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We use the 100-member Max Planck Institute Grand Ensemble (MPI-GE) to disentangle the contributions from colocated dynamic atmospheric conditions and local thermodynamic effects of moisture limitation as drivers of variability in European summer heat extremes. Using a novel extreme event definition, we find that heat extremes with respect to the evolving mean climate increase by 70% under a moderate warming scenario during the twenty-first century. With a multiple regression approach, we find that the dynamical mechanisms representing blocking and anticyclonic conditions are the main driver of variability in extreme European summer temperatures, both in past and future climates. By contrast, local thermodynamic drivers play a secondary role in explaining the total variability in extreme temperatures. We also find that considering both dynamical and thermodynamical sources of variability simultaneously is crucial. Assessing only one type of drivers leads to an overestimation of their effect on extreme temperatures, particularly when considering only thermodynamical drivers. Lastly, we find that although most past and future heat extremes occur under favorable dynamical atmospheric conditions; this occurs 10–40% less frequently over Central Europe in the twenty-first century. By contrast, heat extremes over Central Europe occur 40% more frequently under concurrent extreme moisture limitation in the twenty-first Century. Our findings highlight a new type of neutral-atmosphere, moisture-driven heat extremes, and confirm that the increase in European heat extremes and associated variability increase are dominated by the local thermodynamic effect of moisture limitation.

The aims of this study are to assess the impacts of accelerated climate change on summer maximum temperatures since the early 1990s in the Australian city of Sydney’s eastern coastal and western inland suburbs. Western Sydney currently experiences far more intense summer (December–March) heat waves than coastal Sydney, with maximum temperatures exceeding those of coastal Sydney by up to 10 °C. Aside from increased bushfire danger, extreme temperature days pose health and socio-economic threats to western Sydney. Permutation tests of consecutive summer periods, 1962–1991 and 1992–2021, are employed to determine the differential climate change impacts on maximum summer temperatures at two locations: Sydney and Richmond, representative of eastern and western Sydney, respectively. Attribution of observed maximum summer temperature trends in Sydney and Richmond was performed using machine learning techniques applied to known Australian region oceanic and atmospheric climate drivers. It was found that there is a marked disparity in the percentage of summer days above the 95th percentile during the accelerated climate change period (1992–2021) between Richmond (+35%) and Sydney (−24%), relative to 1962–1991. The climate drivers detected as attributes were similar in both Sydney and Richmond, but, unsurprisingly, Sydney was more affected than Richmond by the oceanic climate drivers.

Recent satellite measurements of glacier mass balances show mountain glaciers all over the world had generally negative mass balances in the first decades of the 21st century. Mean summer temperatures all over the world rose from the 1961–1990 period to the 1991–2020 period, implying increasingly negative mass balances. We studied archived annual balances for 38 northern hemisphere glaciers to assess changes within the 1961–2020 period. We used a modified double-mass curve to visualize mass balance changes occurring around 1990. Mean balances in 1961–1990 were already small negative for many of the studied glaciers and became even more negative in 1991–2020 for glaciers in the Alps, at high latitudes and in western North America. The largest mass balance changes were for some glaciers in the Alps. We are unable to explain the lack of change in mean balance for one glacier in High Mountain Asia. We found complex changes for eight glaciers in Scandinavia, even including one glacier with a positive balance. We explain these changes by visualizing the deviations in winter and summer balances from their respective 1961–1990 mean values. High winter balances in the 1990s for Scandinavia partly obscured the emerging trend of increasingly negative summer balances, which we expect to continue in the future.

We compare a Bayesian modelling-based technique with weighted averaging (WA) and weighted averaging-partial least squares (WA-PLS) regression in pollen-based summer temperature transfer function calibration. We test the methods using a new, 113-sample calibration set from Estonia, Lithuania and European Russia, and a Holocene fossil pollen sequence from Lake Kharinei, a previously studied lake in northeast European Russia. We find WA-PLS to outperform WA, probably because of smaller edge-effect biases in the ends of the calibration set gradient. The Bayesian-based calibration models show further improved performance compared with WA-PLS in leave-one-out cross-validation, while additional h-block cross-validation shows the Bayesian method to be little affected by spatial autocorrelation. Comparison with independent climate proxies reveals, however, some clear biases in the Bayesian palaeotemperature reconstructions, likely reflecting in part some specific limitations of our calibration set. As the selected prior parameters can significantly affect both Bayesian cross-validation performance and reconstructions, there is a clear need to further test the Bayesian method in different geographic contexts and over different timescales, with special attention given to the selection of the most realistic priors in each situation. In general, our finding that statistically well-performing transfer functions may produce clearly differing palaeotemperature reconstructions urges caution in transfer function-based inferences. We additionally test a spatially restricted, 58-sample subset of the full 113-sample calibration set. We find some reduced biases with the smaller set, likely because of complex, partially bimodal responses of several taxa along the longer temperature gradient, ill-suited for calibration methods assuming unimodal responses to climate.

This study investigates the dominant modes of surface air temperature (SAT) variability and associated circulation changes over the Arabian Peninsula (AP) during summer for the period 1979–2016 based on an empirical orthogonal function (EOF) analysis. The analysis results reveal that the first leading EOF mode is related to the weakening of the subtropical westerly jet stream, which may impact the AP temperature variability through the mid‐latitude Rossby wave trains (successive troughs and ridges). This can be explained by the high correlation of the AP summer temperatures with the quasi‐stationary mid‐latitude/extratropical Eurasian Rossby wave train type patterns, which influences the air temperature variability by modulating the Asian Jets. Furthermore, the high AP SAT variability is also closely associated with strong middle to lower tropospheric descent (subsidence) anomalies, which cause warm temperature anomalies over this region. Summer climatological 250‐hPa level wave activity fluxes illustrated the influence of quasi‐stationary mid‐latitude/extratropical Eurasian Rossby waves on the AP summer temperatures variability for the period 1979–2016.

Analysis of pollen records from North America and Europe reveals a warming trend over the Holocene, consistent with climate-model simulations. Preserved pollen presents climate past In spite of decades of work, climate trends over the Holocene—the past 11,700 years—remain extensively debated. For example, climate models forced by known changes in insolation tend to simulate warming while reconstructions using proxies such as marine records often reveal cooling over the late Holocene, before sharp warming in the industrial era. Now, Jeremiah Marsicek and colleagues re-analyse extensive pollen records from North America and Europe and show a warming trend over the Holocene, consistent with climate model simulations. Evidence for cooling appears to be constrained to the North Atlantic region, rather than being a global signal. Cooling during most of the past two millennia has been widely recognized 1 , 2 and has been inferred to be the dominant global temperature trend of the past 11,700 years (the Holocene epoch) 3 . However, long-term cooling has been difficult to reconcile with global forcing 4 , and climate models consistently simulate long-term warming 4 . The divergence between simulations and reconstructions emerges primarily for northern mid-latitudes, for which pronounced cooling has been inferred from marine and coastal records using multiple approaches 3 . Here we show that temperatures reconstructed from sub-fossil pollen from 642 sites across North America and Europe closely match simulations, and that long-term warming, not cooling, defined the Holocene until around 2,000 years ago. The reconstructions indicate that evidence of long-term cooling was limited to North Atlantic records. Early Holocene temperatures on the continents were more than two degrees Celsius below those of the past two millennia, consistent with the simulated effects of remnant ice sheets in the climate model Community Climate System Model 3 (CCSM3) 5 . CCSM3 simulates increases in ‘growing degree days’—a measure of the accumulated warmth above five degrees Celsius per year—of more than 300 kelvin days over the Holocene, consistent with inferences from the pollen data. It also simulates a decrease in mean summer temperatures of more than two degrees Celsius, which correlates with reconstructed marine trends and highlights the potential importance of the different subseasonal sensitivities of the records. Despite the differing trends, pollen- and marine-based reconstructions are correlated at millennial-to-centennial scales, probably in response to ice-sheet and meltwater dynamics, and to stochastic dynamics similar to the temperature variations produced by CCSM3. Although our results depend on a single source of palaeoclimatic data (pollen) and a single climate-model simulation, they reinforce the notion that climate models can adequately simulate climates for periods other than the present-day. They also demonstrate that amplified warming in recent decades increased temperatures above the mean of any century during the past 11,000 years.

By employing multi-reanalysis daily datasets and station data, this study focuses on the evolution characteristics of the daily-scale Silk Road pattern (SRP) and its effect on summer temperatures in the Yangtze River Valley (YRV). The results manifest that the evolution characteristics of positive- and negative-phase SRP (referred to SRP+ and SRP−) exhibit marked distinctions. The anomaly centers of SRP+ over West Central Asia (WCA) and Mongolia emerge firstly, vanishing simultaneously one week after peak date; however, the Far East (FE) anomaly centers can persist for a longer period. The SRP− starts with the WCA and FE centers, with a rapid decline in the strength of the WCA center and preservation of other anomaly centers after its peak. In the vertical direction, daily-scale SRP mainly concentrates in the mid-to-upper troposphere. Baroclinicity accounts for its early development and barotropic instability process favors the maintenance. Moreover, the SRP+ (SRP−) is inextricably linked to heat wave (cool summer) processes in the YRV. Concretely, before the onset of SRP+ events, an anomalous anticyclone and significant negative vorticities over East Asia related to SRP+ favor the zonal advance between the South Asia high (SAH) and western Pacific subtropical high (WPSH), inducing local descents over YRV area. The sinking adiabatic warming and clear-sky radiation warming can be considered as the possible causes for the YRV heat waves. The adiabatic cooling with the local ascents leads to more total cloud cover (positive precipitation anomalies) and less solar radiation incident to surface of the YRV, inducing the cool summer process during SRP−.

Heat waves such as the one in Europe 2003 have severe consequences for the economy, society, and ecosystems. It is unclear whether temperatures could have exceeded these anomalies even without further climate change. Developing storylines and quantifying the highest possible temperature levels is challenging given the lack of a long homogeneous time series and methodological framework to assess them. Here, we address this challenge by analyzing summer temperatures in a nearly 5000-yr preindustrial climate model simulation, performed with the Community Earth System Model CESM1. To assess how anomalous temperatures could get, we compare storylines generated by three different methods: 1) a return-level estimate, deduced from a generalized extreme value distribution; 2) a regression model, based on dynamic and thermodynamic heat wave drivers; and 3) a novel ensemble boosting method, generating large samples of reinitialized extreme heat waves in the long climate simulation. All methods provide consistent temperature estimates, suggesting that historical exceptional heat waves such as those in Chicago in 1995, Europe in 2003, and Russia in 2010 could have been substantially exceeded even in the absence of further global warming. These estimated unseen heat waves are caused by the same drivers as moderate observed events, but with more anomalous patterns. Moreover, altered contributions of circulation and soil moisture to temperature anomalies include amplified feedbacks in the surface energy budget. The methodological framework of combining different storyline approaches of heat waves with magnitudes beyond the observational record may ultimately contribute to adaptation and to the stress testing of ecosystems or socioeconomic systems to increase resilience to extreme climate stressors.

The Last Interglacial (LIG), a warmer period 130,000–116,000 years before present, is a potential analogue for future climate change. Stronger LIG summertime insolation at high northern latitudes drove Arctic land summer temperatures 4–5 °C higher than in the pre-industrial era. Climate model simulations have previously failed to capture these elevated temperatures, possibly because they were unable to correctly capture LIG sea-ice changes. Here, we show that the latest version of the fully coupled UK Hadley Center climate model (HadGEM3) simulates a more accurate Arctic LIG climate, including elevated temperatures. Improved model physics, including a sophisticated sea-ice melt-pond scheme, result in a complete simulated loss of Arctic sea ice in summer during the LIG, which has yet to be simulated in past generations of models. This ice-free Arctic yields a compelling solution to the long-standing puzzle of what drove LIG Arctic warmth and supports a fast retreat of future Arctic summer sea ice.Arctic climate in the Last Interglacial (LIG)—a warm period 130,000–116,000 years ago—is poorly simulated by modern climate models. A model with improved sea-ice melt-pond physics reproduces LIG Arctic temperatures, suggests an ice-free Arctic during this period and predicts the same by 2035.

In the context of global warming, the impact of summer high temperature events is increasing. The accumulated summer high temperature is often used to reflect the overall hotness of summer. The internal variation of the accumulated temperature can be affected by both the frequency and intensity. In this study, by using the daily data during summers of 1960–2018, we examine the relative importance of the two factors with a multiple linear regression method. It is demonstrated that that the dominant result of summer accumulated temperature is sensitive to the change of threshold. As the threshold increases, the importance of frequency gradually increases, while the importance of the intensity decreases. In addition, it is found that when the threshold changes, the sensitivity of the dominant results is different over regions. This can provide a basis for the selection of regional thresholds and further improve the representation of accumulated temperature for high summer temperatures.