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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]

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]

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 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]

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]

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]

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]

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]

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]

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]

Recent years were characterized by spatially co‐occurring hot and wet extremes around the globe, raising questions about the contribution of human‐induced global warming to the changing likelihoods of such extreme years. To characterize spatially co‐occurring extremes we investigate recent trends in global and regional land area that is concurrently affected by hot or wet annual maxima taking observational uncertainty into account. Observed trends in the land area affected by extreme events are assessed in the context of Earth System Model (ESM) simulations for present‐day and early‐industrial climate conditions in a detection and attribution setting. We compare different reanalysis and station‐based observational products to account for observational data uncertainty. At the global scale, trends of spatially co‐occurring hot or wet annual maxima in all observational products can be explained by ESM simulations driven by historical radiative forcing that accounts for human‐induced changes in the composition of the atmosphere but cannot be explained by ESM simulations that account for an early‐industrial radiative forcing. At the regional scale, trends in spatially co‐occurring hot annual maxima are in general coherent among observational products and can in most cases be attributed to human influence on the climate system. Trends in spatially co‐occurring wet annual maxima show differences in some regions, highlighting the importance of a multi‐dataset approach to overcome observational product dependencies. Despite observational uncertainty, we find robust detection and attribution results for many regions. These results can complement previous assessments on regional exposure to hot and wet events from the new IPCC AR6 report. Plain Language Summary: Recent years were characterized by spatially co‐occurring hot and wet extremes around the globe, leading to questions about the contribution of human‐induced climate change to the occurrence of such extreme years. In this study, we investigate trends in the global and regional land area that is concurrently affected by hot or wet annual maxima. Due to observational uncertainties, we investigate different observation‐based data products for temperature and rainfall. By comparing observational trends in the land area affected by extreme events to respective trends from Earth System Model ensemble simulations accounting for climate conditions of the past decades and early‐industrial climate conditions, we can evaluate their attribution to human‐induced climate change. On the global scale, observed trends of spatially co‐occurring hot or wet annual maxima cannot be simulated by climate models when considering early‐industrial climate conditions, but are captured by climate models considering recent climate conditions. This holds also true for the detection and attribution of regional trends in concurrent land area affected by hot annual maxima. Observational products agree in many regions on the detection and attribution of regional trends in concurrent land area affected by wet annual maxima, but also disagree in some regions. Key Points: Global and regional trends of spatially concurrent hot or wet annual maxima can be attributed to human‐induced climate changeIn some regions observational products show inconsistencies in the sign of detectable trends in concurrent wet annual maximaLarge regional differences in spatial exposure and steady increase in concurrent land area affected by hot or wet annual maxima is detected [ABSTRACT FROM AUTHOR]

The influence of climate feedbacks on regional hydrological changes under warming is poorly understood. Here, a moist energy balance model (MEBM) with a Hadley Cell parameterization is used to isolate the influence of climate feedbacks on changes in zonal‐mean precipitation‐minus‐evaporation (P − E) under greenhouse‐gas forcing. It is shown that cloud feedbacks act to narrow bands of tropical P − E and increase P − E in the deep tropics. The surface‐albedo feedback shifts the location of maximum tropical P − E and increases P − E in the polar regions. The intermodel spread in the P − E changes associated with feedbacks arises mainly from cloud feedbacks, with the lapse‐rate and surface‐albedo feedbacks playing important roles in the polar regions. The P − E change associated with cloud feedback locking in the MEBM is similar to that of a climate model with inactive cloud feedbacks. This work highlights the unique role that climate feedbacks play in causing deviations from the "wet‐gets‐wetter, dry‐gets‐drier" paradigm. Plain Language Summary: Climate feedbacks, which act to amplify or dampen global warming, play an important role in shaping how the climate system responds to changes in greenhouse‐gas concentrations. Here, we use an idealized climate model, which makes a simplified assumption about how energy is transported in the atmosphere, to examine how climate feedbacks influence the patterns of precipitation and evaporation change under global warming. We find that the cloud feedback acts to narrow the band of rainfall on the equator known as the Intertropical Convergence Zone and that the surface‐albedo feedback acts to shift the location of maximum rainfall. We also find that the cloud feedback accounts for most of the uncertainty associated with feedbacks in regional hydrological change under warming. The idealized model with a locked cloud feedback also simulates a change in precipitation and evaporation that is similar to a comprehensive climate model with an inactive cloud feedback. Key Points: A moist energy balance model (MEBM) is used to investigate the influence of climate feedbacks on regional hydrological changes under warmingCloud feedbacks act to narrow and increase tropical P − E and are the dominant source of feedback uncertainty in regional hydrological changesThe MEBM with a locked cloud feedback largely replicates a climate model with an inactive cloud feedback [ABSTRACT FROM AUTHOR]

Future climate projections suggest a poleward shift of the maximum intensity of tropical cyclones (TCs) over the western North Pacific. However, the global nature of the latitudinal change in TC genesis under global warming remains poorly understood. We show, using large‐ensemble high‐resolution atmospheric model simulations (d4PDF) with four warming scenarios, that the poleward shift is a robust change over the globe, attributable to the weakening of the Hadley circulation. The weakened ascent driven by the upper‐tropospheric warming suppresses the TC genesis within 5°–20° latitudes, whereas the weakened descent enhances the TC genesis in the poleward latitudes. We further estimate the poleward shift of TC genesis to emerge at the 2 K global warming over the Arabian Sea, South Atlantic and Pacific Oceans and at the 4 K warming over the North Pacific. The present results underscore the potential for increasing social and economic risks associated with TCs at higher latitudes. Plain Language Summary: Climate models have projected a decrease in TC genesis frequency in future warming. However, the global nature of the latitudinal change in TC genesis under global warming remains uncertain partly due to insufficient resolution as well as the ensemble size of climate model simulations. We show a global feature of the robust poleward shift of the TC genesis during the active seasons of both hemispheres scaled with the global warming level, which can be attributed to the weakening of the Hadley circulation. The weakened ascending branch of the Hadley circulation, driven by the increased upper tropospheric warming, potentially hinders TC genesis within 5°–20° latitudes. Conversely, the weakened descending branch of the Hadley circulation enhances the likelihood of TC genesis within 20°–35° latitudes. We further estimate that the signal of TC genesis is expected to emerge over high latitudes of the Arabian Sea, South Atlantic and South Pacific Oceans at the 2 K warming and at the 4 K warming over the North Pacific. The present analyses have significant implications not only for assessing the reliability of future TC‐related changes in climate models but also for estimating the increased TC‐related hazards at higher latitudes under global warming. Key Points: We project a global feature of the robust poleward shift of tropical cyclone (TC) genesis during active seasons of both hemispheresMore TC genesis at high latitudes can be attributed to the weakening of the Hadley circulationPoleward shift of TC genesis emerges at 2 K warming over Arabian Sea, South Atlantic and Pacific Oceans and at 4 K warming over North Pacific [ABSTRACT FROM AUTHOR]

Based on outputs of 28 coupled models from the Phase 6 of the Coupled Model Intercomparison Project (CMIP6), we show that the response of the Southeast Asian summer monsoon to the El Niño‐Southern Oscillation (ENSO) during post‐ENSO summer will likely strengthen in a warmer climate, which can be attributed to concurrently weakened sea‐surface temperature anomalies (SSTAs) in the western equatorial Pacific (WEP). The weakened WEP SSTAs are primarily caused by enhanced latent heat damping due to increased surface wind speed anomalies, which are associated with the eastward shift of the El Niño‐induced anomalous Walker circulation due to El Niño‐like sea surface temperature change in the tropical Pacific under global warming. Besides, the climatological zonal ocean currents will slow down due to the weakening of climatological Walker circulation, which also acts to weaken the WEP SSTAs via reducing the advection of anomalous temperature by the mean current. Plain Language Summary: As an important component of the Asian monsoon system, the Southeast Asian summer monsoon (SEASM) is crucial for the livelihoods of billions of people in East Asia, and is closely connected to a climate phenomenon called El Niño‐Southern Oscillation (ENSO). Understanding how the relationship between SEASM and ENSO will change in the future is important for enhancing our knowledge of climate change in East Asia. Outputs of 28 climate models from the Phase 6 of the Coupled Model Intercomparison Project show that ENSO will exert enhanced impacts on the SEASM in a warmer climate. The enhanced influences of ENSO on the monsoon will exacerbate the reduction of rainfall over the western North Pacific during the post‐El Niño summer. We find that such projected changes are mainly caused by weakened warm sea surface temperature (SST) anomalies (SSTAs) in the western equatorial Pacific (WEP). Further analyses indicate that the change in WEP SSTAs can be linked to the El Niño‐like change in climatological SSTs in the tropical Pacific. This study depicts detailed physical processes responsible for the projected changes in ENSO's impacts on the SEASM. Key Points: The effects of the El Niño‐Southern Oscillation on the Southeast Asian summer monsoon will strengthen under global warmingThe enhanced El Niño's impacts result from the weakened warm sea‐surface temperature (SST) anomalies in the western equatorial Pacific (WEP)The weakened WEP SST anomalies are related to the eastward shift of anomalous Walker circulation and the slackened mean zonal ocean currents [ABSTRACT FROM AUTHOR]

In the coming decades, coastal flooding will become more frequent due to sea‐level rise and potential changes in storms. To produce global storm surge projections from 1950 to 2050, we force the Global Tide and Surge Model with a ∼25‐km resolution climate model ensemble from the Coupled Model Intercomparison Project Phase 6 High Resolution Model Intercomparison Project (HighResMIP). This is the first time that such a high‐resolution ensemble is used to assess changes in future storm surges across the globe. We validate the present epoch (1985–2014) against the ERA5 climate reanalysis, which shows a good overall agreement. However, there is a clear spatial bias with generally a positive bias in coastal areas along semi‐enclosed seas and negative bias in equatorial regions. Comparing the future epoch (2021–2050) against the historical epoch (1951–1980), we project ensemble‐median changes up to 0.1 (or 20%) in the 1 in 10‐year storm surge levels. These changes are not uniform across the globe with decreases along the coast of Mediterranean and northern Africa and southern Australia and increases along the south coast of Australia and Alaska. There are also increases along (parts) of the coasts of northern Caribbean, eastern Africa, China and the Korean peninsula, but with less agreement among the HighResMIP ensemble. Information resulting from this study can be used to inform broad‐scale assessment of coastal impacts under future climate change. Plain Language Summary: In the next few decades, coastal flooding is expected to become more frequent due to rising sea levels and changes in storms. To understand and prepare for these changes, we use a global hydrodynamic and multiple climate models to investigate how storm surges (a temporarily rise in water level during a storm) will respond to a warmer climate. These are the first global projections of storm surges based on highly detailed climate models (25–50 km). We compare the model output for recent years (1985–2014) with real‐world weather data, known as reanalysis data, and find a good overall agreement. However, the comparison also shows relatively large differences with larger or smaller values in certain areas. For the future (2021–2050), results show storm surge changes up to 20%. These changes vary around the world. Some areas (Mediterranean, northern Africa, and southern Australia) might experience lower storm surges, whereas other areas (South Australia, Alaska, the northern Caribbean, eastern Africa, China, and the Korean Peninsula) might experience higher storm surges. By using advanced computer models as done here, we are able to better understand how climate change could impact coastal area and thus make informed decisions for the future. Key Points: Storm surge projections from 1950 to 2050 based on the Global Tide and Surge Model and a ∼25 km‐resolution High Resolution Model Intercomparison Project climate model ensembleValidation against ERA5 reanalysis (1985–2014) shows that the model performs well globally, but also reveals a clear spatial biasThe median‐ensemble change of the 1 in 10‐year storm surge levels from 2021–2050 compared to 1951–1980 shows changes up to 0.1 m or 20% [ABSTRACT FROM AUTHOR]

Despite multiple advances in the understanding of the water cycle intensification in a warmer climate, climate models still diverge in their hydrological projections. Here we constrain annual runoff projections over individual and aggregated Arctic river basins. For this purpose, we use two ensembles of global climate models and two statistical methods: a regression scheme assuming similar runoff sensitivities at interannual versus climate change timescales, and a Bayesian method where models are used to derive a posterior runoff response conditioned on historical observations. While both techniques are shown to narrow model uncertainties, more or less substantially depending on rivers, the Bayesian method is less sensitive to the choice of the model ensemble and is more skillful when tested with synthetic observations. It has also been applied over the whole Arctic watershed, showing so far a limited narrowing of the inter‐model spread, but its skill will further improve with increasing climate change. Plain Language Summary: Despite considerable progress in understanding the intensification of the water cycle in response to global warming, projections of changes in the various components of the continental water balance remain highly model‐dependent. This is particularly the case for the evolution of runoff, which remains very sensitive to the way atmospheric and continental processes are represented. Here we evaluate and compare two statistical methods to constrain climate projections of annual runoff at high latitudes via available or synthetic observations. Our Bayesian method, based on historical observations, is found to be more robust than a previous method based on observed interannual climate variability. It underlines the importance of having reliable flow reconstructions to constrain runoff projections and of using empirical observational constraints with caution, as they are likely to lead to over‐confident projections. Key Points: Runoff sensitivity to temperature depends on the considered timescaleObservational constraints based on interannual variability can thus lead to overconfident projectionsObservational constraints based on historical trends can be effective if such trends are driven by human emissions of greenhouse gasses [ABSTRACT FROM AUTHOR]

We show that the seasonal cycles of clouds over the mid‐latitude oceans in the Northern Hemisphere are predictors of the responses of clouds to increasing sea‐surface temperatures globally. These regions are therefore "natural laboratories" in which the processes responsible for low‐cloud feedbacks on global scales are observed as seasonal changes in local cloud properties. We use an ensemble of configurations of a global‐climate model to show that the sensitivities of cloud‐radiative anomalies to surface temperature and lower‐tropospheric stability in the "laboratory" regions predict the models' global cloud‐radiative feedbacks. Models with greater changes in low‐clouds between seasons are shown to have stronger negative feedbacks in the mid‐latitudes, and stronger positive feedbacks from the subtropical stratocumulus. The biases in the simulated seasonal cycles, compared to observations, imply that both feedbacks are too weak in the model. The consequences of this for configuring our model to have a lower climate sensitivity are discussed. Plain Language Summary: As the Earth's climate warms, feedbacks from changes in clouds are crucial for determining the rate of warming. In some climate models, positive cloud feedbacks are known to contribute to projected temperature increases which fall outside the range that is considered plausible given our current understanding of the Earth's climate. Methods are needed which directly relate present‐day model errors to projected cloud feedbacks so that we can understand how to improve models and simultaneously obtain plausible feedback strengths. We show that in the Met Office Hadley Centres' climate model, the seasonal cycles of clouds in a few key regions, specifically the poleward ocean basins in the Northern Hemisphere, can be used to predict cloud feedbacks, globally, across a wide range of configurations of the model. These regions, particularly the North‐west Pacific, are "natural laboratories" in which the same processes that are responsible for global, cloud‐feedbacks onto global‐warming rates, occur annually as part of the local seasonal cycle. Studying clouds in these regions and model biases in predictions of these clouds will allow us to directly improve estimates of global climate change. Key Points: Seasonal cycles of clouds constrain cloud feedbacksThe northern ocean basins are natural laboratories for low‐cloud feedbacksThe hot‐model problem in HadGEM3 will not easily be solved by tuning [ABSTRACT FROM AUTHOR]

In contrast to the "wet gets wetter and dry gets drier" paradigm, here, using observations and climate model simulations, we show that the mean rainfall over the semi‐arid northwest parts of India and Pakistan has increased by 10%–50% during 1901–2015 and is expected to increase by 50%–200% under moderate greenhouse gas (GHG) scenarios. The GHG forcing primarily drives the westward expansion of the Indian summer monsoon rainfall (ISMR) and is facilitated by a westward expansion of the Indian Ocean (IO) warm pool. Mechanistically, the westward expansion of ISMR is a consequence of the episodic genesis over IO and the northward propagation of an expanded Inter‐Tropical Convergence Zone on a sub‐seasonal time scale. While an adaptation strategy to increased hydrological disasters is a must, harnessing the augmented rainfall would lead to a substantial boost in food productivity, bringing transformative changes in the socio‐economic condition of people in the region. Plain Language Summary: An apparent eastward shift of the Indian monsoon has led to the arid conditions in the west and north‐west regions of India where monsoon was once active, and the Indus Valley civilizations thrived (5,300–3,300‐year BP). A reversal of the process and a westward expansion of the present‐day Indian monsoon would transform the west and north‐west India to a humid "monsoonal" climate and provide food security to the expanding population of the country. The present study shows that the Indian monsoon is indeed expanding to the west with 10% decrease of mean rainfall in the northeast and 25% increase in the west and north‐west during the historical period with a potential of 50%–100% increase in the north‐west under SSP2–4.5. Harvesting the increased rainfall has the potential for significant increase in food productivity bringing in transformative changes in the socio‐economic condition of people of the region. Key Points: Global warming could potentially cause a westward expansion of the Indian monsoonRainfall in northwest India and Pakistan has increased and will continue to rise due to greenhouse gasesIncreased monsoon rainfall can improve food productivity and socio‐economic conditions in the region [ABSTRACT FROM AUTHOR]

Uncertainties associated with the response of shallow clouds to global warming remain a great challenge for climate projection. Due to the small size of these clouds, parameterizations are required to represent them in both current‐ and next‐generation climate models. We present a quantitative evaluation of several important assumptions used in both mass‐flux and Assumed‐PDF Higher‐Order Closure parameterizations of shallow convection. We use large‐eddy simulations (LESs) of four different shallow convection regimes as benchmarks and apply a qt (total moisture)–w (vertical velocity) quadrant analysis technique to identify the "coherent structures" of moist and dry up/down‐drafts. The statistics of these coherent structures and the environment are then used to evaluate commonly used assumptions in mass‐flux parameterizations related to (a) the convective downdrafts and (b) the subplume variability of convective updrafts. For quantitative evaluation of the PDF closure used in AP‐HOCs, we perform offline calculations with the PDF closure used in the Cloud Layers Unified By Bi‐normals and the Simplified Higher‐Order Closure schemes by supplying the closure with statistical quantities directly calculated from the LESs. Then, the impact of parameterization assumptions embedded in the PDF closure in the same two categories is analyzed and understood through comparisons of the output from the closure with the statistics of the moist and dry up/down‐drafts from the LESs. Plain Language Summary: This study examines critically several key simplifying assumptions about convective downdrafts and small‐scale variability associated with shallow clouds that are made in two types of shallow convection parameterizations widely used in numerical weather and climate models and demonstrates quantitatively the impact of these assumptions on the parameterized cloud water content, depth, and turbulent transport. Key Points: A qt–w quadrant analysis is applied to identify convective coherent structures in large‐eddy simulations of various shallow cloud regimesStatistics from the quadrant analysis is used to evaluate assumptions in mass‐flux and Assumed‐PDF Higher‐Order Closure shallow convection parameterizationsSimplifying assumptions on convective downdrafts and subplume variability are linked to parameterization deficiencies [ABSTRACT FROM AUTHOR]

Mortality due to extreme temperatures is one of the most worrying impacts of climate change. In this analysis, we use historic mortality and temperature data from 106 cities in the United States to develop a model that predicts deaths attributable to temperature. With this model and projections of future temperature from climate models, we estimate temperature‐related deaths in the United States due to climate change, changing demographics, and adaptation. We find that temperature‐related deaths increase rapidly as the climate warms, but this is mainly due to an expanding and aging population. For global average warming below 3°C above pre‐industrial levels, we find that climate change slightly reduces temperature‐related mortality in the U.S. because the reduction of cold‐related mortality exceeds the increase in heat‐related deaths. Above 3°C warming, whether the increase in heat‐related deaths exceeds the decrease in cold‐related deaths depends on the level of adaptation. Southern U.S. cities are already well adapted to hot temperatures and the reduction of cold‐related mortality drives overall lower mortality. Cities in the Northern U.S. are not well adapted to high temperatures, so the increase in heat‐related mortality exceeds the reduction in cold‐related mortality. Thus, while the total number of climate‐related mortality may not change much, climate change will shift mortality in the U.S. to higher latitudes. Plain Language Summary: Deaths due to extreme temperatures is one of the most important impacts of climate change. Here we estimate future temperature related deaths in the US using climate projection, population projection, and adaptation assumptions. We find that in 3°C of global warming level, temperature‐related deaths will increase by a factor of five, mostly due to aging and increasing population. Below 3°C warming, impact of climate change slightly decreases temperature‐related deaths, because the decrease in cold‐related deaths exceeds the increase in heat‐related deaths. Above 3°C warming, impact of climate change depends on the level of adaptation. Furthermore, we find that temperature‐related mortality shifts Northward. This is due to increase of heat‐related deaths in Northern cities, which are currently poorly adapted to heat. Key Points: Temperature‐related deaths in the U.S. will increase by a factor of 5 with 3°C of warming, mostly due to aging and increasing populationImpact of climate change is not significant until 3°C of global warming, and it depends on the level of adaptation beyond that pointTemperature‐related deaths will shift Northward, due to increasing heat‐related deaths in poorly heat‐adapted Northern cities [ABSTRACT FROM AUTHOR]

Water vapor in the Arctic can be attributed to local evaporation and transport from mid‐latitudes. Here we investigate the response of Arctic water vapor to declining sea ice in a climate model, using an idealized warming scenario in which the Arctic becomes ice free year‐round. We find distinct monthly patterns in water vapor change with warming, with a strong influence of sea ice loss on changes to evaporation, except in summer when transports dominate. Before the Arctic becomes ice‐free, total column water increases at a rate slower than that indicated by the Clausius‐Clapeyron relationship; once ice‐free, total column water increases at a rate equal to Clausius‐Clapeyron. The exception is summer when the increase is initially faster then becomes slower when ice‐free. The boundary layer structure changes, under global warming, from stratified to well mixed in all seasons except summer, which remains largely unchanged throughout the ice‐free transition. Plain Language Summary: Surface evaporation from the Arctic Ocean is limited by the presence of sea ice, which creates a natural barrier between the ocean and atmosphere above. We show the loss of Arctic sea ice, in a climate model affects atmospheric water vapor and find that this varies throughout the year. The greatest increase in atmospheric water vapor is in winter, during the Arctic night, whilst there is very little change in summer. There are two reasons why sea ice loss does not impact water vapor in the summer: first, the summer air temperature barely changes between ice‐covered and ice‐free, whereas in winter the loss of ice cover can increase air temperatures by at least 20°C; second the summer Arctic water budget is dominated by transport of water vapor from midlatitudes rather than local evaporation. We also show changes in the vertical structure of the near‐surface atmosphere and cloud types, with a transition from stable to turbulent regimes in autumn and winter. Key Points: As Arctic sea ice declines with increased warming, Arctic evaporation and water vapor increase most in autumn and winterArctic sea ice limits water vapor availability, but once the Arctic is ice‐free, it increases with the Clausius‐Clapeyron relationshipArctic boundary layer changes from stably stratified to well mixed, during winter and autumn, but less change in spring and summer [ABSTRACT FROM AUTHOR]

Predictions of biodiversity trajectories under climate change are crucial in order to act effectively in maintaining the diversity of species. In many ecological applications, future predictions are made under various global warming scenarios, as described by a range of different climate models. We propose a clustering methodology to synthesize and interpret the outputs of these various predictions.We propose an interpretable and flexible two‐step methodology to measure the similarity between predicted species range maps and to cluster the future scenario predictions utilizing a spectral clustering technique. We implement and provide code for this method.We find that clustering based on predicted species range maps is mainly driven by the amount of warming rather than climate model or future scenario. We contrast this with clustering based only on predicted climate variables, which is driven primarily by climate models, that is, scenarios of the same climate model are clustered together, even when the amount of warming input to the models is varied.The differences between species‐based and climate‐based clusterings illustrate that it is crucial to incorporate ecological information to understand the relevant differences between climate models. Our findings can be used to better synthesize forecasts of biodiversity change under the wide spectrum of results that emerge when considering potential future scenarios. [ABSTRACT FROM AUTHOR]

Model output from climate projections often requires bias‐adjustment to compensate for systematic model errors. A bias‐adjustment method for extreme precipitation intensity is proposed that preserves the scaling equation for different accumulation levels from hourly to daily, using intensity‐duration‐frequency (IDF) modeling. A validation is performed within a pseudo‐reality setting, based on hourly precipitation from 28 regional climate model projections of the EURO‐CORDEX ensemble over Belgium. The scaling‐based adjustment methods improve upon previous methods, an optimal method is identified, and, analytical quantile mapping methods must be avoided due to three identified problems. The ensemble mean of the adjusted extreme precipitation intensity obeys the above‐mentioned scale‐invariance property, which is consistent with observed extreme intensities. We thus show that IDF modeling provides added value in the context of bias‐adjustment, and, that the particular IDF model proposed balances well between accuracy and the preservation of desired properties such as scale invariance and consistency among rainfall durations. Plain Language Summary: Heavy precipitation is known to have major impacts on society, including crop damage, soil erosion, landslides, and increased flood risk. In recent years, there is a growing body of evidence that human‐induced climate change has intensified extreme precipitation on the global scale. Both regional and global climate models predict that this will continue as the climate warms. Nevertheless, trend analysis or climate‐change attribution of local rainfall extremes remains particularly difficult for many reasons including high variability in space and time. Therefore it is essential to use statistical methods that make use of all available information. Climate model simulations are known to exhibit systematic biases. Here, for the first time, we use a well‐established technique in hydrology (intensity‐duration‐frequency modeling) to adjust extreme precipitation intensity as a function of the rainfall duration and event probability. Validation results with a large multi‐model ensemble illustrate that the new method improves upon existing approaches. As an illustration, we present a bias‐adjusted multi‐model climate ensemble for future projections of heavy rainfall statistics over Belgium. Key Points: New bias‐adjustment methods for subdaily extreme precipitation consistent across different precipitation durationsPseudo‐reality cross‐validation shows higher skill than existing bias‐adjustment methods for subdaily extremesApplication to regional climate model projections over Belgium shows, despite large uncertainties, consistent future increase in subdaily precipitation extremes [ABSTRACT FROM AUTHOR]

Compound dry and hot events (CDHEs) have increased significantly and caused agricultural losses and adverse impacts on human health. It is thus critical to investigate changes in CDHEs and population exposure in responding to climate change. Based on the simulations of the Coupled Model Intercomparison Project Phase 6 (CMIP6), future changes in CDHEs and population exposure are estimated under four Shared Socioeconomic Pathways climate scenarios (SSPs) at first. And then the driving forces behind these changes are analyzed and discussed. The results show that the occurrence of CDHEs is expected to increase by larger magnitudes by the end of the 21st century (the 2080s) than that by the mid‐21st century (2050s). Correspondingly, population exposure to CDHEs is expected to increase significantly responding to higher global warming (SSP3‐7.0 and SSP5‐8.5) but is limited to a relatively low level under the modest emission scenarios (SSP1‐2.6). Globally, compared to 1985–2014, the exposure is expected to increase by 8.5 and 7.7 times under SSP3‐7.0 and SSP5‐8.5 scenarios by the 2080s, respectively. Regionally, Sahara has the largest increase in population exposure to CDHEs, followed by the Mediterranean, Northeast America, Central America, Africa, and Central Asia. The contribution of climate change to the increase of exposure is about 75% by the 2080s under the SSP5‐8.5 scenarios, while that of population change is much lower. The conclusion highlights the importance and urgency of implementing mitigation strategies to alleviate the influence of CDHEs on human society. Plain Language Summary: Under global warming, the occurrence of compound dry and hot events (CDHEs) is expected to increase, which may cause more severe damage to human society. Based on the Coupled Model Intercomparison Project Phase 6, the changes in population exposure to CDHEs and the driving forces are estimated and discussed in this study. The results show that the occurrence of CDHEs and population exposure are expected to increase substantially, especially under high‐emission scenarios. Sahara is expected to have the largest increase in population exposure to CDHEs, followed by the Mediterranean, Northeast America, Central America, Africa, and Central Asia. The influence of climate change on the increase in exposure is much larger than that of the population change. Therefore, it is important and urgent to make mitigation strategies to alleviate the impacts of CDHEs on human society. Key Points: The occurrence of summertime compound dry and hot events is projected to increase substantially over the 21st century across the globeExposure is expected to increase significantly under SSP3‐7.0 and SSP5‐8.5 but is limited to a low level under SSP1‐2.6 scenariosClimate change determines the increase in population exposure in most regions of the world [ABSTRACT FROM AUTHOR]

Millions of lakes from around the world freeze during winter. These frozen surfaces provide essential ecosystem services that are vital to many northern communities. However, the availability of safe lake ice that is oftentimes required to support these services is under threat from climate change. Here we use a 100‐member ensemble of climate model simulations to investigate changes in the presence of safe lake ice for different recreation and provisioning activities across the Northern Hemisphere. Our projections suggest that the duration of safe ice for recreational purposes will shorten, on average, by 13, 17, and 24 days within a 1.5°C, 2°C, and 3°C warmer world (relative to 1900–1929), respectively. The projected change in the duration of safe ice will be greater in higher latitudes, but with the most densely populated lower‐latitude regions experiencing the greatest percent change. The use of lake ice to support critical transportation infrastructure will also be influenced by future warming through the loss of thicker ice this century. However, our projections suggest that the magnitude of change in the duration of safe ice will differ depending on the ice thickness requirements. For transportation that requires the thickest ice cover, the number of days with safe ice will decline by 90%, 95%, and 99% with 1.5°C, 2°C, and 3°C global warming, respectively. We highlight the need for the development and implementation of adaptation plans to address the imminent loss of critical wintertime transportation infrastructure across the Northern Hemisphere. Key Points: The availability of safe lake ice for recreation will decrease, on average, by 13 and 24 days in response to a global warming of 1.5°C and 3°CThe most densely populated regions across the Northern Hemisphere are projected to experience the greatest percent loss of safe lake iceWithout human intervention, the duration of safe ice for winter ice roads is projected to decline by up to 99% within a 3°C warmer world [ABSTRACT FROM AUTHOR]

Africa's central Sahel region has experienced prolonged drought conditions in the past, while rainfall has recovered more recently. Global climate models project anything from no change to a strong wetting trend under unabated climate change; and they have difficulty reproducing the complex historical record. Here we show that when a period of dominant aerosol forcing is excluded, a consistent wetting response to greenhouse‐gas induced warming emerges in observed rainfall. Using the observed response coefficient estimate as a constraint, we find that Coupled Model Intercomparison Project Phase 6 climate models with a realistic past rainfall response show a smaller spread, and higher median, of projected future rainfall change, compared to the full ensemble. In particular, very small or negative rainfall trends are absent from the constrained ensemble. Our results provide further evidence for a robust Sahel rainfall increase in response to greenhouse‐gas forcing, consistent with recent observations, and including the possibility of a very strong increase. Plain Language Summary: Rainfall is a critical resource for a large population in the African Sahel region, but rainfall levels have strongly varied in the past. It is unclear what will happen in the next decades, because some climate models suggest little to no change in average rainfall, while other models project a strong increase due to climate change. Our study aims to narrow down this uncertainty. In the past, both greenhouse gases and aerosols influenced Sahel rainfall, to different degrees during different periods; and models may not capture both mechanisms equally well. However, future rainfall changes will likely be driven mainly by greenhouse gas levels. We identify models that closely match the rainfall change that was observed in a recent period with dominant greenhouse gas forcing. These models also tend to project stronger rainfall increases than other models. Indeed, their multi‐model mean projection is an increase by almost 50% by 2040; while none of them projects stable rainfall levels or even a reduction. Thus, it appears more likely now that rainfall in the Sahel will increase substantially over the next few decades. Key Points: We identify the response of Sahel rainfall to greenhouse gas‐induced global warming in the historical recordMany global climate models of the latest generation (Coupled Model Intercomparison Project Phase 6) do not reproduce the observed rainfall responseObservational constraint reduces model spread and implies stronger rainfall increase under further warming than in full ensemble [ABSTRACT FROM AUTHOR]

While the annual mean Arctic Amplification (AA) index varied between two and three during the 1970–2000 period, it reached values exceeding four during the first two decades of the 21st century. The AA did not change in a continuous fashion but rather in two sharp increases around 1986 and 1999. During those steps the mean global surface air temperature trend remained almost constant, while the Arctic trend increased. Although the "best" CMIP6 models reproduce the increasing trend of the AA in 1980s they do not capture the sharply increasing trend of the AA after 1999 including its rapid step‐like increase. We propose that the first sharp AA increase around 1986 is due to external forcing, while the second step close to 1999 is due to internal climate variability, which models cannot reproduce in the observed time. Plain Language Summary: The rate of Arctic warming varied in time, while the rate of global warming was nearly constant over the period 1960–2020. This led to a variable Arctic Amplification (AA) defined as a ratio of the Arctic warming trend to mean global warming trend. In addition, the Arctic experienced sudden changes in the rate of warming with step‐like changes in annual mean Arctic Amplification around the years 1986 and 1999. Climate models do not capture the second observed sharp increase of the AA. We suggest that the first AA increase around 1986 is primarily due to external forcing (increasing concentration of carbon dioxide) while the second sharp increase around 1999 is dominated by internal climate variability which current models cannot capture accurately within the time scale of the physical phenomena. Key Points: Annual mean Arctic Amplification (AA) within the period 1970–2020 changed in steep steps around 1986 and 1999. It reached values over 4.0Even those CMIP6 models best at reproducing the AA did not reproduce the second sudden increase near 1999We conjecture that the first AA sharp increase is due to external forcing, while the second is due to internal climate variability [ABSTRACT FROM AUTHOR]

Understanding the response of extreme precipitation (EP) at a city scale to global warming is critical to reducing the respective risk of urban flooding. Yet, current knowledge on this issue is limited. Here, focusing on an urban agglomeration in the tropics, Singapore, we reveal that future global warming enhances both frequency and intensity of EP, based on simulations with a state‐of‐the‐art convection‐permitting regional climate model. EP intensification can reach maximum "super" Clausius‐Clapeyron rate (≥ $\ge $+7% per K warming) rate, implying a "new normal" of "extreme events get more extreme," which is consistently for both Representative Concentration Pathways 8.5 and 4.5. The intensification is lower for moderate and light precipitation. Also, global warming was found to dampen the urban effect on EP events. The EP enhancement is attributed to the increased atmospheric moisture and convective inhibition due to enhanced low‐level stratification that delays a convection to develop until it becomes more intense. Plain Language Summary: Understanding the response of extreme precipitation (EP) at a city scale to global warming is critical to reducing the respective risk of urban flooding. Here we show that future global warming will enhance both frequency and intensity of EP, based on simulations with a state‐of‐the‐art convection‐permitting regional climate model for an urban agglomeration in the tropics, Singapore. EP is estimated to intensify much more than moderate and light precipitation, implying a "new normal" of "the extreme events get more extreme." Also, global warming was found to dampen the urban effect on EP events. The EP enhancement is attributed to the increased atmospheric moisture and convective inhibition due to enhanced low‐level stratification that delays a convection to develop until it becomes more intense. Key Points: New normal of "extreme events get more extreme" in future city‐scale precipitation is revealedGlobal warming could modify and even reduce the urban footprint on extreme precipitation (EP) eventsThe intensification of EP can reach the maximum at the "super" Clausius‐Clapeyron (≥ $\ge $+7% per K warming) rate [ABSTRACT FROM AUTHOR]

It sounds straightforward. As the Earth warms due to the increased concentration of greenhouse gases in the atmosphere, global temperatures rise and so heatwaves become warmer as well. This means that a fixed temperature threshold is passed more often: the probability of extreme heat increases. However, land use changes, vegetation change, irrigation, air pollution, and other changes also drive local and regional trends in heatwaves. Sometimes they enhance heatwave intensity, but they can also counteract the effects of climate change, and in some regions, the mechanisms that impact on trends in heatwaves have not yet been fully identified. Climate models simulate heatwaves and the increased intensity and probability of extreme heat reasonably well on large scales. However, changes in annual daily maximum temperatures do not follow global warming over some regions, including the Eastern United States and parts of Asia, reflecting the influence of local drivers as well as natural variability. Also, temperature variability is unrealistic in many models, and can fail standard quality checks. Therefore, reliable attribution and projection of change in heatwaves remain a major scientific challenge in many regions, particularly where the moisture budget is not well simulated, and where land surface changes, changes in short‐lived forcers, and soil moisture interactions are important. Plain Language Summary: Heatwaves are arguably the most deadly weather phenomena. As the Earth warms due to higher concentrations of greenhouse gases, one would expect heatwaves to become worse as well, killing even more people unless they are better protected against the heat. However, it turns out that the world is not so simple and that many other factors also influence heatwaves. Land use changes, irrigation, air pollution, and other changes also drive trends in heatwaves. Some of these cause much larger trends while some have counteracted the climate change‐driven trends up to now. In some regions, the causes of high trends have not yet been identified. Current generation climate models often do not simulate all these mechanisms correctly so will have to be improved before we can more confidently trust their description of past trends and projections of future trends in heatwaves. Key Points: The IPCC AR6 WG1 states the "frequency and intensity of hot extremes have increased"The IPCC notes that the effect of increased greenhouse gas on high temperatures is moderated or amplified at local scales by other factorsConfident quantitative attribution statements of the human influence on heatwaves are limited by our understanding of these local processes [ABSTRACT FROM AUTHOR]

There is low confidence in projections of Antarctic sea ice area (SIA), due to deficiencies in climate model sea ice processes. Ensemble regression techniques can help to reduce this uncertainty. We investigate relationships between SIA climatology and 21st century change in the Coupled Model Intercomparison Project, phase 6 (CMIP6) multi‐model ensemble. In summer, under a strong forcing scenario, each model loses the majority of its sea ice. Therefore, models with greater historical SIA exhibit greater reductions, so the observed climatology of SIA strongly constrains projections. Ensemble spread in historical summer SIA is smaller than in CMIP phase 5 (CMIP5), and CMIP6 gives a more robust constraint on future SIA. In winter, by 2100 under a strong forcing scenario, 40% of SIA disappears on average, and ensemble spread in historical mean SIA explains approximately half the spread in projected change. A greater winter ice loss in CMIP6 than CMIP5 is explained by the higher climate sensitivities of some CMIP6 models. Plain Language Summary: Antarctic sea ice area is important for ecosystems, human activity, and for the dynamics of the atmosphere and ocean. However, major climate change assessments such as the Intergovernmental Panel on Climate Change Sixth Assessment Report have placed little confidence in projections of Antarctic sea ice area. This is because climate models struggle to simulate many aspects of sea ice area as observed by satellites. However, not all models should be treated equally. Models with relatively more sea ice area in the recent past project greater losses in the future, especially in summer. This suggests that models with historical sea ice area closest to what we have observed may be more reliable in their future simulations. We use this information in a simple statistical model to show that, firstly, the newest climate models largely show near‐total sea ice loss in summer by the end of the 21st century, which was not universally true for older climate models. Secondly, newer climate models lose more winter sea ice than their predecessors in the same time period, which is related to the known greater global warming response to given greenhouse gas concentrations in the newer models. Key Points: We compare Coupled Model Intercomparison Project (CMIP), phase 5 and the CMIP, phase 6 (CMIP6) projections of Antarctic sea ice loss, assessing drivers of uncertainty and the robustness of projectionsUnder strong forcing, CMIP6 models lose most Antarctic summer sea ice by 2100, so projections are constrained by historical climatologyIncreased winter sea ice loss in CMIP6 is related to increased equilibrium climate sensitivity [ABSTRACT FROM AUTHOR]

Previous studies documented possible connections between low frequency climate modes in the Northern Hemisphere ocean basins. We use observed sea surface temperatures and 270 large ensemble climate model simulations, which allows for improved methods of separating external and internal variability, such as removing the ensemble mean from each simulation. Detrending methods for observations have also improved since some of these previous studies were conducted. We also devise a modified statistical test using bootstrapping that is tuned specifically to this analysis. With these tools, we reexamine relationships among these modes. While previous studies have argued for the existence of an inter‐basin link, our results suggest that any internal connections between these modes are indistinguishable from random noise. Further, we show that external forcing affects each region in similar ways. This suggests that anthropogenic warming can cause an indirect link between the two basins, confounding the interpretation of a potential relationship. Plain Language Summary: We reexamine possible connections between climate patterns in the North Atlantic and North Pacific oceans. Improved climate model simulations and appropriate statistical methods allow us to build on previous research of these linkages. In contrast to previous studies, no natural connections are detected. However, global warming is shown to affect each region in similar ways, suggesting that climate change could cause an indirect link between the two basins. Key Points: A multi model large ensemble archive and modified statistical assumptions provide a framework for studying climatic relationshipsAn analysis of relationships between leading Northern Hemisphere climate modes does not show any internal connectionsExternal forcing such as global warming is shown to be a possible confounding factor in climate relationships [ABSTRACT FROM AUTHOR]

Meteorological to hydrological drought propagation has been widely studied to reflect the relationship between these drought categories and better understand drought mechanisms. However, global warming may alter the drought propagation features, which are not fully understood. This study aims to investigate changes in meteorological and hydrological drought conditions, especially their propagation features in 1.5–3.0°C warmer climates for 8,655 watersheds globally. First, the three‐month scale standardized precipitation index and the standardized runoff index are calculated based on the precipitation simulated by the 15 global climate models and the runoff simulated by the four hydrological models, respectively. Drought events are then identified using the run theory, followed by the calculation of drought propagation features (i.e., pooling, lag, and lengthening) for matched meteorological and hydrological droughts. As a result, both meteorological and hydrological drought conditions (i.e., duration and severity) would relieve in warmer climates due to increased precipitation for regions excluding Western North America, South America, the Mediterranean, Southern Africa, East Asia, and Australia. However, the drought conditions would be more severe during drought propagation from meteorological to hydrological droughts over most regions. During drought propagation, the worsening drought conditions over half of the regions would be more serious first and then relieved with the rising temperature. These results indicate that efforts to slow down global warming can suppress the deterioration of drought conditions in the propagation. Plain Language Summary: Droughts can be categorized into meteorological, hydrological, agricultural, and socioeconomic types from different impacted aspects. Investigating meteorological to hydrological drought propagation can reflect the relationship between these two drought categories to understand the drought mechanism better. However, it is not fully understood whether global warming would alter the drought propagation features or not. Therefore, we evaluated the change of meteorological and hydrological drought conditions, especially their propagation features in 1.5 to 3.0°C warmer climates for 8,655 watersheds around the world. Here we show that both meteorological and hydrological drought conditions would relieve in warmer climates due to the increase of precipitation for regions excluding Western North America, South America, the Mediterranean, Southern Africa, East Asia, and Australia. However, the drought conditions would be more severe during drought propagation over most regions in warmer climates. Our findings promote a better understanding of drought propagation changes under global warming. Key Points: Both meteorological and hydrological drought conditions are projected to relieve in warmer climates for around half of global regionsThe duration and severity developing from meteorological to hydrological droughts would be more severe over most regionsThe worsening duration and severity during the propagation over half of the regions would intensify first and then ease in warmer climates [ABSTRACT FROM AUTHOR]

The assessment of climate change impacts in regions with complex orography and land‐sea interfaces poses a challenge related to shortcomings of global climate models. Furthermore, climate indices based on absolute thresholds are especially sensitive to systematic model biases. Here we assess the effect of bias adjustment (BA) on the projected changes in temperature extremes focusing on the number of annual days with maximum temperature above 35°C. To this aim, we use three BA methods of increasing complexity (from simple scaling to empirical quantile mapping) and present a global analysis of raw and BA CMIP5 projections under different global warming levels. The main conclusions are (1) BA amplifies the magnitude of the climate change signal (in some regions by a factor 2 or more) achieving a more plausible representation of future heat threshold‐based indices; (2) simple BA methods provide similar results to more complex ones, thus supporting the use of simple and parsimonious BA methods in these studies. [ABSTRACT FROM AUTHOR]

The hydrological characteristics of a river, including the magnitude and timing of high and low flows, are important determinants of its ecological functioning. Climate change will alter these characteristics, triggering ecological changes in river ecosystems. This study assesses risks of ecological change in 321 major river basins across the globe due to global warming relative to pre-industrial conditions of 1.0, 1.5, 2.0 and 3.0°C. Risks associated with climate-driven changes to high and low flows, relative to baseline (1980-2010; 0.6°C warming), are investigated using simulations from nine global hydrological models forced with climate projections from five global climate models, resulting in an ensemble of 14,445 baseline-scenario members for each warming scenario (9 × 5 × 321). At the globalscale, the likelihood of high risks of significant ecological change in both high and low flows increase with global warming: across all basins there is a medium-high risk of change in high (low) flows in 21.4% (22.4%) of ensemble members for 1.0°C warming, increasing to 61.5% (63.2%) for 3.0°C. Risks are particularly pronounced for low flows at 3.0°C for many rivers in South America, southern Africa, Australia, southern Europe and central and eastern USA. Results suggest that boreal regions are least likely to see significant ecological change due to modified river flows but this may be partly the result of the exclusion of processes such as permafrost dynamics from most global hydrological models. The study highlights the ecological fragility and spatial heterogeneity of the risks that unmitigated climate change poses to global river ecosystems. [ABSTRACT FROM AUTHOR]

Responses of summer precipitation in China to global 1.5°C warming with transient and stabilized pathways are investigated through the analysis of the Common Earth System Model climate simulations. Precipitation increases more significantly in southeast China in the stabilized scenario compared with the transient one. The difference is primarily attributable to dynamic factors related to circulation changes and driven by differences of land‐ocean thermal contrast between the two scenarios. The stabilized warming favors conditions of larger ocean warming and smaller land warming, leads to enhanced meridional temperature gradient and ultimately speeds up the jet stream over East Asia. Ageostrophic wind at the entrance of the accelerated jet strengthens ascending motion and precipitation along the coast of Asia from southeast China to India. The enhanced heating over India further induces a Kelvin‐wave response with an anomalous anticyclone that contributes to the enhanced westward shifted of the western North Pacific Subtropical High. Southerly winds at the west flank of the anticyclone transport moisture northward from tropical oceans, and strengthen precipitation in southeast China. Plain Language Summary: This study deals with the issue of regional precipitation response to 1.5°C global warming in accordance to the Paris Agreement on Climate Change for two different pathways, either transient or stabilized. Compared with the transient warming scenario, summer precipitation increases more significantly in southeast China in the stabilized one. This feature of distinctive precipitation responses, with strong implications for policy making in terms of regional climate mitigation and adaptation, is furthermore explored through a moisture budget analysis. Dynamic effect in relation to changes of atmospheric circulation is found to be the major contributor to the difference. The cause of the significant difference in precipitation in South China is attributed to changes of land‐ocean thermal contrast, leading to a series of atmospheric circulation adjustments. Results presented here satisfactorily addressed, for the first time, the long‐standing issue on global warming, namely, how the atmosphere responds distinctively under the transient and stabilized anthropogenic forcing pathways which show however an identical global warming level. Key Points: The summer precipitation increases more significantly in southeast China in the stabilized warming scenario compared with the transient oneThe dynamic effect in relation to changes of atmospheric circulation constitutes the major factor of distinctive precipitation responsesThe differential meridional thermal gradient related to a contrasted land‐ocean warming leads to dynamic changes [ABSTRACT FROM AUTHOR]

The simultaneous occurrence of extremely wet winters at multiple locations in the same region can contribute to widespread flooding and associated socio‐economic losses. However, the spatial extent of precipitation extremes (i.e., the area in which nearby locations experience precipitation extremes simultaneously) and its future changes are largely overlooked in climate assessments. Employing new multi‐thousand‐year climate model simulations, we show that under both 2.0 °C and 1.5 °C warming scenarios, wintertime total precipitation extreme extents would increase over about 80%–90% of the Northern Hemisphere extratropics (i.e., of the latitude band 28°–78°N). Stabilizing at 1.5 °C rather than 2.0 °C would reduce the average magnitude of the increase by 1.7–2 times. According to the climate model, the increased extents are caused by increases in precipitation intensity rather than changes in the spatial organization of the events. Relatively small percentage increases in precipitation intensities (e.g., by 4%) can drive disproportionately larger, by 1–2 orders of magnitude, growth in the spatial extents (by 93%). Plain Language Summary: One of the most impact‐relevant and studied effects of global warming is the intensification of precipitation extremes. When extremely wet winters occur simultaneously at multiple locations within the same region, their cumulative impacts can be particularly high and enhanced as a result of limited resources available to cope with simultaneous damages. Despite the impacts caused by widespread extremes, climate change studies have typically disregarded the spatial extension of the extremes. Here, based on new multi‐thousand‐year climate model simulations, we show that—over most of the Northern Hemisphere extratropics, that is, most of the latitude band 28°–78°N—the spatial footprint of total wintertime precipitation extremes is projected to largely widen in the future. This widening results from a warmer, and therefore moister, atmosphere that will intensify precipitation. Holding global warming to 1.5 °C rather than 2.0 °C, in line with the Paris Agreement, would be beneficial to society as it could limit the average increase in the extension over the Northern Hemisphere extratropics by up to a factor of 2. To develop better preparedness for such extreme events, stakeholders should consider that a small increase in precipitation intensities (for example, by 4%) could result in large (by 93%) increases in spatial extent. Key Points: The spatial extent of wintertime total precipitation extremes is projected to increase over most of the Northern Hemisphere in the futureChanges in the spatial organization, that is, dependence, of precipitation extremes only marginally affect the spatial extentsIncreased precipitation magnitudes can cause a disproportionate (even 20–90 times larger) increase in the precipitation extreme extents [ABSTRACT FROM AUTHOR]

The Komodo dragon (Varanus komodoensis) is an endangered, island‐endemic species with a naturally restricted distribution. Despite this, no previous studies have attempted to predict the effects of climate change on this iconic species. We used extensive Komodo dragon monitoring data, climate, and sea‐level change projections to build spatially explicit demographic models for the Komodo dragon. These models project the species' future range and abundance under multiple climate change scenarios. We ran over one million model simulations with varying model parameters, enabling us to incorporate uncertainty introduced from three main sources: (a) structure of global climate models, (b) choice of greenhouse gas emission trajectories, and (c) estimates of Komodo dragon demographic parameters. Our models predict a reduction in range‐wide Komodo dragon habitat of 8%–87% by 2050, leading to a decrease in habitat patch occupancy of 25%–97% and declines of 27%–99% in abundance across the species' range. We show that the risk of extirpation on the two largest protected islands in Komodo National Park (Rinca and Komodo) was lower than other island populations, providing important safe havens for Komodo dragons under global warming. Given the severity and rate of the predicted changes to Komodo dragon habitat patch occupancy (a proxy for area of occupancy) and abundance, urgent conservation actions are required to avoid risk of extinction. These should, as a priority, be focused on managing habitat on the islands of Komodo and Rinca, reflecting these islands' status as important refuges for the species in a warming world. Variability in our model projections highlights the importance of accounting for uncertainties in demographic and environmental parameters, structural assumptions of global climate models, and greenhouse gas emission scenarios when simulating species metapopulation dynamics under climate change. [ABSTRACT FROM AUTHOR]

We analyze projected changes in climate extremes (extreme temperatures and heavy precipitation) in the multimodel ensembles of the fifth and sixth Coupled Model Intercomparison Projects (CMIP5 and CMIP6). The results reveal close similarity between both ensembles in the regional climate sensitivity of the projected multimodel mean changes in climate extremes, that is, their projected changes as a function of global warming. This stands in contrast to widely reported divergences in global (transient and equilibrium) climate sensitivity in the two multimodel ensembles. Some exceptions include higher warming in the South America monsoon region, lower warming in Southern Asia and Central Africa, and higher increases in heavy precipitation in Western Africa and the Sahel region in the CMIP6 ensemble. The multimodel spread in regional climate sensitivity is found to be large in both ensembles. In particular, it contributes more to intermodel spread in projected regional climate extremes compared with the intermodel spread in global climate sensitivity in CMIP6. Our results highlight the need to consider regional climate sensitivity as a distinct feature of Earth system models and a key determinant of projected regional impacts, which is largely independent of the models' response in global climate sensitivity. Plain Language Summary: Many articles analyze and compare global climate sensitivity in climate models, that is, how their global warming differs at a given level of CO2 concentrations. However, global warming is only one quantity affecting impacts. To assess human‐ and ecosystem‐relevant impacts, it is essential to evaluate the regional climate sensitivity of climate models, that is, how their regional climate features differ at a given level of global warming. We analyze here regional climate sensitivity in the new multimodel ensemble that will underlie the conclusions of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC). This ensemble of model projections is called the "Sixth Coupled Model Intercomparison Project" or CMIP6. We find that differences in regional climate sensitivity between models in CMIP6 often contribute more to the uncertainty of regional extremes projections than the uncertainty in global mean warming between models. Overall, the regional climate sensitivity features in the CMIP6 models' projections ensemble are very similar to those of the prior ensemble (CMIP5), although the model ensembles have been highlighted to differ in their global climate sensitivity over the 21st century. Key Points: Changes in climate extremes as a function of global warming are quasilinear and determine a "regional climate sensitivity" in CMIP5 and CMIP6The regional climate sensitivity of climate extremes is found to be very similar in CMIP5 and CMIP6, unlike global climate sensitivityModel spread in regional climate sensitivity in CMIP6 contributes more to uncertainty of projected extremes than global climate sensitivity [ABSTRACT FROM AUTHOR]

Changes in climate are usually considered in terms of trends or differences over time. However, for many impacts requiring adaptation, it is the amplitude of the change relative to the local amplitude of climate variability which is more relevant. Here, we develop the concept of "signal‐to‐noise" in observations of local temperature, highlighting that many regions are already experiencing a climate which would be "unknown" by late 19th century standards. The emergence of observed temperature changes over both land and ocean is clearest in tropical regions, in contrast to the regions of largest change which are in the northern extratropics—broadly consistent with climate model simulations. Significant increases and decreases in rainfall have also already emerged in different regions with the United Kingdom experiencing a shift toward more extreme rainfall events, a signal which is emerging more clearly in some places than the changes in mean rainfall. Plain Language Summary: Changes in climate are translated into impacts on society not just though the amount of change, but how this change compares to the variations in climate that society is used to. Here we demonstrate that significant changes, when compared to the size of past variations, are present in both temperature and rainfall observations over many parts of the world. Key Points: The signal of changes in observed temperature and rainfall due to global warming has clearly emerged in many regions and at mesoscalesTropical regions have experienced the largest changes in temperature relative to the amplitude of internal variabilitySignals of increasing extreme rainfall are emerging more quickly than signals in mean rainfall over many parts of the United Kingdom [ABSTRACT FROM AUTHOR]

The anthropogenic‐induced global warming and local urbanization exert important influences on temperature extremes in Eastern China. Here we use China station observations and climate models to investigate their effects on the warm and cold days and nights simultaneously. We quantified the contribution from these two factors based on an optimal fingerprinting method. We find that both anthropogenic and urbanization signals can be clearly detected and separated from each other in the nighttime temperature extremes. The effect of urbanization may explain as much as one third of the observed changes in cold and warm nights while the urbanization signal is weak in the daytime extremes. The results are robust against sampling uncertainty in the estimate of urbanization signal, but uncertainty due to collinearity between the urbanization signal and global warming is difficult to assess. Plain Language Summary: Understanding the causes behind changes in temperature extremes is of significance for reliably projecting future climate change. Previous studies have separately shown that global warming and the urbanization effects are the two important drivers for the increase of warm extremes and decrease of cold extremes in Eastern China. In this study, we consider these two factors simultaneously using an optimal fingerprinting method. We find that climate models can well reproduce the observed changes in extreme temperature when the urbanization effects are included. Both global warming and urbanization have contributed to changes in nighttime temperature extremes, with global warming contributing slightly more. On the other hand, changes in daytime temperature extremes seem to be predominantly due to global warming. Key Points: Global warming and urbanization exert important influences on both warm and cold days and nights in Eastern ChinaBoth anthropogenic and urban signals are detected in nighttime extreme temperatures while only the former is detected in daytime extremesThe effect of urbanization is estimated to have contributed as much as one third of the observed warming in nighttime temperature extremes [ABSTRACT FROM AUTHOR]

The equilibrium climate sensitivity, that is, the global‐mean surface‐air temperature change in response to a doubling of the carbon dioxide concentration is a widely used metric in climate change studies. Its exact value is rarely known because its estimation requires a long integration time of several thousand years. We propose a method to estimate an accurate value of the equilibrium response from fully coupled climate models at a reasonable computational cost. Using this method, our state‐of‐the‐art climate model CNRM‐CM6‐1 reaches a stationary state after only few hundred of years of integration. This "Fast‐Forward" method consists of an optimal two‐step forcing pathway designed using the framework of a two‐layer energy balance model. It can be applied easily to any coupled climate model. Key Points: A simple method for estimating the equilibrium climate sensitivity is proposedThe method allows to simulate the stationary climate corresponding to any given radiative perturbation with a limited computational costThe method can be applied to any atmosphere‐ocean coupled climate model [ABSTRACT FROM AUTHOR]

The Max Planck Institute Grand Ensemble (MPI‐GE) is the largest ensemble of a single comprehensive climate model currently available, with 100 members for the historical simulations (1850–2005) and four forcing scenarios. It is currently the only large ensemble available that includes scenario representative concentration pathway (RCP) 2.6 and a 1% CO2 scenario. These advantages make MPI‐GE a powerful tool. We present an overview of MPI‐GE, its components, and detail the experiments completed. We demonstrate how to separate the forced response from internal variability in a large ensemble. This separation allows the quantification of both the forced signal under climate change and the internal variability to unprecedented precision. We then demonstrate multiple ways to evaluate MPI‐GE and put observations in the context of a large ensemble, including a novel approach for comparing model internal variability with estimated observed variability. Finally, we present four novel analyses, which can only be completed using a large ensemble. First, we address whether temperature and precipitation have a pathway dependence using the forcing scenarios. Second, the forced signal of the highly noisy atmospheric circulation is computed, and different drivers are identified to be important for the North Pacific and North Atlantic regions. Third, we use the ensemble dimension to investigate the time dependency of Atlantic Meridional Overturning Circulation variability changes under global warming. Last, sea level pressure is used as an example to demonstrate how MPI‐GE can be utilized to estimate the ensemble size needed for a given scientific problem and provide insights for future ensemble projects. Key Points: The 100‐member MPI‐GE is currently the largest publicly available ensemble of a comprehensive climate modelMPI‐GE currently has the most forcing scenarios of all large ensemble projects: RCP2.6, RCP4.5, RCP8.5, and 1% CO2The power of MPI‐GE is to estimate the forced response and internal variability, including changing variability, to unprecedented precision [ABSTRACT FROM AUTHOR]

Climate models project that extreme precipitation events will intensify in proportion to their intensity during the 21st century at large spatial scales. The identification of the causes of this phenomenon nevertheless remains tenuous. Using a large ensemble of North American regional climate simulations, we show that the more rapid intensification of more extreme events also appears as a robust feature at finer regional scales. The larger increases in more extreme events than in less extreme events are found to be primarily due to atmospheric circulation changes. Thermodynamically induced changes have relatively uniform effects across extreme events and regions. In contrast, circulation changes weaken moderate events over western interior regions of North America and enhance them elsewhere. The weakening effect decreases and even reverses for more extreme events, whereas there is further intensification over other parts of North America, creating an "intense gets intenser" pattern over most of the continent. Plain Language Summary: Climate models project that extreme precipitation events will intensify during the 21st century at large spatial scales, with several studies suggesting that the most extreme events will exhibit the highest rate of intensification. Identification of the causes of this phenomenon nevertheless remains tenuous, partly because estimating long‐term changes in precipitation extremes is difficult, particularly for precipitation extremes at impact‐relevant spatial scales. Robustly estimated changes in precipitation extremes at small spatial scales can only be obtained from large extreme precipitation data sets from large ensemble simulations. We employ a large ensemble regional climate simulation experiment performed for North America. The large volume of output from this experiment allows us to confidently obtain statistical evidence that precipitation intensification occurs more rapidly with warming for more extreme events at impact‐relevant spatial scales, and secondly, to determine the causes for this phenomenon. The effect of atmospheric moisture increases caused by greenhouse gas warming is found to be similar for extreme precipitation events of different intensities, ranging from 2‐ to 50‐year events. In contrast, atmospheric circulation change due to greenhouse gas warming tends to reduce the effect of the atmospheric moisture increases on less intense events rather than intensifying the effect on more extreme events. Key Points: More rapid increases are found in more extreme precipitation events in response to warmingThe more rapid increases in more extreme events are caused by atmospheric circulation changesThermodynamically induced changes have relatively uniform effects across extreme events [ABSTRACT FROM AUTHOR]

Amplified regional warming suggests that some regions suffer more from global warming. However, present knowledge is still not enough to understand this paramount aspect of global warming. By using climate model simulations, we first highlight that regional warming amplifications directly following anthropogenic emission would torment many undeveloped countries. Then, we find that cloud has the largest contribution to polar amplification, rather than the frequently blamed sea ice decline. The summertime sea ice decline plays the second role in generating strong wintertime polar amplification via lagged energy release. Our findings also propose that heat uptake by the deeper ocean greatly favors the terrestrial amplification. Additionally, the cloud also shows its importance in helping dryland amplification. Our findings suggest that these robust regional warming amplifications are very likely inevitable under anthropogenic emission, therefore strictest global mitigation is required to prevent unacceptable warming over the high risk regions. Plain Language Summary: Amplified regional warming points out that some regions are more suffering under global warming. Thus, we performed this study to figure out robust regional warming amplifications directly following the anthropogenic greenhouse gas emission. We addressed the influences of these regional warming amplifications to human society, such an amplified dryland warming (relative to humid regions) has greater influences on some undeveloped countries. Furthermore, we achieved some new scientific findings that are crucial to understanding causes of amplified regional warming, such as cloud's dominant role on amplified pole warming (relative to lower‐latitudes) rather than the frequently blamed sea ice decline. We also found the important role of deeper ocean heat uptake and cloud in helping amplified land warming (relative to ocean) and amplified dryland warming, respectively. Taken together, our study greatly helps to understand human influences on regional climate change. Key Points: Human‐induced global warming has greater influences on some undeveloped countriesCloud has the largest contribution to polar amplification, rather than the frequently blamed sea ice declineHeat uptake by the deeper ocean greatly favors the terrestrial amplification [ABSTRACT FROM AUTHOR]

Arabian Sea (AS) warming has been significantly accelerated since the 1990s, in particular in the spring season. Here we link the AS warming changes to the Atlantic multidecadal oscillation (AMO). A set of Atlantic pacemaker experiments with a slab mixed‐layer ocean model successfully reproduces the AS spring multidecadal variability and its connection with the AMO. An atmospheric teleconnection from the Atlantic to the AS in the preceding winter and associated thermodynamic air‐sea feedback is found to be important. The teleconnection can be reestablished by the atmospheric model when the AMO sea surface temperature (SST) and its trans‐basin footprint over the western Pacific are prescribed simultaneously. The western Pacific SST warming associated with the AMO positive phase induces a Gill‐type Rossby wave over the AS, showing anomalously low pressures and converging southerlies that weaken winter northerlies. Thus, the wind‐evaporation‐SST feedback results in and maintains the AS warm SST anomalies to the subsequent spring. Plain Language Summary: The rapid warming of the Arabian Sea (AS) since the 1990s not only has significant impacts on the monsoon climate change and extreme weather events (flood, heat wave, and cyclone) in Arabian Peninsula and Indian subcontinent but also poses increasingly severe risks of damage to the coastal and marine ecosystems. However, the cause of this recent acceleration of AS warming remains unclear. Here using observations and atmosphere‐ocean coupled models, we link the observed AS warming changes to the Atlantic multidecadal oscillation (AMO) and show that more than 70% of AS multidecadal variability can be explained by the AMO. This Atlantic‐AS teleconnection involves atmosphere‐ocean interactions across multiple ocean basins, with a contribution from the western Pacific (WP). The SST footprint of the AMO over the WP acts as a relay for the effect of the AMO on the AS by exciting an atmospheric teleconnection and subsequently thermodynamic feedbacks over the AS. The concurrent cold‐to‐warm phase shift of the AMO and its WP SST footprint since the 1990s contribute constructively to the rapid warming of the AS. Our results highlight an unexpected multiple‐basin interaction at decadal timescales, which plays a key role in the attribution of historical regional SST warming. Key Points: The observed Arabian Sea warming changes (slowdown and acceleration) are linked to the Atlantic multidecadal oscillation for the first timeThe teleconnection involves air‐sea interactions across multiple ocean basins, with a contribution from western Pacific that acts as a relayThe decadal phase shift of Atlantic‐Western Pacific trans‐basin variability since the 1990s contributes to the rapid warming of Arabian Sea [ABSTRACT FROM AUTHOR]

Arctic moisture intrusions have played an important role in warming the Arctic over the past few decades. A prior study found that Coupled Model Intercomparison Project Phase 5 (CMIP5) models exhibit large regional biases in the moisture flux across 70°N. It is shown here that the systematic misrepresentation of the moisture flux is related to the models' overprediction of zonal wavenumber k = 2 contribution and underprediction of k = 1 contribution to the flux. Models with a warmer tropical upper troposphere and El‐Niño‐like tropical surface temperature tend to simulate stronger k = 2 flux, while k = 1 flux is uncorrelated with tropical upper tropospheric temperature and is associated with La‐Niña‐like surface temperature. The models also overpredict the transient eddy moisture flux while underpredicting the stationary eddy flux. Moreover, future projections in Representative Concentration Pathway 8.5 (RCP8.5) simulations show trends in moisture flux that is consistent with biases in historical simulations, suggesting that these CMIP5 projections reflect the same error(s) that cause the model biases. Plain Language Summary: The Arctic is the region where climate change has been most rapid. A growing body of work indicates that moisture intrusions into Arctic have played an important role in warming the Arctic over the past decades. Coupled Model Intercomparison Project Phase 5 (CMIP5) models have served as a critical tool for projecting future climate changes. Therefore, it is imperative to evaluate whether the physical processes governing moisture intrusions are accurately represented by the models. It is shown here that there is a systematic misrepresentation of the moisture flux into the Arctic related to the models' biased representation of tropical temperatures. Moreover, future projections in Representative Concentration Pathway 8.5 (RCP8.5) simulations show moisture flux trends that are consistent with biases in historical simulations, suggesting that these CMIP5 projections reflect the same error(s) that cause the model biases. It is common practice to regard averages across climate model as being the true response to climate forcing. The findings here question this widespread assumption and underscore the need to pay close attention to model biases and their causes. Key Points: Climate models overpredict (underpredict) zonal‐wavenumber k = 2 (k = 1) contribution to moisture flux across Arctic boundaryThe models with warmer tropical upper troposphere tend to simulate stronger k = 2 flux, while no such relation is present for k = 1 fluxClimate models overpredict transient eddy contribution to the flux at the expense of stationary eddy contribution [ABSTRACT FROM AUTHOR]

Effects of free‐tropospheric thermodynamic properties and large‐scale subsidence on the nocturnal growth of marine stratocumulus clouds are investigated through large‐eddy simulation based on Flight 5 of the Physics of Stratocumulus Top research campaign. It was characterized by a weak inversion and moist troposphere. Sensitivity simulations are performed using variations in the subsidence and free‐tropospheric temperature and humidity. The results confirm that the cloud‐top entrainment instability parameter κ alone cannot unambiguously control the behaviors of marine stratocumulus due to the opposite response of liquid water path (LWP) to changes in the humidity and temperature jumps with the same variation in κ, thereby both jumps should be considered separately. However, sometimes it could be considered as a joint factor of the humidity and temperature jumps controlling LWP even though cloud‐top entrainment instability does not occur or κ < 0. An obvious role of subsidence is to push the inversion layer down nearly identically and at the same rate under different ambient conditions. Enhanced subsidence, as expected, diminishes the entrainment rate, cloud‐top height, cloud thickness, and LWP. However, it has a small influence on the inversion thickness and the dynamic instability across the inversion. An LWP budget analysis shows that the direct effect of subsidence is a small reduction in the LWP, but the indirect effect of subsidence is large due to contributions from other physical processes. Therefore, subsidence is an important physical process controlling the LWP budget, even though its direct contribution is significantly smaller than the largest contributions from both radiation and entrainment. Key Points: Effects of subsidence and inversion jumps on nonclassical MSc are investigated using implicit large‐eddy simulationsContributions of individual physical processes to LWP tendency are analyzedIn contrast to classical MSc, weakened inversion increases entrainment and LWP in nonclassical MSc [ABSTRACT FROM AUTHOR]

Abstract: On interannual to decadal time scales, the climate mode with many of the strongest societal impacts is the El Niño–Southern Oscillation (ENSO). However, quantifying ENSO's changes in a warming climate remains a formidable challenge, due to both the noise arising from internal variability and the complexity of air‐sea feedbacks in the tropical Pacific Ocean. In this work, we use large (≥30‐member) ensembles of climate simulations to show that anthropogenic climate change can produce systematic increases in ENSO teleconnection strength over many land regions, driving increased interannual variability in regional temperature extremes and wildfire frequency. As the spatial character of this intensification exhibits strong land‐ocean contrasts, a causal role for land‐atmosphere feedbacks is suggested. The identified increase in variance occurs in multiple model ensembles, independent of changes in sea surface temperature variance. This suggests that in addition to changes in the overall likelihoods of heat and wildfire extremes, the variability in these events may also be a robust feature of future climate. [ABSTRACT FROM AUTHOR]

Experimental studies assessing climatic effects on ecological communities have typically applied static warming treatments. Although these studies have been informative, they have usually failed to incorporate either current or predicted future, patterns of variability. Future climates are likely to include extreme events which have greater impacts on ecological systems than changes in means alone. Here, we review the studies which have used experiments to assess impacts of temperature on marine, freshwater and terrestrial communities, and classify them into a set of 'generations' based on how they incorporate variability. The majority of studies have failed to incorporate extreme events. In terrestrial ecosystems in particular, experimental treatments have reduced temperature variability, when most climate models predict increased variability. Marine studies have tended to not concentrate on changes in variability, likely in part because the thermal mass of oceans will moderate variation. In freshwaters, climate change experiments have a much shorter history than in the other ecosystems, and have tended to take a relatively simple approach. We propose a new 'generation' of climate change experiments using down-scaled climate models which incorporate predicted changes in climatic variability, and describe a process for generating data which can be applied as experimental climate change treatments. [ABSTRACT FROM AUTHOR]