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Central European winters have warmed markedly since the mid-20th century. Yet cold winters are still associated with severe societal impacts on energy systems, infrastructure and public health. It is therefore crucial to anticipate storylines of worst-case cold winter conditions, and to understand whether an extremely cold winter, such as the coldest winter in the historical record of Germany in 1963 (−6.3 °C or −3.4 σ seasonal DJF temperature anomaly relative to 1981–2010), is still possible in a warming climate. Here, we first show based on multiple attribution methods that a winter of similar circulation conditions to 1963 would still lead to an extreme seasonal cold anomaly of about −4.9 to −4.7 °C (best estimates across methods) under present-day climate. This would rank as second-coldest winter in the last 75 years. Second, we conceive storylines of worst-case cold winter conditions based on two independent rare event sampling methods (climate model boosting and empirical importance sampling): winter as cold as 1963 is still physically possible in Central Europe today, albeit very unlikely. While cold winter hazards become less frequent and less intense in a warming climate overall, it remains crucial to anticipate the possibility of an extreme cold winter to avoid potential maladaptation and increased vulnerability. [ABSTRACT FROM AUTHOR]

For sectors like agriculture, hydrology and ecology, increasing interannual variability (IAV) can have larger impacts than changes in the mean state, whereas decreasing IAV in winter implies that the coldest seasons warm more than the mean. IAV is difficult to reliably quantify in single realizations of climate (observations and single-model realizations) as they are too short, and represent a combination of external forcing and IAV. Single-model initial-condition large ensembles (SMILEs) are powerful tools to overcome this problem, as they provide many realizations of past and future climate and thus a larger sample size to robustly evaluate and quantify changes in IAV. We use three SMILE-based regional climate models (CanESM-CRCM, ECEARTH-RACMO and CESM-CCLM) to investigate downscaled changes in IAV of summer and winter temperature and precipitation, the number of heat waves, and the maximum length of dry periods over Europe. An evaluation against the observational data set E-OBS reveals that all models reproduce observational IAV reasonably well, although both under- and overestimation of observational IAV occur in all models in a few cases. We further demonstrate that SMILEs are essential to robustly quantify changes in IAV since some individual realizations show significant IAV changes, whereas others do not. Thus, a large sample size, i.e., information from all members of SMILEs, is needed to robustly quantify the significance of IAV changes. Projected IAV changes in temperature over Europe are in line with existing literature: increasing variability in summer and stable to decreasing variability in winter. Here, we further show that summer and winter precipitation, as well as the two summer extreme indicators mostly also show these seasonal changes. [ABSTRACT FROM AUTHOR]

In recent summers, Europe experienced record‐breaking heatwaves, wildfires (in Northern Europe), and large‐scale water scarcity. Apart from anthropogenic warming, one contribution leading to such exceptionally hot weather was a weaker jet stream allowing a quasi‐stationary high‐pressure system to persist for many days. Here, we quantify changes in the frequency and persistence of the Central European large‐scale circulation types using various climate models. Independent of the circulation type, the models project warmer and drier future summer conditions in Central Europe, but no consistent shift to a more persistent summer or winter circulation. Most of the frequency and persistence changes are small and either within the internal variability or inconsistent across models. The model projections in this study do not support the claim of more persistent weather over Central Europe. Reconciling the results of different approaches and classifications is therefore critical to understand and predict changes in extreme weather over Europe. Plain Language Summary: The atmospheric flow over Central Europe is a key component of both its weather and climate. Recent studies have suggested that the Central European weather patterns are becoming more persistent due to our influence on the climate system. Persistent conditions can lead to record‐breaking droughts and heatwaves. It is therefore important to know how the flow conditions (also called circulation types) may change in the future. Here, we use a wide range of global climate models and classify a circulation type for each day. We distinguish between the eight main wind directions and a high‐ and low‐pressure type. Then, we quantify changes in the frequency and length of these circulation types under a strong global warming scenario at the end of the 21st century. In summer, we find a shift to warmer and drier conditions. Our models also show somewhat more persistent summer westerlies. In winter, the changes are not clear. Most of the changes in the circulation are small and likely within the range expected from natural random weather fluctuations. Our study highlights the importance of using many different climate models and other methods to investigate the highly variable Central European circulation today and under a future climate. Key Points: Climate models project warmer and drier Central European summer conditions under strong global warming independent of the circulation typeFor most circulation types, the models do not agree on the sign and/or magnitude of the projected change in the frequency and persistenceCurrent global climate models do not support a general trend towards more persistent weather in Central Europe [ABSTRACT FROM AUTHOR]

In the last two decades Europe experienced a series of high‐impact heat extremes. We here assess observed trends in temperature extremes at ECA&D stations in Europe. We demonstrate that on average across Europe the number of days with extreme heat and heat stress has more than tripled and hot extremes have warmed by 2.3 °C from 1950–2018. Over Central Europe, the warming exceeds the corresponding summer mean warming by 50%. Days with extreme cold temperatures have decreased by a factor of 2–3 and warmed by more than 3 °C, regionally substantially more than winter mean temperatures. Cold and hot extremes have warmed at about 94% of stations, a climate change signal that cannot be explained by internal variability. The clearest climate change signal can be detected in maximum heat stress. EURO‐CORDEX RCMs broadly capture observed trends but the majority underestimates the warming of hot extremes and overestimates the warming of cold extremes. Key Points: We detect a clear climate change signal in extreme heat, heat stress, and cold over Europe that cannot be explained by internal variabilityOn average across Europe, days with extreme heat and heat stress have tripled and days with extreme cold more than halved from 1950–2018Hot and cold extremes warmed significantly more than the corresponding seasonal mean in Central Europe, by 2.3 and >3 °C, respectively [ABSTRACT FROM AUTHOR]

Single model large ensembles are widely used model experiments to estimate internal climate variability. The underlying assumption is that the internal variability (here: inter-annual variability) of the chosen model is a good approximation of the observed natural (inter-annual) variability. In this study, we test this assumption based on three regional climate model large ensembles (16 members of an EC-EARTH-RACMO ensemble, 21 members of a CESM-CCLM ensemble, 50 members of a CanESM-CRCM ensemble) for four European domains (British Isles, France, Mid-Europe, Alps). Simulated inter-annual variability is evaluated against E-OBS and the inter-annunal variability and its future change are compared across the ensembles. To the knowledge of the authors, this is the first comparison of regional large ensembles over Europe. Analysis comprises seasonal temperature and precipitation, as well as indicators for dry periods and heat waves. Results show a large consistency of all three ensembles with E-OBS data for most indicators and regions, validating the abilities of these ensembles to represent natural variability on the annual scale. EC-EARTH-RACMO shows the highest inter-annual variability for winter temperature and precipitation, whereas CESM-CCLM shows the highest variability for summer temperature and precipitation, as well as for heatwaves and dry periods. Despite these model differences, the sign of the future changes in internal variability is largely the same in all models: for summer temperature, summer precipitation and the number of heat waves, the internal variability increases, while it decreases for winter temperature. Changes of winter precipitation and dry periods are a bit unclear, with a tendency to increase for dry periods. The overall consistency across single model large ensembles and observations strengthens the concept of large ensembles, and underlines their great potential for understanding and quantifying the role of internal climate variability. [ABSTRACT FROM AUTHOR]

The influence of atmospheric circulation on winter temperature and precipitation trends over Europe in the period 2006-50 is investigated in a 21-member initial condition ensemble from a fully coupled global climate model and in a multimodel framework consisting of 40 different models. Five versions of a dynamical adjustment method based on empirical orthogonal function analysis of sea level pressure are introduced, and their performance in removing the effect of atmospheric circulation on temperature and precipitation is tested. The differences in atmospheric circulation as simulated by different models in their control runs and under the historical and representative concentration pathway 8.5 (RCP8.5) forcing scenarios are investigated. Dynamical adjustment is applied to the multimodel ensemble to demonstrate that a substantial fraction of the uncertainty in projected European temperature and precipitation trends is explained by atmospheric circulation variability. A statistically significant response of sea level pressure to anthropogenic forcing is identified in the multimodel ensemble under the RCP8.5 scenario. This forced response in atmospheric circulation is associated with a dynamical contribution to the long-term multimodel mean temperature and precipitation trends. The results highlight the importance of accounting for the impact of atmospheric circulation variability on trends in regional climate projections. [ABSTRACT FROM AUTHOR]

The summer of 2010 was exceptionally warm in eastern Europe and large parts of Russia. We provide evidence that the anomalous 2010 warmth that caused adverse impacts exceeded the amplitude and spatial extent of the previous hottest summer of 2003. "Mega-heatwaves" such as the 2003 and 2010 events likely broke the 500-year-long seasonal temperature records over approximately 50% of Europe. According to regional multi-model experiments, the probability of a summer experiencing mega-heatwaves will increase by a factor of 5 to 10 within the next 40 years. However, the magnitude of the 2010 event was so extreme that despite this increase, the likelihood of an analog over the same region remains fairly low until the second half of the 21st century. [ABSTRACT FROM AUTHOR]

The article offers information related to heatwaves in Europe and Russia in 2003 and 2010, respectively. It discusses factors that triggers the phenomenon such as air pressure system, temperature, and humidity. Also mentioned the role of climate scientists for satellite observations of the climatic events.