefits and promote human activities. However, a degradation of Andean wetlands has been observed and documented in the last decades. Projecting the impacts of climate change on future distribution of wetlands is an essential subject in ecological studies. In this work, the present and future suitability for wetland systems in a pristine section of the CAA using spatial distribution modeling under low and high-emission scenarios are explored. The studied wetlands are strongly driven by bioclimatic variables such as mean annual temperature, precipitation, and its seasonality. Projections show that most of the currently occupied areas will modify under future climate conditions. Changes in temperature and precipitation patterns will decrease the potential suitability in low elevation areas for the next decades for the species inhabiting there, especially south of 29 °S. Additionally, future warmer climatic conditions, greater temperature variability, and reduction in precipitation would probably affect the snow cover and the available water supply which are key limiting factors for the distribution of Andean wetlands. This research is a contribution to understanding possible effects of climate change on high-altitude ecosystems. Mitigation measures for conservation of wetlands in CAA are immediately required to compensate for the impact of climate change under future environmental conditions.

Streamflow simulations from the Inter-Sectoral Impact Model Intercomparison Project phase 2b (ISIMIP2b) were analyzed to evaluate future changes in surface water resources over northern Patagonia, a region that contributes significantly to the total hydropower production of Argentina. Ten global hydrological models (GHMs), forced by four general circulation models, effectively capture the winter streamflow maximum in the Negro river basin. However, most of them face challenges in simulating the late-spring pulse due to a misrepresentation of temperature over the higher elevations of the Andes. We quantified the future streamflow evolution using a multi-model ensemble from a subset of the best-performing GHMs under the RCP2.6 and RCP6.0 emission scenarios for two temporal horizons. According to the multi-model ensemble, there is a projected decrease in the annual streamflow of the analyzed rivers, which is more important considering the RCP6.0 scenario during the late 21st century, reaching up to −40% relative to the 1979–2005 reference period. This reduction is attributed to the projected precipitation decline in the headwaters of the Negro river basin in response to changes in the surface pressure patterns. These results have implications for regional water authorities for the development of adaptation plans considering future demand projections. HIGHLIGHTS A set of global hydrological models (GHMs) from the ISIMIP2b project was used to characterize streamflow changes in the Comahue region.; A decrease in the annual streamflow is projected along the 21st century, particularly for the Neuquén river.; Uncertainty is mainly linked to the global climate models used to drive the GHMs.; Hydropower generation and irrigation for agriculture are expected to face future reductions.;

While the ubiquity and importance of narratives for human adaptation is widely recognized, there is no integrative framework for understanding the roles of narrative in human adaptation. Research has identified several cognitive and social functions of narratives that are conducive to well-being and adaptation as well as to coordinated social practices and enculturation. In this paper, we characterize the cognitive and social functions of narratives in terms of active inference, to support the claim that one of the main adaptive functions of narrative is to generate more useful (i.e., accurate, parsimonious) predictions for the individual, as well as to coordinate group action (over multiple timescales) through shared predictions about collective behavior. Active inference is a theory that depicts the fundamental tendency of living organisms to adapt by proactively inferring the causes of their sensations (including their own actions). We review narrative research on identity, event segmentation, episodic memory, future projections, storytelling practices, enculturation, and master narratives. We show how this research dovetails with the active inference framework and propose an account of the cognitive and social functions of narrative that emphasizes that narratives are for the future--even when they are focused on recollecting or recounting the past. Understanding narratives as cognitive and cultural tools for mutual prediction in social contexts can guide research on narrative in adaptive behavior and psychopathology, based on a parsimonious mechanistic model of some of the basic adaptive functions of narrative. [ABSTRACT FROM AUTHOR]

Coastal zones are facing intensive ecological pressures and challenges, which could vary over a wide range of spatiotemporal scales. Our limited capability to understand and especially predict this variability can lead to the misinterpretation of coastal ecological resilience. Therefore, the assessment and prediction of ecological resilience are particularly important. In this study, a new approach based on the Pressure–State–Response model is developed to assess and predict pixel-scale multi-year ecological resilience (ER) and then applied to investigate the spatiotemporal variations of ER in the China’s coastal zone (CCZ) in the past few decades and predict future ER trend under various scenarios. The results show that ER in the CCZ displayed a general spatial distribution pattern of “higher in the southern half and lower in the northern half” from 1995 to 2020. Over the 25-year period, ER exhibited a declining trend. Specifically, the eastern provinces experiencing the most significant decline. The ER levels across scenarios ranked from high to low as follows: SSP1-2.6 > SSP4-3.4 > SSP2-4.5 > SSP3-7.0 > SSP5-8.5. The assessment and prediction methods designed can be applied to ER studies in other coastal zones, making it a valuable approach for broader applications.

Climate change has been linked to the escalating frequency, duration, and intensity of heat waves in the Mediterranean region, intensifying health concerns for the general populace. Urban environments face elevated health risks due to concentrated populations and the urban heat island effect, further amplifying nighttime heat conditions. This study aims to project changes in heat wave characteristics and the associated population exposure risk in a large Mediterranean city, Thessaloniki, Greece. High-resolution climate simulations, using the WRF model, were conducted for three 5-year periods (2006–2010, 2046–2050, 2096–2100) under the RCP8.5 emission scenario, covering Thessaloniki with a 2 km grid. By the end of the century, Thessaloniki is projected to experience over 60 annual heat wave days, compared to ~8 in the present climate, while some episodes were found to persist beyond 30 days. The relative risk during heat wave days is expected to rise, which is primarily due to nighttime heat stress. Interestingly, the results indicate that minimum apparent temperature might be a more reliable indicator in predicting heat-related mortality compared to maximum apparent temperature. These findings emphasize the growing importance of informed heat mitigation and adaptation strategies and healthcare preparedness in urban areas facing escalating heat-related health challenges. [ABSTRACT FROM AUTHOR]

While the ubiquity and importance of narratives for human adaptation is widely recognized, there is no integrative framework for understanding the roles of narrative in human adaptation. Research has identified several cognitive and social functions of narratives that are conducive to well-being and adaptation as well as to coordinated social practices and enculturation. In this paper, we characterize the cognitive and social functions of narratives in terms of active inference, to support the claim that one of the main adaptive functions of narrative is to generate more useful (i.e., accurate, parsimonious) predictions for the individual, as well as to coordinate group action (over multiple timescales) through shared predictions about collective behavior. Active inference is a theory that depicts the fundamental tendency of living organisms to adapt by proactively inferring the causes of their sensations (including their own actions). We review narrative research on identity, event segmentation, episodic memory, future projections, storytelling practices, enculturation, and master narratives. We show how this research dovetails with the active inference framework and propose an account of the cognitive and social functions of narrative that emphasizes that narratives are for the future—even when they are focused on recollecting or recounting the past. Understanding narratives as cognitive and cultural tools for mutual prediction in social contexts can guide research on narrative in adaptive behavior and psychopathology, based on a parsimonious mechanistic model of some of the basic adaptive functions of narrative.

The Mediterranean Sea is a climate change hotspot since it provides a magnified warming signal. Heavily populated areas (e.g., Spanish Mediterranean coasts) are vulnerable to negative socio-economic impacts. This is particularly important for climate-related economic sectors such as coastal tourism, the focus of this paper. To promote a sustainable development of these activities and provide key information to stakeholders, it is necessary to anticipate changes in climate. Thus, it is fundamental to use climate modelling tools which account for air-sea interactions, which largely determine the climate signal of the Mediterranean coasts. In this paper, a set of regional air-sea coupled climate model simulations from Med-CORDEX are used to (i) study the climatic conditions on the Spanish Mediterranean coasts in the next decade(s) and (ii) to assess the possibility of extending the coastal tourist season towards spring-fall. We show that climate conditions are getting warmer and drier in the area, especially in summer. Heat waves and heavy precipitation will become more frequent. Thermal discomfort will increase in summer and summer conditions are extending towards spring and fall. Our work remarks the urgent need of adaptation measures of the sector, including the extension of the high tourist season to spring-fall, especially in the long term. We make a special effort to compile a set of adaptation measures for stakeholders. This study is part of the project ECOAZUL-MED, which aims to create a climate service tool to optimize the management of relevant sectors of the blue economy in the Spanish Mediterranean coasts.

Water resources in Morocco have been severely influenced by climate change and prolonged drought, particularly in the pre-Saharan zone. The Ziz watershed faces increasing pressure due to the high demographic growth, increased demand for water, excessive groundwater consumption, and investment in agriculture. But how long will water resources withstand these problems? This study, therefore, enters into the context of the assessment of water resources and estimates their vulnerability using the Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), and Standardized Groundwater Index (SGI), on data from the Ziz watershed from 1986 to 2016. Additionally, climate projections were utilized to simulate the future SGI from 2017 to 2100. The Water Evaluation and Planning System (WEAP) was employed to evaluate changes in Land Use and Land Cover (LULC) during the period of 1992–2020, and to generate future scenarios for land class inflows and outflows from 2017 to 2100, in comparison to the reference period of 1986–2016, thereby incorporating the SSP climate scenarios. The results indicate that the Ziz Basin experienced significant drought events in 1986–1989 and 2000–2003. The SPI and SPEI significantly correlated with SGI in some monitoring wells and with specific accumulation periods. The LULC analysis showed an increase in agricultural land and urban land and a decrease in barren or sparse land. Climate data analysis and scenarios predict that under SSP5-8.5, minimum and maximum temperatures will increase by 2.61 °C and 2.93 °C, respectively, and precipitation will decrease by 30% over this century. This substantial shift in climate conditions is reflected in the decline in SGIs, especially in the long term under SSP5-8.5. Water availability will decrease during this century under SSP3-7.0 and SSP5-8.5, as reflected in reduced land class inflows and increased outflows. These findings emphasize the need for stakeholders to implement integrated water governance for sustainability in the Ziz watershed. [ABSTRACT FROM AUTHOR]

The observed Eurasian winter surface cooling from the 1990s to the early 2010s, which is contrary to global warming, has been extensively studied. Previous studies revealed that the surface cooling trend has significantly weakened in the past decade. Based on large‐ensemble simulations, this study reveals that the weakening of Eurasian surface cooling is primarily driven by the atmospheric internal variability, which coincides with the weakening of Arctic mid‐tropospheric warming and Eurasian mid‐tropospheric cooling. Negative Arctic Oscillation (−AO) and Ural blocking (UB) in combination dominate the intensity of Arctic mid‐tropospheric warming and Eurasian mid‐tropospheric cooling. In the future, there is a possibility that the severe Eurasian cooling trend with comparable magnitude to that during 1990–2013 may reemerge accompanied with Arctic mid‐tropospheric warming, in response to the decadal strengthening of −AO and UB. This may occur before the 2050s, when the atmospheric internal variability is able to overwhelm the effects of greenhouse gases. Plain Language Summary: The significant Eurasian surface cooling trend observed in winters from the 1990s to the early 2010s has significantly weakened in the past decade. It coincides with the weakened trends of Arctic mid‐tropospheric warming and Eurasian mid‐tropospheric cooling. In a warming world, we suggest that the weakening of Arctic mid‐tropospheric warming and Eurasian mid‐tropospheric and surface cooling are primarily caused by the atmospheric internal variability. The weakened trends of negative Arctic Oscillation (−AO) and Ural blocking (UB) in recent years contribute to the weakened trends of Arctic mid‐tropospheric warming and Eurasian cooling. There is a possibility that the atmospheric internal variability may overwhelm the effects of increasing greenhouse gases (GHG) sometime before the 2050s, though the increasing GHG dominate the long‐term increase of air temperature. Then, the strong negative trend of AO and intensified UB may lead to the reemergence of the severe Eurasian cooling trend before the 2050s. Key Points: The significant Arctic mid‐tropospheric warming and Eurasian cooling observed in winters before the 2010s has weakened in the past decadeThe combined effects of Arctic Oscillation and Ural blocking dominate the intensity of Arctic mid‐tropospheric warming and Eurasian coolingStrong Eurasian cooling may reemerge before the 2050s if the atmospheric internal variability overwhelms the effects of greenhouse gases [ABSTRACT FROM AUTHOR]

Predicting current and future wildfire frequency and size is central to wildfire control and management. Multiple fire danger indices (FDIs) that incorporate weather and fuel conditions have been developed and utilized to support wildfire predictions and risk assessment. However, the scale‐dependent performance of individual FDIs remains poorly understood, which leads to large uncertainty in the estimated fire sizes under climate change. Here, we calculate four commonly used FDIs over the conterminous United States using high‐resolution (4 km) climate and fuel data sets for the 1984–2019 period. The relationships of these four FDIs to the observed wildfire sizes show that higher values of FDIs correlate to larger total fire sizes; this correlation is more robust at larger spatial scales. Sensitivity analysis indicates that the daily minimum relative humidity and precipitation are the most important drivers of the annual mean fire danger. In the instances of extreme fire danger, wind speed becomes a critical factor and should be considered in the calculation of the FDI. To assess the impact of climate change on future fire size, we calculate the present‐day and end‐of‐century FDIs using the 12 km regional climate model simulations. The four FDIs generally predict consistent changes in future fire potential, suggesting an overall higher fire potential in conjunction with a prolonged wildfire season in future climate. Regionally, the four FDIs also reveal similar seasonal patterns as the enhancement arises mostly in spring and summer over the southwest US while in summer and fall over the northern and eastern US. Plain Language Summary: Fire danger index (FDI), a measure used to assess the risk and severity, relies on a combination of weather and fuel conditions. Multiple FDIs have been frequently used to predict and manage the risk of wildfire. However, it is unclear how well these indices work at different scales, causing uncertainty in predicting the likelihood of fire ignition and the potential size of a fire. Here, we analyzed four commonly used FDIs and conducted sensitivity analysis (SA) to determine their most important drivers. SA results indicate that daily minimum relative humidity, precipitation, and wind speed as the most important drivers. In addition, FDIs highly correlate with total fire size at annual and conterminous United States (CONUS) scale and such correlation decreases at finer spatial and temporal scales. We also used a regional climate model simulation to derive FDIs for current and future climate conditions. Our results suggest an overall increase in fire potential and a prolonged wildfire season in the future climate. Moreover, the enhanced fire frequency is projected to occur in spring and summer over the southwest US whereas in summer and fall over the northern and eastern CONUS. Key Points: The correlation between fire danger indices (FDIs) and observed wildfire size are scale dependentSensitivity analysis indicates that the daily minimum relative humidity and wind speed are the most important drivers of fire dangerCoupling FDIs with regional climate model simulation show higher fire potential in US in future climate [ABSTRACT FROM AUTHOR]

Coupled glacio-hydrological models have recently become a valuable method for predicting the hydrological response of catchments in mountainous regions under a changing climate. While hydrological models focus mostly on processes of the non-glacierized part of the catchment with a relatively simple glacier representation, the latest generation of standalone (global) glacier models tend to describe glacier processes more accurately by using new global datasets and explicitly modeling ice-flow dynamics. Yet, to the authors' knowledge, existing catchment-scale coupled glacio-hydrological models either do not include these most recent advances in glacier modeling or are simply not available to other users. By making use of the capabilities of the free, distributed, physically-based Water Flow and Balance Simulation Model (WaSiM) and the Open Global Glacier Model (OGGM), a coupling scheme is developed to bridge the gap between global glacier representation and local catchment hydrology. The WaSiM-OGGM coupling scheme is used to further assess the impacts under future climates on the glaciological and hydrological processes in the Gepatschalm catchment (Austria), by considering a combination of three climate projections under the Representative Concentration Pathways (RCP) 2.6, 4.5, and 8.5. Additionally, the results are compared to the original WaSiM model with the integrated Volume-Area (VA) scaling approach for modeling glaciers. Although both models (WaSiM with VA scaling and WaSiM-OGGM coupling scheme) perform very similar during the historical simulations (1971–2010), large discrepancies arise when looking into the future (2011–2100). In terms of runoff, the VA scaling model suggests a reduction of the mean monthly peak between 10–19%, whereas a reduction of 26–41% is computed by the coupling scheme. Similarly, results suggest that glaciers will continuously retreat until 2100. By the end of the century, between 20–43% of the 2010 glacier area will remain according to the VA scaling model, but only 1–23% is expected to remain with the coupling scheme. The results from the WaSiM-OGGM coupling scheme raises awareness of including more sophisticated glacier evolution models when performing hydrological simulations at the catchment scale in the future. As the WaSiM-OGGM coupling scheme is released as open-source software, it is accessible to any interested modeler with limited or even no glacier knowledge.

Abstract Predicting current and future wildfire frequency and size is central to wildfire control and management. Multiple fire danger indices (FDIs) that incorporate weather and fuel conditions have been developed and utilized to support wildfire predictions and risk assessment. However, the scale‐dependent performance of individual FDIs remains poorly understood, which leads to large uncertainty in the estimated fire sizes under climate change. Here, we calculate four commonly used FDIs over the conterminous United States using high‐resolution (4 km) climate and fuel data sets for the 1984–2019 period. The relationships of these four FDIs to the observed wildfire sizes show that higher values of FDIs correlate to larger total fire sizes; this correlation is more robust at larger spatial scales. Sensitivity analysis indicates that the daily minimum relative humidity and precipitation are the most important drivers of the annual mean fire danger. In the instances of extreme fire danger, wind speed becomes a critical factor and should be considered in the calculation of the FDI. To assess the impact of climate change on future fire size, we calculate the present‐day and end‐of‐century FDIs using the 12 km regional climate model simulations. The four FDIs generally predict consistent changes in future fire potential, suggesting an overall higher fire potential in conjunction with a prolonged wildfire season in future climate. Regionally, the four FDIs also reveal similar seasonal patterns as the enhancement arises mostly in spring and summer over the southwest US while in summer and fall over the northern and eastern US.

Wetlands serve a critical function in water storage and ecological diversity maintenance. However, human activities have resulted in wetland loss in the middle and lower reaches of the Yangtze River Basin (MLYRB), while the wetland distribution in this area shows great discrepancy in previous estimates. It is, therefore, imperative to estimate the distribution of potential wetlands at present and project their variation under future climate change scenarios. In this study, we simulate the wetland distribution in the MLYRB at 15″ resolution using 5 machine learning methods with 19 predicting factors of topographic index, vegetation index, climate data, hydrological data, and soil type data. A 5-fold cross-validation with observed permanent wetlands shows that the reconstructions from Adaptive Boosting tree (AdaBoost) algorithm have the highest accuracy of 97.5%. The potential wetland area in the MLYRB is approximately ~1.25 × 105 km2, accounting for 15.66% of the study region. Direct human activities have led to the loss of nearly half of the potential wetlands. Furthermore, sensitivity experiments with the well-trained models are performed to quantify the response of the total wetland area to each influencing factor. Results indicate vulnerability of wetland areas to increases in leaf area index (LAI), coldest season temperature, warmest season temperature, and solar radiation. By the 2100s, the potential wetland area is expected to decrease by 40.5% and 50.6% under the intermediate and very high emissions scenarios, respectively. The changes in LAI and the coldest season temperature will contribute to 50% and 40% of this loss of potential wetlands, respectively. Wetland loss may further undermine biodiversity, such as waterfowl, and fail to provide functions such as flood protection, and water supply. This work reveals the spatial pattern of potential wetland areas and their sensitivity to climate changes, stressing the need for effective strategies to mitigate wetland loss at specific regions in the MLYRB. [ABSTRACT FROM AUTHOR]

This paper presents the latest analyses and integrates results of many past studies on the spatial and temporal variations of the annual frequency and intensity of tropical cyclones (TCs) making landfall along different areas of the East Asian (EA) coast. Future projections of such variations based on the past investigations are also presented. No statistically significant trend in the number of landfalling TCs could be identified in most of the EA coastal regions, except for an increasing one in Vietnam and a decreasing one in South China. Multi-decadal as well as interannual variations in the frequency of landfalling TCs are prevalent in almost all the EA coastal regions. Only TCs making landfall in Vietnam and the Korean Peninsula showed an increase in landfall intensity, with no trend in the other regions. Nevertheless, more intense landfalling TCs were evident in most regions during the past two decades. Multidecadal variations were not observed in some regions although interannual variations remained large. Various oscillations in the atmospheric circulation and the ocean conditions can largely explain the observed changes in the frequency and intensity of landfalling TCs in different regions of the EA coast. In the future, most climate models project a decrease in the number of TCs making landfall but an increase in the intensity of these TCs in all the EA coastal regions, especially for the most intense ones.

This study utilizes China’s records of non-accidental mortality along with twenty-five simulations from the NASA Earth Exchange Global Daily Downscaled Projections to evaluate forthcoming heat stress and heat-related mortality across China across four distinct scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). The findings demonstrate a projected escalation in the heat stress index (HSI) throughout China from 2031 to 2100. The most substantial increments compared to the baseline (1995–2014) are observed under SSP5-8.5, indicating a rise of 7.96°C by the year 2100, while under SSP1-2.6, the increase is relatively modest at 1.54°C. Disparities in HSI growth are evident among different subregions, with South China encountering the most significant elevation, whereas Northwest China exhibits the lowest increment. Projected future temperatures align closely with HSI patterns, while relative humidity is anticipated to decrease across the majority of areas. The study’s projections indicate that China’s heat-related mortality is poised to surpass present levels over the forthcoming decades, spanning a range from 215% to 380% from 2031 to 2100. Notably, higher emission scenarios correspond to heightened heat-related mortality. Additionally, the investigation delves into the respective contributions of humidity and temperature to shifts in heat-related mortality. At present, humidity exerts a greater impact on fluctuations in heat-related mortality within China and its subregions. However, with the projected increase in emissions and global warming, temperature is expected to assume a dominant role in shaping these outcomes. In summary, this study underscores the anticipated escalation of heat stress and heat-related mortality across China in the future. It highlights the imperative of emission reduction as a means to mitigate these risks and underscores the variances in susceptibility to heat stress across different regions.

Marine heatwaves (MHWs) are prevalent in the South China Sea (SCS) and are primarily caused by the anomalous western Pacific subtropical high (WPSH) which suppresses the SCS summer monsoon. Our study investigates future summer MHWs in the SCS in response to the enhanced WPSH. The results show that the WPSH will be strengthened in most models under the highest emission scenario. Total days of summer SCS MHWs will significantly increase with the enhancement of the WPSH and peak at the end of the 21st century. The high‐value area of total days of summer MHWs (>50 days) appears in the south‐central SCS. The intensity of MHWs exhibits little response to the strengthening WPSH. In addition, the weakening of the SCS cold filament due to the anomalous WPSH also favors summer MHWs. Furthermore, increased future severe summer SCS MHWs will create a higher bleaching risk for coral reefs. Plain Language Summary: Marine heatwaves (MHWs) can have devastating impacts on marine ecosystems when seawater temperatures are warmer than the 90th percentile for at least five consecutive days based on a fixed 30‐year (or longer) baseline. The western Pacific subtropical high (WPSH) is an anticyclonic system in the northwestern Pacific that affects MHWs in the South China Sea (SCS). Based on the latest climate models, we calculate the total days and intensity of summer MHWs in the SCS under increased variability in the WPSH in future projections. Total days of summer MHWs will rapidly increase and peak at the end of the 21st century. Furthermore, the total days of summer MHWs are associated with SCS upwelling and cold filament, which is also influenced by strong WPSH. More concerning are the increases in severe summer MHWs, which will make coral reefs more susceptible to bleaching in the SCS in the future. Key Points: Increasing variability in the western Pacific subtropical high (WPSH) leads to more frequent, stronger WPSH events in future projectionsThe total days and intensity of summer marine heatwaves (MHWs) in the South China Sea (SCS) show different responses to the enhanced WPSHTotal days of summer MHWs in the SCS increase with the strengthened WPSH, resulting in a high coral bleaching risk [ABSTRACT FROM AUTHOR]

How future multiple tropical cyclone events (MTCEs) could change is crucial for effective risk management and ensuring human safety, however, it remains unclear. This study projects changes in MTCEs by 2050 in the major basins of the Northern Hemisphere using high‐resolution climate models. Results show a significant increase in the frequency and duration of MTCEs over the North Atlantic (NA), a notable decrease over the western North Pacific (WNP), and little change over the eastern North Pacific (ENP). The increase in MTCEs over the NA is concentrated in August–September, while the decrease over the WNP occurs in most months. In contrast, the ENP exhibits large yet insignificant seasonal variation, suggesting considerable uncertainty in this basin. Further analysis shows that mid‐level vertical motion dominates the MTCE changes over the WNP, while vertical wind shear contributes the most to the NA, which may be linked to future changes in tropical convection. Plain Language Summary: Multiple tropical cyclone (TC) events (MTCEs), that is two or more TCs simultaneously occurring in the same basin, pose great risks to human society. This study projects future changes in the MTCEs by 2050, showing a significant increase over the North Atlantic (NA) while a robust reduction over the western North Pacific (WNP). The future MTCEs over the eastern North Pacific (ENP) show little change relative to the present climate. The increase of MTCEs over the NA is concentrated in August–September, while the decrease over the WNP occurs nearly from April to November. In contrast, there is large yet insignificant seasonal variation over the ENP, which could lead to little change in annual MTCEs. Furthermore, these changes are primarily attributed to the changes in local large‐scale dynamic conditions associated with tropical convection in future decades. Key Points: The projection of future multiple tropical cyclone events (MTCEs) shows a decline in the western North Pacific (WNP) but a significant increase in the North Atlantic (NA)The mid‐level vertical motion dominates the MTCE changes over the WNP, while vertical wind shear is important for the NAFuture monthly MTCEs show large yet insignificant seasonal variation over the eastern North Pacific, causing little trend in annual MTCEs [ABSTRACT FROM AUTHOR]

In this study, we utilized three different indices to assess drought conditions in the Doñana National Park (DNP) located in southern Spain. These indices included the Standardized Precipitation Index (SPI), which is based on precipitation statistics, the Standardized Precipitation Evapotranspiration Index (SPEI), which incorporates both precipitation and air temperature data, and the Groundwater Recharge Drought Index (GRDI), a newly developed index specifically designed to evaluate groundwater drought. The analysis covered the time period from 1985 to 2015, and future projections were made for the years 2030–2060 under different climate scenarios (RCP 4.5 and RCP 8.5). Our findings revealed a significant decrease in total precipitation of approximately 13–14% compared to historical records (1985–2015). Moreover, severely to extremely wet periods exhibited a reduction ranging from 25% to 38%. A key contribution of this study is the application of the GRDI index, which allowed us to assess groundwater recharge rates. We observed a decline in the simulated mean recharge rates during the 21st century when compared to the historical period spanning from 1950 to 2009. This decline can be attributed to increased evapotranspiration. The results of this research provide valuable insights for the Spanish water resources administration. The observed reductions in precipitation and groundwater recharge rates emphasize the need for appropriate mitigation measures. The findings will aid the administration in formulating an integrated water resources management strategy in the Doñana National Park and its surrounding basin. By understanding the projected changes in drought conditions, the administration can make informed decisions to ensure sustainable water resource management in the region. [ABSTRACT FROM AUTHOR]

As we confront novel environmental challenges, a full understanding of the physical and biological processes that govern species responses to climate change will help maintain biodiversity and support conservation measures that are more robust to irreducible uncertainty. However, climate impacts are so complex, and the literature on salmon and trout is so vast that researchers and decision makers scramble to make sense of it all. Therefore, we conducted a systematic literature review of climate impacts on salmon and anadromous trout as a resource for stakeholders, managers, and researchers. We reviewed studies published from 2010 to 2021 that address climate impacts on these fish and organized them in a database of 1169 physical and 1853 biological papers. Papers are labeled with keywords across eight categories related to subject matter and study methods. We compared the literature by biological process and life stage and used these comparisons to assess strengths and weaknesses. We then summarized expected phenotypic and genetic responses and management actions by life stage. Overall, we found the largest research gaps related to species interactions, behavioral responses, and effects that carry over across life stages. With this collection of the literature, we can better apply scarce conservation resources, fill knowledge gaps, and make informed decisions that do not ignore uncertainty. [ABSTRACT FROM AUTHOR]

This paper presents the latest analyses and integrates results of many past studies on the spatial and temporal variations of the annual frequency and intensity of tropical cyclones (TCs) making landfall along different areas of the East Asian (EA) coast. Future projections of such variations based on the past investigations are also presented. No statistically significant trend in the number of landfalling TCs could be identified in most of the EA coastal regions, except for an increasing one in Vietnam and a decreasing one in South China. Multi-decadal as well as interannual variations in the frequency of landfalling TCs are prevalent in almost all the EA coastal regions. Only TCs making landfall in Vietnam and the Korean Peninsula showed an increase in landfall intensity, with no trend in the other regions. Nevertheless, more intense landfalling TCs were evident in most regions during the past two decades. Multidecadal variations were not observed in some regions although interannual variations remained large. Various oscillations in the atmospheric circulation and the ocean conditions can largely explain the observed changes in the frequency and intensity of landfalling TCs in different regions of the EA coast. In the future, most climate models project a decrease in the number of TCs making landfall but an increase in the intensity of these TCs in all the EA coastal regions, especially for the most intense ones. [ABSTRACT FROM AUTHOR]

Plant growth is restricted to times of the year when actual evapotranspiration (AET) is greater than zero because AET requires both the presence of water in the soil and temperatures warm enough to allow transpiration. Locations where water rather than temperature limits plant growth, such as semi‐arid areas of the southwestern United States, often have a bimodal growing season, such that distinct AET (growth) peaks occur in the spring and late summer, with a period of very limited plant growth occurring during the intervening summer months. We hypothesized that future warming will increase the zone containing bimodal growth seasons, likely resulting in significant changes in the competitive relationships between plant species that differ in their tolerance of a bimodal seasonality. This will likely alter plant distributions. Using climate projections to drive a water balance model, we mapped geographic regions within the continental United States projected to experience bimodal growing seasons in the future. The area containing bimodal seasonality increased under all 13 general circulation models (GCMs) and two representative concentration pathways (RCPs) examined. This robust result (seen in all alternative futures examined) nevertheless showed considerable variability depending on the GCM examined. The bimodal zone was projected to increase 13%–212% (49,000–792,000 km2) by the late 21st century relative to 1981–2010 estimates. Climate futures that contained the greatest temperature increases and greatest precipitation decreases projected the greatest expansion in the bimodal zone. For plant species that depend on relatively long, consistent time periods that are favorable to growth each year, the projected shift in seasonality may be an acute disturbance that could cause widespread mortality. These changes will likely have cascading ecological and management implications, including changes in the dominant plant life history strategies that occur in affected areas. [ABSTRACT FROM AUTHOR]

Abstract Permafrost covers a wide area of the Northern Hemisphere, including high-altitude mountainous areas and even at mid-latitudes. There is concern that the thawing of mountain permafrost can cause slope instability and substantially impact alpine ecosystems, and because permafrost in mountainous areas is difficult to observe, detailed analyses have not been performed on its current distribution and future changes. Although previous studies have observed permafrost only at a limited number of points in Japan (e.g., Daisetsu Mountains, Mt. Fuji, and Mt. Tateyama in the Northern Japan Alps), we show that permafrost potentially exists in nine domains in Japan (Daisetsu Mountains, Mt. Fuji, Northern and Southern Japan Alps, Hidaka Mountains, Mt. Shiretokodake, Sharidake, Akandake, and Yotei). In the Daisetsu Mountains and Mt. Fuji, the environmental conditions required for maintaining at least some permafrost are projected to remain in the future if a decarbonized society is achieved (RCP2.6 or RCP4.5). However, if greenhouse gas emissions continue to increase (RCP8.5), the environmental conditions required for sustaining permafrost are projected to disappear in the second half of the twenty-first century. In other domains, the environmental conditions required for maintaining permafrost are either projected to disappear in the next ten years (Hidaka Mountains, Northern Japan Alps) or they have almost disappeared already (Southern Japan Alps, Mt. Shiretokodake, Sharidake, Akandake, and Yotei). Our projections show that climate change has a tremendous impact on Japan's mountain permafrost environment and suggests the importance of monitoring the mountain environment and considering measures for adapting to future climate change.

The TRANSLATE project was established in 2021 by Met Éireann, the Irish national meteorological service, to provide standardized future climate projections for Ireland. This paper outlines the principles and main methods that were used to generate the first set of such projections and presents selected results to the end of the 21st century. Two separate ensembles of dynamically downscaled CMIP5 projections were analyzed. These produce very consistent results, increasing confidence in both, and in the methods used. Future projected fields show plenty of detail (depending on local geography), but the change maps relative to the base period are much smoother, reflecting the global climate change signal. Future forcing uncertainty is represented by 3 different emission scenarios, while model response uncertainty is represented by sub-ensembles corresponding to different climate sensitivities. The resulting matrix of distinct climate ensembles is complemented by ensembles of temperature threshold-based projections, drawn from the same underlying simulations.

Cities are increasingly vulnerable to climate change's impacts and poorly adapted to extreme variability. This study aimed to evaluate climate projections of air temperature and precipitation in seven cities in the Metropolitan Region of São Paulo that correspond to the Greater ABC Paulista. We used high-resolution models Eta-HADGEM2_ES (CMIP5), CNRM-CM6-1-HR (CMIP6), and the TerraClimate database to analyze future projections and the specific warming levels (SWLs), respectively. Model data were validated with observed data and bias was removed. A bias correction factor was generated and used in the climate projections for the different emission scenarios. The results show a consensus between the models and the SWLs (2 and 4°C) for the increase in maximum (Tmax) and minimum (Tmin) temperatures for all municipalities in ABC Paulista in different emission scenarios until the end of the 21st century. For the nearest future (2020–2040), the city of São Caetano do Sul (SCS) shows the highest positive annual anomalies of Tmax concerning the climatological period (1985–2015), for the scenario RCP4.5 (2.8°C) and the RCP8.5 (7.4°C), according to projections from the Eta-HADGEM2_ES, highlighting summer and autumn as the hottest. For precipitation, there was a consensus between the Eta-HADGEM2_ES and the CNRM-CM6-1-HR for a reduction in all scenarios and time-slices 2020–2040 and 2041–2070. The municipalities of Diadema (−78.4%) and SCS (−78%) showed the most significant reductions in December for the RCP8.5, and for SSP5-8.5, SCS shows −30.9% in December for the 2020–2040 time-slice. On the other hand, TerraClimate presents excess rain for Ribeirão Pires (+24.8%) and Santo André (+23.7%) in winter for SWL4°C. These results suggest that an increase in Tmax and Tmin, as projected, should influence the intensity of extreme heat events. Furthermore, a reduction in annual and seasonal rainfall does not mean a decrease in the region's extreme daily events that cause floods and landslides. However, it leaves an alert of water scarcity for the supply and demand of the population. ABC Paulista does not have adaptation plans to face extreme climate change. The results can contribute to the first phase of creating an adaptation plan, giving a first view of the climate threat that should intensify until the end of the twentieth century affecting the most vulnerable municipalities.

Abstract Plant growth is restricted to times of the year when actual evapotranspiration (AET) is greater than zero because AET requires both the presence of water in the soil and temperatures warm enough to allow transpiration. Locations where water rather than temperature limits plant growth, such as semi‐arid areas of the southwestern United States, often have a bimodal growing season, such that distinct AET (growth) peaks occur in the spring and late summer, with a period of very limited plant growth occurring during the intervening summer months. We hypothesized that future warming will increase the zone containing bimodal growth seasons, likely resulting in significant changes in the competitive relationships between plant species that differ in their tolerance of a bimodal seasonality. This will likely alter plant distributions. Using climate projections to drive a water balance model, we mapped geographic regions within the continental United States projected to experience bimodal growing seasons in the future. The area containing bimodal seasonality increased under all 13 general circulation models (GCMs) and two representative concentration pathways (RCPs) examined. This robust result (seen in all alternative futures examined) nevertheless showed considerable variability depending on the GCM examined. The bimodal zone was projected to increase 13%–212% (49,000–792,000 km2) by the late 21st century relative to 1981–2010 estimates. Climate futures that contained the greatest temperature increases and greatest precipitation decreases projected the greatest expansion in the bimodal zone. For plant species that depend on relatively long, consistent time periods that are favorable to growth each year, the projected shift in seasonality may be an acute disturbance that could cause widespread mortality. These changes will likely have cascading ecological and management implications, including changes in the dominant plant life history strategies that occur in affected areas.

Although terrestrial biosphere models (TBMs) with and without nitrogen cycling successfully reproduce the historical terrestrial carbon sink, the influence of nitrogen cycling under interacting and intensifying global change drivers in the future is unclear. Here, we compare TBM projections with and without nitrogen cycling over alternative future scenarios (the Shared Socioeconomic Pathways) to examine how representing nitrogen cycling influences CO2 fertilization as well as the effects of a comprehensive group of physical and socioeconomic global change drivers. Because elevated nitrogen deposition and nitrogen fertilization have stimulated terrestrial carbon sequestration over the historical period, a model without nitrogen cycling must exaggerate the strength of CO2 fertilization to compensate for these unrepresented nitrogen processes and to reproduce the historical terrestrial carbon sink. As a result, it cannot realistically project the future terrestrial carbon sink, overestimating CO2 fertilization as the trajectories of CO2, nitrogen deposition and nitrogen fertilization diverge in future scenarios. Plain Language Summary: Terrestrial biosphere models simulate the terrestrial carbon sink (in plant and soil biomass), which takes up a third of anthropogenic CO2 emissions. However, the influence of nitrogen cycling and nitrogen limitation of plant growth in the Shared Socioeconomic Pathways (SSPs) (recently adopted alternative scenarios for the 21st century) is unclear. Here, we compare a model with and without nitrogen cycling in comprehensive simulations of the SSPs. We find that a model without nitrogen must exaggerate the influence of elevated CO2 on plant growth to compensate for unrepresented nitrogen cycling processes in order to correctly simulate the historical terrestrial carbon sink. Specifically, it does not represent how elevated atmospheric nitrogen input (due to intensive agriculture and fossil fuel burning) and elevated nitrogen fertilization have increased plant growth over the historical period. As a result, models without nitrogen cannot realistically project the future terrestrial carbon sink because they are calibrated to reproduce the historical terrestrial carbon sink but the trajectories of CO2, atmospheric nitrogen input, and nitrogen fertilization diverge from their historical trajectories in future scenarios. This leads to an overestimation of the future terrestrial carbon sink by models without nitrogen with implications for climate change projections and policy. Key Points: Terrestrial biosphere models without N do not represent N deposition or N fertilization, which have stimulated terrestrial C sequestrationExaggerated CO2 fertilization compensates for N deposition and N fertilization in order to reproduce the historical terrestrial C sinkModels without N cannot project the future terrestrial C sink as trajectories of CO2, N deposition, and N fertilization diverge [ABSTRACT FROM AUTHOR]

As cities are increasing technological efficacy on greenhouse gas (GH) emission reduction efforts, the surrounding urban ecosystems and natural resources may be affected by these measures. In this research, climate indicators such as heat index, extreme heat events, intensified urban heat islands (UHIs), and sea breeze are projected for the middle and end of the 21st century to understand the climate change signal on these variables with and without building energy mitigation measures. Cities amplify extreme heat and UHI impacts by concentrating large populations and critical infrastructure in relatively small areas. Here, we evaluate the combined climate and building energy mitigation impacts on localized climate metrics throughout the 21st century across extreme emission scenarios (RCP8.5) for the tropical coastal city of San Juan. The analysis of statistically downscaled global circulation model outputs shows underestimation for uncorrected summer daily maximum temperatures, leading to lower extreme heat intensity and duration projections from the present time which are corrected using bias-corrected techniques. High-resolution dynamic downscaling simulations reveal a strong dependency of changes in extreme heat events in urban settings, however, the intensities shift to lower-level grasslands and croplands with energy mitigation measures (combination of white roof, tilted photovoltaic roof, and efficient heating ventilation and air conditioning systems). The building energy mitigation measures have the potential of reducing the UHI intensities to 1 °C and 0.5 °C for the 2050 and 2100 climate periods, respectively. [ABSTRACT FROM AUTHOR]

Oceanic absorption of atmospheric carbon dioxide (CO2) is expected to slow down under increasing anthropogenic emissions; however, the driving mechanisms and rates of change remain uncertain, limiting our ability to project long‐term changes in climate. Using an Earth system simulation, we show that the uptake of anthropogenic carbon will slow in the next three centuries via reductions in surface alkalinity. Warming and associated changes in precipitation and evaporation intensify density stratification of the upper ocean, inhibiting the transport of alkaline water from the deep. The effect of these changes is amplified threefold by reduced carbonate buffering, making alkalinity a dominant control on CO2 uptake on multi‐century timescales. Our simulation reveals a previously unknown alkalinity‐climate feedback loop, amplifying multi‐century warming under high emission trajectories. Plain Language Summary: Over the past century, humans have been burning fossil fuels and adding extra carbon dioxide to the atmosphere. The ocean has been doing us a big favor by absorbing some of this carbon dioxide, lowering the amount of global warming that occurs. Our study shows that the ocean will begin to lose its ability to absorb carbon dioxide beyond the year 2100, leaving more fossil‐derived carbon in the atmosphere and leading to additional global warming. Our study describes a previously undiscovered mechanism for the slowdown in ocean carbon absorption, where changes in rainfall and warming affect ocean currents that, in turn, change the chemistry of the ocean surface. Key Points: Oceanic uptake of carbon could slow in upcoming centuries through previously unidentified alkalinity‐climate feedbackReduced upwelling and carbonate buffer enhance the influence of alkalinity on the increase in surface ocean carbon dioxideReductions in surface alkalinity will reduce the rate of carbon uptake on multi‐century timescales [ABSTRACT FROM AUTHOR]

Sea level rise will significantly impact coastal areas around the world. As a coastal country, Malaysia's rising sea levels are a significant concern because they would affect 70% of its population. The study of sea level rise is important in order to implement effective mitigation and adaptation strategies. This study investigates the performance of CMIP6 Global Climate Models (GCMs) in simulating sea level rise in the Malaysian seas using various statistical methods. The models' performances were evaluated by comparing historic CMIP6 GCM runs from 1993 to 2010 with sea level measurements from the satellite altimetry AVISO+ using the Taylor diagram. The SCS (SCSPM and SCSEM) had a higher sea level range and trend in both selected areas than the SM and SS. With 1.5 °C warmings, the multi-model ensemble means predicted that the SCS would rise by 16 mm near the Peninsular, with sea levels increasing by 0.908 m at a rate of 1.5 mm/year, and by 14.5 mm near East Malaysia, with sea levels increasing by 0.895 m at a rate of 1.1 mm/year. In contrast, 2.0 °C warmings project that SCSPM and SCSEM would cause sea levels to rise by 20.2 mm and 21.5 mm, respectively, at a rate of 0.6 mm/year and 0.7 mm/year. This information will provide an insight into Malaysian sea levels between now and the end of the twenty-first century, which will be beneficial for government agencies, academics, and relevant stakeholders. [ABSTRACT FROM AUTHOR]

In this study, we investigated the spatio-temporal distribution and performance of seasonal precipitation in all districts of Haryana, India. We analysed the gridded precipitation dataset of the India Meteorological Department (IMD) for a period of 120 years (1901–2020) using different statistical methods. We found that Haryana received a mean precipitation of 37.0, 37.7, 468.3, and 24.8 mm during the winter, pre-monsoon, monsoon, and post-monsoon seasons, respectively. During each season, the eastern districts of Haryana received more precipitation than its western counterparts. Sen's slope results obtained after trend-free pre-whitening (TFPW) showed a statistically significant increasing trend of 0.12 mm (p-value; 0.04) during the pre-monsoon period, whereas decreasing but non-significant trends were observed during the winter, monsoon and post-monsoon seasons at the rate of −0.04 mm (p-value; 0.49), −0.26 mm (p-value; 0.52), −0.05 mm (p-value; 0.33) per year, respectively, for the entire Haryana state. The winter precipitation is expected to increase under the Representative Concentration Pathway 4.5 (RCP4.5) scenario, whereas pre-monsoon precipitation is expected to decrease under the RCP8.5 scenario by the end of the 21st century. The monsoon precipitation is expected to decrease under all RCP scenarios, whereas post-monsoon precipitation is expected to gradually increase under the RCP8.5 scenario by the end of the 21st century. HIGHLIGHTS Spatio-temporal distribution, variability, trends, categorization analysis of precipitation for different seasons.; Most stable and variable precipitation was observed during monsoon and post-monsoon season respectively.; Declining trend in precipitation observed during winter, post-monsoon and summer monsoon season while increasing trend was observed during pre-monsoon season.; Future precipitation projections shows increasing/decreasing trend in different seasons under RCP2.6, RCP4.5 and RCP8.5 scenario by the end of 21st century.;

The literature linking climatic drivers and migration is growing, but there is still limited evidence and substantial uncertainty regarding future bilateral flows driven by climate stress on a global scale. The aim of this paper is to fill this gap by projecting changes in the flows of international migrants from medium-term population and climate change projections. We employ a bilateral gravity equation for emigration rates controlling for decadal weather averages of temperature, precipitation, droughts, and extreme precipitation in the origin countries. We use the parameter estimates of the gravity equation to estimate global, regional, and country-by-country emigration flows for several combinations of socio-economic development and climate change. Results indicate that global emigration flows are projected to increase to around 110 million in 2060 for SSP1 and RCP 4.5 and SSP5 and RCP 4.5; to 135 million for SSP5 and RCP 8.5; to 163 million for SSP3 and RCP 4.5. We report that changes in emigration flows are largely due to population growth in the origin countries.

The loss of Arctic sea ice (ASI) represents a major transformation in the Arctic region, impacting regional and global climate, ecosystems, and socio-economic structures. Observational and reanalysis data have consistently shown a notable shift in polar environmental conditions over recent decades, marked by a substantial reduction in the ASI area and a rise in the variability in its coverage and distribution. Utilizing data from the latest Coupled Model Intercomparison Project phase, our study reveals a consistent pattern highlighting a fundamental shift in ASI dynamics preceding total loss. We observe increasing fluctuations in the September ASI area as the threshold for an ice-free Arctic is approached across various scenarios and models. This pattern is particularly concentrated in the Central Arctic (CA) sub-region. Spatial analyses reveal increasing variance along the CA’s northern coastlines, accompanied by a substantial increase in open water coverage, underscoring the shift from stable to highly variable ice conditions in this region. Additionally, our findings suggest a potential link between increased ASI fluctuations and variability in surface wind speeds. These specific results underscore the urgency of multidisciplinary approaches in addressing the challenges posed by ASI variability, with implications for marine ecosystems, Indigenous communities, and navigational safety.

The Arctic sea ice (ASI) is expected to decrease with further global warming. However, considerable uncertainty remains regarding the temperature range that would lead to a completely ice-free Arctic. Here, we combine satellite data and a large suite of models from the latest phase of the Coupled Model Intercomparison Project (CMIP6) to develop an empirical, observation-based projection of the September ASI area for increasing global mean surface temperature (GMST) values. This projection harnesses two simple linear relationships that are statistically supported by both observations and model data. First, we show that the September ASI area is linearly proportional to the area inside a specific northern hemisphere January–September mean temperature contour T _c . Second, we use observational data to show how zonally averaged temperatures have followed a positive linear trend relative to the GMST, consistent with Arctic amplification. To ensure the reliability of these observations throughout the rest of the century, we validate this trend by employing the CMIP6 ensemble. Combining these two linear relationships, we show that the September ASI area decrease will accelerate with respect to the GMST increase. Our analysis of observations and CMIP6 model data suggests a complete loss of the September ASI (area below 10 $\mathbf{^6}$ km $\mathbf{^2}$ ) for global warming between $1.5\,^\circ$ C and $2.2\,^\circ$ C above pre-industrial GMST levels.

Little is known about how climate intervention through stratospheric aerosol injection (SAI) may affect the climatology of the Southern Hemisphere extratropical cyclones under warming scenarios. To address this knowledge gap, we tracked extratropical cyclones from 2015 to 2099 in a set of projections of three international projects: the Assessing Responses and Impacts of Solar Climate Intervention on the Earth System with Stratospheric Aerosol Injection (ARISE), the Stratospheric Aerosol Geoengineering Large Ensemble (GLENS), and the Geoengineering Model Intercomparison Project (GeoMIP/G6sulfur). Comparisons were performed between no-SAI and SAI scenarios as well as between different timeslices and their reference period (2015–2024). Among the findings, both no-SAI and SAI project a decrease in cyclone frequency towards the end of the century although weaker under SAI scenarios. On the other hand, cyclones tend to be stronger under no-SAI scenarios while keeping their intensity more similar to the reference period under SAI scenarios. This means that under SAI scenarios the climatology of cyclones is less affected by global warming than under no-SAI. Other features of these systems, such as travelling distance, lifetime, and mean velocity show small differences between no-SAI and SAI scenarios and between reference and future periods.