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This paper presents the methodology for the construction of the KNMI'23 national climate scenarios for the Netherlands. We have developed six scenarios, that cover a substantial part of the uncertainty in CMIP6 projections of future climate change in the region. Different sources of uncertainty are disentangled as much as possible, partly by means of a storyline approach. Uncertainty in future emissions is covered by making scenarios conditional on different SSP scenarios (SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5). For each SSP scenario and time horizon (2050, 2100, 2150), we determine a global warming level based on the median of the constrained estimates of climate sensitivity from IPCC AR6. The remaining climate model uncertainty of the regional climate response at these warming levels is covered by two storylines, which are designed with a focus on the annual and seasonal mean precipitation response (a dry‐trending and wet‐trending variant for each SSP). This choice was motivated by the importance of future water management to society. For users with specific interests we provide means how to account for the impact of the uncertainty in climate sensitivity. Since CMIP6 GCM data do not provide the required spatial detail for impact modeling, we reconstruct the CMIP6 responses by resampling internal variability in a GCM‐RCM initial‐condition ensemble. The resulting climate scenarios form a detailed storyline of plausible future climates in the Netherlands. The data can be used for impact calculations and assessments by stakeholders, and will be used to inform policy making in different sectors of Dutch society. Plain Language Summary: To prepare society for the effects of future climate change, we need to know what the future climate will be like. In this paper we explain the method that is used to construct six different scenarios that describe possible future climates of the Netherlands. The scenarios make assumptions about future greenhouse gas emissions, and are based on the outcomes of climate models that simulate the response of the climate to these emissions. The KNMI'23 climate scenarios show that strongly reducing global emissions strongly reduces the expected changes in the climate of the Netherlands. In the scenario in which global emissions continue to rise until 2080, Dutch society will have to adapt to a much stronger increases in heat and precipitation extremes, increased risks of droughts with low river discharge in summer, and increased risk of flooding due to high river discharges in winter. In the coming years the climate scenario data will be used to evaluate what needs to be done to keep the country a safe place for people to live in and to thrive in, under changing climate conditions. Key Points: We present a methodology for the construction of regional climate scenarios using a storyline approach to partition uncertaintyResults from CMIP6 are reconstructed with a GCM‐RCM initial condition ensemble to produce high‐resolution scenario data for end‐usersSix scenario variants cover emission uncertainty (high, moderate, low) and uncertainty in the regional response (dry‐trending, wet‐trending) [ABSTRACT FROM AUTHOR]

As the Arctic and its rivers continue to warm, a better understanding of the possible future impacts on people would benefit from close partnership with Indigenous communities and scientists from diverse fields of study. We present efforts by the Arctic Rivers Project to conduct community‐engaged research to increase collective understanding of the historical and potential future impacts of climate change on rivers, fish, and Indigenous communities. Working in central to northern Alaska and the Yukon Territory in Canada, the project seeks to engage with Indigenous communities in ethical and equitable ways to produces science that is useful, useable, and used that may serve as an example for future research efforts. Toward this goal, we formed an Indigenous Advisory Council and together developed project‐specific knowledge co‐production protocols. This paper provides a novel model of design and implementation to co‐produce knowledge with communities across a large study domain. Plain Language Summary: The Arctic and rivers located in the Arctic and subarctic are warming due to climate change. To understand the impacts this warming will have on people, partnering with impacted Indigenous communities in the region is important. It is also important that these partnerships are ethical and equitable and produce science that is actionable. This paper discusses efforts undertaken by a specific project, the Arctic Rivers Project, to conduct ethical and equitable research with Indigenous communities and generate science that is useful to those communities. Through this research our goal is to better understand potential future impacts of climate change on rivers, fish, and Indigenous communities in central northern Alaska and the Yukon Territory in Canada. To achieve this goal, the project formed an Indigenous Advisory Council (IAC) and together developed guidelines for how we can work collaboratively with Indigenous communities. Our specific process of forming an IAC and guidelines is, to our knowledge, a new way to approach collaborative research when working across a large geographic area. We present our process here so that it may provide an example for other research efforts. Key Points: Arctic climate information can be made useful, useable, and used by equitably accounting for diverse community adaptation needs through knowledge co‐productionInstitutional and community capacity, including means and ability, is necessary for equitable knowledge co‐production to occurWe present an approach for co‐producing knowledge with Indigenous communities that can serve as an example for other scientific efforts [ABSTRACT FROM AUTHOR]

The cloud feedback may result in amplification or damping of Arctic warming. Two common techniques used to diagnose the top‐of‐the‐atmosphere cloud feedback are the Adjusted Cloud Radiative Effect (AdjCRE) method and the Cloud Radiative Kernel (CRK) method. We apply both to CMIP5 and CMIP6 model data, finding that the AdjCRE calculated Arctic shortwave cloud feedback is twice as correlated with sea ice loss in CMIP5, and four times in CMIP6, as the CRK method. We find that the CRK method produces Arctic all‐sky residual percentages exceeding 20% in 15 of 18 models. We use the CRK method to decompose the feedback in CMIP5 and CMIP6 finding that its median value changed from negative to positive driven by a less‐negative cloud optical depth feedback. Despite its lack of closure, we conclude that the CRK method is better suited for Arctic SW feedbacks as it is less impacted by surface albedo changes. Plain Language Summary: The cloud feedback is the process by which cloud property changes in a warming climate can either further enhance warming or damp it. The Arctic is warming faster than the rest of the globe, and one of the largest sources of uncertainty in its climate projections is the cloud feedback. There are two popular methods to calculate the cloud feedback: the Adjusted Cloud Radiative Effect technique, and the Cloud Radiative Kernel technique. In this paper we compare the two methods in a suite of climate models by considering the extent to which changes in Arctic sea ice impact the cloud feedbacks. From this analysis we conclude that the Cloud Radiative Kernel method is less affected by sea ice loss. We then apply the Cloud Radiative Kernel technique to data from the two most recent generations of global climate models to investigate how polar day Arctic cloud feedbacks have changed between these generations. We find that the median value of these Arctic feedbacks is slightly positive in the newest generation of models, a change from slightly negative in the previous generation that is largely fueled by a weakening of the feedback associated with changes in cloud optical depth. Key Points: The Cloud Radiative Kernel method is less sensitive to surface albedo changes than the Adjusted Cloud Radiative Effect techniqueThe Cloud Radiative Kernel method provides poor radiative closure in a suite of global climate modelsThe median shortwave Arctic cloud feedback in recent climate models is slightly positive due to a weakened cloud optical depth feedback [ABSTRACT FROM AUTHOR]

Anthropogenic climate change has an unprecedented impact on ecosystems and their services, with severe consequences for human well‐being, particularly for the marginalised and vulnerable members of society in the Global South. The well‐being of communities relies not only on material and regulating services ecosystems provide but also on non‐material services.In this paper, we unravel the diverse ways that climate change impacts affect Nature's Contributions to People (NCP) and the well‐being of rural populations in four sites in Madagascar—a biodiversity hotspot but one of the economically poorest countries in the world. We conducted participatory community workshops, mapping and semi‐structured interviews with local residents across social subgroups to understand the mechanisms of climate‐related degradation and the resulting impacts on different dimensions of human well‐being through an NCP lens.We found that non‐material services are generally more often associated with well‐being effects. Climate change degrades material and non‐material services through sea level rise, biodiversity loss, drought, precipitation and temperature variability, with consequences for materials, companionship and labour, food and feed, and physical and psychological experiences. Loss of land and forests is expressed through ecological grief.The outcome of our research provides evidence‐based information to local policymakers, conservation practitioners, and climate change agencies.This information can help improve government efforts toward holistic conservation and climate change adaptation by addressing the impacts on the physical and mental well‐being of the most vulnerable communities. Read the free Plain Language Summary for this article on the Journal blog. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

A reference or "no‐feedback" radiative response to warming is fundamental to understanding how much global warming will occur for a given change in greenhouse gases or solar radiation incident on the Earth. The simplest estimate of this radiative response is given by the Stefan‐Boltzmann law as −4σTe‾3≈−3.8 ${-}4\sigma {\overline{{T}_{e}}}^{3}\approx -3.8$ W m−2 K−1 for Earth's present climate, where Te‾ $\overline{{T}_{e}}$ is a global effective emission temperature. The comparable radiative response in climate models, widely called the "Planck feedback," averages −3.3 W m−2 K−1. This difference of 0.5 W m−2 K−1 is large compared to the uncertainty in the net climate feedback, yet it has not been studied carefully. We use radiative transfer models to analyze these two radiative feedbacks to warming, and find that the difference arises primarily from the lack of stratospheric warming assumed in calculations of the Planck feedback (traditionally justified by differing constraints on and time scales of stratospheric adjustment relative to surface and tropospheric warming). The Planck feedback is thus masked for wavelengths with non‐negligible stratospheric opacity, and this effect implicitly acts to amplify warming in current feedback analysis of climate change. Other differences between Planck and Stefan‐Boltzmann feedbacks arise from temperature‐dependent gas opacities, and several artifacts of nonlinear averaging across wavelengths, heights, and different locations; these effects partly cancel but as a whole slightly destabilize the Planck feedback. Our results point to an important role played by stratospheric opacity in Earth's climate sensitivity, and clarify a long‐overlooked but notable gap in our understanding of Earth's reference radiative response to warming. Plain Language Summary: Earth's climate is stable because a warmer planet loses more energy to space, at infrared wavelengths invisible to the naked eye. The rate of change of this energy loss as the planet warms provides an estimate how Earth's energy balance responds to warming, which is simple enough to write on a small piece of paper. When scientists investigate the warming predicted by climate models, they often start from a similar but not identical calculation of how Earth's energy balance responds to warming. This calculation, based on model output, is about 15% less stabilizing than the simple pencil‐and‐paper estimate. In this paper, we explore the causes of this 15% difference between the pencil‐and‐paper estimate and the calculations using climate models. We show that the difference is primarily caused by the lack of assumed warming in climate models high in Earth's atmosphere, where temperatures are not closely linked to surface warming. This lack of warming acts as a hidden destabilizing feedback in current analysis of climate models. Key Points: Earth's reference radiative response, or "Planck feedback," is ∼0.5 W m−2 K−1 less stabilizing than a Stefan‐Boltzmann estimateWe find this deviation is mostly due to the assumed lack of stratospheric warming in calculations of the Planck feedbackThe lack of stratospheric warming serves as an implicit positive feedback in analysis of climate model warming [ABSTRACT FROM AUTHOR]

This paper argues that a uniform global tax-like price on carbon emissions, whose revenues each country retains, can provide a focal point for a reciprocal common climate commitment, whereas quantity targets, which do not nearly so readily present such a single focal point, tend to rely ultimately on individual quantity commitments. The paper postulates the conceptually useful allegory of a futuristic 'World Climate Assembly' (WCA) that votes for a single worldwide price on carbon emissions via the basic democratic principle of one person, one vote majority rule. A WCA-like uniform price-tax counters self-interest by incentivizing countries or agents to internalize the externality because each WCA agent's higher abatement cost from a higher emissions price is counterbalanced by that agent's extra benefit from inducing all other WCA agents to simultaneously lower their emissions in response to the higher price. The paper derives fresh insights and new simple formulae that relate each emitter's most-preferred world price of carbon to the world 'social cost of carbon' (SCC), and further relates the WCA-voted world price of carbon to the world SCC. Some implications are discussed. The overall methodology of the paper is a mixture of mostly classical with some behavioural economics. [ABSTRACT FROM AUTHOR]

The long‐known, widely documented inverse relationship between body size and environmental temperature ("temperature‐size rule") has recently led to predictions of body size decline following current climatic warming ("size shrinking effect"). For keystone pollinators such as wild bees, body shrinking in response to warming can have significant effects on pollination processes but there is still little direct evidence of the phenomenon because adequate tests require controlling for confounding factors linked to climate change (e.g., habitat change). This paper assesses the shrinking effect in a community of solitary bees from well‐preserved habitats in the core of a large nature reserve experiencing climatic warming without disturbances or habitat changes. Long‐term variation in mean body mass was evaluated using data from 1704 individual bees (137 species, 27 genera, 6 families) sampled over 1990–2023. Climate warmed at a fast rate during this period, annual mean of daily maximum temperature increasing 0.069°C/year on average during 2000–2020. Changes in bee body mass verified expectations from the size shrinking effect. The mean individual body mass of the community of solitary bees declined significantly, irrespective of whether the analysis referred to the full species sample or only to the subset of species that were sampled in both the old (1990–1997) and recent (2022–2023) periods. On average, body mass declined ~0.7%·year−1, or an estimated average cumulative reduction of ~20 mg per individual bee from 1990 to 2023. Proportional size reduction was greatest among large‐bodied species, ranging from around −0.6%·year−1 for the smallest species to −0.9%·year−1 for the largest ones. Declining rate was steeper for cavity‐nesting than ground‐nesting species. The pollination and mating systems of bee‐pollinated plants in the study region are probably undergoing significant alterations as a consequence of supra‐annual decline in bee body mass. [ABSTRACT FROM AUTHOR]

This paper presents the response to anthropogenic forcing in the GISS‐E2.1 climate models for the 21st century Shared Socioeconomic Pathways emission scenarios within the Coupled Model Intercomparison Project Phase 6 (CMIP6). The experiments were performed using an updated and improved version of the NASA Goddard Institute for Space Studies (GISS) coupled general circulation model that includes two different versions for atmospheric composition: A non‐interactive version (NINT) with prescribed composition and a tuned aerosol indirect effect and the One‐Moment Aerosol model (OMA) version with fully interactive aerosols which includes a parameterized first indirect aerosol effect on clouds. The effective climate sensitivities are 3.0°C and 2.9°C for the NINT and OMA models, respectively. Each atmospheric version is coupled to two different ocean general circulation models: The GISS ocean model (E2.1‐G) and HYCOM (E2.1‐H). We describe the global mean responses for all future scenarios and spatial patterns of change for surface air temperature and precipitation for four of the marker scenarios: SSP1‐2.6, SSP2‐4.5, SSP4‐6.0, and SSP5‐8.5. By 2100, global mean warming ranges from 1.5°C to 5.2°C relative to 1,850–1,880 mean temperature. Two high‐mitigation scenarios SSP1‐1.9 and SSP1‐2.6 limit the surface warming to below 2°C by the end of the 21st century, except for the NINT E2.1‐H model that simulates 2.2°C of surface warming. For the high emission scenario SSP5‐8.5, the range is 4.6–5.2°C at 2100. Due to about 15% larger effective climate sensitivity and stronger transient climate response in both NINT and OMA CMIP6 models compared to CMIP5 versions, there is a stronger warming by 2100 in the SSP emission scenarios than in the comparable Representative Concentration Pathway (RCP) scenarios in CMIP5. Changes in sea ice area are highly correlated to global mean surface air temperature anomalies and show steep declines in both hemispheres, with the largest sea ice area decreases occurring during September in the Northern Hemisphere in both E2.1‐G (−1.21 × 106 km2/°C) and E2.1‐H models (−0.94 × 106 km2/°C). Both coupled models project decreases in the Atlantic overturning stream function by 2100. The largest decrease of 56%–65% in the 21st century overturning stream function is produced in the warmest scenario SSP5‐8.5 in the E2.1‐G model, comparable to the reduction in the corresponding CMIP5 GISS‐E2 RCP8.5 simulation. Both low‐end scenarios SSP1‐1.9 and SSP1‐2.6 also simulate substantial reductions of the overturning (9%–37%) with slow recovery of about 10% by the end of the 21st century (relative to the maximum decrease at the middle of the 21st century). Plain Language Summary: The projections of future climate change are uncertain because they are dependent on different possible scenarios of human‐caused emissions and their interaction with natural forcings, internal climate variability, and inter‐model differences. This paper presents the results of the climate model of the NASA Goddard Institute for Space Studies, GISS‐E2.1, for the anthropogenically forced climate response for the twenty first century Shared Socioeconomic Pathways emission scenarios within the Coupled Model Intercomparison Project Phase 6 (CMIP6). The sensitivity of the model response to different magnitudes of anthropogenic forcings in the twenty‐first‐century scenarios were performed using two different versions for the atmospheric composition and two different ocean general circulation models. Compared to CMIP5 GISS‐E2 versions, the CMIP6 GISS‐E2.1 climate model shows a stronger warming by 2100 in comparable scenarios due to larger effective climate sensitivity and transient climate response. Both climate models with two different ocean components project decreases in the Atlantic overturning stream function by 2100. Key Points: GISS E2.1 model with different configurations is used to carry out 134 Shared Socioeconomic Pathway (SSP) experimentsGISS‐E2.1 climate model shows a stronger warming by 2,100 in comparable Representative Concentration Pathway scenarios in CMIP5 due to larger effective climate sensitivity and stronger transient climate responseBoth coupled models, E2.1‐G and E2.1‐H, project decreases in the Atlantic overturning stream function by 2100 with the largest decrease in the warmest scenario SSP5‐8.5 in the E2.1‐G model [ABSTRACT FROM AUTHOR]

Arctic tundra consists of diverse habitats that differ in dominant vegetation, soil moisture regimes, and relative importance of organic vs. inorganic nutrient cycling. The Arctic is also the most rapidly warming global area, with winter warming dominating. This warming is expected to have dramatic effects on tundra carbon and nutrient dynamics. We completed a meta‐analysis of 166 experimental warming study papers to evaluate the hypotheses that warming changes tundra biogeochemical cycles in a habitat‐ and seasonally specific manner and that the carbon (C), nitrogen (N), and phosphorus (P) cycles will be differentially accelerated, leading to decoupling of elemental cycles. We found that nutrient availability and plant leaf stoichiometry responses to experimental warming were variable and overall weak, but that both gross primary productivity and the plant C pool tended to increase with growing season warming. The effects of winter warming on C fluxes did not extend into the growing season. Overall, although warming led to more consistent increases in C fluxes compared to N or P fluxes, evidence for decoupling of biogeochemical cycles is weak and any effect appears limited to heath habitats. However, data on many habitats are too sparse to be able to generalize how warming might decouple biogeochemical cycles, and too few year‐round warming studies exist to ascertain whether the season under which warming occurs alters how ecosystems respond to warming. Coordinated field campaigns are necessary to more robustly document tundra habitat‐specific responses to realistic climate warming scenarios in order to better understand the mechanisms driving this heterogeneity and identify the tundra habitats, communities, and soil pools most susceptible to warming. [ABSTRACT FROM AUTHOR]

Warming climate and precipitation changes induce notable shifts in climate zones. In this study, the latest generation of global climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and the previous generation CMIP5 under high‐emission scenarios are used together with observations and applied to the Köppen‐Geiger climate classification. The aim is to shed light on how projected warming and changes in precipitation will influence future climate zones and their associated ecosystems while revealing differences between the two model generations. Compared to CMIP5 models, CMIP6 models exhibit slightly improved performance in replicating the observed Köppen‐Geiger map for the historical (1976–2005) period and similar inter‐model agreement for the future. The models show major changes in climate zones with a range of projections depending on which ensemble subset is used: 37.9%–48.1% of the global land area is projected to change climate zone by the end of the century, with the most pronounced changes expected over Europe (71.4%–88.6%) and North America (51.2%–65.8%). CMIP6 models project a higher rate of areal climate zone change (km2/year) throughout the 21st century, which is mainly driven by their greater global land warming rates. Using a likely equilibrium climate sensitivity subset of CMIP6 models that is consistent with the latest evidence constrains the climate zone shifts, and their projections better match the results of CMIP5 simulations. Although the high warming rates of some CMIP6 models are less credible, the risks associated with them are greater, and they heighten the need for urgent action to preserve terrestrial ecosystems. Plain Language Summary: Köppen‐Geiger climate classification is a tool to map regional climate zones based on a region's temperature and precipitation. In recent decades, increasing temperatures and changing precipitation trends have started to affect the distribution of those climate zones, and more extensive changes are expected throughout the 21st century. In this paper, we assess the observed and expected changes in the global distribution of Köppen‐Geiger climate zones using observations along with the latest and the previous generation of global climate model projections. We find that shifts in climate zones are more pronounced in the latest generation of models due to their questionable greater global warming rate projections. Depending on which subset of model projections is used, up to half of the Earth's land area faces the risk of shifting to a different climate zone by the end of the century, with the greatest changes expected in Europe and North America. The rate of change (affected area per year) is also projected to accelerate through the 21st century, suggesting that vulnerable species and agricultural practices might have less time to adapt to changes in climate zones than previously projected. Key Points: Coupled Model Intercomparison Project Phase 6 (CMIP6) exhibits slightly improved performance in simulating the globally observed historical Köppen‐Geiger climate zones compared to CMIP5By the end of the century, 38%–48% of the global land area is projected to be in a different climate zone than todayThe rate of climate zone change is projected to accelerate, with more pronounced rates in CMIP6 due to considerably higher warming rates [ABSTRACT FROM AUTHOR]

The planet is predicted to become drier because of accelerating global warming, increasing great challenges to the survival of terrestrial species. However, the understanding of when and where increasing aridity in the future will lead to abrupt biodiversity loss is still limited. Here, we predicted the spatiotemporal dynamics of future vertebrate biodiversity loss driven by increasing aridity at the assemblage scale under the scenario framework of the shared socio‐economic pathways (SSPs) and representative concentration pathways (RCPs). The results show that, under the high‐emissions scenario of SSP5‐8.5, more than 24.19% of terrestrial assemblages are projected to have at least one vertebrate species exposed to unprecedented aridity conditions by 2100, leading to 55.29% of terrestrial vertebrate species experiencing local habitat loss. In addition, the mean magnitude of global exposure is expected to reach 17.47% by 2100. Within these assemblages, most species will be simultaneously exposed to unprecedented aridity conditions, with an average exposure abruptness of 78.00%, most of which will occur intensively after 2050. If we manage to reduce greenhouse gas emissions to the SSP1‐2.6 (SSP2‐4.5) scenario, the magnitude of exposure can significantly decrease to 7.35% (10.56%), and the onset of exposure can be delayed by 43 (30) years, averaging approximately 30% (14%) of vertebrate species from local habitat loss. Our findings also highlight that the concurrent extremes of increasing aridity and rising temperature in Southeast Asia and Amazon rainforests may amplify exposure risks, which can motivate decision‐makers to respond early and effectively to mitigate abrupt ecological disruption. Plain Language Summary: The global land surface is predicted to become more drier in the future due to the accelerating global warming, which places great challenges on the survival of terrestrial species. In this paper, we predicted the future spatiotemporal dynamics of biodiversity loss of vertebrate species as a result of the increase in aridity, trying to understand when and where the increasing aridity will cause biodiversity loss intensively and lead to abrupt ecological disruption. We found that, under the high‐emissions scenario (∼4.4°C global temperature rise), more than 24.19% of global terrestrial assemblages are projected to have at least one vertebrate species exposed to aridity condition exceeding their niche, leading to the consequence that 55.29% of species will experience habitat loss. The exposure events within most terrestrial assemblages will occur simultaneously after 2050. If we manage to reduce emissions to the low (intermediate)‐emissions scenario (∼1.8°C and 2.7°C global temperature rise), the onset of exposure can be delay by 43 (30) years. Our findings also highlight that the concurrent extremes of increasing aridity and rising temperature in Southeast Asia and Amazon rainforests may amplify exposure risks, which can motivate decision‐makers to respond early to mitigate abrupt ecological disruption. Key Points: We predicted and highlighted the risk of abrupt biodiversity loss in terrestrial vertebrate species driven by increasing aridityMore than 24% of terrestrial assemblages will be exposed to unprecedented aridity, and 55.29% of species will experience local habitat lossConcurrent extremes of increasing aridity and rising temperature in Southeast Asia and Amazon rainforests may amplify exposure risks [ABSTRACT FROM AUTHOR]

Since the early 1990s the Pacific Walker circulation shows a multi‐decadal strengthening, which contradicts future model projections. Whether this trend, evident in many climate indices especially before the 2015 El Niño, reflects the coupled ocean‐atmosphere response to global warming or the negative phase of the Pacific Decadal Oscillation (PDO) remains debated. Here we show that sea surface temperature trends during 1980–2020 are dominated by three signals: a spatially uniform warming trend, a negative PDO pattern, and a Northern Hemisphere‐Indo‐West Pacific warming pattern. The latter pattern, which closely resembles the transient ocean thermostat‐like response to global warming emerging in a subset of CMIP6 models, shows cooling in the central‐eastern equatorial Pacific but warming in the western Pacific and tropical Indian Ocean. Together with the PDO, this pattern drives the Walker circulation strengthening in the equatorial band. Historical simulations appear to underestimate this pattern, contributing to the models' inability to replicate the Walker cell strengthening. Plain Language Summary: This paper investigates the observed changes in the tropical Pacific during the satellite era, including the recent decadal strengthening of the atmospheric zonal circulation—the Walker cell. We aim to understand the extent to which these changes represent a forced response to rising CO2 concentrations versus natural variability. We apply an approach in which we decompose the observed sea surface temperature trends into three components—a pattern associated with the Pacific Decadal Oscillation, which is part of natural variability, a uniform warming pattern, and a residual pattern. This residual pattern shows a remarkable resemblance to a forced ocean thermostat‐like transient response generated in some of the climate models, characterized by equatorial Pacific (EP) cooling, and a broad warming of the Northern Hemisphere, and the Indian Ocean and West Pacific. These results challenge studies arguing that the recent strengthening of the Pacific Walker cell can be explained simply by multi‐decadal natural variability in the tropics. Furthermore, the inability of climate models at large to fully capture this forced pattern with historical forcing puts into focus the reliability of future projections of climate change in the tropical Pacific, specifically the timing of emergence of the eastern EP warming. Key Points: A multi‐decadal strengthening of the Pacific Walker cell is observed in a wide range of indices, especially after 1990A Northern Hemisphere ‐ Indo West Pacific warming sea surface temperature pattern, which differs from the Pacific Decadal Oscillation, is evident since 1980This pattern resembles a forced response to abrupt CO2 forcing, emerging in a subset of climate models, and contributes to the Walker circulation strenthening [ABSTRACT FROM AUTHOR]

The economic and financial risks of global warming have become a hot issue of academic interest. This article analyzes global warming, financial risk, and the economic statistics of 30 provinces in China from 2010 to 2020 as a sample to assess the influence of the severity of global warming on financial risk. Global warming is found to affect financial risk and to have a substantial favorable influence on the amount of financial risk. Global warming also has significant effects on households, enterprises, financial institutions, and governments. There is heterogeneity in the effects of climate variation on financial risk. Global warming will cause a greater accumulation of financial risk in economically developed regions. Additionally, it will lead to financial risks by causing a decline in the incomes of residents, a decline in the profits of enterprises, growth in the number of loans that financial institutions consider to be nonperforming, and a widening of the gap between government revenue and expenditures. All of these effects will have an adverse domino effect on the economy. To reduce the financial risks caused by global warming, countermeasures are being offered to ensure social cohesion, conduct risk stress testing, create risk mitigation instruments, and encourage environmentally responsible development. This paper discusses policies and provides policymakers with recommendations on how to cope with the systematic financial risks induced by climate variation. [ABSTRACT FROM AUTHOR]

The necessity to achieve global sustainability and renewable energy resources to overcome the threat of climate change has led to unparalleled social and economic alterations ubiquitous throughout the world. The environment surrounding pollution correlated with global warming is essential to technological advances for developing energy resources. Renewable and sustainable energy resources are eco‐friendly energy sources that transform heat directly into electrical energy. The transformation of the global energy system underway in various countries can play a predominant role in power sectors. It helps in establishing a low‐power solution with high performance in advance. This review paper highlights technological feasibility within the economic activity of sustainable resources in various sectors. The sustainable resource would represent the world's most advanced technology and cost‐effective global power transition pathway. The present status, prospects, and updated information about these energy resources have been discussed in detail. This review provides a recommendation on which energy would be suitable for electrical energy generation and would establish a green environment for the next generation to survive in the world. [ABSTRACT FROM AUTHOR]

Advances in high‐performance computing have enabled large‐eddy simulations (LES) of turbulence, convection, and clouds. However, their potential to improve parameterizations in global climate models (GCMs) is only beginning to be harnessed, with relatively few canonical LES available so far. The purpose of this paper is to begin creating a public LES library that expands the training data available for calibrating and evaluating GCM parameterizations. To do so, we use an experimental setup in which LES are driven by large‐scale forcings from GCMs, which in principle can be used at any location, any time of year, and in any climate state. We use this setup to create a library of LES of clouds across the tropics and subtropics, in the present and in a warmer climate, with a focus on the transition from stratocumulus to shallow cumulus over the East Pacific. The LES results are relatively insensitive to the choice of host GCM driving the LES. Driven with large‐scale forcing under global warming, the LES simulate a positive but weak shortwave cloud feedback, adding to the accumulating evidence that low clouds amplify global warming. Plain Language Summary: Clouds remain one of the largest uncertainties in our understanding and in predictions of climate change because it is challenging to represent their small‐scale dynamics in climate models. However, high‐resolution simulations can provide faithful simulations of clouds and turbulence in limited areas, and these can be used to calibrate climate models. So far, only a limited set of simulations has been used for calibration of climate models, with focus on a few specific locations. This study presents an experimental setup that allows the high‐resolution simulations to be run anywhere on the globe, in any climate state, driven by output from different climate models. The setup is used to create a library of high‐resolution simulations of clouds across the tropics and subtropics in both the current and a warmer climate. The library substantially expands the data set available for the calibration and evaluation of climate models. Key Points: A library of high‐resolution simulations of clouds is created with large‐eddy simulations (LES) driven by a few global climate models (GCMs)Clouds simulated by LES driven by different GCMs are more similar to one another than the corresponding GCM‐simulated cloudsUnder global warming, LES‐simulated low clouds exhibit a weak but positive feedback on warming [ABSTRACT FROM AUTHOR]

This paper explores the interplay between the biophysical and economic geographies of climate change impacts on agriculture. It does so by bridging the extensive literature on climate impacts on yields and physical productivity in global crop production, with the literature on the role of adaptation through international trade in determining the consequences of climate change impacts. Unlike previous work in this area, instead of using a specific crop model or a set of models, we employ a statistical meta-analysis that encompasses all studies available to the IPCC-AR5 report. This permits us to isolate specific elements of the spatially heterogeneous biophysical geography of climate impacts, including the role of initial temperature, differential patterns of warming, and varying crop responses to warming across the globe. We combine these climate impact estimates with the Global Trade Analysis Project model of global trade in order to estimate the national welfare changes that are decomposed into three components: the direct (biophysical impact) contribution to welfare, the terms of trade effect, and the allocative efficiency effect. We find that when we remove the spatial variation in climate impacts, the terms of trade impacts are cut in half. Given the inherent heterogeneity of climate impacts in agriculture, this points to the important role of trade in distributing the associated welfare impacts. When we allow the biophysical impacts to vary across the empirically estimated uncertainty range taken from the meta-analysis, we find that the welfare consequences are highly asymmetric, with much larger losses at the low end of the yield distribution. This interaction between the magnitude and heterogeneity of biophysical climate shocks and their welfare effects highlight the need for detailed representation of both in projecting climate change impacts. [ABSTRACT FROM AUTHOR]

The frequency with which tropical cyclones (TCs) occur controls all other aspects of tropical cyclone risk since a storm that does not occur can do no harm. Yet this frequency is poorly understood. There is no accepted theory that explains the average number of TCs that occur each year on the Earth, nor how that number will change with global warming. Arguments based on global budgets of heat or moisture do not yet appear helpful, nor does a detailed understanding of the physical processes of TC genesis. Empirical indices that predict TC frequency as a function of large‐scale environmental variables can explain some of its relative variations in space and time, but not its absolute value. Global numerical models with horizontal grid spacings on the order of 25–50 km have allowed much improved simulations of TC activity, however. Many such models project a decrease in frequency with warming, but some project an increase. Idealized simulations, including those at higher resolutions, offer promise by allowing a systematic, deductive investigation of the roles of individual environmental factors. In addition to the larger‐scale environmental modulation of genesis likelihood, precursor disturbances, or "seeds", may exert an independent influence on TC frequency. Plain Language Summary: The term tropical cyclone frequency refers to the average number of tropical cyclones (also known as hurricanes, typhoons, etc.) which occur each year, either over the earth as a whole or in smaller regions. In this paper, the authors review the state of the science regarding what is known about tropical cyclone frequency. The state of the science is not great. There are around 80 tropical cyclones in a typical year, and we do not know why it is this number and not a much larger or smaller one. We also do not know much about whether this number should increase or decrease as the planet warms‐‐‐thus far, it has not done much of either on the global scale, though there are larger changes in some particular regions. No existing theory predicts tropical cyclone frequency. In this situation, we are left with numerical models as our primary tool, and the authors discuss the strengths, weaknesses, and different ways of using such models to investigate tropical cyclone frequency. Idealized simulations, in which the planet is made simpler than it really is, are allowing some new insights. Another promising avenue of investigation involves studying the weaker disturbances that sometimes strengthen into tropical cyclones. Key Points: We do not understand why the number of tropical cyclones per year is what it is, nor how it may be changingIn the absence of theory, our main tools are numerical modelsPromising research directions include idealized simulations at high resolution and study of precursor disturbances, or "seeds" [ABSTRACT FROM AUTHOR]

Compound climate extremes, such as events with concurrent temperature and precipitation extremes, have significant impacts on the health of humans and ecosystems. This paper aims to analyze temporal and spatial characteristics of compound extremes of monthly temperature and precipitation, evaluate the performance of the sixth phase of the Coupled Model Intercomparison Project (CMIP6) models in simulating compound extremes, and investigate their future changes under Shared Socioeconomic Pathways (SSPs). The results show a significant increase in the frequency of compound warm extremes (warm/dry and warm/wet) but a decrease in compound cold extremes (cold/dry and cold/wet) during 1985–2014 relative to 1955–1984. The observed upward trends of compound warm extremes over China are much higher than those worldwide during the period of interest. A multi‐model ensemble (MME) of CMIP6 models performs well in simulating temporal changes of warm/wet extremes, and temporal correlation coefficients between MME and observations are above 0.86. Under future scenarios, CMIP6 simulations show substantial rises in compound warm extremes and declines in compound cold extremes. Globally, the average frequency of warm/wet extremes over a 30‐yr period is projected to increase for 2070–2099 relative to 1985–2014 by 18.53, 34.15, 48.79, and 59.60 under SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5, respectively. Inter‐model uncertainties for the frequencies of compound warm extremes are considerably higher than those of compound cold extremes. The projected uncertainties in the global occurrences of warm/wet extremes are 3.82 times those of warm/dry extremes during 2070–2099 and especially high for the Amazon and the Tibetan Plateau. Plain Language Summary: Compound climate extremes, such as the events with concurrent temperature and precipitation extremes, have significant impacts on the health of humans and ecosystems. Can climate model simulate the historical compound extremes? If yes, how the global compound extremes will change in the future? In this study, we found that the global climate model performs well in simulating temporal changes of warm/wet and warm/dry extremes during the period 1955–2014. With greenhouse gas emissions continuing to increase in the future, compound warm/dry and warm/wet extremes show a continuous increase in frequency in the next few decades, while compound cold/dry and cold/wet extremes are projected to occur less frequently. Key Points: A multi‐model ensemble of CMIP6 models performs well in simulating temporal changes of warm/wet extremesThe inter‐model uncertainties for the frequencies of compound warm extremes are considerably higher than those of compound cold extremesThe projected uncertainties in the global occurrences of warm/wet extremes are 3.82 times those of warm/dry extremes during 2070–2099 [ABSTRACT FROM AUTHOR]

Precipitation extremes are increasing globally due to anthropogenic climate change. However, there remains uncertainty regarding impacts upon flood occurrence and subsequent population exposure. Here, we quantify changes in population exposure to flood hazard across the contiguous United States. We combine simulations from a climate model large ensemble and a high‐resolution hydrodynamic flood model—allowing us to directly assess changes across a wide range of extreme precipitation magnitudes and accumulation timescales. We report a mean increase in the 100‐year precipitation event of ~20% (magnitude) and >200% (frequency) in a high warming scenario, yielding a ~30–127% increase in population exposure. We further find a nonlinear increase for the most intense precipitation events—suggesting accelerating societal impacts from historically rare or unprecedented precipitation events in the 21st century. Plain Language Summary: Heavy rainfall is increasing globally due to human‐caused global warming. However, it is still unclear how these increases in heavy rainfall might affect flood risk. In this paper, we investigate how global warming and population changes together may be affecting the number of people at risk from floods in the United States. We combine simulations from a climate model and flood model—allowing us to consider a wide range of heavy rainfall events. We report a ~20% increase in the size and a >200% increase in the frequency of very heavy and rare rainfall events, which leads to a ~30–127% increase in the number of people at risk from floods. Finally, we find that the heaviest rainfall events increase by the widest margin—suggesting the possibility of major increases in damage and disruption caused by severe floods in the 21st century. Key Points: Population exposure to flood hazard is increasing due to both climate‐driven increases in extreme rainfall as well as demographic shiftsThere is a wide range of plausible increases in population exposed to flood hazard, depending strongly on climate and growth scenarioWe find a nonlinear increase for most extreme events, suggesting accelerating societal impacts from historically unprecedented rainfall [ABSTRACT FROM AUTHOR]

From 1988 to July 2019 more than 100 review articles were published, including opinion papers and book chapters, that focused on potential climate change effects on plant pathogens and the future crop disease risks. Therefore, an overview of them is presented herein, particularly helpful for beginners and non‐experts in climate change biology research. Specifically, this overview contributes to a faster and more convenient identification of appropriate review articles, for example, related to a certain crop, pathogen, plant disease or country of interest. However, not all important crops, pathogens, diseases and countries are considered specifically and in‐depth in any of these review articles, suggesting that there are still research gaps prevalent, which are also highlighted herein. Nevertheless, the overview suggests that researchers are increasingly busy and successful in summarizing the fragmented information spread throughout the international literature. Consequently, they are providing 'step‐by‐step' a comprehensive, in‐depth, and continuously updated knowledge platform on potential climate change effects on plant pathogens and the respective crop disease risks in the future, although some aspects will, by nature, be repeated. [ABSTRACT FROM AUTHOR]

The climate is an aggregate of the mean and variability of a range of meteorological variables, notably temperature (T) and precipitation (P). While the impacts of an increase in global mean surface temperature (GMST) are commonly quantified through changes in regional means and extreme value distributions, a concurrent shift in the shapes of the distributions of daily T and P is arguably equally important. Here, we employ a 30‐member ensemble of coupled climate model simulations (CESM1 LENS) to consistently quantify the changes of regionally and seasonally resolved probability density functions of daily T and P as function of GMST. Focusing on aggregate regions covering both populated and rural zones, we identify large regional and seasonal diversity in the probability density functions and quantify where CESM1 projects the most noticeable changes compared to the preindustrial era. As global temperature increases, Europe and the United States are projected to see a rapid reduction in wintertime cold days, and East Asia to experience a strong increase in intense summertime precipitation. Southern Africa may see a shift to a more intrinsically variable climate but with little change in mean properties. The sensitivities of Arctic and African intrinsic variability to GMST are found to be particularly high. Our results highlight the need to further quantify future changes to daily temperature and precipitation distributions as an integral part of preparing for the societal and ecological impacts of climate change and show how large ensemble simulations can be a useful tool for such research. Plain Language Summary: The weather varies naturally from day to day and between regions, seasons, and years. Ecosystems and our society are both adapted to the average weather conditions of a given place and to how variable the temperature and rainfall amounts are around that average. As the global surface temperature changes, whether through natural cycles or human interference, so may this variability. In this paper, we investigate changes to the distributions of daily temperature and rainfall for different levels of surface temperature increase. By using a large set of simulations from the same climate model, we estimate their means and shapes, currently and in the near future. We find that in parts of Europe and the United States, wintertime cold days will disappear more rapidly with global warming than hot days increase, leading to a less variable climate state. In Africa and the Arctic, however, climate conditions will rapidly transition out of the range of preindustrial variability and into a climate state not yet experienced by modern society. We emphasize that in order to prepare for the impacts of climate change, we need information about changes to average properties and to extreme events and about the potential changes to daily variability itself. Key Points: Daily temperature and precipitation distributions from CESM1 Large Ensemble are shown to be functions of region, season, and surface temperatureLarge differences are found in regional distributions, where they are particularly sensitive to surface temperature anomalyWe identify regions where global warming may rapidly shift seasonal climate away from preindustrial conditions [ABSTRACT FROM AUTHOR]

Risk of climate‐related impacts results from the interaction of climate‐related hazards (including hazardous events and trends) with the vulnerability and exposure of human and natural systems. Despite the commitment of the Paris Agreement, the integrate research on climate change risk combining risk‐causing factors and risk‐bearing bodies, the regional differences in climate impacts are still missing. In this paper we provide a quantitative assessment of hazards and socioeconomic risks of extreme events, risks of risk‐bearing bodies in China under global warming of 1.5 and 2.0 °C based on future climate scenarios, and quantitative evaluation theory for climate change risk. For severe heat waves, hazards might significantly intensify. Affected population under 2.0 °C warming might increase by more than 60% compared to that of 1.5 °C. Hazards of severe droughts and floods might strengthen under Representative Concentration Pathway 8.5 scenario. Economic losses might double between warming levels of 1.5 and 2.0 °C, and the population affected by severe floods might continuously increase. Under the integrate effects of multiple disasters, the regions with high population and economic risks would be concentrated in eastern China. The scope would gradually expand to the west with socioeconomic development and intensification of extreme events. High ecological risks might be concentrated in the southern regions of the Yangtze River Basin, while the ecological risk in northern China would expand. High agriculture yield risks might be distributed mainly in south of the North China Plain, the Sichuan Basin, south of the Yangtze River, and west of Northwest China, and the risk levels might continuously increase. Plain Language Summary.: Based on the climate and socioeconomic scenario data from the Inter‐Sectoral Impact Model Inter‐comparison Project and International Institute for Applied Systems Analysis, risks from climate change were identified under different warming levels, considering socioeconomic damage and ecosystem and food production losses. The relatively developed areas of eastern China exhibit high risks, and the risks show a westward and northward expansion trend. Socioeconomic damage, natural ecosystem, and food production losses would increase with socioeconomic development and intensification of global warming. We believe that a quantitative assessment of climate change risk should integrate climate‐related hazards with the vulnerability and exposure of human and natural systems. These results can provide decision‐making support for governments and a database for adapting to climate change. Key Points: Risks of socioeconomic development, ecosystem and food production would increase between 1.5 °C and 2.0 °C warming, economic losses might doubleIncreases in annual socioeconomic losses of 2.0 °C warming would be more significant than those of 1.5 °CEastern China exhibits high integrate risks of climate change, which present westward and northward trends from 1.5 °C to 2.0 °C warming [ABSTRACT FROM AUTHOR]

Globally, treelines form a transition zone between tree‐dominated forest downslope and treeless alpine vegetation upslope. Treelines represent the highest boundary of "tree" life form in high‐elevation mountains and at high latitudes. Recently, treelines have been shifting upslope in response to climate warming, so it has become important to understand global tree diversity and treeline distributions. However, to the best of our knowledge, no global database on tree flora of treelines exists, which limits our capacity to undertake macroecological analyses. Here, for the first time, we present a global data set on the trees of the treeline ecotone, supported by an online ToTE database. We synthesized the database from 1202 studies published over the last 60 years (1962 to 2022) following the Preferred Reporting Items in Systematic Reviews and Meta‐Analysis (PRISMA) protocol. We classified the tree species in the database into three categories: treeline tree (TL) species, near to treeline (NTL) tree species, and tree species with an upper montane range limit (TUMR). The ToTE Version‐1 presents a total of 208 tree taxa, including 189 species, five subspecies, and 14 varieties, belonging to 54 genera and 26 families distributed across 34 mountain regions worldwide that either grow exactly at the treeline or have a range limit below the treeline. Of the total taxa, 155, 14, and 39 belong to TL, NTL, and TUMR, respectively. Genera such as Abies, Picea, Pinus, Larix, and Juniperus are more represented in the treeline tree category. On the other hand, Acer, Prunus, Populus, and Quercus have more representatives in the near to treeline category, whereas Erica, Nothofagus, and Polylepis contribute more tree species with an upper montane range limit. Furthermore, families such as Rosaceae and Pinaceae include trees that occur both at the treeline and with an upper montane range limit, whereas Sapindaceae includes trees that occur exclusively near to treeline. Our database also includes information on the global distribution patterns of treeline tree species richness across mountains and biomes. The mountains with the highest number of tree species are the Andes (39) followed by the Himalaya (37). Close to 67% of tree species show restricted distributions in different mountains, with the highest endemism in the Andes and the Himalaya. In terms of tree species distribution, Pinus sylvestris was widespread, with a distribution across nine mountain regions, followed by Picea glauca and Fagus sylvatica, both distributed across five mountain regions. In terms of species' distribution across biomes, the temperate biome harbors the highest treeline tree species richness (152 species), which may reflect the fact that the majority of studies are available from the temperate regions of the world. The remaining 56 species are distributed within five other biomes, with the least in dry tropical and subarctic (four species each). Furthermore, currently 40 treeline tree species fall under different International Union for Conservation of Nature threat categories. We anticipate that our database will help advance research on macroecological, biogeographic, evolutionary, climate‐change, and conservation aspects of the treeline on a global scale. The data are released under a Creative Commons Attribution 4.0 international license. Please cite this data paper when the data are reused. [ABSTRACT FROM AUTHOR]

Regional hydrological sensitivity (i.e., precipitation change per degree local surface warming) contributes substantially to the uncertainty in future precipitation projections over tropical oceans. Here, we investigate the sensitivity of relative precipitation (P*, precipitation divided by the basin average precipitation) to local sea surface temperature (SST) change by dissecting it into three components, namely the sensitivity of P* to relative SST (SSTrel, SST minus the tropical mean SST) changes, the sensitivity of P* to surface convergence changes, and the sensitivity of surface convergence to SST gradient changes. We show that the relationships between P* and SSTrel, and between P*, surface convergence, and SST gradients are largely constant during climate change. This allows us to constrain regional hydrological sensitivity based on present‐day SST‐precipitation relationships. The sensitivity of surface convergence to SST gradient changes is a main source of uncertainty in regional hydrological sensitivity and is likely underestimated in GCMs. Plain Language Summary: Understanding how precipitation will change over tropical oceans is important because these changes influence the atmospheric circulation, which in turn affects the global climate and weather patterns. Climate models disagree on their projections of precipitation changes over tropical oceans in part due to a lack of understanding on how precipitation should respond to a given amount of local surface warming. We find that the sensitivity of precipitation to future changes in local sea surface temperature (which is commonly referred to as regional hydrological sensitivity) largely depends on the present‐day relationship between precipitation and local sea surface temperature, as well as that between precipitation and the spatial gradient in sea surface temperature, and both relationships are observable and thus can serve as constraints. We find that inter‐model differences in regional hydrological sensitivity result primarily from differences in the response of surface winds to sea surface temperature gradient changes. Key Points: Regional hydrological sensitivity is an important source of uncertainty in rainfall projections over tropical oceansRegional hydrological sensitivity can be constrained by components of rainfall‐temperature relationship that stay constant during warmingUncertainty in regional hydrological sensitivity originates largely from surface convergence sensitivity to temperature gradient changes [ABSTRACT FROM AUTHOR]

As global warming intensifies, the coupling relationship between negative Indian Ocean Dipole (nIOD) and La Niña has substantially changed. However, the characteristics and mechanisms of these changes are not yet fully understood. Here, we find that the impact of La Niña on nIOD has considerably weakened since 1999, with the frequency of nIOD occurrences during La Niña years plummeting to a mere one‐third of the pre‐1999 levels. This is primarily attributed to the early onset of Indian summer monsoon and the decrease in La Niña intensity, while the effect of variations in Bjerknes feedback is relatively minor. Model simulations suggest that the influence of La Niña on nIOD will continue to weaken under future global warming through similar mechanisms as in the observations, increasing the complexity of air‐sea coupling in the Indian Ocean. Plain Language Summary: The negative Indian Ocean Dipole (nIOD) has significant impacts on both local and global climate change. La Niña is a major trigger for nIOD. However, as the globe warms up, the connection between nIOD and La Niña has changed a lot. This study analyze observation and reanalysis data from the 1950s onwards to see how nIOD and La Niña are linked. We find that La Niña has had less impact on nIOD since 1999. This is because the summer monsoon starts earlier, causing changes in wind patterns over the Indian Ocean. La Niña normally brings westerly wind anomalies in the Indian Ocean, but these winds are weakened because of the early monsoon. This makes it harder for nIOD to form. The feedback loop known as the Bjerknes feedback doesn't play a big role in maintaining nIOD. Furthermore, the reduction in La Niña intensity also contribute to weakening the relationship between La Niña and nIOD. Models predict that La Niña's impact on nIOD will continue to weaken under future global warming, increasing the complexity of air‐sea coupling in the Indian Ocean and leading to more challenges in forecasting. Key Points: The relationship between La Niña and negative Indian Ocean Dipole has weakened significantly in this centuryThe spring‐summer easterly anomaly induced by the premature summer monsoon weakens the La Niña‐induced westerly anomalyThe impact of La Niña on negative Indian Ocean Dipole will continue to weaken under future global warming [ABSTRACT FROM AUTHOR]

Horizontal and vertical moisture advection in the lower troposphere of the Arctic under progressing global warming is examined using a large‐scale ensemble model data set. Advection is decomposed into terms related to the basic state of the atmosphere and transient eddies and compared against a non‐warming experiment. During summer, horizontal moisture advection increases mainly by transient eddies advecting moisture from the lower latitudes. During winter, enhanced evaporation due to reduced sea ice becomes a source of moisture diminishing the role of transient eddies moistening the atmosphere. This effect intensifies under extreme global warming, turning the change in total horizontal advection in the lower troposphere negative. Diminished horizontal advection during winter is counteracted by vertical advection accompanied with enhanced evaporation and upper‐level horizontal advection maintaining the increase in column moisture. These results improve our understanding of how the water cycle in the Arctic responds via atmospheric processes under global warming. Plain Language Summary: This study uses a data set with a large number of members to investigate how the atmosphere is moistened in the Arctic (north of 70˚N) under various stages of global warming. The movement of moisture is summarized in terms of horizontal and vertical components of advection, a measure of how the atmosphere is moistened in a given specific humidity gradient and wind, which is decomposed into parts related to the average state of the atmosphere and parts related to high‐frequency phenomena, such as cyclones. It is found that (a) during summer, moisturization of the Arctic is mainly driven by horizontal movement of moisture from a remote source in the lower latitude, (b) during winter, this moisturization due to horizontal movement of moisture is suppressed and is driven more by vertical movement of moisture due to reduction of sea ice and increased evaporation. As global warming progresses, the role or horizontal movement of moisture is taken over by the local process of evaporation and vertical movement of moisture. This research helps us understand how the water cycle in the Arctic changes with severe global warming and improves our knowledge of the atmospheric processes that govern the climate system through various feedbacks. Key Points: Moisture advection in the Arctic under progressing global warming is examined using a large‐scale ensemble model simulation data setMoistening effect of horizontal advection in the lower troposphere is enhanced for summer and diminished for winter under extreme warmingEnhanced horizontal advection in the upper layer and surface evaporation are consistent with increased column moisture during winter [ABSTRACT FROM AUTHOR]

Climate change induces significant changes in storm characteristics, particularly for short‐duration extreme storms (heavy rain features), impacting their intensity and spatio‐temporal distribution. Although alterations in precipitation intensity are well documented, past studies examining changes in spatio‐temporal distribution of storms (storm rainrates) were region‐specific and focused on isolated aspects of change in space or time, eluding a comprehensive understanding of the precise nature and extent of these changes. Bridging this gap, this study introduces a novel grid‐based measure of storm homogeneity, "spatio‐temporal homogeneity" metric and investigates the global patterns of change in combined spatio‐temporal characteristics of extreme storms. Analyzing the 30 min × 0.1° × 0.1° resolution Global Precipitation Measurements, the study finds that extreme storms are shrinking in both space and time due to rising surface air temperatures, predominantly in tropics. In contrast, temperate regions experience expanded extreme storms with increasing temperatures. The study also identifies a global trend toward more front‐loading in storms with rising temperatures, driven by a substantial increase in tropics and southern temperate regions. Conversely, storms in northern temperate regions become slightly more rear‐loaded as temperature increases. Furthermore, the study finds that characteristics of short–duration storms (6–12 hr) are more sensitive to temperature changes. Overall, this study contributes valuable insights into the global spatio‐temporal changes of extreme storms, highlighting regions most susceptible to alterations in storm patterns due to climate change. These findings are essential for developing effective adaptation strategies and flood management practices to cope with the changing nature of extreme storms in a warming climate. Plain Language Summary: Extreme rainfall can lead to floods, affect ecosystems, and challenge water management. How intense the rain is, how wide an area it covers, and how long it lasts are key factors in determining flood risk. Additionally, whether the rainfall starts strong and tapers off (front‐loaded) or begins gently and then fades quickly (rear‐loaded)—also plays a role. As the climate changes, it's crucial to understand how these extreme storm characteristics are evolving to better prepare for the future. This study introduces a new way to measure changes in the size and duration of extreme storms in response to rising temperatures worldwide. It also examines whether warmer temperatures make storms more likely to start strong and taper off or the opposite. The findings show that in tropical regions, extreme storms are becoming effectively shorter and covering effectively smaller areas as temperatures increase. Conversely, in temperate regions, storms are lasting longer and covering effectively larger areas. Additionally, storms in areas below 30°N are tending toward more front‐loading, while those above 30°N are becoming more rear‐loaded. This research helps us understand how warming temperatures are changing storm patterns and can inform better flood preparedness and water management strategies. Key Points: Introduces Spatio‐Temporal Homogeneity metric to effectively track comprehensive changes in storm characteristics across both space and timeRising temperature causes "spatio‐temporally peakier" storms in tropics, intense precipitation burst in smaller area over shorter durationRising temperature leads to more front‐loading in storms, notably in tropics and southern temperate regions, increasing flash flood risk [ABSTRACT FROM AUTHOR]

Observations and climate projections suggest a larger increase in tropical cyclone (TC)‐induced rainfall than that can be explained by the Clausius‐Clapeyron relationship of 7% increase in vapor content for each 1°C degree rise in temperature. However, these studies using diverse data sources and methods over various periods show inconsistencies regarding the location of this increase ‐ whether in the TC inner core or outer regions ‐ and offer differing explanations for the reported trends. This study uses the Pseudo‐global warming methodology on simulations of 117 western North Pacific TCs making landfall in Southeast Asia to investigate changes in TC rainfall structure by the end of the century under the SSP2‐4.5 and SSP3‐7.0 scenarios. Specifically, it tests the sensitivity of changing trends to various analysis methods used in previous studies and identifies the underlying physical mechanisms driving these changes. The findings indicate an amplified increase in rainfall in the TC inner core across all future scenarios, along with potentially decreased rainfall in the outer region under certain future climate conditions. Among TC categories, Supertyphoons exhibit the most significant increased rainfall across future states. Changes in TC primary and secondary circulations, TC structure, and the convergence of heat and moisture are the main factors shaping future rainfall patterns, outweighing the effects of changes in atmospheric and convective stability. Plain Language Summary: Tropical cyclone (TC)‐related rainfall is increasing with global warming. Typically, a 1°C increase in temperature leads to about a 7% increase in the atmosphere's water vapor holding capacity. However, the rise in TC rainfall outpaces this rate. Observations indicate this enhanced increase occurs in the TC outer region due to greater environmental moisture. Contrarily, modeling future projections suggest this concentrates in the inner core due to intensified TCs. This study analyzes a large data set of 819 simulations from 117 TCs making landfall in Southeast Asia to capture changes in future rainfall patterns under two contemporary climate change scenarios. Our findings reveal that the enhanced increase occurs in the TC inner core in all future states, while rainfall in the outer region decreases under specific climate conditions. Supertyphoons generate the heaviest rainfall, with minimal variations observed across climate scenarios. Variations of all dynamic and thermodynamic factors closely tied to TC rainfall are investigated to provide a comprehensive picture of the physics behind the changes. The interplay between TC dynamics (e.g., primary and secondary circulations), TC structure, and thermodynamic conditions (e.g., convergence of moisture, and temperatures), plays a critical role in the changing behaviors of TC rainfall. Key Points: Rainfall increases in the cyclone's inner core across all future states but decreases in the outer region under specific statesVariations in cyclone circulations, structure, convergence of moisture and heat in future climates drive rainfall changing patternsSupertyphoons cause the heaviest rainfall compared to other categories, with slight variations noted across climate conditions [ABSTRACT FROM AUTHOR]

We show that the winter Beaufort High (BH) index defined by sea level pressure (SLP) has a robust negative trend under the scenarios SSP5‐8.5 and SSP2‐4.5, with a reduction by about 5 hPa and 2 hPa, respectively, by the end of the 21st century. The negative trends in the BH SLP are associated with the changes in the background SLP over the Arctic basin. However, the vorticity of the winter BH tends to intensify under SSP5‐8.5, but shows no robust increase under SSP2‐4.5. The intensification is associated with the enhanced ridge over the Western Arctic. Therefore, it is necessary to take into account the dynamic aspects of the BH, such as vorticity. Based on this assessment, under the most likely emissions scenario, the winter BH is likely to weaken through the 21st century, in terms of SLP, but shows no robust changes in term of vorticity. Plain Language Summary: We used the latest IPCC global climate model outputs to investigate the wintertime changes in the Beaufort High (BH). Under the climate change scenarios, during winter, the sea level pressure (SLP) over the BH region is expected to decrease. The SLP reduction is up to 5 hPa by the end‐of‐the‐century. Thus, the BH seems to become weaker. However, its vorticity tends to increase under SSP5‐8.5, mostly due to the intensification of the ridge over the western North America. Key Points: The Beaufort High (BH) index defined by sea level pressure (SLP) decreases under warming climate scenariosMeanwhile, the BH vorticity tends to intensify due to the change in the ridge over the Western ArcticBesides the SLP, impact studies of the BH on the Arctic Ocean need to consider its dynamics such as vorticity [ABSTRACT FROM AUTHOR]

There is ample evidence for ice layers and lenses within glacial firn. The standard model for ice layer formation localizes the refreezing by perching of meltwater on pre‐existing discontinuities. Here we argue that even extreme melting events provide insufficient flux for this mechanism. Using a thermomechanical model we demonstrate a different mechanism of ice layer formation. After a melting event when the drying front catches up with the wetting front and arrests melt percolation, conductive heat loss freezes the remaining melt in place to form an ice layer. This model reproduces the depth of a new ice layer at the Dye‐2 site in Greenland. It provides a deeper insight into the interpretation of firn stratigraphy and past climate variability. It also improves the simulation of firn densification processes, a key source of uncertainty in assessing and attributing ice sheet mass balance based on satellite altimetry and gravimetry data. Plain Language Summary: Firn covers a significant portion of Earth's glaciers and ice sheets. It can store surface meltwater and prevent runoff into the ocean. The widespread presence of ice layers embedded in firn formed by meltwater refreezing may prevent meltwater storage and contribute to sea level rise. However, current models of ice layer formation, originally developed for snow, do not seem to work in firn. This work presents a different mechanism for ice layer formation without invoking pre‐existing ice layers within the firn. Our model shows that the sequencing of ice layers formed by subsequent melting events depends on the overall heat added to the firn. Deeper layers occur in warmer, more porous firn during intense melt events in a warming climate. This insight enhances our understanding of firn layering and can help deduce past climate variations. Our model aids in understanding the density evolution of firn to reduce uncertainties in remote sensing data that determines the ice sheet mass loss and its contribution to global sea‐level rise. Key Points: A new ice layer forms without meltwater perching when freezing localizes after a melt event as heat conduction dominates over advectionDeeper ice layers form in warming climatic conditions whereas denser ice layers form near surface in net‐zero climatic conditionsResults indicate the possibility of deducing past variability in climate from firn stratigraphy and vice versa [ABSTRACT FROM AUTHOR]

Aim: Climate change has profound effects on species' distributions, and it is crucial to understand how well physiological limits correspond to distribution patterns to provide realistic estimations of future range shifts and/or extinctions. Seaweeds are foundation species of global coastal ecosystems, and sea surface temperature is a main predictor to explain their distributions and redistributions under global warming. We here test the hypothesis that, in contrast to other marine ectotherms, physiological knowledge of temperature niches is a weak predictor for seaweed distributions. Location: Global. Time Period: Present (1984–2019). Taxa: Seaweeds. Methods: We analysed the predictive power of physiological temperature limits to predict real‐world distributions in 126 globally distributed seaweed species with linear and generalized linear mixed models. Results: In 72% of the species, there was a difference of ≥|2|°C between the physiological and the realized thermal limits. Both, thermal underfilling (distributional thermal limits narrower than the physiological limits) and overfilling (distributional thermal limits wider than the physiological limits) were present. Thus, in only 28% of the species the physiological limits corresponded to the distributional limits. While heat‐tolerance is a significant predictor for upper distributional temperature limits, we found no relationship between cold‐tolerance and lower distributional temperature limits and the latter two seem to be independent. Main Conclusions: Physiological thermal limits have limited predictive power for seaweed distributions and deviations may be large. Especially cold‐tolerances are a weak predictor, and forecasting of migrations under changing global conditions (e.g. towards the poles) will need special attention. This indicates that responses towards climate change might be highly variable between seaweed species and difficult to predict. Further, nearly 60% of the investigated species had populations which are close to or beyond their reported upper survival limits and are thus probably under threat of eradication by elevation of sea surface temperature. [ABSTRACT FROM AUTHOR]

Drought is more frequent and intensified due to global warming. Changed conditions in Beijing‐Tianjin–Hebei region which is drier and warmer than before, make it necessary to investigate various optimized irrigation schemes in the winter wheat production. In this study, the DSSAT–CERES‐Wheat model verified by field experimental data was applied to simulate the yield of winter wheat in Beijing–Tianjin–Hebei region from 2010 to 2069a under RCP8.5 climate scenario. The irrigation schemes were set up by adjusting the irrigation amount and irrigation structure to evaluate their adaptive capacity to climate change. The results showed that the regional average yield reduction rates of potential drought were 81.98% and 78.86% in 2010–2039a and 2040–2069a, which were higher in the north than that in the south. The yield reduction rate of potential drought increased with the decrease of irrigation amount, and the adaptive capacity declined with the decrease of irrigation amount, under the same irrigation structure. When 3‐9‐6 irrigation structure was applied, the regional averages of adaptive capacity to potential drought were 28.30%, 26.23%, and 22.22% in 2010–2039a, 29.00%, 26.67%, and 21.76% in 2040–2069a. The shortage of water resources caused by climate change and the possibility of drought limit the potential yield of winter wheat as high as 80% in this region. Priority shall be given to meeting the water demand in jointing stage and filling stage. Irrigation scheme of 3‐9‐6 structure with 180 mm irrigation amount shall be recommended and its adaptive capacity to climate change is the strongest in the near term and the medium‐term. Even if a further 20% reduction in irrigation is applied (144 mm), the dual goals of reducing yield loss and saving 8.28 × 108 t irrigation water per winter wheat season can be achieved. [ABSTRACT FROM AUTHOR]

This is the first paper that analyzes data from atmosphere model intercomparison project‐type climate simulations using a cloud‐system‐resolving global nonhydrostatic model without cumulus parameterization focussing particulaly on the relationship between clouds and circulation, and their changes due to global warming. The decrease in fractional coverage of low clouds is key to evaluating cloud radiative effects, because changes in shortwave cloud radiative effects overwhelm those of longwave cloud radiative effects. Thus, improved evaluation of low clouds is important, even in high‐resolution climate simulations. An analysis of heat redistribution by explicitly computed clouds revealed that column‐integrated heating rate due to phase changes correlates highly with vertical velocity at the altitude corresponding to 500 hPa and is closely linked to column water vapor, similar to the present climate result. Using data from year 1 to year 5, the effective climate sensitivity was evaluated to be 3.6−3.7°C. Possible convective aggregation is also examined using an index of modified subsidence fraction and characteristic changes in the number of cold pools. Despite previous idealized‐planet simulations showing more aggregated tropical convection under warmer conditions, here we show a decrease in the subsidence fraction and an increase in the number of smaller cold pools, suggesting that it is possible to realize less convective organization with warming under real atmospheric conditions. Key Points: We used global nonhydrostatic climate simulations to study how clouds and large‐scale circulations change in response to global warmingChanges in the shortwave cloud radiative effect are key to evaluating the net cloud radiative effect, even in high‐resolution simulationsWe found no evidence of an increased amount of tropical convective aggregation in response to global warming [ABSTRACT FROM AUTHOR]

Global mean precipitation changes due to climate change were previously shown to be relatively small and well constrained by the energy budget. However, local precipitation changes can be much more significant. In this paper we propose that for large enough scales, for which the water budget is closed (precipitation [P] roughly equals evaporation [E]), changes in P approach the small global mean value. However, for smaller scales, for which P and E are not necessarily equal and convergence of water vapor still plays a role, changes in P could be much larger due to dynamical contributions. Using 40 years of two reanalysis data sets, 39 Coupled Model Intercomparison Project Phase 5 (CMIP5) models and additional numerical simulations, we identify the scale of transition in the importance of the different terms in the water budget to precipitation to be ~3,500–4,000 km and demonstrate its relation to the spatial scale of precipitation changes under climate change. Plain Language Summary: Predicting precipitation changes due to climate change is of great importance for society. We propose that the present‐day characteristic scale of the hydrological cycle (for which precipitation roughly equals evaporation) predicts the spatial scale of future precipitation changes under global warming. For smaller scales than the characteristic scale of the hydrological cycle, changes in precipitation could be much larger than the global mean change due to water vapor convergence contributions. However, above this scale the precipitation changes approach the relatively small global mean change. Using reanalysis data sets, Coupled Model Intercomparison Project Phase 5 (CMIP5) models, and additional numerical simulations, we identify the characteristic scale of the hydrological cycle to be ~3,500–4,000 km and demonstrate its relation to the spatial scale of precipitation changes under climate change. These results suggest that changes in precipitation on the regional‐continental scale could be much larger than the global mean change. Key Points: The present‐day characteristic scale of the hydrological cycle predicts the spatial scale of precipitation changes under climate changeUsing reanalysis data sets and CMIP5 models, we identify the characteristic scale of the hydrological cycle to be ~3,500–4,000 kmThese results suggest that changes in precipitation on the continental scale could be much larger than the global mean change [ABSTRACT FROM AUTHOR]

The response of soil organic carbon (SOC) decomposition to global warming is a potentially major source of uncertainty in climate prediction. However, the magnitude and direction of SOC cycle feedbacks under climate warming remain uncertain because of the knowledge gap about the global‐scale spatial pattern and temperature sensitivity (Q10) mechanism of SOC decomposition.Here, we collected data of Q10 and corresponding soil variables from 81 peer‐reviewed papers using laboratory incubation to explore how Q10 varied among different ecosystems at the global scale and whether labile and recalcitrant SOC pools had equal Q10 values.Q10 with a global average of 2.41 substantially varied among different ecosystems, ranging from the highest in cropland soils (2.76) and the lowest in wetland soils (1.84). Hump‐shaped correlations of Q10 values with the maximum at SOC = 190 g/kg and the minimum at clay = 37% were observed. However, the main influencing factors of Q10 differed among various ecosystems. Q10 values showed a clear decrease with increasing incubation temperature but no significant decrease above 25°C. In general, labile SOC was less sensitive than recalcitrant SOC to warming. Structural equation model analyses showed that total N and SOC accounted for 53% and 46%, respectively, of the variation in Q10 of labile SOC and recalcitrant SOC. This finding suggested that Q10 values of labile and recalcitrant SOC pools had different controlling factors.Our findings highlighted the importance of Q10's variations in ecosystem types and the response of recalcitrant SOC to warming in predicting the soil C cycling and its feedback to climate change. Therefore, ecosystem type and difference in Q10 of labile and recalcitrant SOC should be considered to precisely predict the soil C dynamics under global warming. A plain language summary is available for this article. Plain Language Summary [ABSTRACT FROM AUTHOR]

The Fixed Anvil Temperature (FAT) hypothesis proposes that upper tropospheric cloud fraction peaks at a special isotherm that is independent of surface temperature. It has been argued that a FAT should result from simple ingredients: Clausius‐Clapeyron, longwave emission from water vapor, and tropospheric energy and mass balance. Here the first cloud‐resolving simulations of radiative‐convective equilibrium designed to contain only these basic ingredients are presented. This setup does not produce a FAT: the anvil temperature varies by about 40% of the surface temperature range. However, the tropopause temperature varies by only 4% of the surface temperature range, which supports the existence of a Fixed Tropopause Temperature (FiTT). In full‐complexity radiative‐convective equilibrium simulations, the spread in anvil temperature is smaller by about a factor of 2, but the tropopause temperature remains more invariant than the anvil temperature by an order of magnitude. In other words, our simulations have a FiTT, not a FAT. Plain Language Summary: Tropical anvil clouds play a large role in Earth's radiation balance, and their effect on anthropogenic global warming has been a point of contention. One popular school of thought is the Fixed Anvil Temperature (FAT) hypothesis, which argues that no matter how much the Earth warms, anvil clouds would continue to radiate to space at the same temperature. This behavior would amplify the warming caused by the addition of greenhouse gases to the atmosphere. In this paper, we show that the chain of logic underlying the FAT hypothesis—which attributes anvil cloud formation to a rapid decline of radiative cooling at the top of the troposphere—contains many weak and unsupported links. These weak links undermine the FAT hypothesis, which does not hold empirically in our simulations. However, the radiative tropopause does remain at a fixed temperature as the surface warms in our simulations. Therefore, we find evidence for a Fixed Tropopause Temperature (FiTT) rather than a FAT. There is currently no accepted theory for the tropopause temperature or why it appears to be independent of the surface temperature. Key Points: A Fixed Anvil Temperature (FAT) does not result from temperature‐dependent longwave radiative emission from water vaporSimulations of radiative‐convective equilibrium without a FAT still have a Fixed Tropopause Temperature (FiTT)A FiTT does not imply a FAT because anvil clouds are not produced by enhanced detrainment below the tropopause [ABSTRACT FROM AUTHOR]

In the Paris Agreement countries have agreed to act together to hold global warming well below 2°C over preindustrial levels and to pursue efforts to limit warming to 1.5°C. To assess if the world is on track to meet this long‐term temperature goal, countries' pledged emissions reductions (Nationally Determined Contributions, NDCs) need to be analyzed for their implied warming. Several research groups and nongovernmental organizations have estimated this warming and arrived at very different results but have invariably concluded that the current pledges are inadequate to hold warming below 2°C, let alone 1.5°C. In this paper we analyze different methods to estimate 2100 global mean temperature rise implied by countries' NDCs, which often only specify commitments until 2030. We present different methods to extend near‐term emissions pathways that have been developed by the authors or used by different research groups and nongovernmental organizations to estimate 21st century warming consequences of Paris Agreement commitments. The abilities of these methods to project both low and high warming scenarios in line with the scenario literature is assessed. We find that the simpler methods are not suitable for temperature projections while more complex methods can produce results consistent with the energy and economic scenario literature. We further find that some methods can have a strong high or low temperature bias depending on parameter choices. The choice of methods to evaluate the consistency of aggregated NDC commitments is very important for reviewing progress toward the Paris Agreement's long‐term temperature goal. Key Points: Several methods to project 2100 temperature rise from countries' climate commitments are introduced and analyzedSimple methods can neither reproduce the scenario literature nor assess if emissions reduction pledges are 2°C consistentScenario database‐based methods can reproduce literature ranges and be suitable for the assessment of Paris Agreement commitments [ABSTRACT FROM AUTHOR]

Abstract: Alpine and Arctic treeline expansion depends on establishment of tree seedlings beyond the current treeline, which is expected to occur with climate warming. However, treelines often fail to respond to higher temperatures, and it is therefore likely that other environmental factors are important for seedling establishment. We aimed to analyse our current understanding of how temperature and a range of other environmental drivers affect tree seedling establishment at the alpine and Arctic treelines world‐wide and to assess the relative importance of temperature compared with other factors and how they interact. We collected 366 observations from 76 experimental and observational papers for a qualitative analysis of the role of a wide range of environmental factors on tree seed germination, tree seedling growth, survival and natural occurrence. For a subset of these studies, where the experimental design allowed, we conducted formal meta‐analyses to reveal if there were global drivers for different seedling life traits. The analyses showed that a wide range of abiotic and biotic factors affected tree seedling establishment besides from temperature, including water, snow, nutrients, light and surrounding vegetation. The meta‐analyses showed that different seedling life stages do not respond similarly to environmental factors. For example, temperature had positive effects on growth, while tree seedling survival and germination showed mixed responses to warming. Further, warming was as often as not the strongest factor controlling tree seedling establishment, when compared to with one of five other environmental factors. Moreover, warming effects often depended on other factors such as moisture or the presence of surrounding vegetation. Our results suggest that population dynamics of trees at the alpine and Arctic treeline is responsive to environmental changes and show that there is a clear need for multifactorial studies if we want to fully understand and predict the interplay between warming and other environmental factors and their effect on tree seedling establishment across current treelines. A plain language summary is available for this article. [ABSTRACT FROM AUTHOR]

Community‐level climate change indicators have been proposed to appraise the impact of global warming on community composition. However, non‐climate factors may also critically influence species distribution and biological community assembly. The aim of this paper was to study how fire–vegetation dynamics can modify our ability to predict the impact of climate change on bird communities, as described through a widely‐used climate change indicator: the community thermal index (CTI). Potential changes in bird species assemblage were predicted using the spatially‐explicit species assemblage modelling framework – SESAM – that applies successive filters to constrained predictions of richness and composition obtained by stacking species distribution models that hierarchically integrate climate change and wildfire–vegetation dynamics. We forecasted future values of CTI between current conditions and 2050, across a wide range of fire–vegetation and climate change scenarios. Fire–vegetation dynamics were simulated for Catalonia (Mediterranean basin) using a process‐based model that reproduces the spatial interaction between wildfire, vegetation dynamics and wildfire management under two IPCC climate scenarios. Net increases in CTI caused by the concomitant impact of climate warming and an increasingly severe wildfire regime were predicted. However, the overall increase in the CTI could be partially counterbalanced by forest expansion via land abandonment and efficient wildfire suppression policies. CTI is thus strongly dependent on complex interactions between climate change and fire–vegetation dynamics. The potential impacts on bird communities may be underestimated if an overestimation of richness is predicted but not constrained. Our findings highlight the need to explicitly incorporate these interactions when using indicators to interpret and forecast climate change impact in dynamic ecosystems. In fire‐prone systems, wildfire management and land‐use policies can potentially offset or heighten the effects of climate change on biological communities, offering an opportunity to address the impact of global climate change proactively. [ABSTRACT FROM AUTHOR]

Abstract: At the 21st session of the United Nations Framework Convention on Climate Change Conference of the Parties (COP21) in Paris, an agreement to strengthen the effort to limit the global temperature increase well below 2°C was decided. However, even if global warming is limited, some regions might still be substantially affected by climate change, especially for continents like Africa where the socio‐economic conditions are strongly linked to the climatic conditions. In the paper we will discuss the analysis of indices assigned to the sectors health, agriculture, and infrastructure in a 1.5, 2, and 3°C global warming world for the African continent. For this analysis an ensemble of 10 different general circulation model‐regional climate model simulations conducted in the framework of the COordinated Downscaling EXperiment for Africa was investigated. The results show that the African continent, in particular the regions between 15°S and 15°N, has to expect an increase in hot nights and longer and more frequent heat waves even if the global temperature will be kept below 2°C. These effects intensify if the global mean temperature will exceed the 2°C threshold. Moreover, the daily rainfall intensity is expected to increase toward higher global warming scenarios and will affect especially the African Sub‐Saharan coastal regions. [ABSTRACT FROM AUTHOR]

Forests provide essential ecosystem services that range from the production of timber to the mitigation of natural hazards. Rapid environmental changes, such as climate warming or the intensification of disturbance regimes, threaten forests and endanger forest ecosystem services. In light of these challenges, it is essential to understand forests' demographic processes of regeneration, growth, and mortality and their relationship with environmental conditions. Specifically, understanding the regeneration process in present‐day forests is crucial since it lays the foundation for the structure of future forests and their tree species composition. We used Swiss National Forest Inventory (NFI) data covering vast bio‐geographic gradients over four decades to achieve this understanding. Trees that reached a diameter at breast height of 12 cm between two consecutive NFI campaigns were used to determine regeneration and were referred to as ingrowth. Employing three independent statistical models, we investigated the number, species, and diameter of these ingrowth trees. The models were subsequently implemented into a forest simulator to project the development of Swiss forests until the mid‐21st century. The simulation results showed an ingrowth decrease and a shift in its species composition, marked by a significant reduction in Norway spruce Picea abies and concurrent increases in broadleaves. Nevertheless, the pace of this change towards climatically better adapted species composition is relatively slow and is likely to slow down even further as ingrowth declines in the future, in contrast to the fast‐changing climatic conditions. Hence, support through adaptive planting strategies should be tested in case ingrowth does not ensure the resilience of forests in the future. We conclude that since the regeneration of forests is becoming increasingly challenging, the current level at which ecosystem services are provided might not be ensured in the coming decades. [ABSTRACT FROM AUTHOR]

In a warming climate, an intensifying fire regime and higher likelihood of extreme rain are expected to increase watershed sediment yield in many regions. Understanding regional variability in landscape response to fire and post‐fire rainfall is essential for managing water resources and infrastructure. We measured sediment yield resulting from sequential wildfire and extreme rain and flooding in the upper Carmel River watershed (116 km2), on the central California coast, USA, using changes in sediment volume mapped in a reservoir. We determined that the sediment yield after fire and post‐fire flooding was 854–1,100 t/km2/yr, a factor of 3.5–4.6 greater than the long‐term yield from this watershed and more than an order of magnitude greater than during severe drought conditions. In this first large‐scale field validation test of the WEPPcloud/wepppy framework for the Water Erosion Prediction Project (WEPP) model on a burned landscape, WEPP predicted 81%–106% of the measured sediment yield. These findings will facilitate assessing and predicting future fire effects in steep watersheds with a Mediterranean climate and indicate that the increasingly widespread use of WEPP is appropriate for evaluating post‐fire hillslope erosion even across 100‐km2 scales under conditions without debris flows. Plain Language Summary: In a warming climate, more wildfire and more extreme rain will cause more erosion, producing more sediment that will be carried downstream by rivers. Understanding how much sediment a landscape produces after fire and extreme rain is essential for managing water resources and infrastructure, because sediment fills up storage space in reservoirs and can interfere with proper functioning of water systems and roads. We measured how much sediment was produced in a watershed due to wildfire followed by extreme rain and flooding, studying the Carmel River on the central California coast, USA. We evaluated how much sediment this watershed produced by measuring the volume of sediment deposited within a reservoir that the watershed drains into. We determined that the rate of sediment exported from the study watershed due to a large fire and post‐fire floods was much greater than the long‐term rate there. Having compared our results with the amount of sediment predicted by a model called the Water Erosion Prediction Project model, we found that the model performed well and realistically predicted the amount of sediment that this landscape would shed. These findings will facilitate assessing and predicting future fire effects in steep watersheds with a Mediterranean‐type climate. Key Points: A 116‐km2 central California watershed produced sediment yield of 854–1,100 t/km2/yr in the first year after a fire and extreme rainPost‐fire sediment yield in an extremely wet year without debris flows was 3.5–4.6 times greater than the long‐term rateThe Water Erosion Prediction Project model predicted 81%–106% of the measured post‐fire sediment eroded from hillslopes [ABSTRACT FROM AUTHOR]

Species distribution models (SDMs) are often built upon the "niche conservatism" assumption, such that they ignore the possibility of "evolutionary rescue" and may underestimate species' future range limits under climate change. We select aphids and ladybirds as model species and develop an eco‐evolutionary model to explore evolutionary rescue in a predator–prey system under climate change. We model the adaptive change of species' thermal performances, accounting for biotic interactions. Our study suggests that, without considering evolutionary adaptation, the warming climate will result in a reduction in aphid populations and the extinction of ladybirds in large parts of the United States. However, when incorporating evolutionary adaptation into the model, aphids can adapt to climate change, whereas ladybirds demonstrate geographic variation in their evolutionary rescue potential. Specifically, ladybirds in southern regions are more likely to be rescued than those in the north. In certain northern regions, ladybirds do not avoid extinction due to severe warming trends and seasonality of the climate. While higher warming trends do prompt stronger evolutionary changes in phenotype, they also lead to reduced aphid population abundance such that ecology constrains ladybird population growth. Higher seasonality induces an ecological effect by limiting the length of reproductive season, thereby reducing the capacity for evolutionary rescue. Together, these findings reveal the complex interplay between ecological and evolutionary dynamics in the context of evolutionary adaptation to climate change. [ABSTRACT FROM AUTHOR]

Probabilistic projections from the UK Climate Projections 2018 are presented for four global warming levels (GWLs) at 1.5, 2, 3, and 4°C above the 1850–1900 baseline. Our results show how uncertainties associated with climate models and four representative concentration pathways (RCP) emission scenarios translate to UK regional scale changes in maximum temperature and precipitation, with data also available for minimum and mean temperatures, humidity and surface net downward shortwave radiation flux. We compare weighting the likelihood of RCPs based on (hypothetical) policy decisions, against our baseline assumption that each RCP is equally likely. Differences between weighted and unweighted GWL distributions are small, particularly in relation to the full breadth of uncertainties that are incorporated into the probabilistic projections. Finally we quantify the relative importance of scenario, model and internal variability on regional projected GWLs and show that uncertainty associated with an uncertain climate response to forcings dominates at all GWLs. Plain Language Summary: Global warming levels define the global averaged increase in temperature since the pre‐industrial period. This study looks at what the regional climate in the UK could be like in the future. We estimate how temperature and precipitation in the UK might change under four different global warming levels (GWLs) (1.5, 2, 3, and 4°C above pre‐industrial times). We account for a wide range of outcomes from both climate models and future emissions scenarios. Assuming that the range of future emissions scenarios are equally likely, the center of the ranges of years that we could reach GWLs of 1.5, 2, 3, and 4°C are 2032, 2050, 2072, and 2078 respectively. The largest influence of future climate on these range estimates comes from our understanding of how the Earth actually responds to changes in greenhouse gases. Even if we knew the exact quantity of greenhouse gas emissions we would emit in the future, we still wouldn't be able to predict the exact changes in UK climate with perfect accuracy because our understanding of the regional climate response to these emissions requires further investigation. Key Points: Probabilistic climate projections from the UK are presented for four global warming levels (GWLs) across four representative concentration pathways (RCP)We show how uncertainty associated with climate models and future emission scenarios translate to UK regional scale changesUncertainty associated with an uncertain climate response to forcings dominates at all GWLs [ABSTRACT FROM AUTHOR]

Surface, aircraft, and satellite measurements indicate pervasive early cold season (Augut–September) CO2 emissions across Arctic regions, consistent with increased ecosystem metabolism in plants and soils. A key remaining question is whether cold season sources will become large enough to permanently shift the Arctic into a net carbon source. Polar orbiting GHG satellites provide robust estimation of regional carbon budgets but lack sufficient spatial coverage and repeat frequency to track sink‐to‐source transitions in the early cold season. Mission concepts such as the Arctic Observing Mission (AOM) advocate for flying imaging spectrometers in highly elliptical orbits (HEO) over the Arctic to address sampling limitations. We perform retrieval and flux inversion simulation experiments using the AURORA mission concept, leveraging a Panchromatic imaging Fourier Transform Spectrometer (PanFTS) in HEO. Our simulations demonstrate the potential benefits of increased CO2 sampling for detecting emissions during the early cold season. Plain Language Summary: The Arctic is warming rapidly, leading to an acceleration of carbon exchange across tundra and boreal ecosystems. These changing flows of carbon can be difficult to detect using traditional observing systems. We propose that measurement systems which observe Arctic ecosystems continuously from a quasi‐GEO orbit can more accurately detect these important changes, such that unexpected and dangerous feedbacks to climate warming can be monitored and accounted for. Key Points: The Arctic Fourier Transform Spectrometer Investigation (AURORA) mission concept addresses GHG sampling limitations in the ArcticAURORA uses a highly elliptical orbit (HEO) to increase repeat frequency, and a panchromatic iFTS for SWIR O2 and CO2 bands (0.7–2.5 μm)Simulation experiments show potential benefits of increased sampling frequency for grid scale detection of early cold season CO2 emissions [ABSTRACT FROM AUTHOR]

Basic ecological theory suggests that a tradeoff between competitiveness and stress tolerance dictates species range limits at regional extents. However, empirical support for this key theory remains deficient because the necessary spatial and temporal coverage and scalability of field observations has rarely been achieved. We harnessed an extensive dendroecological network (> 22 000 tree‐ring samples from 816 forest inventory plots) to disentangle competition‐limited from climate‐limited growth in both overstory and understory trees. Growth synchrony among trees thereby served as an integral metric of climate sensitivity, an approach that we justify in supplementary analyses of growth responses to temperature, precipitation, and the standardized precipitation‐evapotranspiration index. Sampling plots were arranged along elevational climate and vegetation gradients throughout the Carpathian Mountains, ranging from mixed‐species lowland forests to coniferous forests at high elevations. With mixed‐effect modelling, we also identified non‐climatic factors (stand characteristics, species diversity, and disturbance history) that modulate spatial patterns in the growth rate and synchrony of European beech Fagus sylvatica and Norway spruce Picea abies. Beech exhibited reduced growth and increased climate sensitivity towards higher elevations but performed better when species diversity was higher. The growth of spruce increased towards its lower range boundary, but understory cohorts grew poorly under interspecific competition. Overall, climate sensitivity was lower in more productive stands with benign climatic conditions and in recently disturbed sites with reduced stand density. These contrasting performances at mid‐elevations where the two species overlap (900–1300 m a.s.l.) reflect their evolutionary history, which enables them to be competitive (beech) or cold‐stress tolerant (spruce). This history will affect interactions between the two species under climate warming and shape macroecological patterns in the Carpathian ecoregion and likely other parts of Europe. Our findings point to a growing advantage of competitively stronger species in montane and subalpine vegetation zones. [ABSTRACT FROM AUTHOR]

The impact of global warming on lightning flash rates remains relatively unknown. In this study, the South China Sea (SCS) and the surrounding areas within Southeast Asia were selected to examine the long‐term trend and future projection of lightning activity based on the currently longest satellite‐based lightning data set available and climate models. Our study revealed a reduction in the observed lightning flash rates around the SCS, with a linear trend of −0.11 fl km−2 yr−2 during 1996–2013. In contrast, the precipitation around the SCS exhibited an increasing trend and was negatively correlated with the local lightning flash rate. The sea surface temperature gradient over equatorial Pacific Ocean, latent heat flux over the equatorial Indian Ocean, local convective available potential energy, precipitation and aerosol changes collectively accounted for 82% of the variance in the lightning fluctuations over the SCS and Southeast Asia. Multiple linear regression proxies of lightning flash rates were constructed and applied to the climate models. The models indicated that lightning activity around the SCS is projected to intensify by 10% and 12% by the end of the 21st century under SSP245 and SSP370, respectively. Plain Language Summary: The projection of future changes in lightning activity is uncertain owing to various factors, and different regions exhibit distinct trajectories. In this study, the focus was on the South China Sea (SCS) and Southeast Asia, and past variations in lightning activity was examined and used to predict future variations in lightning activity. Employing a multiple linear regression approach, we identified the large‐scale thermodynamic drivers and local environmental factors that influence lightning activity around the SCS. The research findings indicated a reduction in lightning activity over the past few decades over the SCS and Southeast Asia region. The simulation results indicate that in the future under ongoing global warming, regional lightning activity will intensify. Key Points: Lightning activity and precipitation show opposing regional trends around the South China Sea (SCS)Remote thermodynamic and local environmental factors both contribute to the variability in lightning around the SCSUnder future climate change scenarios, lightning activity around the SCS is projected to gradually increase [ABSTRACT FROM AUTHOR]

Global warming exacerbates the increase of soil moisture drought by accelerating the water cycle, posing potential threats to food security and ecological sustainability. The design of drought prevention and mitigation policies should be based on the reliable detection of the future change signal in droughts, so it is critical to know when the signal can be detected (Time of Emergence, ToE) in the background noise of the climate system. While the ToE framework has been successfully applied for temperature‐related signal detection, the ToE for changes in drought has not been well studied. Based on 66 Coupled Model Intercomparison Project Phase 6 model ensemble members under four Shared Socio‐economic Pathways, we conduct a global ToE analysis of seasonal soil moisture drought characteristics and discuss the impact of different warming levels. Six subregions with robust increase in soil moisture droughts are identified. For drought frequency, most of the subregion's ToE is centered around 2080, however for drought intensity it is much earlier and can even reach around 2040 in AMZ. For drought frequency and drought intensity, approximately 14%–22% and 47%–49% of global land areas would reach ToE in 21st century. The global land areas with ToE of increasing droughts would increase by at least 1/5 when global warming level is kept to 2°C rather than 1.5°C above pre‐industrial conditions. This suggests that limiting global warming can significantly delay the emergence time of increases in seasonal soil moisture droughts, allowing additional adaptation time for the drought‐related sectors. Plain Language Summary: Global warming has increased the frequency of droughts, especially soil moisture droughts with widespread impacts. Thus, when would the soil moisture drought change exceed the noise of the climate system and signal "emerge" (Time of Emergence, ToE) has far‐reaching implication for relevant government departments and stakeholders to make corresponding adaptations. In this work, the future changes in seasonal soil moisture droughts are projected by using Coupled Model Intercomparison Project Phase 6 (CMIP6, multi‐model simulations of historical and future climate) data under four possible future development scenarios (named Shared Socio‐economic Pathways), and the effects of controlling global warming levels on the ToE of droughts are discussed. Results show that the frequency of seasonal soil moisture droughts would increase over 42%–48% of global land areas in the future, and 14%–22% of global land areas would show detectable signals of increased drought frequency before 2100. If the global warming level is controlled within 2°C rather than 1.5°C, the areas with ToE would increase by at least one fifth, except for drought intensity under the scenario of the most energy‐saving and emission reduction. This work highlights the risk of rapid emergence of robust soil moisture drought increases under climate change. Key Points: The timing of detectable future changes in seasonal soil moisture droughts are identified through the time of emergence frameworkDetectable increase signals in drought frequency and intensity are predicted in 14%–22% and 47%–49% of land areas by the end of this centuryThe areas of detectable signals for drought characteristics would increase by 1/5 when limiting warming within 2°C compared to 1.5°C [ABSTRACT FROM AUTHOR]

Climate change poses a particular threat to long‐lived trees, which may not adapt or migrate fast enough to keep up with rising temperatures. Assisted gene flow could facilitate adaptation of populations to future climates by using managed translocation of seeds from a warmer location (provenance) within the current range of a species. Finding the provenance that will perform best in terms of survival or growth is complicated by a trade‐off. Because trees face a rapidly changing climate during their long lives, the alleles that confer optimal performance may vary across their lifespan. For instance, trees from warmer provenances could be well adapted as adults but suffer from colder temperatures while juvenile. Here we use a stage‐structured model, using both analytical predictions and numerical simulations, to determine which provenance would maximize the survival of a cohort of long‐lived trees in a changing climate. We parameterize our simulations using empirically estimated demographic transition matrices for 20 long‐lived tree species. Unable to find reliable quantitative estimates of how climatic tolerance changes across stages in these same species, we varied this parameter to study its effect. Both our mathematical model and simulations predict that the best provenance depends strongly on how fast the climate changes and also how climatic tolerance varies across the lifespan of a tree. We thus call for increased empirical efforts to measure how climate tolerance changes over life in long‐lived species, as our model suggests that it should strongly influence the best provenance for assisted gene flow. [ABSTRACT FROM AUTHOR]

Under the current pattern of climate change, mountain bird populations are generally shifting their ranges to higher elevations, tracking their climatic optima. Nevertheless, space limitations at high altitudes constrain mountain species' resilience to climatic change, making them particularly vulnerable. In extreme cases, the climatic niche of some species can move beyond mountaintops, ultimately driving such species to extinction. This study presents the case of the northern wheatear Oenanthe oenanthe in mainland Spain and compares its breeding distribution from 2003 to 2022. Spain, where the species mostly occupies mountain areas, represents its southernmost distribution limit in Europe. We built environmental favourability models using information from the two most recent Spanish bird atlases and a set of climatic, topographic, human activity and lithological variables to determine the factors affecting the occurrence of the species. The influence of climate compared to all other factors was obtained using variation partitioning analysis. The northern wheatear has suffered a strong reduction (67%) in occupied areas and also in favourability throughout mainland Spain (especially in the south) where climate change may have far‐reaching consequences, including local extinctions. Climate explained more than 90% of the variation in the model obtained for 2022. Interestingly, the occupied areas were, on average, 100 m higher in 2022 than in 2003. If the effects of climate warming persist, the northern wheatear will likely disappear in its southernmost distribution limit, being the Sierra de las Nieves National Park population the most vulnerable in mainland Spain. For this reason, it is necessary to implement monitoring programmes for northern wheatear populations, with priority for mountain systems wherein they already occupy higher elevations, as well as further studies on other mountain species. [ABSTRACT FROM AUTHOR]