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The onset of periods with very high or low air temperatures has aroused general interest for a long time, which is understandable since it has many dangerous effects directly affecting humans. Such perilous climatic phenomena include exceptionally cold and exceptionally warm months, which this study investigates for all Europe and for its five physico‐geographic regions over the 190‐year period of 1831–2020. Therefore, the research in this paper includes two periods characteristic of the history of climate – the late Little Ice Age (LIA) and present‐day warming. The studies are based on average monthly air temperature values from 40 weather stations in Europe. In this paper, exceptionally cold months (ECMs) or exceptionally warm months (EWMs) are considered to have occurred when the average air temperature at a station differed from the respective long‐term average by at least two standard deviations. The highlights of the study include the identification of a drop in the number of ECMs by 20 over the entire 190‐year period, and a highly statistically significant increase in EWMs by 44 between 1980 and 2020. These changes proceeded with different intensities from one physico‐geographic region of Europe to another. [ABSTRACT FROM AUTHOR]

The tracking of thunderstorms provides critical information on their frequency and behaviour for early warning, prediction and preparedness. Thunderstorm tracking has previously been constrained by the boundaries of a particular country or has focused on a particular category such as severe thunderstorms and mesoscale convective systems. However, less severe thunderstorms also pose a risk to life and property and occur more frequently and thus warrant inclusion in investigations of thunderstorm behaviour. In this paper, we present a new thunderstorm event catalogue, including all detected thunderstorms with at least three lightning flashes, derived from a tracking methodology applied to Northwest Europe within the bounds of 48° to 65°N and 15°W to 10°E between 2008 and 2018. The catalogue is based on ATDnet lightning flash data which was clustered into thunderstorms using a spatio‐temporal proximity assessment lightning clustering code written in the R coding language. The thunderstorm lightning clusters enabled the production of thunderstorm behaviour statistics such as speed, direction of movement, lightning flashes per minute and duration. This revealed that in winter, thunderstorms are shorter lived and move faster than in summer as well as more typically tracking from the west rather than from the south‐west. Thunderstorm behaviour characteristics were attributed to weather pattern types for the first time, providing probabilistic data that can be attributed to synoptic conditions. This can improve preparedness and early warning. Such results demonstrate how this new thunderstorm event catalogue, which includes all types and severities of thunderstorms unconstrained by political boundaries, can provide additional important information to enhance understanding of thunderstorm behaviour in the region. Our lightning clustering method may be useful for similar studies in other locales. [ABSTRACT FROM AUTHOR]

In this paper we present daily mean wind speed as a new variable in the publicly accessible E‐OBS gridded datasets. Each of the variables in the E‐OBS dataset is provided at a spatial resolution of 0.1° × 0.1° and 0.25° × 0.25°. The variable "daily mean wind speed" starts from 1980 and is updated every month. The main method that we apply is the use of adaptive covariate selection to model the monthly mean wind speed as a function of covariates, like altitude, distance to coast and surface roughness. Then, we use Gaussian process regression to interpolate the daily anomalies from the station locations to the grid locations. In addition, we develop ensemble dispersion improvement auto‐tune (EDIT) to improve the reliability of the local ensemble spread. In order to communicate the methodological uncertainty in the resulting dataset, the E‐OBS wind speed grid is provided as a 20‐member ensemble of random realizations. As part of a preliminary analysis, we investigate the hypothesized wind speed stilling effect in recent decades. Indeed, we do find a small yet significant wind speed stilling effect in the E‐OBS dataset. [ABSTRACT FROM AUTHOR]

Statistical downscaling methods (SDMs) are techniques used to downscale and/or bias‐correct climate model results to regional or local scales. The European network VALUE developed a framework to evaluate and inter‐compare SDMs. One of VALUE's experiments is the perfect predictor experiment that uses reanalysis predictors to isolate downscaling skill. Most evaluation papers for SDMs employ simple statistical diagnostics and do not follow a process‐based rationale. Thus, in this paper, a process‐based evaluation has been conducted for the more than 40 participating model output statistics (MOS, mostly bias correction) and perfect prognosis (PP) methods, for temperature and precipitation at 86 weather stations across Europe. The SDMs are analysed following the so‐called "regime‐oriented" technique, focussing on relevant features of the atmospheric circulation at large to local scales. These features comprise the North Atlantic Oscillation, blocking and selected Lamb weather types and at local scales the bora wind and the western Iberian coastal‐low level jet. The representation of the local weather response to the selected features depends strongly on the method class. As expected, MOS is unable to generate process sensitivity when it is not simulated by the predictors (ERA‐Interim). Moreover, MOS often suffers from an inflation effect when a predictor is used for more than one station. The PP performance is very diverse and depends strongly on the implementation. Although conditioned on predictors that typically describe the large‐scale circulation, PP often fails in capturing the process sensitivity correctly. Stochastic generalized linear models supported by well‐chosen predictors show improved skill to represent the sensitivities. [ABSTRACT FROM AUTHOR]

This paper looks at the level of persistence in the temperature anomalies series of 114 European cities. Once this level of persistence has been identified, the time trend coefficients are estimated and the results indicate that most of the series examined display positive trends, supporting thus climate warming. Moreover, the results obtained confirm the hypothesis that long‐memory behaviour cannot be neglected in the study of temperature time series, changing, therefore, the estimated effect of global warming. [ABSTRACT FROM AUTHOR]

Growing season length (GSL) indices derived from surface air temperature are frequently used in climate monitoring applications. The widely used Expert Team on Climate Change Detection and Indices (ETCCDI) definition aims to give a broadly applicable measure of the GSL that is indicative of the duration of the mild part of the year. In this paper long‐term trends in that index are compared with an alternative measure calculated using a time series decomposition technique (empirical ensemble mode decomposition [EEMD]). It is demonstrated that the ETCCDI index departs from the mild‐season definition as its start and end dates are determined by temperature events operating within the synoptic timescale; this raises the inter‐annual variance of the index. The EEMD‐derived index provides a less noisy and more realistic index of the GSL by filtering out the synoptic‐scale variance and capturing the annual‐cycle and longer timescale variability. Long‐term trends in the GSL are comparable between the two indices, with an average increase in length of around 5 days/decade observed for the period 1965–2016. However, the results using the EEMD index display a more coherent picture of significant trends than has been previously observed. Furthermore, the EEMD‐derived growing season parameters are more closely related to variations in seasonal‐mean hemispheric‐scale atmospheric circulation patterns, with around 57% of the inter‐annual variation in the start of the growing season being connected to the North Atlantic Oscillation and East Atlantic patterns, and around 55% of variation in the end of the growing season being associated with East Atlantic/west Russia‐type patterns. Long‐term trends and inter‐annual variability of the thermal growing season length across Europe are compared by comparing two indices: the ETCCDI definition and a new index calculated using a time series decomposition technique (EEMD). Long‐term trends are comparable between the two indices. However, the EEMD index displays a much more coherent picture of significant trends than has been previously observed, and a much closer relationship to hemispheric modes of atmospheric circulation variability. [ABSTRACT FROM AUTHOR]

In a changing climate, it is likely that precipitation patterns will experience shifts in amount and seasonality, with a tendency towards increased drought in many parts of Europe. In order to investigate what could be some of the feedbacks of dry conditions on temperature, this paper has investigated close to 30 European locations to assess the influence of observed dry summer days on daily maximum temperature ( Tmax) as well as a clustering of rainless days, and finally the temperature impact related to drought conditions as defined by the Standardized Precipitation Index. The results show that for the three main European climatic regions investigated ('Mediterranean', 'Maritime', 'Continental'), the influence of rainless days is discernible, with an average difference between mean summer Tmax and Tmax during rainless days only of up to 1.5 °C. A further aim of the study is to determine whether recent shifts in the occurrence of rainless days during the summer have a bearing on temperature trends. Results show that shifts in rainless days explain only a fraction of the observed temperature change at the locations studied, thereby hinting that the enhanced greenhouse effect remains the dominant mechanism for temperature change. Finally, using a regional climate model, very preliminary insight into a 'greenhouse climate' highlights the fact that changes in dry conditions seem to confirm the findings for current climate, i.e. they account for only a fraction of the increase in temperatures. Copyright © 2012 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

We estimate the potential predictability of European winter temperature using factors based on physical studies of their influences on European winter climate. These influences include sea surface temperature patterns in different oceans, major tropical volcanoes, the quasi-biennial oscillation in the tropical stratosphere, and anthropogenic climate change. We first assess the predictive skill for winter mean temperature in northern Europe by evaluating statistical hindcasts made using multiple regression models of temperature for Europe for winter and the January-February season. We follow this up by extending the methodology to all of Europe on a 5° × 5° grid and include rainfall for completeness. These results can form the basis of practical prediction methods. However, our main aim is to develop ideas to act as a benchmark for improving the performance of dynamical climate models. Because we consider only potential predictability, many of the predictors have estimated values coincident with the winter season being forecast. However, in each case, these values are predictable on average with considerable skill in advance of the winter season. A key conclusion is that to reproduce the results of this paper, dynamical forecasting models will require a fully resolved stratosphere. Copyright © 2011 Royal Meteorological Society and British Crown copyright, the Met Office [ABSTRACT FROM AUTHOR]

This paper presents a new 300-year daily series of Mean Sea-Level Pressure (MSLP) for the city of London. Daily barometer readings recorded in the vicinity of London were digitised from several sources and by joining these data with previously available data, a near-continuous series was constructed to span the period 1692-2007. The data were quality controlled and then corrected to represent daily means of MSLP at standard modern-day conditions. This series was then subjected to a statistical homogenisation procedure. The Penalized Maximal t-test was used with several reference series to identify breakpoints in the series over the period 1780-2007. In the absence of suitable reference series, the homogeneity of the earlier 1692-1779 period was tested using the Penalized Maximal F-test. Both tests were implemented through the RHtestV2 software on the monthly and annual means derived from the daily data. The majority of the identified breakpoints could be supported by meta-data and most occur at the juncture of the component series. A major feature of the homogenised series is that the long-term mean is 1.2 hPa lower than that of the previous monthly series for London created under the EU ADVICE project for the period 1774-1999. The long-term mean of 1015.2 hPa for the new series is more consistent with other long MSLP series in the UK. Copyright © 2011 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Classifications by self‐organizing maps (SOMs) have been used to study links between extreme weather events and atmospheric circulation. However, SOMs may often provide a too generalized image of circulation, which is too coarse to properly resolve meteorological extremes. Several approaches have been used to circumvent this limitation, including an increase in the number of nodes and/or relaxation of the stress on topological ordering of nodes, through adjusting the neighbourhood radius. Here, we (1) test whether weighting of training fields based on extremity of their circulation could lead to SOMs that would better represent circulation extremes without impairing the topological ordering of nodes, and (2) we investigate whether Sammon maps (SM), which have so far been limited to validation of SOMs in climatology, could provide a viable alternative to SOMs in studying weather extremes. We show that removing a certain percentage of circulation fields closest to the climatological mean has a greater effect on the representation of circulation extremes than more than doubling the SOM array size. Additionally, this step allows for decreasing the neighbourhood radius, the parameter responsible for topological ordering, which would not otherwise be possible without impairing the topology of the map. The SOMs are compared with two newly developed methods that discretize SMs based on arbitrarily chosen and distribution‐based bins. We demonstrate the usefulness of both methods in climate model validation and show that both methods are able to capture circulation variability in its extremes in more detail than the SOMs. The distribution‐based method does not suffer from sample‐size issues and outperforms all other classifications in extracting ERA5 patterns leading to extreme temperature minima over central Europe. Our results suggest that classifications based on SM could be a viable alternative to SOMs when SOMs lack the ability to discriminate circulation outliers leading to temperature extremes. [ABSTRACT FROM AUTHOR]

This work improves the characterization and knowledge of the surface wind climatology over Europe with the development of an observational database with unprecedented quality control (QC), the European Surface Wind Observational database (EuSWiO). EuSWiO includes more than 3,829 stations with sub‐daily resolution for wind speed and direction, with a number of sites spanning the period of 1880–2017, a few hundred time series starting in the 1930s and relatively good spatial coverage since the 1970s. The creation of EuSWiO entails the merging of eight different data sets and its submission to a common QC. About 5% of the total observations were flagged, correcting a great part of the extreme and unrealistic values, which have a discernible impact on the statistics of the database. The daily wind variability was characterized by means of a classification technique, identifying 11 independent subregions with distinct temporal wind variability over the 2000–2015 period. Significant decreases in the wind speed during this period are found in five regions, whereas two regions show increases. Most regions allow for extending the analysis to earlier decades. Caution in interpreting long‐term trends is needed as wind speed data have not been homogenized. Nevertheless, decreases in the wind speed since the 1980s can be noticed in most of the regions. This work contributes to a deeper understanding of the temporal and spatial surface wind variability in Europe. It will allow from meteorological to climate and climate change studies, including potential applications to the analyses of extreme events, wind power assessments or the evaluation of reanalysis or model‐data comparison exercises at continental scales. [ABSTRACT FROM AUTHOR]

While long‐term changes in measures of central tendency of climate elements, that is, mean temperature, are well acknowledged, studies of trends in measures of their variability are much less common. This is despite the fact that trends in variability can have higher effect on climate extremes than trends in mean. Here, four measures of intraseasonal variability are examined: (a) standard deviation of mean daily temperature, (b) the range between the 90th and 10th quantile of mean daily temperature, (c) mean absolute value of day‐to‐day temperature change, and (d) one‐day lagged temporal autocorrelation. ECA&D daily data from 168 stations and linear regression method are utilized to calculate trends of these characteristics in period from 1961 to 2018. Significant trends (positive and negative) are revealed with substantial differences between seasons, regions and measures. The most considerable decreases in temperature variability were recorded in winter, for temporal autocorrelation in eastern Europe and for variance‐based measures in northern Europe. For example, the standard deviation has decreased by more than 10% in the Arctic Ocean. This can indicate a decrease in the frequency of cold extremes in Scandinavia. On the contrary, increasing persistence may suggest a greater likelihood of cold extremes in the East European Plain. Increases in variability prevail only in summer, but not for all measures and not as clearly as decreases in winter. Trends in temporal autocorrelation and day‐to‐day change appear to be sensitive to data issues, such as inhomogeneities and changes in observational procedures. [ABSTRACT FROM AUTHOR]

Globally, the impacts of climate change can vary across different regions. This study uses a probability framework to evaluate recent historical (1976–2016) and near‐future projected (until 2049) climate change across Europe using Climate Research Unit and ensemble climate model datasets (under RCPs 2.6 and 8.5). A historical assessment shows that although the east and west of the domain experienced the largest and smallest increase in temperature, changes in precipitation are not as smooth as temperature. Results indicate that the maximum changes between distributions of the variables (temperature and precipitation) mainly occur at extreme percentiles (e.g., 10% and 90%). A group analysis of four subregions of Europe, namely east (G1), north (G2), west/south (G3), and UK/Ireland (G4), shows that G1 and G4 are expected to have the largest increase in temperature and precipitation extremes, respectively. Although maximum increases in temperature in G3 and G4 occur at larger percentiles, G1 and G2 experience maximum increases at both large and small percentiles. The maximum increase of precipitation over the study domain, however, occurs mainly at larger extremes. To quantify changes in the distribution of projection (2020–2049) relative to the historical reference (1976–2005), two measures are defined, namely a change in occurrences (KS statistic) and intensities at different quantiles (Δ). Results confirm that the temperature distribution tends to shift to higher temperatures. Changes in distribution and extremes of precipitation are spatially variable. Furthermore, extremes are expected to be intensified under RCP 8.5. The quantile analysis and defined measures reveal changes in the entire probability distribution, reflecting possible climate changes in the future. [ABSTRACT FROM AUTHOR]

During the last 20 years some very hot and dry summers affected Europe, resulting in regionally record‐breaking high temperature or low precipitation values. Long‐term changes of such extremely hot and dry summers are of great relevance for our society, as they are connected with manifold negative impacts on human society, natural ecosystems, and diverse economic sectors. Long‐term variations in drought and five record drought summer half years are studied based on 63 stations across Europe with high‐quality precipitation and temperature time series spanning the period 1901–2018. Eight drought indices are deployed to analyse drought intensity, frequency, and duration; four of them purely precipitation‐based and four integrating potential evapotranspiration in the computation. Additionally, three heavy precipitation indices and simultaneous increases in drought and heavy precipitation are studied. The five driest summer half years over Europe are identified (1947, 2018, 2003, 1921, and 1911). They are analysed by aggregating eight drought indices into the aggregated drought evaluation index (ADE) for five subregions. The ADE shows increasing summer drought conditions over most of Europe, except for some stations in northern Europe. The increase in drought conditions during the warm part of the year is particularly pronounced for indices integrating evapotranspiration in their definition. At the same time, the intensity of heavy precipitation events shows a positive trend, as well as an increased contribution to total precipitation. Several stations in central Europe show simultaneously increasing drought conditions and increasing heavy precipitation events. This increases the risks connected with precipitation extremes. [ABSTRACT FROM AUTHOR]

Little use has been made up till now of the concept of climate analogues to link the present and the past, i.e. places whose current climate ('target' locations) is similar to that experienced some decades ago at distant locations ('reference' sites). Indeed, most research up till now has focused on analogues between present and future climates. Here we assess at what period of time the climate at a target station in Europe has reached-or will reach-that of a reference location, and show that the velocity of northward-moving isotherms can attain 15 km year−1. Such displacements in space imply that temperatures at many target sites in Europe have already exceeded those experienced by stations located 300-500 km to the south in the last half-century. Such results can serve to better portray what a rapidly changing climate means to a lay audience, and can provide useful information to the policy-making community. [ABSTRACT FROM AUTHOR]

Changes in large-scale circulation patterns over the North-Atlantic-European region are presented and analyzed for the 20th century. First, changes in decadal frequency of Hess-Brezowsky macrocirculation patterns (MCP) are evaluated for the period between 1881 and 2000. Frequency of several MCP types increased or decreased considerably during these 120 years, which may be explained by large-scale changes in circulation characteristics, e.g. by changes in cyclone activity in the different regions. Therefore, cyclone center identification and cyclone tracks and intensity analysis have been accomplished on the basis of the European Centre for Medium-range Weather Forecast (ECMWF) reanalysis data sets (ERA-40) on a 2.5° horizontal resolution grid for the period between 1957 and 2002. Results suggest that both the number of midlatitude cyclones and the cyclone activity increased considerably in the North-Atlantic-European region, especially in the northwestern part of the domain. Copyright © 2006 Royal Meteorological Society. [ABSTRACT FROM AUTHOR]

The relationship between the North Atlantic oscillation (NAO) and winter temperature and precipitation over northern Europe has long been known. However, its strength is variable within this region. In this paper, an analysis of the regional variability of the influence of the NAO on winter precipitation in northern Europe is developed using empirical orthogonal function analysis, cluster analysis and simple correlation. Results show that precipitation in most of the region studied is affected by the NAO, although with varying intensity. The NAO strongly influences winter precipitation along the Norwegian coast, in northern Sweden and in southern Finland. It is evident that the region on the lee side of the Scandes (the mountain chain between Norway and Sweden) is protected from the effects of the moist western winds from the Atlantic that, in turn, are strongly related to the NAO. As a result, precipitation in this shielded area is mainly related to southeasterly winds. Copyright © 2003 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

This paper investigates temperature variability in the Alps and their surroundings based on 97 instrumental series of monthly mean temperatures. A discussion of the initial homogenizing procedure illustrates its advantages and risks. A comparison of the homogenized series with the original series clearly shows the necessity to homogenize. Each of the original series had breaks (an average of five per series) and the mean of all series was systematically biased by non-climatic noise. This noise has subdued the long-term amplitude of the temperature evolution in the region by 0.5 K. The relatively high spatial resolution of the data enabled a regionalization within the study area of 680 000 km2 into six sub-regions based on principal component analysis of the monthly series. Long-term temperature evolution proved to be highly similar across the region—thus making a mean series (averaged over all 97 single series) representative of the study area. Trend analysis (based on progressive forward and backward Mann–Kendall statistics and on progressive analysis of linear regression coefficients) was performed on seasonal and annual series. The results diverge from those of global datasets. This is mainly due to the extension of the 240-year Alpine dataset by 100 years prior to the mid-19th century, and also due to the advantages of a dense and homogenized regional dataset. The long-term features include an initial decrease of the annual and seasonal series to a minimum followed by a positive trend until 1998. The minima are 1890 for the entire year and winter, 1840 for spring and 1920 for summer and autumn, respectively. The initial decreasing trend is more evident in spring and summer, less in autumn and smallest in winter. The mean annual temperature increase since 1890 in the Alps is 1.1 K, which is twice as much as the 0.55 K in the respective grid boxes of the most frequently used global dataset of the Climatic Research Unit (CRU), University of East Anglia. To enable an easier and more systematic handling of the dataset, these data have been interpolated to a 1°×1° longitude–latitude grid. The 105 low-elevation and 16 high-elevation grid point series are widely available without restrictions for scientific research and can be obtained from the authors. Copyright © 2001 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

This review paper summarizes recent research work on abrupt climatic changes and oscillations. The climatic system is viewed as a dissipative, highly non-linear system, under non-equilibrium conditions, and, as such, should be expected to have some unusual properties. These unusual properties include bifurcation points with marked instability just before the point, magnification of semi-periodic oscillations around bifurcation points, and variations in the strength of teleconnections with distance from equilibrium. These properties are discussed and illustrated for the climatic system using both the historical, Holocene and glacial climatic records. It is found that there are abrupt climatic changes and oscillations on all time-scales. The amplitudes and frequencies of climate variability and teleconnections are found to vary between different time periods. A number of persistent oscillations exist, particularly one about 1500 years, but their amplitudes vary considerably between time periods. The Holocene appears to be no more climatically benign than the similar period in the Eemian. The importance of the North Atlantic thermohaline circulation for generating abrupt climatic changes in Europe, particularly in association with sudden pulses of fresh water, is illustrated. The concept of antiphase temperature changes between the North and South Atlantic is discussed. Externally generated abrupt climatic deteriorations owing to explosive volcanic eruptions and variations in solar irradiance are also discussed. Copyright © 2001 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

The main purpose of the analysis is to characterize the location of extratropical lows relative to the jet streaks over Europe and the North Atlantic. Algorithms are presented for jet streak detection and cyclone positioning relative to jet streaks. All time steps in the tracked cyclone lifetime together as well as cyclogenesis, maximum deepening and cyclolysis stages separately are examined. The analysis includes strong jet streaks (>50 ms−1) detected in 300 hPa wind fields in the winter period (1958–2002). The location of cyclones in the jet streak‐associated coordinate system is determined. The cyclone positions, situated near jet streak (<1,300 km), are depicted in the circular distribution diagrams and counted within 15° intervals and jet streak quadrants. The distribution of low‐pressure systems at the cyclogenesis and maximum deepening stages resembles the four‐quadrant model of upper‐level divergence: modal intervals are situated in the Left Front (LF) (primary mode: 45–60°) and the Right Rear (RR) (secondary mode: 195–210°) quadrants. Significant changes in cyclone counts at the LF‐LR and LR‐RR boundaries are likely to be a response to the divergence field aloft. Bimodality is distinctly pronounced in the case of cyclogenesis events and maximum deepening phases. The cyclolysis sites are unimodally distributed with maximum frequency in the Left Rear (LR) quadrant. The modal intervals of cyclogenesis and maximum deepening samples deviate towards the LF‐LR and RR‐LR boundary lines from the bisectors of the LF and RR quadrants, respectively. Such angular displacement is congruent with the shift of divergence‐convergence meridional dipoles in the entrance and exit region towards the cyclonic side of the jet stream. The incipient and maximum deepening stages of cyclones are located within the divergent quadrants in almost 80% of cases (of those near jet streaks). Nearly 60% of the cyclolysis events are situated in the convergent quadrants. [ABSTRACT FROM AUTHOR]

The bioclimatology of thermal stress over Europe between 1979 and 2019 was analysed using the Universal Thermal Climate Index (UTCI) derived from ERA5‐HEAT reanalysis. The bioclimatology of different European regions was assessed using Köppen–Geiger climate classification. The annual number of hours with heat stress (UTCI > 32°C) increased significantly during the study period for all the analysed Köppen–Geiger climate subclasses, showing also a clear increase towards southern Europe. The highest percentage of hours (20% of all hours) with cold stress (UTCI < −13°C) occur over northern Europe. A significant increasing trend (>0.05 hr·year−1) in the number of hours with heat stress was observed for 23 out of 32 analysed European cities representative for the Köppen–Geiger climate subclasses. For these cities not only the number of hours with heat stress has increased but also the heat stress is more persistent, while the number of cases and the persistence of the periods with cold stress have decreased over the last four decades. The UTCI values showed a statistically significant increase between 0.6 and 3.2°C for all the analysed cities over the study period reflecting the rising of global mean temperatures. [ABSTRACT FROM AUTHOR]

This study presents the monthly 10‐m wind speed climatology, decadal variability and possible trends in the North Atlantic and Europe from ERA5 reanalysis from 1979 to 2018 and investigates the physical reasons for the decadal variability. Additionally, temporal time series are examined in three locations: the central North Atlantic, Finland and Iberian Peninsula. The 40‐year mean and the 98th percentile wind speeds emphasize a distinct land‐sea contrast and a seasonal variation with the strongest winds over the ocean and during winter. The strongest winds and the highest variability are associated with the storm tracks and local wind phenomena such as the mistral. The extremeness of the winds is examined with an extreme wind factor (the 98th percentile divided by mean wind speeds) which in all months is higher in southern Europe than in northern Europe. Mostly no linear trends in 10‐m wind speeds are identified in the three locations but large annual and decadal variability is evident. The decadal 10‐m wind speeds were stronger than average in the 1990s in northern Europe and in the 1980s and 2010s in southern Europe. These decadal changes were largely explained by the positioning of the jet stream and storm tracks and the strength of the north–south pressure gradient in the North Atlantic. The 10‐m winds have a positive correlation with the North Atlantic Oscillation in the central North Atlantic and Finland on annual scales and during cold season months and a negative correlation in Iberian Peninsula mostly from July to March. The Atlantic Multi‐decadal Oscillation has a moderate negative correlation with the winds in the central North Atlantic but no correlation in Finland and Iberian Peninsula. Overall, our results emphasize that while linear trends in wind speeds may show a general long‐term trend, more information on the changes is obtained by analysing long‐term variability. [ABSTRACT FROM AUTHOR]

Regional climate predictions for the next decade are gaining importance, as this period falls within the planning horizon of politics, economy, and society. The potential predictability of climate indices or extremes at the regional scale is of particular interest. The German MiKlip project ("mid‐term climate forecast") developed the first regional decadal prediction system for Europe at 0.44° resolution, based on the regional model COSMO‐CLM using global MPI‐ESM simulations as boundary conditions. We analyse the skill of this regional system focussing on extremes and user‐oriented variables. The considered quantities are related to temperature extremes, heavy precipitation, wind impacts, and the agronomy sector. Variables related to temperature (e.g., frost days, heat wave days) show high predictive skill (anomaly correlation up to 0.9) with very little dependence on lead‐time, and the skill patterns are spatially robust. The skill patterns for precipitation‐related variables (e.g., heavy precipitation days) and wind‐based indices (like storm days) are less skilful and more heterogeneous, particularly for the latter. Quantities related to the agronomy sector (e.g., growing degree days) show high predictive skill, comparable to temperature. Overall, we provide evidence that decadal predictive skill can be generally found at the regional scale also for extremes and user‐oriented variables, demonstrating how the utility of decadal predictions can be substantially enhanced. This is a very promising first step towards impact‐related modelling at the regional scale and the development of individual user‐oriented products for stakeholders. [ABSTRACT FROM AUTHOR]

The relationship between River Ammer flood frequency variability, extreme summer climate over Europe, and solar forcing is investigated. First, we used observational data to evaluate extreme weather and climate anomaly patterns associated with flood and solar forcing as well as the possible dynamical mechanisms behind them. Then, the annual resolution flood layer record from the Lake Ammer sediments is analysed to evaluate millennial‐scale variability of floods and possible related extreme climate patterns back to 5,500 years BP. A composite analysis reveals that observed River Ammer flood frequency variability at interannual to multidecadal time scales is connected to large‐scale extreme precipitation and temperature patterns. From a synoptic‐scale perspective, the extreme precipitation pattern associated with floods is related to an increase in the frequency of high upper‐level potential vorticity (PV) events over western Europe and a decrease over eastern Europe and western Russia. Increased (decreased) frequency of upper‐level high PV events is related to more (less) surface extreme precipitation occurrence. Furthermore, we show that increased frequency of upper‐level high PV events over western Europe is associated with enhanced blocking activity over eastern Europe. Therefore, the out of phase interannual to millennial‐scale variations of River Ammer flood frequency and solar irradiance, as presented in previous studies, can be explained by a solar modulation of eastern European‐western Russia summer blocking and associated upstream upper‐level wave breaking activity. In addition, we identify two distinct quasi‐periodic signals in both frequency of Lake Ammer flood layer and solar irradiance records with periods of ~900 years and ~2,300 years. We argue that similar cycles should dominate millennial‐scale variations of blocking activity in eastern Europe‐western Russia as well as extreme precipitation and flood frequency variability over central and western Europe during the last ~5,500 years. [ABSTRACT FROM AUTHOR]

Evaluating the capability of global climate models (GCMs) in reproducing the historical records represents a way of building confidence in their capability for future projections. Among the different ways of evaluating them, here we focus on their capability in reproducing the temporal clustering of heavy precipitation events across Europe in light of four climate modes [the Arctic Oscillation (AO), the North Atlantic Oscillation (NAO), the East Atlantic (EA) pattern, and the Scandinavia pattern (SCAND)], and GCMs from the Coupled Model Intercomparison Project Phase 5 (CMIP5) and the large ensemble runs using the Community Earth System Model (CESM). We use a peak over threshold (POT) approach to identify heavy precipitation events, and Cox regression to relate the occurrence of these events to the climate modes. We find that the GCMs can capture the temporal clustering in heavy precipitation across Europe as a function of these four climate modes; moreover, our findings indicate the GCMs can better reproduce the relationship between heavy precipitation and AO/SCAND, than NAO/EA. Comparing the results based on CMIP5 models and CESM, we find that the inter‐model uncertainties are larger than the intra‐model ones in most of the cases, even though CESM tends to have a poorer performance for EA; this shortcoming for CESM is likely due to the pattern of the Z500 anomalies which is different from the reference data when EA is in the positive phase, affecting the transport of moisture across Europe. [ABSTRACT FROM AUTHOR]

The year 2018 was affected by very long‐lasting, stable summer conditions in vast parts of Europe, in many regions already starting in April and lasting until October. We investigate the thermal characteristics of this year in a secular time perspective, using a spatially well‐distributed dataset of 67 European stations (west of ~30°E) with daily long‐term air temperature observations. Our dataset comprises many of the longest and most reliable (homogenous) temperature measurements available in Europe, mainly starting already in the 19th or rarely even 18th century. Individual time series length is considered to analyse the summer 2018 temperatures into a more than two‐century time perspective, while European time series are presented for the period 1855–2018 and records of five European regions are considered from 1881 onwards. The extreme long duration of the 2018 summer most clearly manifested itself in pronounced new continental maxima of summer half year (April–September) temperature averages and the number of days with maximum temperatures ≥20 and ≥25°C. Furthermore, those indices reached new local maxima at about half of our investigated stations. Records of other temperature indices, rather representing intense heat conditions, were particularly broken in the extended Baltic Sea region, supported by distinct and long‐lasting anticyclonic conditions in this area. However, the extreme summer of 2003 still dominates the ranking of most of these indices on the continental level, even though it is now generally closely followed by summer 2018. We show that long‐term variations of teleconnection indices and the Atlantic Multidecadal Oscillation, as well as seasonal and anthropogenic effects, supported both the recent hot summers and the extreme summer of 2018. [ABSTRACT FROM AUTHOR]

Most of the nature‐related economic costs and human losses in many regions of Europe are due to extreme weather events such as heat waves, cold spells, persistent droughts, heavy precipitation and intense cyclonic wind‐storms. Extreme precipitation events are projected by climatic models to become more intense over the continent while droughts might last longer by the end of the century. In dry regions as Southern Europe, soils are predicted to dry out as temperatures and evapotranspiration rise and rain‐bearing atmospheric circulations become less frequent. Prospects on the future of climate indices linked to extreme phenomena are herein derived by using observed and model projected daily meteorological data. Specifically, E‐OBS high resolution gridded datasets of observed precipitation and surface minimum and maximum temperatures have been used as the regional observed baseline. For projections, the same meteorological variables have been obtained from a set of regional climate models integrated in the European EURO‐CORDEX project, considering the RCP8.5 future emissions scenario. A quantile–quantile adjustment has been applied to the simulated regional scenarios to reduce biases in modelled extreme regimes. Results suggest that warm days will substantially increase across Europe, consistently with a decrease of cold nights. An increase in heat wave amplitude is expected across the continent, with South Eastern Europe and the Mediterranean as the most affected regions. In contrast, Northern Europe will undergo the largest decrease in cold spell magnitude. An overall rise in the frequency and volume of heavy precipitations is projected in all seasons, even if the number of dry days is also expected to increase, except in the Baltic countries. Regarding abnormally long dry periods (extreme droughts), we find that the occurrence of episodes would reduce over Europe as consequence of projected increases in length. [ABSTRACT FROM AUTHOR]

We analyse annually resolved tree‐ring stable carbon (δ13C) and oxygen (δ18O) isotopic chronologies from Swiss stone pine (Pinus cembra L.) in Romania. The chronologies cover the period between 1876 and 2012 and integrate data from four individual trees from the Calimani Mts in the eastern Carpathians where climatic records are scarce and starts only from 1961. Calibration trials show that the δ13C values correlate with local April–May relative humidity and with regional to larger scale (European) summer precipitation. δ18O correlates significantly with local relative humidity, cloud cover, maximum temperature, as well as European scale drought conditions. In all cases, the climate effects on δ13C values are weaker than those recorded in the δ18O data, with the latter revealing a tendency toward higher (lower) values of δ18O during extremely dry (wet) years. The most striking signal, however, is the strong link between the interannual δ18O variability recorded in the Calimani Mts and large‐scale circulation patterns associated with North Atlantic and Mediteraneean Sea sea surface temperatures. High (low) values of δ18O occur in association with a high (low) pressure system over the central and eastern part of Europe and with a significantly warmer (colder) Mediterranean Sea surface temperature. These results demonstrate the possibility of using tree ring oxygen isotopes from the eastern Carpathians to reconstruct regional drought conditions in eastern Europe on long‐term time scales and larger scale circulation dynamics over the preinstrumental periods. [ABSTRACT FROM AUTHOR]

The spatial dependence of meteorological variables is crucial for many impacts, for example, droughts, floods, river flows, energy demand, and crop yield. There is thus a need to understand how well it is represented in downscaling (DS) products. Within the COST Action VALUE, we have conducted a comprehensive analysis of spatial variability in the output of over 40 different DS methods in a perfect predictor setup. The DS output is evaluated against daily precipitation and temperature observations for the period 1979–2008 at 86 sites across Europe and 53 sites across Germany. We have analysed the dependency of correlations of daily temperature and precipitation series at station pairs on the distance between the stations. For the European data set, we have also investigated the complexity of the downscaled data by calculating the number of independent spatial degrees of freedom. For daily precipitation at the German network, we have additionally evaluated the dependency of the joint exceedance of the wet day threshold and of the local 90th percentile on the distance between the stations. Finally, we have investigated regional patterns of European monthly precipitation obtained from rotated principal component analysis. We analysed Perfect Prog (PP) methods, which are based on statistical relationships derived from observations, as well as Model Output Statistics (MOS) approaches, which attempt to correct simulated variables. In summary, we found that most PP DS methods, with the exception of multisite analog methods and a method that explicitly models spatial dependence yield unrealistic spatial characteristics. Regional climate model‐based MOS methods showed good performance with respect to correlation lengths and the joint occurrence of wet days, but a substantial overestimation of the joint occurrence of heavy precipitation events. These findings apply to the spatial scales that are resolved by our observation network, and similar studies with higher resolutions, which are relevant for small hydrological catchment, are desirable. [ABSTRACT FROM AUTHOR]

Projections of climate change impacts over Europe are derived using a new quantile–quantile adjustment method. E‐OBS high‐resolution gridded data sets of daily observed precipitation and 2‐m surface minimum and maximum temperatures have been used as the current climate baseline. For projections, the same meteorological variables have been obtained from a set of regional climate models (RCMs) integrated in the EURO‐CORDEX project, and by considering the RCP4.5 and RCP8.5 future emissions scenarios. To enhance the reliability of RCM data at local scale, new developments of a previous quantile–quantile adjustment have been applied to the simulated regional scenarios. This method focuses not only on the bulk spectrum of the cumulative distribution functions but also on its tails. Results show an overall improvement in reproducing the present climate baseline when using calibrated series instead of raw RCM outputs. Next, we have used these locally adjusted series to quantify the climate change signal through a number of annual and seasonal indicators. A significant increase of the minimum and maximum temperatures in all seasons is projected over Europe, being more marked in the Mediterranean for summer and autumn. Prospects on future seasonal and annual changes in precipitation are more diverse, showing an overall decrease in southern Europe and the Mediterranean, while precipitation is expected to increase towards the north of the continent. With these sources of information at hand, including and accounting for the identification of the most vulnerable geographical areas, policy makers and stakeholders can respond more effectively to the future challenges imposed by climate change. [ABSTRACT FROM AUTHOR]

Global drought extremes are projected to increase under future warming scenarios. However, global drought risk and pattern remain to be revealed below 1.5 and 2 °C warming levels. Here we used multi‐model simulations to estimate global drought trend based on multiple drought indicators. The frequency and duration of meteorological drought may increase much faster than surface soil moisture drought and root zone soil moisture drought under anthropogenic warming, with a probable ~36% (62%) increase in frequency and a ~15% (20%) increase in duration at 1.5 °C (2 °C) level relative to the reference period over the globe. A 5% (14%) increase of drought frequency is expected at 1.5 °C (2 °C) warming in the surface soil moisture, and a 5% (2%) increase of duration is also likely in the 0–10 cm soil layer. Unprecedented increased drought risk is anticipated at 2 °C level, with potential drought hot spots in North America, South America, southern Africa, Australia and Europe. Drought condition under future warming may be much worse in local areas. The drought frequency in the drylands is much less (>34%) than the humid areas, but the duration is much higher (>40%). The 2 °C relative to 1.5 °C warming is expected to bring higher drought risk than the 1.5 °C relative to 1 °C period with regard to the frequency. Drought characteristics for SPI under different levels of global warming. [ABSTRACT FROM AUTHOR]

Spatial and temporal patterns of trends in annual and seasonal precipitation over Germany during 1951–2013 were analysed using the ensemble empirical mode decomposition (EEMD) method. Three widely used and recognized high‐resolution observation‐based gridded precipitation products, the Climatic Research Unit (CRU) time‐series data, Global Precipitation Climatology Centre (GPCC) Full Data Reanalysis data and the EU‐FP6 project ENSEMBLES derived data set (EOBS), were used and compared. Comparison among different products showed that the CRU used a considerably lower number of gauge stations (maximum 36) in the construction of gridded product over Germany and should be used with great caution for other applications, and overall CRU presented less precipitation and smaller inter‐annual variability; GPCC and EOBS agreed well in the spatial and temporal distribution of seasonal and annual precipitation, as well as the identified trends. The spatiotemporal analysis of trends showed that trends in precipitation during 1951–2013 were, in most cases, highly nonlinear and varying over time. In particular, the spring, summer and autumn precipitation showed large variations in trends. Therefore, the assumption of linear trends on which previous studies were based is invalid. Annual precipitation showed increasing trends in over 66% of Germany (particularly northern and eastern Germany), and the magnitude of increasing trends were generally enhanced over time, e.g. GPCC showed that the average magnitude of increasing trends rose from 6.3% for the 1951–1980 period to 12% for the 1951–2013 period. There were considerable spatial and temporal variabilities in trends in seasonal precipitation totals over Germany. This study is among one of the first studies applying the EEMD method to a comprehensive analysis of time‐varying trends in precipitation over Germany, which is expected to improve our understanding of the complex and nonlinear regional climate system. Spatial and temporal patterns of the EEMD‐derived trend of the four seasonal precipitation totals (DJF, MAM, JJA, SON; the trend is presented as the percentage of the climatology mean during the whole period 1951–2013 for easy interpretation and comparison) from EOBS for five different periods, with ending years of 1980, 1990, 2000, 2010 and 2013. [ABSTRACT FROM AUTHOR]

Climate models have provided driving data for impact studies for decades. However, the uncertainties related to the use of such data have typically not been sufficiently considered. We investigate how CORDEX climate simulations, which were corrected for bias based on MESAN reanalysis data for the period of 1989–2010, match the gridded observational data set E‐OBS. Furthermore, we investigate whether the bias‐corrected simulations contain significant residual bias (RB), which we defined as the bias exceeding the range of the observational uncertainty (Uobs) that emerges from differences between the two data sets MESAN and E‐OBS. Because the reference period selected in climate change impact studies often differs from the period used for bias correction, we further investigated whether the RB and other performance metrics of the periods 1989–2010 and 1961–1990 differ. We conducted this assessment for whole Europe and for biogeographical zones. Most of the used performance metrics show a good match of the simulations with MESAN in the period of 1989–2010. The comparison against E‐OBS yields worse results, indicating a significant difference between the two observational data sets. Minor bias exceeding the range of Uobs (RB) occurred over large land areas of Europe in this period. Based on the analysis conducted for the period of 1961–1990, the RB is several times larger than that of the period of 1989–2010; the other metrics also show worse performances. Our findings imply that both the selection of the reference climate data set and reference period warrant greater attention in impact studies. In particular, we recommend researchers to use a bias correction period as reference period in their studies. Alternatively, a new bias correction should be applied if any different period is to be used as a reference. This study pointed out several aspects of disagreement between the bias‐corrected EURO‐CORDEX climate simulations and observational data sets E‐OBS and MESAN. The testing was performed separately for the bias correction period of 1989–2010 and the testing period of 1961–1990. Our findings imply that both the selection of the reference climate data set and reference period warrant greater attention in impact studies. [ABSTRACT FROM AUTHOR]

Evapotranspiration plays an essential role in estimating water balance, runoff and effective precipitation. To determine historical and projected water availability for Europe, we contribute high‐resolution (1 km) estimates of monthly and annual potential evapotranspiration (ET0) and actual evapotranspiration (AET0). In the ET0 calculation, the monthly and annual heat index I and annual α parameter were estimated following the Thornthwaite method, and AET0 was calculated using the Budyko approach. The variables were estimated for a climate normal period that largely precedes an anthropogenic warming signal (1961–1990), and for two CMIP5 multi‐model future projections (2011–2040 and 2041–2070). We project widespread and relatively uniform ET0 increases of around 50–100 mm by the 2020s and 75–125 mm by the 2050s for most of Europe. These values imply important changes that may affect runoff and groundwater recharge. AET0 was identified as important driver of water availability with more regional variability. Spatial mapping of changes relative to the normal baseline imply that all except northern parts of Europe are vulnerable to water deficits, with pronounced decrease expected in southern Europe. We provide high‐resolution maps and data as an important tool for future natural resources management and climate change mitigation planning. [ABSTRACT FROM AUTHOR]

ABSTRACT: During the last decades, the effects of global warming have become apparent also in Europe, causing relevant impacts in many sectors. Under projected future global warming, such a tendency can be expected to persist until the end of this century and beyond. Identifying which climate‐related impacts are likely to increase, and by how much, is an important element of any effective strategy for managing future climate risks. This study investigates whether energy demand for cooling and heating buildings can be expected to increase or decrease under climate change. Two indicators of weather‐related energy consumption for heating and cooling buildings are considered: heating degree‐days (HDD) and cooling degree‐days (CDD). The evolution of these indicators has been analysed based on 11 high‐resolution bias‐adjusted EURO‐CORDEX simulations for two emission representative concentration pathways (RCP4.5 and RCP8.5). Both indicators have been validated over the period 1981–2010 using an independent data set that contains more than 4000 station data, showing very high correlation over most of Europe. Trends of HDD and CDD from 1981 to 2100, together with their uncertainties, are analysed. For both RCPs, all simulations project a significant decrease for HDD, especially over Scandinavia and European Russia, and an increase of CDD which peaks over the Mediterranean region and the Balkans. Overall, degree‐day trends do not show remarkable differences if population weighting is applied. If a constant population scenario is considered, the decrease in HDD will outbalance the increase in CDD in the 21st century over most of Europe. Thus the related energy demand (expressed as Energy Degree‐days, EDD) is expected to decrease. If, however, population projections over the 21st century are included in the calculations, it is shown that despite the persisting warming, EDD will increase over northern Europe, the Baltic countries, Great Britain, Ireland, Benelux, the Alps, Spain, and Cyprus, resulting in an overall increase in EDD over Europe. [ABSTRACT FROM AUTHOR]

ABSTRACT This study compares the multivariate predictions of daily temperature, temperature range, precipitation, surface wind and solar radiation of a single-model analogue approach with an original multi-model analogy over 12 regions in Europe and Maghreb. Both approaches are based on two-level analogue models where atmospheric predictors are either dynamic or thermodynamic. In the multi-model approach, independent analogue models with predictand-specific predictors are used. In the single-model one, a unique analogue model and its associated set of predictors is applied to all predictands. Testing numerous large-scale predictors, we first identify the best predictor sets for each modelling strategy. Those obtained for the single-model approach are significantly different from those of the predictand-specific models. This is especially the case for local temperature and wind speed. Both methods perform similarly for precipitation, temperature range and radiation. We next assess the ability of both approaches to simulate physically coherent multivariate weather scenarios. With the single-model method, weather scenarios are obtained for each prediction day from observations sampled simultaneously on one analogue day. The physical consistency between variables is thus automatically fulfilled each day. This allows the single-model method to reproduce well the observed inter-predictand correlations, especially the significant correlations between radiation and precipitation and between radiation and temperature range. These results suggest a hybrid analogue model using a single-model for radiation, temperature range and precipitation, combined with a univariate approach for wind. Two options are proposed for temperature for which either the predictand-specific method or a single-model approach with an additional correction are conceivable. This hybrid approach leads to a possible compromise between reasonable univariate prediction skills and realistic inter-predictands correlations, both classically required for many impact studies. [ABSTRACT FROM AUTHOR]

ABSTRACT In 2015, large parts of Europe were characterized by extraordinary high summer temperatures, accompanied by very dry conditions, particularly in central-eastern Europe. Several major heat episodes occurred from the end of June until mid-September. We provide an ad-hoc evaluation of the observed climatological extremes in a secular context, by using a set of long station time series in daily resolution. Our data set comprises 42 temperature and 43 precipitation records, predominantly starting already in the 19th century. To investigate local record values, the individual full record length is analysed for each station, while regionally averaged analyses are presented for the core study period of 1901-2015. The study area covers Europe's central latitudes (44° to 52°N), extending from England in the west up to the central Ukraine in the east. During summer 2015, various indices representing extremely high maximum and minimum temperatures (strongly) exceeded previous record high values, mainly in an area extending from eastern Germany to western Ukraine. Additionally, severely to extremely dry conditions with unusually frequent dry days were prevailing particularly in the (central-) eastern part of the study area. Drought indices combining temperature and precipitation revealed drought conditions comparable or even worse than those of former extreme summers like 2003. [ABSTRACT FROM AUTHOR]

ABSTRACT The ability of circulation type classifications ( CTCs) to resolve surface climatic and environmental variables is essential with respect to their application in synoptic climatological applications. This 'synoptic skill' depends on several factors including inherent properties of classification methods but as well varying boundary conditions. In this contribution the relevance of the size of the spatial domain for which CTCs are derived is investigated. To this end varying automated CTCs are applied to daily gridded sea level pressure data for 1950-2010 and in each case eight spatial domains of varying size centred around 44 locations spread over the greater north Atlantic European region. For the resulting more than 7000 CTCs the synoptic skill for daily temperature and precipitation taken from the E- OBS v4.0 data set has been estimated using varying evaluation metrics. Resulting values of evaluation metrics aggregated according to varying domain sizes reveal a distinct influence of the size of the domain on the synoptic skill of CTCs. In general highest skill appears to be achieved for domain sizes with a horizontal dimension of roughly 1300-1800 km (in west-east direction) thus covering most frequent size ranges of synoptic scale systems. However, optimal domain sizes tend to be smaller for precipitation (compared to temperature) in summer (compared to winter) and in more continental regions (compared to more oceanic regions). Distinct deviations from the overall finding of relatively small optimal domains emerge for temperatures above/below certain thresholds for which in certain locations and seasons continental scale domains yield highest synoptic skill. Finally the comparison of varying CTCs concerning the effect of the domain size for synoptic skill shows marked differences between methods and moreover clearly elucidates that differences in synoptic skill that can be attributed to varying domain sizes reach comparable magnitude than those related to differing methods. [ABSTRACT FROM AUTHOR]

ABSTRACT Ensembles of high-resolution regional climate model ( RCM) simulations are crucial for assessing regional climate change and the associated uncertainties. This article presents an RCM ensemble generation technique which explores uncertainties arising from the positioning of synoptic systems in the large-scale atmospheric forcing by shifting the atmospheric fields from global climate model ( GCM) runs horizontally. Here, we discuss how the so-called Atmospheric Forcing Shifting ( AFS) affects temperature and precipitation over Europe for the period 1980-1984. We use ERA-40 reanalysis data in which the atmospheric fields are shifted to each direction by 25 and 50 km, respectively, to run RCM simulations with COSMO-CLM at 50-km resolution. The analysis of the AFS ensemble includes comparisons with E- OBS observations and COSMO-CLM runs driven by different GCMs. AFS has an evident effect on the spatiotemporal distributions of temperature and particularly precipitation, which is most pronounced during hydrological summer (May to October) when spatial weather patterns are more variable. Furthermore, AFS produces realistic changes in the likelihood and intensity of extreme precipitation. The changes induced by AFS depend strongly on orography, i.e. precipitation increases are likely to occur where moist air masses are shifted towards the windward mountain side and vice versa. Thus, increasing the RCM ensemble spread by means of AFS is a simple and useful method for sampling observed climate statistics and assessing the variability and changes in mean and extreme climate. [ABSTRACT FROM AUTHOR]

ABSTRACT As both global (GCM) and regional (RCM) climate models have their own advantages, the most comprehensive picture of changes in precipitation and their uncertainty ranges can be achieved by comparing the results of both model categories. Here we have evaluated seasonal changes in indices representing excess or scarcity of precipitation in Europe on the basis of simulations performed with ten GCMs with a reasonably high spatial resolution and, for comparison, with five RCMs driven by one and the same GCM. We found no fundamental differences between the GCMs and RCMs in the projected tendency towards a more extreme precipitation climate, characterized by increases both in indices representing wet conditions and also dry conditions. Most evidently in the Northern European summer and Southern European winter, the differences in the responses of the various indices between the present sets of GCMs and RCMs could be explained by the dissimilar changes in seasonal mean precipitation. The scatter among the projected changes was in general much smaller for the RCM than for the GCM simulations. The projections of individual RCMs mainly fall within the interval determined by the GCM projections. This indicates that the GCM ensemble yielded more comprehensive estimates for the uncertainty ranges in the extreme precipitation indices. [ABSTRACT FROM AUTHOR]

ABSTRACT This study presents a new gridded dataset providing absolute monthly mean temperatures across the Greater Alpine Region (GAR) of Europe at a spatial resolution of 5 arcmin (6 × 9 km in the region) from 1780 to 2008. The starting point was a set of long-term homogenized station time series. To assure the quality of the analyses back in time, when the station density decreases, missing measurements were reconstructed by an Empirical Orthogonal Function analysis that can deal with gappy data. It is shown that the reconstructed values comprise similar statistical features to the observations and that the method produces no breaks between the reconstructions and the observations. The compound anomaly dataset was then interpolated separately for two different altitude ranges to preserve anomaly gradients between high and low elevations. This allowed for the derivation of individual anomalies at each grid point in GAR. Finally, these smooth anomalies were blended with the highly resolved monthly mean absolute temperature fields, provided by a project of the European Climate Support Network. The added value of this new high resolution and long-term temperature dataset is shown and discussed using the examples of the height of the 0 °C altitude and vertical lapse rates. For the first time, these and other features are now available for more than two centuries in a topographically complex region like GAR. [ABSTRACT FROM AUTHOR]

ABSTRACT Through the use of the climatic classification of Köppen-Trewartha (K-T), the ability to reproduce the current climate of Europe has been shown for an ensemble of 15 regional climate model simulations nested in six global climate models. Depending on the simulation, between 55.4 and 81.3% of the grid points are in agreement with observations regarding the location of climate types in current climate simulations (1971-2000). In this respect, the result of the ensemble of 15 simulations is better than that of any individual model, with 83.5% of the grid points in agreement with observations. K-T classification has also been used to analyse the projected climate change over the 21st century under the SRES-A1B emissions scenario. It was found that 22.3% of the grid points in the domain change their climate by the period 2021-2050 compared to current climate and 48.1% change by 2061-2090. The climate shifts affecting the biggest extensions are projected in Central Europe and Fennoscandia, but other smaller areas suffer more intense changes which potentially are more dangerous to vegetation and ecosystems. Generally, these changes occur at a sustained rate throughout the century, reaching speeds of up to 90 × 103 km2 decade−1 in the retreat or expansion of some climates. [ABSTRACT FROM AUTHOR]

At low elevations (500 m a.s.l.) Central Europe's surface temperature increased about 1.3 °C since 1981. Interestingly, at high elevations (2200 m a.s.l.) in the Alps, temperature rose less than 1 °C over the same period. Detailed investigations of temperature, humidity and the radiation budget at lowland and alpine climate stations now show that the difference in temperature rise is likely related to unequal solar- and greenhouse warming. The analysis shows that the important decline of anthropogenic aerosols in Europe since the mid-1980s led to solar brightening at low elevations, whereas inherent low aerosol concentrations at high elevations led to only minor changes of solar radiation in the Alps. In the Lowland, absolute humidity and also total net radiation show an about 6% K−1 Clausius-Clapeyron conform increase with temperature since the 1980s. In the Alps, however, the percentage increase rate of humidity and total net radiation is more than twice as large. This large water vapour increase in the Alps is likely related to strong warming and thermal advection in the Lowlands, and may also have increased due to atmospheric circulation changes. Hence, while in the Alps temperature increased primarily due to strong water vapour enhanced greenhouse warming, solar brightening combined with anthropogenic greenhouse gas and water vapour feedback greenhouse warming led to a higher temperature increase at low elevations in Central Europe. Copyright © 2012 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Under the aspect of future climate change, it is important for decision makers to know how drought conditions might change on the regional scale in order to map out adequate adaptation and mitigation strategies. Recent RCM simulations provided by the ENSEMBLES project are used to analyse changes in dry and wet conditions in Europe by the mid of the 21st century under the A1B emission scenario. Eight RCMs are selected to capture the uncertainties of the projected changes. An empirical statistical error correction approach is applied to modelled daily mean air temperature and precipitation amount to account for RCM errors, and commonly used drought indices-the Standardized Precipitation Index (SPI), the self calibrated Palmer Z-Index (scZI) and Palmer Drought Severity Index (scPDSI)-are calculated. Changes in the mean, in interannual variability, and in frequency, length, distance, magnitude, and area of dry and wet events are investigated. The statistical significance of the projected multi-model mean changes and the according uncertainties are analysed for nine European subregions. Furthermore, distributional changes of the dry and wet spell characteristics are assessed. Changes in the mean, and in dry and wet event characteristics show the most pronounced changes towards drier and wetter conditions in the southern- and northernmost European subregions, respectively. Here, the changes are highly significant and confident, while the projected changes are more dissonant for the other subregions. Severe changes in the extremes of event length, distance, magnitude, and area particularly arise in the southern- and northernmost European subregions. The projected changes in interannual variability are less significant and confident. However, significantly increasing interannual variability is projected in regions with pronounced changes in the mean towards wetter as well as towards drier conditions. Copyright © 2011 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Seasonal mean temperatures averaged over the European region have warmed at a rate of 0.35-0.52 K/decade since 1980. The last decade has seen record-breaking seasonal temperatures in Europe including the summer of 2003 and the spring, autumn, and winter of 2007. Previous studies have established that European summer warming since the early twentieth century can be attributed to the effects of human influence. The attribution analysis described here employs temperature data from observations and experiments with two climate models and uses optimal fingerprinting to partition the climate response between its anthropogenic and natural components. These responses are subsequently combined with estimates of unforced climate variability to construct distributions of the annual values of seasonal mean temperatures with and without the effect of human activity. We find that in all seasons, anthropogenic forcings have shifted the temperature distributions towards higher values. We compute the associated change in the likelihood of having seasons whose temperatures exceed a pre-specified threshold. We first set the threshold equal to the seasonal temperature observed in a particular year to assess the effect of anthropogenic influences in past seasons. We find that in the last decade (1999-2008) it is extremely likely (probability greater than 95%) that the probability has more than doubled under the influence of human activity in spring and autumn, while for summer it is extremely likely that the probability has at least quadrupled. One of the two models employed in the analysis indicates it is extremely likely the probability has more than doubled in winter too. We also compute the change in probability over a range of temperature thresholds which enables us to provide updates on the likely change in probability attributable to human influence as soon as observations become available. Such near-real time information could be very useful for adaptation planning. © Crown Copyright 2010. Published by John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The relationships between the main patterns of variability of the Atlantic sea-surface temperatures (SSTs) and the European land-surface temperatures (LSTs) at interannual-to-multidecadal time scales are investigated along the period 1872-2004. Principal component analysis (PCA) is used firstly to obtain the main spatio-temporal patterns of variability of the LSTs and SSTs. Singular Spectral Analysis (SSA) is then used to decompose the time series associated with these patterns into nonlinear trends and quasi-periodic oscillations, searching for common oscillatory modes to the SSTs and LSTs. The potential predictability of the LSTs based on the SSTs is also analysed. Regarding the SSA results, three robust oscillations of periods around 13.7, 7.5 and 5.2 years, present both in the Atlantic SSTs and north-western European LSTs, were isolated. These oscillations were found to be associated mainly with a quadripolar SST pattern in the North Atlantic region, usually related to the North Atlantic Oscillation (NAO) atmospheric mode of variability. The predictability study revealed that the SSTs of the Atlantic Ocean are able to account for about 12% of the north-western European LSTs variance. Additionally, an oscillatory component with period around 3.6 years was identified, but no significant connection between SST and LST was found for this mode. In addition, at this time scale, we find that the El Niño-Southern Oscillation (ENSO) is leading the Atlantic SST quadripolar pattern by 6 months. Finally, the analysis of the nonlinear trends showed the presence of oscillations with periods around 60-100 years, both in the SSTs and LSTs. At these later time scales, our results reveal that the multidecadal behaviour of the southern European LSTs is related to Atlantic Multidecadal Oscillation (AMO) during the period 1872-1940, unlike the northern and eastern European LSTs, while, during the period 1941-2004, the AMO sign seems to be present in whole Europe. Copyright © 2010 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Variability in aspects of the hydrological cycle over the Europe-Atlantic region during the summer season is analysed for the period 1979-2007, using observational estimates, reanalyses and climate model simulations. Warming and moistening trends are evident in observations and models although decadal changes in water vapour are not well represented by reanalyses, including the new European Centre for Medium Range Weather Forecasts (ECMWF) Interim reanalysis. Over the north Atlantic and northern Europe, observed water vapour trends are close to that expected from the temperature trends and Clausius-Clapeyron equation (7% K), larger than the model simulations. Precipitation over Europe is dominated by large-scale dynamics with positive phases of the North Atlantic Oscillation coinciding with drier conditions over north Europe and wetter conditions over the Mediterranean region. Evaporation trends over Europe are positive in reanalyses and models, especially for the Mediterranean region (1-3% per decade in reanalyses and climate models). Over the north Atlantic, declining precipitation combined with increased moisture contributed to an apparent rise in water vapour residence time. Maximum precipitation minus evaporation over the north Atlantic occurred during summer 1991, declining thereafter. Copyright © 2010 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

The article presents an analysis of critical clustering of dry summer conditions in Europe from 1750 until 2009. It notes that moisture availability in the continent is computed based on 22 stations possessing established instrumental records intended for precipitation and temperature. In addition, it mentions the relevance of self-calibrating Palmer Drought Severity Index in the study which is actually grounded on soil moisture content.

The article identifies the factors contributing to the return period of windstorms in Europe. Assessment of the magnitude and frequency of extreme wind speed plays a fundamental role in safety, engineering and reinsurance applications and preparations for extreme weather. It is evident that windstorms and strong winds represent a major loss for reinsurance companies. Factors contributing to the occurrence of wind storms include unstable surface wind field and the continued changes in the global climate.