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Determining the underlying mechanisms leading to extreme events in dynamical systems is a challenging task. Under mild hypotheses, large deviations theory predicts that, as one increases the threshold defining an extreme, dynamical trajectories which reach the extreme look more and more like one another: they converge towards a typical, i.e. most probable, trajectory called the instanton. In this paper, we use a 2000-year simulation of the IPSL-CM6A-LR model under a stationary pre-industrial climate to test this prediction on the case of hot extremes. We investigate whether the physical mechanisms leading to extreme temperatures at four locations in Europe are more similar with increasing extreme temperatures. Our results show that most physical variables exhibit the expected convergence towards a most probable trajectory, with some geographical and temporal variations. In particular, we observe the presence of a cut-off low in some trajectories, which suggests the existence of multiple pathways leading to extreme temperatures. These findings confirm the relevance of instanton dynamics to understand the physical mechanisms driving extreme events in climate models. [ABSTRACT FROM AUTHOR]

Europe and in particular its southern part are expected to undergo serious climate changes during summer in response to anthropogenic forcing, with large surface warming and decrease in precipitation. Yet, serious uncertainties remain, especially over central and western Europe. Several mechanisms have been suggested to be important in that context but their relative importance and possible interplays are still not well understood. In this paper, the role of soil-atmosphere interactions, cloud-temperature interactions and land-sea warming contrast in summer European climate change and how they interact are analyzed. Models for which evapotranspiration is strongly limited by soil moisture in the present climate are found to tend to simulate larger future decrease in evapotranspiration. Models characterized by stronger present-day anti-correlation between cloud cover and temperature over land tend to simulate larger future decrease in cloud cover. Large model-to-model differences regarding land-sea warming contrast and its impacts are also found. Warming over land is expected to be larger than warming over sea, leading to a decrease in continental relative humidity and precipitation because of the discrepancy between the change in atmospheric moisture capacity over land and the change in specific humidity. Yet, it is not true for all the models over our domain of interest. Models in which evapotranspiration is not limited by soil moisture and with a weak present-day anti-correlation between cloud cover and temperature tend to simulate smaller land surface warming. In these models, change in specific humidity over land is therefore able to match the continental increase in moisture capacity, which leads to virtually no change in continental relative humidity and smaller precipitation change. Because of the physical links that exist between the response to anthropogenic forcing of important impact-related climate variables and the way some mechanisms are simulated in the context of present-day variability, this study suggests some potentially useful metrics to reduce summer European climate change uncertainties. [ABSTRACT FROM AUTHOR]

Recently, much attention has been devoted to better understand the internal modes of variability of the climate system. This is particularly important in mid-latitude regions like the North-Atlantic, which is characterized by a large natural variability and is intrinsically difficult to predict. A suitable framework for studying the modes of variability of the atmospheric circulation is to look for recurrent patterns, commonly referred to as Weather Regimes. Each regime is characterized by a specific large-scale atmospheric circulation pattern, thus influencing regional weather and extremes over Europe. The focus of the present paper is the study of the Euro-Atlantic wintertime Weather Regimes in the climate models participating to the PRIMAVERA project. We analyse here the set of coupled historical simulations (hist-1950), which have been performed both at standard and increased resolution, following the HighresMIP protocol. The models' performance in reproducing the observed Weather Regimes is assessed in terms of different metrics, focussing on systematic biases and on the impact of resolution. We also analyse the connection of the Weather Regimes with the Jet Stream latitude and blocking frequency over the North-Atlantic sector. We find that—for most models—the regime patterns are better represented in the higher resolution version, for all regimes but the NAO-. On the other side, no clear impact of resolution is seen on the regime frequency of occurrence and persistence. Also, for most models, the regimes tend to be more tightly clustered in the increased resolution simulations, more closely resembling the observed ones. However, the horizontal resolution is not the only factor determining the model performance, and we find some evidence that biases in the SSTs and mean geopotential field might also play a role. [ABSTRACT FROM AUTHOR]

Wind direction kept in ships' logbooks is a consolidated but underexploited observational source of relevant climatic information. In this paper, we present four indices of the monthly frequency of wind direction, one for each cardinal direction: Northerly (NI), Easterly (EI), Southerly (SI) and Westerly (WI), based on daily wind direction observations taken aboard ships over the English Channel. These Directional Indices (DIs) are the longest observational record of atmospheric circulation to date at the daily scale, covering the 1685–2014 period. DIs anomalies are associated with near-surface climatic signals over large areas of Europe in all seasons, with zonal indices (WI and EI) and meridional indices (NI and SI) often affecting different regions. Statistical models including all DIs are able to explain a considerable amount of European climate variability, in most cases higher than that accounted for by the North Atlantic Oscillation. As such, the DIs are able to reproduce the known European climatic history and provide new insights of certain episodes from monthly to multi-decadal time scales such as the warm winter decade of 1730–1739 or the extremely cold 1902 summer. The DIs show the potential to better constrain the atmospheric circulation response to external forcings and its associated anomalies. In particular, we provide first observational evidences of all year-round atmospheric circulation signals following the strongest tropical volcanic eruptions of the last three centuries. These signatures are more complex than previously thought and suggest that the well-reported winter warming and summer cooling cannot be simply interpreted in terms of changes in zonality. [ABSTRACT FROM AUTHOR]

The aim of this paper is threefold. Firstly, to present a representative set of large-scale weather regimes for each month of the year over the Euro-Atlantic region and compare them amongst three commonly employed global reanalyses. Secondly, to measure the impact of the weather regimes on near-surface wind speed variability. Lastly, to validate the regime's ability to reconstruct monthly wind speed anomalies. Wind speed reconstruction provides critical information on the role of weather regimes as source of predictability of wind speed, by identifying areas where wind is poorly or highly influenced by weather regimes as a whole. Conclusions are extracted about the adequacy of weather regimes to characterize local wind speed variability over Europe. [ABSTRACT FROM AUTHOR]

How climate change will unfold in the years to come is a central topic in today's environmental debate, in particular at the regional level. While projections using large ensembles of global climate models consistently indicate a future decrease in summer precipitation over southern Europe and an increase over northern Europe, individual models substantially modulate these distinct signals of change in precipitation. So far model improvements and higher resolution from regional downscaling have not been seen as able to resolve these disagreements. In this paper we assess whether 2 decades of investments in large ensembles of downscaling experiments with regional climate model simulations for Europe have contributed to a more robust model assessment of the future climate at a range of geographical scales. We study climate change projections of European seasonal temperature and precipitation using an ensemble-suite comprised by all readily available pan-European regional model projections for the twenty-first-century, representing increasing model resolution from ~ 50 to ~ 12 km grid distance, as well as lateral boundary and sea surface temperature conditions from a variety of global model simulations. Employing a simple scaling with global mean temperature change we identify emerging robust signals of future seasonal temperature and precipitation changes also found to resemble current observed trends, where these are judged to be statistically significant. [ABSTRACT FROM AUTHOR]

In this paper we characterize the seasonal and inter-annual variabilities of cloud fraction profiles in both observations and simulation since they are critical to better assess the impact of clouds on climate variability. The spaceborne lidar onboard CALIPSO, providing cloud vertical profiles since 2006, is used together with a 23-year WRF simulation at 20 km resolution. A lidar simulator helps to compare consistently model with observations. The bias in observations due to the satellite under-sampling is first estimated. Then we examine the vertical variability of both occurrence and properties of clouds. It results that observations indicate a similar occurrence of low and high clouds over continent, and more high than low clouds over the sea except in summer. The simulation shows an overestimate (underestimate) of high (low) clouds comparing to observations, especially in summer. However the seasonal variability of cloud vertical profiles is well captured by WRF. Concerning inter-annual variability, observations show that in winter, those of high clouds is twice the low clouds one, an order of magnitude that is is well simulated. In summer, the observed inter-annual variability is vertically more homogeneous while the model still simulates more variability for high clouds than for low clouds. The good behavior of the simulation in winter allows us to use the 23 years of simulation and 8 years of observations to estimate the time period required to characterize the natural variability of the cloud fraction profile in winter, i.e. the time period required to detect significant anomalies and trends. [ABSTRACT FROM AUTHOR]

Recent winter seasons have evidenced that global warming does not exclude the occurrence of exceptionally cold and/or snowy episodes in the Northern mid-latitudes. The expected rarefaction of such events is likely to exacerbate both their societal and environmental impacts. This paper therefore aims to evaluate model uncertainties underlying the fate of wintertime cold extremes over Europe. Understanding why climate models (1) still show deficiencies in simulating present-day features and (2) differ in their responses under future scenarios for the twentyfirst century indeed constitutes a crucial challenge. Here we propose a weather-regime approach in order to separate the contributions of large-scale circulation and non-dynamical processes to biases or changes in the simulated mean and extreme temperatures. We illustrate our methodology from the wintertime occurrence of extremely cold days in idealized atmosphere-only experiments performed with two of the CMIP5 climate models (CNRM-CM5 and IPSL-CM5A-LR). First we find that most of the present-day temperature biases are due to systematic errors in non-dynamical processes, while the main features of the large-scale dynamics are well captured in such experiments driven by observed sea-surface temperatures, with the exception of a generalized underestimation of blocking episodes. Then we show that uncertainties associated with changes in large-scale circulation modulate the depletion in cold extremes under an idealized scenario for the late twentyfirst century. These preliminary results suggest that the original methodology proposed in this paper can be helpful for understanding spreads of larger model-ensembles when simulating the response of temperature extremes to climate change. [ABSTRACT FROM AUTHOR]

The projected climate change signals of a five-member high resolution ensemble, based on two global climate models (GCMs: ECHAM5 and CCCma3) and two regional climate models (RCMs: CLM and WRF) are analysed in this paper (Part II of a two part paper). In Part I the performance of the models for the control period are presented. The RCMs use a two nest procedure over Europe and Germany with a final spatial resolution of 7 km to downscale the GCM simulations for the present (1971-2000) and future A1B scenario (2021-2050) time periods. The ensemble was extended by earlier simulations with the RCM REMO (driven by ECHAM5, two realisations) at a slightly coarser resolution. The climate change signals are evaluated and tested for significance for mean values and the seasonal cycles of temperature and precipitation, as well as for the intensity distribution of precipitation and the numbers of dry days and dry periods. All GCMs project a significant warming over Europe on seasonal and annual scales and the projected warming of the GCMs is retained in both nests of the RCMs, however, with added small variations. The mean warming over Germany of all ensemble members for the fine nest is in the range of 0.8 and 1.3 K with an average of 1.1 K. For mean annual precipitation the climate change signal varies in the range of −2 to 9 % over Germany within the ensemble. Changes in the number of wet days are projected in the range of ±4 % on the annual scale for the future time period. For the probability distribution of precipitation intensity, a decrease of lower intensities and an increase of moderate and higher intensities is projected by most ensemble members. For the mean values, the results indicate that the projected temperature change signal is caused mainly by the GCM and its initial condition (realisation), with little impact from the RCM. For precipitation, in addition, the RCM affects the climate change signal significantly. [ABSTRACT FROM AUTHOR]

This paper presents a comparison of principal component (PC) regression and regularized expectation maximization (RegEM) to reconstruct European summer and winter surface air temperature over the past millennium. Reconstruction is performed within a surrogate climate using the National Center for Atmospheric Research (NCAR) Climate System Model (CSM) 1.4 and the climate model ECHO-G 4, assuming different white and red noise scenarios to define the distortion of pseudoproxy series. We show how sensitivity tests lead to valuable “a priori” information that provides a basis for improving real world proxy reconstructions. Our results emphasize the need to carefully test and evaluate reconstruction techniques with respect to the temporal resolution and the spatial scale they are applied to. Furthermore, we demonstrate that uncertainties inherent to the predictand and predictor data have to be more rigorously taken into account. The comparison of the two statistical techniques, in the specific experimental setting presented here, indicates that more skilful results are achieved with RegEM as low frequency variability is better preserved. We further detect seasonal differences in reconstruction skill for the continental scale, as e.g. the target temperature average is more adequately reconstructed for summer than for winter. For the specific predictor network given in this paper, both techniques underestimate the target temperature variations to an increasing extent as more noise is added to the signal, albeit RegEM less than with PC regression. We conclude that climate field reconstruction techniques can be improved and need to be further optimized in future applications. [ABSTRACT FROM AUTHOR]

This paper analyses the influence of different atmospheric circulation indices on the multi-scalar drought variability across Europe by using the Standardized Precipitation Evapotranspiration Index (SPEI). The monthly circulation indices used in this study include the North Atlantic oscillation (NAO), the East Atlantic (EA), the Scandinavian (SCAN) and the East Atlantic-Western Russia (EA-WR) patterns, as well as the recently published Westerly Index (WI), defined as the persistence of westerly winds over the eastern north Atlantic region. The results indicate that European drought variability is better explained by the station-based NAO index and the WI than by any other combination of circulation indices. In northern and central Europe the variability of drought severity for different seasons and time-scales is strongly associated with the WI. On the contrary, the influence of the NAO on southern Europe droughts is stronger than that exerted by the WI. The correlation patterns of the NAO and WI with the SPEI show a spatial complementarity in shaping drought variability across Europe. Lagged correlations of the NAO and WI with the SPEI also indicate enough skill of both indices to anticipate drought severity several months in advance. As long as instrumental series of the NAO and WI are available, their combined use would allow inferring European drought variability for the last two centuries and improve the calibration and interpretation of paleoclimatic proxies associated with drought. [ABSTRACT FROM AUTHOR]

This paper presents an evaluation of the multi-model simulations for the 4th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) in terms of their ability to simulate the ERA40 circulation types over the Euro-Atlantic region in winter season. Two classification schemes, k-means and SANDRA, have been considered to test the sensitivity of the evaluation results to the classification procedure. The assessment allows establishing different rankings attending spatial and temporal features of the circulation types. Regarding temporal characteristics, in general, all AR4 models tend to underestimate the frequency of occurrence. The best model simulating spatial characteristics is the UKMO-HadGEM1 whereas CCSM3, UKMO-HadGEM1 and CGCM3.1(T63) are the best simulating the temporal features, for both classification schemes. This result agrees with the AR4 models ranking obtained when having analysed the ability of the same AR4 models to simulate Euro-Atlantic variability modes. This study has proved the utility of applying such a synoptic climatology approach as a diagnostic tool for models' assessment. The ability of the models to properly reproduce the position of ridges and troughs and the frequency of synoptic patterns, will therefore improve our confidence in the response of models to future climate changes. [ABSTRACT FROM AUTHOR]

This paper analyzes the ability of the multi-model simulations from the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) to simulate the main leading modes of variability over the Euro-Atlantic region in winter: the North-Atlantic Oscillation (NAO), the Scandinavian mode (SCAND), the East/Atlantic Oscillation (EA) and the East Atlantic/Western Russia mode (EA/WR). These modes of variability have been evaluated both spatially, by analyzing the intensity and location of their anomaly centres, as well as temporally, by focusing on the probability density functions and e-folding time scales. The choice of variability modes as a tool for climate model assessment can be justified by the fact that modes of variability determine local climatic conditions and their likely change may have important implications for future climate changes. It is found that all the models considered are able to simulate reasonably well these four variability modes, the SCAND being the mode which is best spatially simulated. From a temporal point of view the NAO and SCAND modes are the best simulated. UKMO-HadGEM1 and CGCM3.1(T63) are the models best at reproducing spatial characteristics, whereas CCSM3 and CGCM3.1(T63) are the best ones with regard to the temporal features. GISS-AOM is the model showing the worst performance, in terms of both spatial and temporal features. These results may bring new insight into the selection and use of specific models to simulate Euro-Atlantic climate, with some models being clearly more successful in simulating patterns of temporal and spatial variability than others. [ABSTRACT FROM AUTHOR]

In this paper, we examine the trends of temperature series in Europe, for the mean as well as for the variance in hot and cold seasons. To do so, we use as long and homogenous series as possible, provided by the European Climate Assessment and Dataset project for different locations in Europe, as well as the European ENSEMBLES project gridded dataset and the ERA40 reanalysis. We provide a definition of trends that we keep as intrinsic as possible and apply non-parametric statistical methods to analyse them. Obtained results show a clear link between trends in mean and variance of the whole series of hot or cold temperatures: in general, variance increases when the absolute value of temperature increases, i.e. with increasing summer temperature and decreasing winter temperature. This link is reinforced in locations where winter and summer climate has more variability. In very cold or very warm climates, the variability is lower and the link between the trends is weaker. We performed the same analysis on outputs of six climate models proposed by European teams for the 1961–2000 period (1950–2000 for one model), available through the PCMDI portal for the IPCC fourth assessment climate model simulations. The models generally perform poorly and have difficulties in capturing the relation between the two trends, especially in summer. [ABSTRACT FROM AUTHOR]

This paper analyzes the soil–atmosphere feedbacks and uncertainties under current (1960–1990) and plausible future climate conditions (2070–2100, using the A2 greenhouse gases emission scenario). For this purpose, two vegetation descriptions differing only in the grassland and grass-with-trees proportion in some parts of the domain have been created. The combination of these two different climate scenarios and two vegetation descriptions defines four different 30-year experiments, which have been completed using a regional climate model. The domain is centered around the Mediterranean basin and covers most of Europe. The study focuses on the summer season when there are major differences between the two vegetation descriptions and when the impact of land–surface processes on precipitation is largest. Present climate experiments show large evapotranspiration differences over areas where vegetation changes have taken place. Precipitation increases (up to 3 mm day−1 in some regions) follow evapotranspiration increases, although with a more complex spatial structure. These results indicate a high sensitivity at regional scales of summer precipitation processes to vegetation changes. Future climate simulations show very similar changes to those observed in the current climate experiments. This indicates that the impacts of climate change are relatively independent to the land-cover descriptions used in this study. [ABSTRACT FROM AUTHOR]

There is considerable interest in the potential impact of climate change on the feasibility and predictability of renewable energy sources including wind energy. This paper presents dynamically downscaled near-surface wind fields and examines the impact of climate change on near-surface flow and hence wind energy density across northern Europe. It is shown that: Simulated wind fields from the Rossby Centre coupled Regional Climate Model (RCM) (RCAO) with boundary conditions derived from ECHAM4/OPYC3 AOGCM and the HadAM3H atmosphere-only GCM exhibit reasonable and realistic features as documented in reanalysis data products during the control period (1961–1990). The near-surface wind speeds calculated for a climate change projection period of 2071–2100 are higher than during the control run for two IPCC emission scenarios (A2, B2) for simulations conducted using boundary conditions from ECHAM4/OPYC3. The RCAO simulations conducted using boundary conditions from ECHAM4/OPYC3 indicate evidence for a small increase in the annual wind energy resource over northern Europe between the control run and climate change projection period and for more substantial increases in energy density during the winter season. However, the differences between the RCAO simulations for the climate projection period and the control run are of similar magnitude to differences between the RCAO fields in the control period and the NCEP/NCAR reanalysis data. Additionally, the simulations show a high degree of sensitivity to the boundary conditions, and simulations conducted using boundary conditions from HadAM3H exhibit evidence of slight declines or no change in wind speed and energy density between 1961–1990 and 2071–2100. Hence, the uncertainty of the projected wind changes is relatively high. [ABSTRACT FROM AUTHOR]

European heatwaves at the 0.5, 1.0, 1.5 and 2.0 ∘ C global warming levels above the pre-industrial temperature are examined using bias-corrected daily-mean temperature data from 60 simulations performed with 25 global climate models (GCMs). A heatwave event is defined here to consist of at least three consecutive days above the 90th percentile of summer daily-mean temperatures and a break of 1 day is allowed. At the 2.0 ∘ C global warming level compared with 0.5 ∘ C, the multi-GCM mean annual count of heatwave days is projected to be three to fourfold in northern and more than sixfold in southern Europe. The total annual heatwave extremity index, or the sum of exceedings above the threshold temperature over all the heatwave days, becomes approximatively fourfold in the north and tenfold in the south. In central Europe, the date of the strongest heatwave of year is delayed by about 1 week. By concatenating the bias-corrected output data of all the GCM runs, 1200-year samples were created from which probabilities of occurrence of the strongest heatwaves can be determined very robustly under all four warming levels. An intense heatwave occurring once in 10 years at the 0.5 ∘ C warming level has an annual probability of about 50% in northern and 80–90% in southern Europe under 2.0 ∘ C. Corresponding probabilities for 100-year heatwaves would be nearly 20% in the north and about 60% in the south. Finally, we discuss factors that explain the stronger increase in heatwave duration and extremity in the south than north. [ABSTRACT FROM AUTHOR]

The increasing intensity and frequency of high-temperature events in response to climate change can potentially impact the aviation industry, since aircraft takeoff and landing performances depend on near-surface air temperature. Previous studies have combined climate data with aircraft technical data to estimate the future impact of rising high temperatures on aircraft takeoff. They found a decrease of maximum takeoff weights and the lengthening of takeoff distances. The Mediterranean region is a climate change "hot spot" area, specially concerned by extreme high-temperatures increase. In this study, the magnitude and trends of the daily maximum near-surface temperature extremes in summer were analysed over major airports in Southwestern Europe. Trends in the period 1961–2014 were analysed from observations and reanalysis. Future changes by 2021–2050 and 2071–2100, with respect to 1961–2005, were analysed from simulations performed with Regional and Global Climate Models (RCMs and GCMs). Before assessing future climate projections, climate models were evaluated in present climate, and the RCM and GCM ensembles were compared to each other. No clear added value was found for RCMs over GCMs in present climate at the airport scale in these terms. GCMs project larger temperature changes than RCMs over the same locations. Multi-model ensemble mean projected changes under the RCP8.5 scenario range between + 1.7 and + 3.2 ∘ C by the near term, and between + 4.9 and + 8.5 ∘ C by the long term, across the airports and the RCM and GCM ensembles. This increase of high-temperature extremes would impact airport operations. Adaptation or mitigation policies would become necessary. [ABSTRACT FROM AUTHOR]

El Niño-Southern Oscillation (ENSO) influence on European precipitation (Pcp) has been deeply analyzed. Most of the previous studies focus on the atmospheric response in wintertime during the peak of the ENSO episode, showing boreal summer a season with a marginal ENSO signal. Furthermore, the stationarity of the ENSO teleconnection with Europe has not been considered in many works, which could mask possible nonstationary impacts in other seasons like summer. In this research we find a strong influence of eastern Pacific-like ENSO on the leading variability mode of European summer Pcp, showing a dipole-like configuration and linking El Niño with drier(wetter) conditions in northern(southern) Europe. This relationship is not limited to the total cumulative Pcp, but also to the low and extreme Pcp. This impact on European rainfall is found from the 1960s to the 1990s, a 30 years-long period when the position of the extratropical northern jet stream, which acts as a waveguide, favors the teleconnection pathway to Europe. Strikingly, the ENSO events behind this teleconnection reach their peak in summer. However, we show that the resultant Pcp in Europe also depend on the ENSO characteristic of the previous seasons, which could be used for predictability purposes. [ABSTRACT FROM AUTHOR]

The backward nonlinear local Lyapunov exponent (BNLLE) was developed based on the NLLE method to quantitatively investigate the local predictability of extreme events. By studying the dynamical characteristics of error growth preceding extreme events, the local predictability limits of these events can be determined. In this study, the BNLLE method is used to quantify the local predictability limits of two extreme high-temperature events (EHTEs) that occurred in Europe during the summer of 2019. The results show that the error dynamics are dependent on the geographical location. During the early forecast period, positive error-growth rates are mainly located in southern regions, whereas negative error-growth rates are mainly located in northern regions. However, the variations in the error growth rates exhibit regional differences with the forecast time. As such, the relative growth of initial errors (RGIEs) also depends on the geographical location. From the RGIEs, the local predictability limits of the two EHTEs are determined to be 11 and 9 days, respectively. By measuring the forecast skill, the local predictability limits (11 and 9 days) are verified to be reasonable and realistic. Therefore, the BNLLE method can quantify the local predictability of EHTEs, and is an effective technique for studying the predictability of future extreme weather and climate events. [ABSTRACT FROM AUTHOR]

Inter-variable correlations (e.g., between daily temperature and precipitation) are key statistical properties to characterise probabilities of simultaneous climate events and compound events. Their correct simulations from climate models, both in values and in changes over time, is then a prerequisite to investigate their future changes and associated impacts. Therefore, this study first evaluates the capabilities of one 11-single run multi-model ensemble (CMIP6) and one 40-member single model initial-condition large ensemble (CESM) over Europe to reproduce the characteristics of a reanalysis dataset (ERA5) in terms of temperature–precipitation correlations and their historical changes. Next, the ensembles' correlations for the end of the 21st century are compared. Over the historical period, both CMIP6 and CESM ensembles have season-dependent and spatially structured biases. Moreover, the inter-variable correlations from both ensembles mostly appear stationary. Thus, although reanalysis displays significant correlation changes, none of the ensembles can reproduce them, with internal variability representing only 30% on the inter-model variability. However, future correlations show significant changes over large spatial patterns. Yet, those patterns are rather different for CMIP6 and CESM, reflecting a large uncertainty in changes. In addition, for historical and future projections, an analysis conditional on atmospheric circulation regimes is performed. The conditional correlations given the regimes are found to be the main contributor to the biases in correlation over the historical period, and to the past and future changes of correlation. These results highlight the importance of the large-scale circulation regimes and the need to understand their physical relationships with local-scale phenomena associated to specific inter-variable correlations. [ABSTRACT FROM AUTHOR]

Satellite-derived products and reanalyses show consistent increases in downward surface solar radiation (SSR) and decreases in cloud cover over North America and Europe from the 1980s to 2010s. These trends show a strong seasonality, with the largest changes in boreal summer. A set of timeslice experiments with an atmospheric general circulation model (AGCM) forced with prescribed changes in sea surface temperature/sea ice extent (SST/SIE), greenhouse gas (GHG) concentrations, and anthropogenic aerosol (AA) emissions, together and separately, is performed to assess the relative roles of different forcings in these observed trends. The model reproduces the main observed features over Europe and North America, including the seasonality of trends, suggesting a dominant role of forced changes in the recent trends in SSR and cloud cover. Responses to individual forcings indicate that recent decadal trends in SSR over Europe are predominantly driven by AA emission reductions, with an additional influence from SST/SIE and GHG changes. In contrast, changes in AA, SST/SIE, and GHG contribute more equally to simulated decadal trends in SSR and cloud cover over North America, although SST/SIE play the most important role. In our simulations, responses of SSR to AA emission reductions are primarily governed by aerosol-radiation interactions. Responses to SST/SIE and GHG changes are predominantly due to cloud cover changes, which are driven by atmospheric circulation and humidity changes. This process level understanding of how different forcing factors influence decadal trends in SSR and cloud cover is valuable for understanding past changes and future projections in global and regional surface energy budgets, surface warming, and global and regional hydrological cycles. [ABSTRACT FROM AUTHOR]

Three consecutive dry summers in western Europe (2018–2019–2020) had widespread negative impacts on society and ecosystems, and started societal debate on (changing) drought vulnerability and adaptation measures. We investigate the occurrence of multi-year droughts in the Rhine basin, with a focus on event probability in the present and in future warmer climates. Additionally, we investigate the temporally compounding physical drivers of multi-year drought events. A combination of multiple reanalysis datasets and multi-model large ensemble climate model simulations was used to provide a robust analysis of the statistics and physical processes of these rare events. We identify two types of multi-year drought events (consecutive meteorological summer droughts and long-duration hydrological droughts), and show that these occur on average about twice in a 30 year period in the present climate, though natural variability is large (zero to five events can occur in a single 30 year period). Projected decreases in summer precipitation and increases in atmospheric evaporative demand, lead to a doubling of event probability at 1 ∘ C additional global warming relative to present-day and an increase in the average length of events. Consecutive meteorological summer droughts are forced by two, seemingly independent, summers of lower than normal precipitation and higher than normal evaporative demand. The soil moisture response to this temporally compound meteorological forcing has a clear multi-year imprint, resulting in a relatively larger reduction of soil moisture content in the second year of drought, and potentially more severe drought impacts. Long-duration hydrological droughts start with a severe summer drought followed by lingering meteorologically dry conditions. This limits and slows down the hydrological recovery of soil moisture content, leading to long-lasting drought conditions. This initial exploration provides avenues for further investigation of multi-year drought hazard and vulnerability in the region, which is advised given the projected trends and vulnerability of society and ecosystems. [ABSTRACT FROM AUTHOR]

During the past century, several extreme summer floods in Central Europe were associated with so-called Vb-cyclones propagating from the Mediterranean Sea north-eastward to Central Europe. The processes intensifying the precipitation in synoptic situations with Vb-cyclones in the Danube, Elbe, and Odra catchments are only partially understood. Our study aims to investigate these processes with Lagrangian moisture-source diagnostics for 16 selected Vb-events. Moreover, we analyse the characteristics of typical moisture source regions during 1107 Vb-events from 1901 to 2010 based on ERA-20C reanalysis dynamically downscaled with COSMO-CLM+NEMO. We observe moisture contributions by various source regions highlighting the complex dynamical interplay of different air masses leading to moisture convergence in synoptic situations with Vb-cyclones. Overall, up to 80% of the precipitation originates from the European continent, indicating the importance of continental moisture recycling, especially within the respective river catchment. Other major moisture uptake regions are the North Sea, the Baltic Sea, the North Atlantic, and for a few events the Black Sea. Remarkably, anomalies in these oceanic source regions show no connection to precipitation amounts in synoptic situations with Vb-cyclones. In contrast, the Vb-cyclones with the highest precipitation are associated with anomalously high evaporation in the Mediterranean Sea, even though the Mediterranean Sea is only a minor moisture source region on average. Interestingly, the evaporation anomalies are not connected with sea-surface temperature but with wind-speed anomalies (Spearman's rank correlation coefficient R ≈ 0.7, significant with p < 0.01 ) indicating mainly dynamically driven evaporation. The particular role of the Mediterranean Sea hints towards possible importance of Mediterranean moisture for the early-stage intensification of Vb-cyclones and the pre-moistening of the continental uptake regions upstream of the target catchments. [ABSTRACT FROM AUTHOR]

European climate is associated with variability and changes in the mid-latitude atmospheric circulation. In this study, we aim to investigate potential future change in circulation over Europe by using the EURO-CORDEX regional climate projections at 0.11° grid mesh. In particular, we analyze future change in 500-hPa geopotential height (Gph), 500-hPa wind speed and mean sea level pressure (MSLP) addressing different warming levels of 1 °C, 2 °C and 3 °C, respectively. Simple scaling with the global mean temperature change is applied to the regional climate projections for monthly mean 500-hPa Gph and 500-hPa wind speed. Results from the ensemble mean of individual models show a robust increase in 500-hPa Gph and MSLP in winter over Mediterranean and Central Europe, indicating an intensification of anticyclonic circulation. This circulation change emerges robustly in most simulations within the coming decade. There are also enhanced westerlies which transport warm and moist air to the Mediterranean and Central Europe in winter and spring. It is also clear that, models showing different responses to circulation depend very much on the global climate model ensemble member in which they are nested. For all seasons, particularly autumn, the ensemble mean is much more correlated with the end of the century than most of the individual models. In general, the emergence of a scaled pattern appears rather quickly. [ABSTRACT FROM AUTHOR]

The impacts of Arctic stratospheric polar vortex (SPV) on wintertime precipitation over the Northern Hemisphere are analyzed based on various datasets. Two groups of ensemble climate model experiments with the SPV nudged towards strong and weak states are performed to clarify stratospheric impacts on changes in precipitation. During weak SPV events, precipitation rates over the western and southeastern parts of North Pacific Ocean, the southern part of North Atlantic Ocean, and Southern Europe are larger, whereas the total precipitation rates over the central North Pacific, the northern part of North Atlantic and Northern Europe are smaller than those during strong SPV events. The SPV-induced changes in precipitation over the North Atlantic are stronger than those over the North Pacific. The convective (large-scale) precipitation changes play a major role in the total precipitation changes over the southern (northern) parts of middle latitudes associated with SPV changes. The tropospheric zonal wind deceleration around 60°N associated with weak SPV events is responsible for lower-tropospheric anomalous cyclonic flows over the two oceans at middle latitudes. The anomalous cyclonic flows lead to more large-scale precipitation in the southeastern parts of the oceans and less large-scale precipitation over Northern Europe and the central North Pacific during weak SPV events. The stratosphere–troposphere coupling over the North Atlantic is stronger than that over the North Pacific, leading to stronger large-scale precipitation responses over the former region. In addition, convective precipitation rates between 30 and 45°N are basically larger during weak SPV events than during strong SPV events. This is because more baroclinic waves associated with a southward shift of storm tracks during weak SPV events cause more heat exchanges between the lower latitudes and higher latitudes. Consequently, the upper tropospheric temperature and static ability between 30 and 45°N are reduced, leading to larger convective available potential energy and more convective precipitation during weak SPV events. [ABSTRACT FROM AUTHOR]

Extra-tropical windstorms are one of the costliest natural hazards affecting Europe, and windstorms that develop a sting jet are extremely damaging. A sting jet is a mesoscale core of very high wind speeds that occurs in Shapiro–Keyser type cyclones, and high-resolution models are required to adequately model sting jets. Here, we develop a low-cost methodology to automatically detect sting jets, using the characteristic warm seclusion of Shapiro–Keyser cyclones and the slantwise descent of high wind speeds, within pan-European 2.2 km convection-permitting climate model (CPM) simulations. The representation of wind gusts is improved with respect to ERA-Interim reanalysis data compared to observations; this is linked to better representation of cold conveyor belts and sting jets in the CPM. Our analysis indicates that Shapiro–Keyser cyclones, and those that develop sting jets, are the most damaging windstorms in present and future climates. The frequency of extreme windstorms is projected to increase by 2100 and a large contribution comes from sting jet storms. Furthermore, extreme wind speeds and their future changes are underestimated in the global climate model (GCM) compared to the CPM. We conclude that the CPM adds value in the representation of extreme winds and surface wind gusts and can provide improved input for impact models compared to coarser resolution models. [ABSTRACT FROM AUTHOR]

Under the influence of global warming, heatwaves are becoming a major threat in many parts of the world, affecting human health and mortality, food security, forest fires, biodiversity, energy consumption, as well as the production and transportation networks. Seasonal forecasting is a promising tool to help mitigate these impacts on society. Previous studies have highlighted some predictive capacity of seasonal forecast systems for specific strong heatwaves such as those of 2003 and 2010. To our knowledge, this study is thus the first of its kind to systematically assess the prediction skill of heatwaves over Europe in a state-of-the-art seasonal forecast system. One major prerequisite to do so is to appropriately define heatwaves. Existing heatwave indices, built to measure heatwave duration and severity, are often designed for specific impacts and thus have limited robustness for an analysis of heatwave variability. In this study, we investigate the seasonal prediction skill of European summer heatwaves in the ECMWF System 5 operational forecast system by means of several dedicated metrics, as well as its added-value compared to a simple statistical model based on the linear trend. We are able to show, for the first time, that seasonal forecasts initialized in early May can provide potentially useful information of summer heatwave propensity, which is the tendency of a season to be predisposed to the occurrence of heatwaves. [ABSTRACT FROM AUTHOR]

Correction to: Climate Dynamics https://doi.org/10.1007/s00382-021-05941-3 The original html version of the article contained an error in the formatting of Fig. The original article can be found online at https://doi.org/10.1007/s00382-021-05941-3. The caption was swapped and below is the corrected caption. [Extracted from the article]

Heatwaves are extreme weather events that have become more frequent and intense in Europe over the past decades. Heatwaves are often coupled to droughts. The combination of them lead to severe ecological and socio-economic impacts. Heatwaves can self-amplify through internal climatic feedback that reduces local precipitation. Understanding the terrestrial sources of local precipitation during heatwaves might help identify mitigation strategies on land management and change that alleviate impacts. Moisture recycling of local water sources through evaporation allows a region to maintain precipitation in the same region or, by being transported by winds, in adjacent regions. To understand the role of terrestrial moisture sources for sustaining precipitation during heatwaves, we backtrack and analyse the precipitation sources of Northern, Western, and Southern sub-regions across Europe during 20 heatwave periods between 1979 and 2018 using the moisture tracking model Water Accounting Model-2layers (WAM-2layers). In Northern and Western Europe, we find that stabilizing anticyclonic patterns reduce the climatological westerly supply of moisture, mainly from the North Atlantic Ocean, and enhances the moisture flow from the eastern Euro-Asian continent and from within their own regions—suggesting over 10% shift of moisture supply from oceanic to terrestrial sources. In Southern Europe, limited local moisture sources result in a dramatic decrease in the local moisture recycling rate. Forests uniformly supply additional moisture to all regions during heatwaves and thus contribute to buffer local impacts. This study suggests that terrestrial moisture sources, especially forests, may potentially be important to mitigate moisture scarcity during heatwaves in Europe. [ABSTRACT FROM AUTHOR]

The majority of regional climate change assessments for the Euro-CORDEX region is based on high resolution atmosphere models. These models use prescribed lower boundary conditions, such as sea surface temperatures (SST) from global ocean General Circulation Models (GCMs), that do not respond to changes simulated by the regional atmosphere model, thus lacking an important feedback to the atmosphere. However, research during the past decade indicated that the use of coupled atmosphere–ocean models can lead to significantly altered model solutions compared to standalone atmosphere models for the present day climate imposing some uncertainty on the widely used uncoupled future scenarios. We here present the first multi-model and multi scenario (RCP2.6, RCP4.5, RCP8.5) ensemble of future climate change scenarios downscaled with a coupled atmosphere—ocean model in which sea surface temperature and sea ice fields are explicitly simulated by a coupled state-of-the-art high resolution ocean model and communicated to the atmosphere at 3-hourly time steps. Our ensemble generally confirms results of previous uncoupled ensembles over land areas implying that the coupling effect is restricted mainly to the coupled area and the adjacent coastal zone. By contrast, over the North Sea and Baltic Sea small scale processes point to important coupling effects that mediate the response to climate change and that can not be simulated by uncoupled models. Our results therefore impose general uncertainty on the usage of regional climate change data from uncoupled ensembles over marine areas such as for purposes of offshore wind or mussel farming, the planing of marine protected areas, and marine recreation along the coastal zone. It further sets in question the usage of uncoupled scenario data (such as Euro-CORDEX) to force high resolution ocean models. Comparing coupled and uncoupled hindcast simulations reveals that the coupling effect over land is most pronounced during the warm season when prescribed and modelled sea surface temperatures (SST) differ strongest. In addition, a generally weaker wind regime in summer damps the heat dispersion in the atmosphere so that air temperature anomalies can extent further over land compared to winter. Future projections are discussed under consideration of land-sea warming characteristics for selected climate indices as well as mean seasonal climate change. At the end of the century a clear land-sea pattern is seen in all scenarios with stronger warming over land than over open sea areas. On average land areas warm at a rate 1.5 times faster than areas over the open ocean. Over the coupled area, i.e. the North Sea and Baltic Sea tropical nights are impacted strongest and the Baltic Sea turns out to be a hot spot in future climate. This has been unrecognized in previous studies using high resolution atmosphere models with prescribed SSTs from global models which do not represent small scale ocean processes in the Baltic Sea adequately. [ABSTRACT FROM AUTHOR]

Convection-permitting climate models have shown superior performance in simulating important aspects of the precipitation climate including extremes and also to give partly different climate change signals compared to coarser-scale models. Here, we present the first long-term (1998–2018) simulation with a regional convection-permitting climate model for Fenno-Scandinavia. We use the HARMONIE-Climate (HCLIM) model on two nested grids; one covering Europe at 12 km resolution (HCLIM12) using parameterized convection, and one covering Fenno-Scandinavia with 3 km resolution (HCLIM3) with explicit deep convection. HCLIM12 uses lateral boundaries from ERA-Interim reanalysis. Model results are evaluated against reanalysis and various observational data sets, some at high resolutions. HCLIM3 strongly improves the representation of precipitation compared to HCLIM12, most evident through reduced "drizzle" and increased occurrence of higher intensity events as well as improved timing and amplitude of the diurnal cycle. This is the case even though the model exhibits a cold bias in near-surface temperature, particularly for daily maximum temperatures in summer. Simulated winter precipitation is biased high, primarily over complex terrain. Considerable undercatchment in observations may partly explain the wet bias. Examining instead the relative occurrence of snowfall versus rain, which is sensitive to variance in topographic heights it is shown that HCLIM3 provides added value compared to HCLIM12 also for winter precipitation. These results, indicating clear benefits of convection-permitting models, are encouraging motivating further exploration of added value in this region, and provide a valuable basis for impact studies. [ABSTRACT FROM AUTHOR]

For the first time, we analyze 2.2 km UK Met Office Unified Model convection-permitting model (CPM) projections for a pan-European domain. These new simulations represent a major increase in domain size, allowing us to examine the benefits of CPMs across a range of European climates. We find a change to the seasonality of extreme precipitation with warming. In particular, there is a relatively muted response for summer, which contrasts with much larger increases in autumn and winter. This flattens the hourly extreme precipitation seasonal cycle across Northern Europe which has a summer peak in the present climate. Over the Western Mediterranean, where autumn is the main extreme precipitation season, there is a regional increase in hourly extreme precipitation frequency, but local changes for lower precipitation thresholds are often insignificant. For mean precipitation, decreases are projected across Europe in summer, smaller decreases in autumn, and increases in winter; comparable changes are seen in the driving general circulation model (GCM) simulations. The winter mean increase is accompanied by a large decrease of winter mean snowfall. Comparing the driving GCM projections with the CPM ones, the CPMs show a robust enhanced intensification of precipitation extremes at the convection-permitting scale compared to coarser resolution climate model projections across various European regions for summer and autumn. [ABSTRACT FROM AUTHOR]

We perform simulations with the WRF regional climate model at 12 and 3 km grid resolution for the current and future climates over Central Europe and evaluate their added value with a focus on the daily cycle and frequency distribution of rainfall and the relation between extreme precipitation and air temperature. First, a 9 year period of ERA-Interim driven simulations is evaluated against observations; then global climate model runs (MPI-ESM-LR RCP4.5 scenario) are downscaled and analyzed for three 12-year periods: a control, a mid-of-century and an end-of-century projection. The higher resolution simulations reproduce both the diurnal cycle and the hourly intensity distribution of precipitation more realistically compared to the 12 km simulation. Moreover, the observed increase of the temperature–extreme precipitation scaling from the Clausius–Clapeyron (C–C) scaling rate of ~ 7% K−1 to a super-adiabatic scaling rate for temperatures above 11 °C is reproduced only by the 3 km simulation. The drop of the scaling rates at high temperatures under moisture limited conditions differs between sub-regions. For both future scenario time spans both simulations suggest a slight decrease in mean summer precipitation and an increase in hourly heavy and extreme precipitation. This increase is stronger in the 3 km runs. Temperature–extreme precipitation scaling curves in the future climate are projected to shift along the 7% K−1 trajectory to higher peak extreme precipitation values at higher temperatures. The curves keep their typical shape of C–C scaling followed by super-adiabatic scaling and a drop-off at higher temperatures due to moisture limitation. [ABSTRACT FROM AUTHOR]

In the period 1960–2010, the land surface air temperature (SAT) warmed more rapidly over some regions relative to the global mean. Using a set of time-slice experiments, we highlight how different physical processes shape the regional pattern of SAT warming. The results indicate an essential role of anthropogenic forcing in regional SAT changes from the 1970s to 2000s, and show that both surface–atmosphere interactions and large-scale atmospheric circulation changes can shape regional responses to forcing. Single forcing experiments show that an increase in greenhouse gases can lead to regional changes in land surface warming in winter (DJF) due to snow-albedo feedbacks, and in summer (JJA) due to soil-moisture and cloud feedbacks. Changes in anthropogenic aerosol and precursor (AA) emissions induce large spatial variations in SAT, characterized by warming over western Europe, Eurasia, and Alaska. In western Europe, SAT warming is stronger in JJA than in DJF due to substantial increases in clear sky shortwave radiation over Europe, associated with decreases in local AA emissions since the 1980s. In Alaska, the amplified SAT warming in DJF is due to increased downward longwave radiation, which is related to increased water vapor and cloud cover. In this case, although the model was able to capture the regional pattern of SAT change, and the associated local processes, it did not simulate all processes and anomalies correctly. For the Alaskan warming, the model is seen to achieve the correct regional response in the context of a wider North Pacific anomaly that is not consistent with observations. This demonstrates the importance of model evaluation that goes beyond the target variable in detection and attribution studies. [ABSTRACT FROM AUTHOR]

We assess the differences of future climate changes over Europe in summer as projected by state-of-the-art regional climate models (RCM, from the EURO-Coordinated Regional Downscaling Experiment) and by their forcing global climate models (GCM, from the Coupled Model Intercomparison Project Phase 5) and study the associated physical mechanisms. We show that important discrepancies at large-scales exist between global and regional projections. The RCMs project at the end of the 21st century over a large area of Europe a summer warming 1.5–2 K colder, and a much smaller decrease of precipitation of 5%, versus 20% in their driving GCMs. The RCMs generally simulate a much smaller increase in shortwave radiation at surface, which directly impacts surface temperature. In addition to differences in cloud cover changes, the absence of time-varying anthropogenic aerosols in most regional simulations plays a major role in the differences of solar radiation changes. We confirm this result with twin regional simulations with and without time-varying anthropogenic aerosols. Additionally, the RCMs simulate larger increases in evapotranspiration over the Mediterranean sea and larger increases/smaller decreases over land, which contribute to smaller changes in relative humidity, with likely impacts on clouds and precipitation changes. Several potential causes of these differences in evapotranspiration changes are discussed. Overall, this work suggests that the current EURO-CORDEX RCM ensemble does not capture the upper part of the climate change uncertainty range, with important implications for impact studies and the adaptation policies that they inform. [ABSTRACT FROM AUTHOR]

A Bayesian method known as the Forecast Assimilation (FA) was used to calibrate and combine monthly near-surface temperature and precipitation outputs from seasonal dynamical forecast systems. The simple multimodel (SMM), a method that combines predictions with equal weights, was used as a benchmark. This research focuses on Europe and adjacent regions for predictions initialized in May and November, covering the boreal summer and winter months. The forecast quality of the FA and SMM as well as the single seasonal dynamical forecast systems was assessed using deterministic and probabilistic measures. A non-parametric bootstrap method was used to account for the sampling uncertainty of the forecast quality measures. We show that the FA performs as well as or better than the SMM in regions where the dynamical forecast systems were able to represent the main modes of climate covariability. An illustration with the near-surface temperature over North Atlantic, the Mediterranean Sea and Middle-East in summer months associated with the well predicted first mode of climate covariability is offered. However, the main modes of climate covariability are not well represented in most situations discussed in this study as the seasonal dynamical forecast systems have limited skill when predicting the European climate. In these situations, the SMM performs better more often. [ABSTRACT FROM AUTHOR]

Vb-cyclones are extratropical cyclones propagating from the Western Mediterranean Sea and traveling across the Eastern Alps into the Baltic region. With these cyclones, extreme precipitation over Central Europe potentially triggers significant flood events. Understanding the prediction ability of Vb-cyclones would lower risks from adverse impacts. This study analyzes the robustness of an atmosphere–ocean regional coupled model, including interactive models for the Mediterranean Sea (MED) and North and Baltic Seas (NORDIC) in reproducing observed Vb-cyclone characteristics. We use the regional climate model (RCM) COSMO-CLM (CCLM) in stand-alone and coupled with the ocean model NEMO configurations for the EURO-CORDEX domain from 1979 to 2014, driven by the ERA-Interim reanalysis. Sea surface temperature (SST) is evaluated to demonstrate the stability and reliability of the coupled configurations. Compared to observations, simulated SSTs show biases (~ 1 °C), especially during winter and summer. Generally, all model configurations are able to replicate Vb-cyclones, their trajectories, and associated precipitation fields. Cyclone trajectories are comparably well simulated with the coupled models, as with the stand-alone simulation which is driven by the reanalysis SST in the MED and NORDIC seas. The cyclone intensity shows large deviations from reanalysis reference in the simulations with the interactive MED Sea, and smallest with CCLM. Precipitation characteristics are similarly simulated in the coupled and stand-alone (with reanalysis SST) simulations. The results suggest that our coupled RCM is useful for studying the impacts of highly resolved and interactively simulated SSTs on European extreme events and regional climate, a crucial prerequisite for understanding future climate conditions. [ABSTRACT FROM AUTHOR]

The Arctic stratospheric response to El Niño (EN) and La Niña (LN) is evaluated in a 41 member ensemble of the period 1980 to 2009 in the Goddard Earth Observing System Chemistry-Climate Model. We consider whether the responses to EN and LN are equal in magnitude and opposite in sign, whether the responses to moderate and extreme events are proportionate, and if the response depends on whether sea surface temperature anomalies (SSTs) peak in the Eastern Pacific (EP) or Central Pacific (CP). There is no indication of any nonlinearities between EN and LN, though in ~ 15% of the ensemble members the stratospheric sudden warming (SSW) frequencies for EN and LN are similar, suggesting that a similar SSW frequency for EN and LN, as has occurred over the past ~ 60 years, can occur by chance. The response to extreme EN events is not proportionate to the amplitude of the underlying SST anomalies in spring. EP EN events preferentially increase zonal wavenumber 1 and decrease zonal wavenumber 2 as compared to CP EN events, however the zonal-mean Arctic stratospheric and subpolar surface response is generally little different between EP EN and CP EN once one accounts for the relative weakness of CP events. These differences between EP and CP events and between moderate and extreme EN events only emerge if at least 25 events are composited, however, due to the small signal-to-noise ratio, and hence these differences may be of little practical benefit. [ABSTRACT FROM AUTHOR]

A statistical link is presented between atmospheric blocks in the Euro-Atlantic sector and the frequency of regional-scale heavy precipitation events in Europe. Changes in the odds of European 1-, 3- and 5-day accumulation heavy precipitation in the presence of a block are investigated for different geographical locations of blocks and for summer and winter. The results show a significant modulation of the odds of heavy precipitation events during blocking episodes over the North-Atlantic and Europe. Blocks located further east have only limited effects on the odds of heavy precipitation events over Europe. The spatial patterns are very diverse and are strongly dependent on the location of the blocks and on the season. Generally, the odds of heavy precipitation events are reduced in the area of the blocking anticyclone and increased in the areas southwest to southeast of it and in some cases also north of it. Often areas with increased odds of heavy precipitation coincide with the location of the storm track. [ABSTRACT FROM AUTHOR]

We improve seasonal hindcast skill of European summer climate in an ensemble based coupled seasonal prediction system by selecting individual ensemble members based on their respective consistent chain of processes that describe a physical mechanism. This mechanism is associated with the second mode of seasonal climate variability in the North-Atlantic-European sector and is contrary to the summer North Atlantic Oscillation. We initially analyse the mechanism in the ERA-Interim reanalysis and then test the influence of the mechanism on European hindcast skill in an initialised coupled seasonal climate model. We show that the mechanism originates in the tropical North Atlantic in spring, where either warm or cold sea surface temperature anomalies (SSTs) are connected with the European climate by an upper-level wave-train. This wave-train is accompanied by a zonal pressure gradient, that in turn influences the climate over central Europe in the following summer. We analyse the seasonal summer hindcast skill in a mixed resolution hindcast ensemble simulation generated by MPI-ESM, with 30 members starting every year in May. While the mean over the full ensemble shows no seasonal hindcast skill in summer, we achieve significant hindcast skill through forming a new mean over subselected ensemble members. For this selection, we test every ensemble member for the proposed consistent chain of connections between the wave-train, the zonal pressure gradient and their impact on European summer temperatures, and find that the processes that describe the mechanism are not represented in every ensemble member. Due to its influence on European summer climate, we use the condition of the persistent spring SSTs to anticipate the phase of the mechanism in each considered year. We thus use statistical relations to select ensemble members generated by a dynamical prediction system. With this approach, we significantly enhance the seasonal hindcast skill and the reliability of the hindcasts in the North-Atlantic-European sector, especially in the areas where the mechanism is showing a prominent signal. Since we only use knowledge that would be available in a real forecast set-up, this approach can potentially be applied in operational ensemble prediction systems. [ABSTRACT FROM AUTHOR]

Uncertainties in climate model ensembles are still relatively large. Besides scenario and model response uncertainty, natural variability is another important source of uncertainty. To study regional natural variability on timescales of several decades and more, observations are often too sparse and short. Regional Climate Models (RCMs) can be used to overcome this lack of useful data at high spatial resolutions. In this study, we compare a new 50-member single RCM large ensemble (CRCM5-LE) with an ensemble of 22 EURO-CORDEX models for seasonal temperature and precipitation at 0.11° grid size over Europe—all driven by the RCP 8.5 scenario. This setup allows us to quantify the contribution of natural/model-internal variability on the total uncertainty of a multi-model ensemble. The variability of climate change signals within the two ensembles is compared for three future periods (2020–2049, 2040–069 and 2070–2099). Results show that the single model spread is usually smaller than the multi-model spread for temperature. Similar variabilities can mostly be found in the near future (and to a lesser extent in the mid future) during winter and spring, especially for northern and central parts of Europe. The contribution of internal variability is generally higher for precipitation. In the near future almost all seasons and regions show similar variabilities. In the mid and far future only fall, summer and spring still show similar variabilites. There is a significant decrease of the contribution of internal variability over time for both variables. However, even in the far future for most regions and seasons 25–75% of the overall variability can be explained by internal variability. [ABSTRACT FROM AUTHOR]

The aim of this study is to examine the capability of reanalyses in capturing the temporal clustering of heavy precipitation over Europe. We focus on four widely used products: the National Aeronautics and Space Administration's Modern Era Retrospective-Analysis for Research and Applications (MERRA) and version 2 (MERRA2); European Centre for Medium-Range Weather Forecasts' ERA-Interim; Japanese Meteorological Agency's Japanese 55-year Reanalysis (JRA-55). We define as heavy precipitation days those exceeding the 95th percentile of the precipitation distribution at every pixel, and investigate the temporal clustering in these events with respect to the Arctic Oscillation (AO) or the North Atlantic Oscillation (NAO). We evaluate the performance of these datasets in reproducing the temporal clustering in the observations using Cox regression. The results of this work indicate that: (1) heavy precipitation events over Europe exhibit temporal clustering; (2) all of the reanalysis products we have considered are capable of well reproducing the temporal clustering exhibited by the observations, and in general JRA-55 performs the best; moreover, our findings indicate that MERRA2 performs better than its predecessor MERRA in representing the relationship between heavy precipitation and these two climate indices; (3) all the reanalysis products in general tend to agree in terms of the temporal variability of NAO/AO. [ABSTRACT FROM AUTHOR]

The weather and climate conditions can provide favorable or unfavorable atmospheric background for the maintenance and development of haze events. This study investigates the potential impacts of Arctic warming on the variation of Northern Hemisphere mid-latitude aerosol optical depth (AOD) in winter when haze often occurs. We first analyze the spatio-temporal variability of wintertime AOD in mid-latitudes of Northern Hemisphere from NASA MERRA-2 for the period of 1980–2016 using the empirical orthogonal function analysis and morlet wavelet analysis. It showes increasing trend for AOD in East China and North India and decreasing trend for AOD in Europe and North America during last 37 years while inter-decadal fluctuations exist. In addition to the temporal trends of AOD, two long-term periodic variations with periods of about 7 and 11 years exist, which implies the potential impacts from natural variabilities. Further analysis shows high correlations between the mid-latitude winter AOD (WA) and Arctic summer (May and June) surface temperature (T56). Moreover, the Arctic summer surface temperature demonstrates similar periodic variations with periods of about 7–9 and 11–13 years. Both of these indicate the potential impacts of Arctic summer warming on mid-latitude winter pollution. We then analyze the temporal correlations between Arctic summer temperature and mid-latitude winter AOD in different regions. Arctic T56 correlates negatively with WA in Europe and North America, and positively with that in East Asia, North India and Middle East. Particularly, T56 in western sea of Novaya Zemlya has the most prominent correlation with the WA in mid-latitudes of East Asia, especially in East China. This implies that Arctic T56 in the Arctic circle of Europe could be used for rough estimates of winter AOD in East Asia. [ABSTRACT FROM AUTHOR]

A cross-validated model output statistics (MOS) approach is applied to precipitation data from the high-resolution regional climate model CCLM for Europe. The aim is to remove systematic errors of simulated precipitation in decadal climate predictions. We developed a two-step bias-adjustment approach. In step one, we estimate model errors based on a long-term 'CCLM assimilation run' (regionalizing data from a global assimilation run) and observational data. In step two, the resulting transfer function is applied to the complete set of decadal hindcast simulations (285 individual runs). In contrast to lead-time-dependent bias-adjustment approaches, this one is designed for variables with poor decadal prediction skill and without dominant lead-time-dependent bias. In terms of the CCLM assimilation run, MOS is shown to be effective in predictor selection, model skill improvement, and model bias reduction. Yet, the positive effect of MOS correction is accompanied with an underestimation of precipitation variability. After MOS application, an estimated mean square skill score of more than 0.5 is observed regionally. Simulated precipitation in decadal hindcasts is further improved when the MOS is trained on the basis of other decadal hindcasts from the same regional climate model but with a large underestimation in forecast uncertainty. Our results suggest that the MOS system derived from the assimilation run is less effective but allows the potential climate predictability in decadal hindcasts and forecasts to be retained. Using hindcasts itself for training is recommended unless a statistical method is capable of distinguishing biases and predictions within a hindcasts dataset. [ABSTRACT FROM AUTHOR]

Previous studies have demonstrated that atmospheric diabatic heating over the Tibetan Plateau (TP) exerts significant influences on the "upstream" climate of the Atlantic-African-European sector in boreal summer. Using the NCAR Community Earth System Model, this study demonstrates that the TP-induced change in North Atlantic sea surface temperature (SST) including evident warming over the mid-latitude North Atlantic and cooling over the south can in turn modulate the above TP impact. Compared with the TP heating experiment without Atlantic SST variation, anomalous wave train pattern appears with north-northeastward downstream influences when the change in Atlantic SST is considered. The wave train pattern is characterized by three positive centers over the North Atlantic, the Arctic Ocean, and east of Japan, and four negative centers over northeastern North America, North Europe, the mid-Atlantic, and the northwestern Pacific. It intensifies the northern portions of the TP-induced tropospheric anticyclones over the extratropical North Atlantic and the cyclones over northeastern North America and North Europe. Correspondingly, precipitation decreases over the northwestern Atlantic but increases over northeastern North America and North Europe. Due to the easterly anomalies on the southern side of the weakened thermal low over subtropical Africa, precipitation over the Sahel decreases, indicating a weakening of TP-induced precipitation dipole over the tropical eastern Atlantic and West Africa when the Atlantic SST influence is considered. Overall, the modulation of Atlantic SST variation accounts for above 20 percent of the upstream climate signals induced by the TP thermal effect. [ABSTRACT FROM AUTHOR]

The Atlantic multidecadal variability (AMV) is known to affect the central to eastern (C–E) European summer climate through an associated atmospheric baroclinic response called North-Atlantic-European East West mode as demonstrated in the twentieth century reanalysis (20CRv2). Here, using the atmospheric model ECHAM6.3, we perform sensitivity experiments with prescribed sea surface temperature (SST) anomalies that are representative of the observed positive and the negative AMV phases and investigate the model response to the observed AMV pattern for European summer climate. The results from the experiments reveal that in the negative phase of AMV, the North-Atlantic-European (NAE) climate is mainly governed by the extra-tropical branch of the AMV through a baroclinic-like response. This response brings negative surface air temperature (SAT) anomalies over C–E Europe. The response and its influence are similar to what is found in the 20CRv2. In contrast, in the positive phase of the AMV, the NAE climate in the model experiments is mainly influenced by the tropical branch of the AMV. A stationary Rossby wave response excited in the tropics is associated with negative SAT anomalies over C–E Europe, which is opposite to what is found in the 20CRv2. The model response from the tropical part of the AMV SST is unlikely to be realistic due to the lack of coupled air–sea interaction, when SST is specified. Hence, the results demonstrate that ECHAM6.3 can simulate the observed linear baroclinic response, but only in the negative phase of the AMV. For the positive phase, in agreement with the previous findings, the model response is very sensitive to the tropical branch of the AMV and unrealistic. [ABSTRACT FROM AUTHOR]

Despite the fact that the Little Ice Age (LIA) is well documented for the European Alps, substantial uncertainties concerning the regional spatio-temporal patterns of temperature changes associated with the LIA still exist, especially for their eastern sector. Here we present a high-resolution (4–10 years) 700-year long mean July air temperature reconstruction based on subfossil chironomid assemblages from a remote lake in the Austrian Eastern Alps to gain further insights into the LIA climatic deterioration in the region. The record provides evidence for a prolonged period of predominantly cooler conditions during AD 1530–1920, broadly equivalent to the climatically defined LIA in Europe. The main LIA phase appears to have consisted of two cold time intervals divided by slightly warmer episodes in the second half of the 1600s. The most severe cooling occurred during the eighteenth century. The LIA temperature minimum about 1.5 °C below the long-term mean recorded in the mid-1780 s coincides with the strongest volcanic signal found in the Greenland ice cores over the past 700 years and may be, at least in part, a manifestation of cooling that followed the long-lasting AD 1783–1784 Laki eruption. A continuous warming trend is evident since ca AD 1890 (1.1 °C in 120 years). The chironomid-inferred temperatures show a clear correlation with the instrumental data and reveal a close agreement with paleotemperature evidence from regional high-elevation tree-ring chronologies. A considerable amount of the variability in the temperature record may be linked to changes in the North Atlantic Oscillation. [ABSTRACT FROM AUTHOR]

The connections between European rainfall variability in winter (from January to March) and Northern Hemisphere circulation patterns, as represented by 500-hPa geopotential height, are investigated in the period 1900–2014. Initially, three statistically significant pairs of linearly-related circulation and precipitation patterns, explaining 45% of the variance in the latter field, are identified. The first two essentially represent the North Atlantic Oscillation (NAO) and the East Atlantic (EA) patterns, while the third corresponds to a structure described in recent literature as a blend of the Pacific North America (PNA) pattern and the so-called Asia Bering North America (ABNA) pattern. The residual precipitation field is then examined for patterns that can introduce non-linear modulations into the circulation-precipitation links. It is so found that the NAO impact on European rainfall is modulated by North American and Pacific factors controlling cyclogenesis over Newfoundland. The positive-phase EA rainfall anomalies over Central Europe and the British Isles seem to be markedly affected by the NAO phase. Finally, a possible signature from the Circumglobal Teleconnection Pattern disrupting the NAO influence on East Mediterranean precipitation anomalies is detected. [ABSTRACT FROM AUTHOR]

The present study evaluates the performance of 19 climate models that participated in the coupled model intercomparison project phase 5 (CMIP5) in reproducing climatology, the standard deviation, and the dominant mode of spring surface air temperature (SAT) variations over the mid-high latitudes of Eurasia based on historical runs. Future change of the Eurasian spring SAT under the anthropogenic global warming is also examined by comparing the historical and RCP4.5 run. All the 19 CMIP5 models capture well the observed spatial structure of climatological spring SAT, with the pattern correlation coefficients all larger than 0.94. However, most of the models tend to underestimate the SAT over north Europe and north Siberia and overestimate the SAT south of 50°N. There exists large inter-model spreads in the standard deviation of the spring SAT. Most of the models capture realistically the observed dominant mode of interannual variations of spring SAT. Analyses show that the ability of a CMIP5 model in capturing the dominant mode of Eurasian spring SAT variations is connected with the model's performance in representing the observed atmospheric circulation anomalies related to the Arctic Oscillation and the dominant mode of the atmospheric variations over Eurasia. Six best models are selected based on the ability in simulating the dominant mode of the spring SAT variations in the historical runs. These six models project an increase in the SAT climatology but a decrease in the standard deviation over most of Eurasia. These six models project a decrease in the explained variance as well as in the amplitude of the spring SAT and atmospheric anomalies related to the dominant mode. [ABSTRACT FROM AUTHOR]