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We study trends in drought across the central latitude strip of Europe (defined as the region 47.5–52.5 °N and 2.5°W–32.5°E) during 1950–2019, and their links to atmospheric circulation. Drought characteristics are based on difference between potential evapotranspiration and precipitation in E–OBS data, and atmospheric circulation is characterized in terms of circulation types classified using daily sea level pressure patterns from the NCEP–NCAR reanalysis. Circulation types supporting drought in vegetation season (April–September) are identified, and we analyse changes in their occurrence since 1950, seasonal changes, and the connection with drought trends in individual European regions. We find that while in the early vegetation season, drought develops mainly in Central Europe, in the late vegetation season the most pronounced trends are shifted towards west. The circulation types supporting drought depend on regions and seasons, especially for directional types. The largest increase of the dry circulation types is observed in both seasons in Central Europe, and contributes to the pronounced drying.

Changes in the amount, intensity, frequency and type of precipitation are observed in some places over recent decades (IPCC 2021). While much effort has been devoted to analyzing long-term changes in mean values and extremes, studies on changes in precipitation variability have been rather scarce. Long-term changes in climate variability are, nevertheless, an important aspect of the climate change with various impacts on society and environment. Therefore it is necessary to know whether and how the precipitation variability will change in the future. To this end, it is important that it is simulated correctly by recent climate models. In our study, we analyze outputs from an ensemble of different CMIP6 global climate models and several reanalyses and gridded observed datasets. We study long-term changes in day-to-day precipitation variability and how they differ between various datasets for the historical and current climate. We evaluate how successful the climate models are in reproducing precipitation variability, while identifying biases and errors common to all models or to groups of models. We analyze projected changes of short-term precipitation variability in model simulations over the whole 21st century. We focus on the North Atlantic-European sector. We consider wet-to-wet and dry-to-dry transition probabilities as a measure of short-term precipitation variability, focusing on winter and summer seasons separately. Ref.: IPCC, 2021: Summary for Policymakers. In: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)].

Compound effects of drought and heat are regarded as one of the largest hazards in relation to climate change. Characteristics of dry–hot seasons in Europe are studied in an ensemble of CORDEX regional climate models (RCMs). Evaluation against the E–OBS gridded dataset for 1976–2005 shows that the RCMs are able to reproduce the spatial pattern of the dry–hot season length but the seasons tend to start later and interannual variability of their length is often underestimated. Changes in the median length of dry–hot seasons (compared to the 1976–2005 simulated climate) are analysed for three future time slices (2006–2035, 2036–2065, and 2066–2095) and low and high greenhouse gas concentration pathways. Preliminary results show distinct prolongations of dry–hot seasons for 2036–2065 in the Mediterranean and Western Europe (+10–30 days), regardless the concentration pathway. The lengths of dry–hot seasons are projected to be similar in the 2036–2065 and 2066–2095 time slices under the low concentration pathway but the RCMs simulate major prolongations of dry–hot seasons in the high concentration scenario over large parts of Europe (+20–50 days), indicating substantial changes in future European hydroclimate.

Thirty-year periods are treated in climatology as spans with relatively representative and stable climatic patterns, which can be used for calculating climate normals. Annual and seasonal series of circulation types were used to compare two 30-year sub-periods, 1961–1990 and 1991–2020, the second one being strongly influenced by recent global warming. This analysis was conducted according to the objective classification of circulation types and the climatic characteristics of sunshine duration, temperature, humidity, precipitation, and wind speed as calculated for the territory of the Czech Republic during the 1961–2020 period. For both sub-periods, their statistical characteristics were calculated, and the statistical significance of differences between them was evaluated. There was a statistically significant increase in the annual frequencies of anticyclonic circulation types and a significant decrease in cyclonic circulation types during 1991–2020 compared with 1961–1990. Generally, in both 30-year periods, significant differences in means, variability, characteristics of distribution, density functions, and linear trends appear for all climatic variables analysed except precipitation. This indicates that the recent 30-year “normal” period of 1991–2020, known to be influenced more by recent climate change, is by its climatic characteristics unrepresentative of the stable climatic patterns of previous 30-year periods. Annual and seasonal sunshine duration series do no express significant changes between two 30-year normal periods in terms of their variability, characteristics of distribution, density functions and linear trends. Only increase in annual, MAM and JJA means in 1991–2020 compared to the preceding period was statistically significant. Mean, maximum and minimum temperatures display quite different patterns in two 30-year normal periods in accord with recent warming. They are reflected in statistically significant differences in means, characteristics of distribution, density functions and in significant linear trends in 1991–2020 (annual, JJA, SON). It is pronounced particularly for JJA series. Statistically significant decreases in means of relative humidity between two 30-year normal periods (except SON) are reflected in a significant shift of density functions to lower values. But decreasing linear trends were significant only for MAM. Increasing variability in relative humidity was significant for annual and MAM series. Precipitation totals of the both 30-year periods are represented well by insignificant linear trends, no substantial changes in mean and variability as well as in the character of their distribution represented by the density functions. Wind speeds in two 30-year normal periods represents quite different patterns expressed by statistically significant decreasing linear trends in 1991–2020, significant differences in means, partly in variability and skewness (annual, MAM) and in density functions.

Since long-term changes in climate variability are an important aspect of climate change, it is necessary to know whether and how they will change in the future. To this end, it is also important that they are simulated correctly by climate models. Despite its importance to the society and relevance in various impacts, short-term precipitation variability was given very little attention even in the last IPCC report. In our analysis, we aim to answer these questions: (1) What long-term changes in day-to-day precipitation variability have been observed? (2) Do the short-term precipitation variability and its long-term trends differ between various datasets, and how much? (3) How successful are climate models in reproducing precipitation variability? Is it possible to identify biases and errors common to all or majority of models, or to groups of models? (4) What changes of short-term precipitation variability do climate models project in future? Are the observed changes consistent with the projected changes, that is, does the anthropogenic climate change already manifest in the recently observed changes of variability?We analyze day-to-day variability in precipitation in North Atlantic and European sector. We consider wet-to-wet and dry-to-dry transition probabilities as a measure of short-term precipitation variability, focusing on winter (DJF) and summer (JJA) seasons separately. We compare results obtained from stations data, gridded observed data (E-OBS), various reanalyzes, and outputs of an ensemble of CMIP6 global climate models. We analyze historical model runs starting in 1950 and possible climate change over the 21st century in the simulations under the SSP585 scenarios.

Automated classifications of atmospheric circulation are routinely used to link synoptic-scale circulation with temperature variability. Though powerful in general, classifications have considerable limitations regarding their skill to capture synoptic links to temperature extremes.We evaluate and optimize several parameters of the popular method of self-organizing maps, in order to make the method better suited for studying central European temperature extremes. Furthermore, two methods of discretizing Sammon projections of atmospheric circulation have been developed to complement the image obtained by SOMs, and all methods have been used to analyse ERA5 SLP fields in relation to winter extremes.Here, we plan to apply the new optimized classifications to daily winter and summer SLP fields from the outputs of evaluation and historical runs by CORDEX RCMs to study the skill of the methods to identify RCM biases in simulated circulation and their links to biases in temperature extremes. Furthermore, we plan to utilize various indices of low-frequency large-scale circulation to assess to what extent the eventual biases propagate from the driving (reanalysis, GCM) data.

Investigation of the relationship between climatological variables and circulation patterns expressed by various classifications of circulation types is a key procedure in synoptic climatology. This study provides new insights into circulation drivers of hydroclimate based on an analysis of precipitation and soil drought in multiple parts of the Czech Republic with respect to the subjective classification of the Czech Hydrometeorological Institute and objective classification based on the flow strength, flow direction, and vorticity during the 1961–2020 period. Circulation types are investigated in regard to their contributions to the total precipitation, mean daily precipitation totals, and precipitation probability. Types with a westerly airflow and a trough over Central Europe exhibit the highest proportions in precipitation totals. Types with a cyclone over Central Europe, especially combined with a northwestern or northeastern airflow, result in the highest daily mean totals and precipitation probability. Types with a southwestern airflow transport more precipitation to western parts of the Czech Republic, while those with a northeastern airflow transport more precipitation to the eastern parts, with a slight seasonal shift in the gradient axis between winter and summer. Circulation drivers of drought episodes are investigated based on soil-drought values calculated from the SoilClim model. Increased frequencies of north-eastern anticyclonic types, and decreased frequencies of directional and cyclonic are important for the origin and course of soil-drought episodes. In addition, the suitability of both classifications for long-term trends analysis is investigated.

The study deals with links between drought and atmospheric circulation in different parts of Europe (Western Europe, Central Europe, Eastern Europe, Northern Europe, and Southern Europe) during 1950–2019. The links are evaluated using drought characteristics (based on a difference between potential evapotranspiration and precipitation) calculated from gridded EOBS data and atmospheric circulation types that were classified using daily sea level pressure patterns obtained from the NCEP-NCAR reanalysis. Circulation types supporting drought in warm half-year are identified, and we analyse changes in their occurrence in the period after 1950, seasonal changes, and the connection with drought trends in individual European regions.

Climate change-induced rise in global temperatures is linked to changes in hot extremes. The recent summer of 2021 was marked by extremely high temperatures over the Mediterranean, which together with numerous wildfires considerably affected human society and natural environment. Using daily maximum temperatures from the ERA-5 reanalysis, we aim to assess the severity of heat waves in 2021 in the context of past major European heat waves (since 1950) through analysing their length, spatial extent, intensity, and overall magnitude. We show that the summer of 2021 was record-breaking in terms of total duration of heat waves and their magnitude was comparable to those in 2003 and 2010. The past two decades (2002–2021) almost completely redraw the spatial pattern of the occurrence of the historically most severe heat wave in European regions. Before 2002, heat waves of 1955, 1972, and 1994 were the most severe in many parts of Europe. Considering the whole 1950–2021 period, however, those heat waves remain as historically the most severe only over a small portion of their original area, and the map is dominated by the 2003, 2010, 2018, and 2021 events. This documents a rapid change in heat wave characteristics in Europe over the last two decades.

Many studies in Europe have investigated the relationship between climatological variables and circulation patterns expressed by various classifications of circulation types. This study provides new insights based on an analysis of precipitation in the western (Bohemia—BOH) and eastern (Moravia and Silesia—M&S) parts of the Czech Republic with respect to the subjective classification of the Czech Hydrometeorological Institute and objective classification based on the flow strength, flow direction, and vorticity during the 1961–2020 period. Circulation types are investigated in regard to their contributions to the total precipitation, mean daily precipitation totals, and precipitation probability (daily totals ≥ 1.0 mm). Types with a westerly airflow and a trough over Central Europe exhibit the highest proportions in precipitation totals. Types with a cyclone over Central Europe, especially combined with a northwestern (BOH) or northeastern (M&S) airflow, result in the highest daily mean totals and precipitation probability. Types with a southwestern airflow transport more precipitation to BOH, while those with a northeastern airflow transport more precipitation to M&S, with a slight seasonal shift in the gradient axis between winter and summer. Circulation types under both classifications are examined from the perspective of their precipitation representation in BOH and M&S and the differences between these two regions. In addition, the suitability of both classifications for precipitation analysis is investigated.

Regional Climate Models (RCMs) are powerful tools to study changes in the climate system on the regional scale. However, the reliability of their simulations has been considerably limited by the longstanding issue that climate models often fail to reproduce various aspects of the historical climate. In our study, we analyse how RCMs from the EURO-CORDEX project are able to reproduce extreme winter weather. We analyse temporal and spatial characteristics of extreme wind gust, extremely cold temperature, and extreme precipitation. Model outputs are validated against observed data from the European gridded observational database (EOBS) and the novel ERA5 reanalysis. We focus on the Central European domain (defined between 48–52°N and 10–19°E) over the 1979 – 2017 period. We investigate a set of 9 simulations of 3 different RCMs driven by 3 different global climate models which allow us to analyse the influence of driving data on the RCM’s performance. Since local climate elements are relatively tightly linked to a large-scale atmospheric circulation over Europe in winter, we also evaluate the ability of RCMs to reproduce the atmospheric circulation and its links to selected high-impact winter weather in detail. We use the classification of circulation based on the method of Sammon mapping. Investigation of these links can lead to better physical understanding of the climate and to the identification of inadequacies in simulated characteristics of the studied events. All of this is an important step forward in further improving the models and enhancing the credibility of climate change scenarios based on climate model simulations.

Compound events of weather extremes considerably affect various sectors of human society and natural environment and therefore it is essential to understand projected changes of their characteristics in the future climate. We focus on the combination of low temperature and high wind velocity, because their compound effect strongly influences human thermal comfort in cold weather, as characterized by the wind chill factor. In our study, we analyse frequency of this extreme events and projected changes of their characteristics in simulations of RCMs from the EURO-CORDEX project. We investigate a set of 9 simulations of 3 different RCMs driven by 3 different global climate models which allow us to analyse the influence of driving data on the RCM’s outputs. We focus on the Central European domain defined between 48–52°N and 10–19°E. The frequency of the compound events from historical simulations over 1970-2100 are compared to the projected frequencies under the RCP4.5 and RCP8.5 emission scenarios for the end of the 21st century (2070-2100). Since local climate is relatively tightly linked to a large-scale atmospheric circulation over Europe in winter, we also evaluate links of the compound events to the atmospheric circulation.

Among the variables that can be employed to characterize agricultural drought, soil drought is of particular importance. This contribution uses gridded soil-drought values calculated from the SoilClim model for the 1961-2019 period to analyse soil drought episodes (based on the 10th percentile) in four lowlands, relatively homogeneous regions in central Europe that provide a longitudinal transect over central Europe. These areas are predominantly located at altitudes of below 400 m asl and include central Bohemia, southern Moravia and an adjacent part of Slovakia, southern Slovakia and eastern Slovakia. The results indicate that, after 1990, such episodes occurred largely in the summer half-year (April-September), accompanied by an increasing linear trend in the 1961-2019 period, while the situation was reversed in the winter half-year (October-March). Selected drought episodes are further divided into three phases (Phase I - origin, Phase II - course, Phase III - end) and investigated separately in terms of precipitation and objective classification of circulation types based on flow strength, direction and vorticity. Decreases in the frequency of precipitation-rich cyclonic and the directional types associated with higher daily precipitation totals, together with increases in precipitation-poor anticyclonic types, were responsible for soil-drought Phases I and II, with the opposite pertaining to Phase III. Differences in the effects of circulation types on precipitation and soil-drought occurrence were considerable, particularly for central Bohemia compared with the other three regions. The results obtained are also discussed with respect to data uncertainty and their broader spatiotemporal context.

We assessed future changes in spring frost risk for the Aare river catchment that comprises the Swiss Plateau, the most important agricultural region of Switzerland. An ensemble of 15 bias-corrected regional climate model (RCM) simulations from the EXAR data set forced by the RCP 4.5 and RCP 8.5 concentration pathways were analysed for two future periods. Correlating actual meteorological observations and Swiss phenological spring index, we proposed and tested an RCM-compatible methodology (based on temperature data only) for estimating a start of spring and severity of frost events. In the historical climate, a significant advancement in start of spring was observed and frost events were more frequent in those years in which spring started sooner. In 2021&ndash, 2050, spring is projected to start eight (twelve) days earlier, considering the RCP 4.5 (8.5) scenario. Substantial changes were simulated for the 2070&ndash, 2099 period under RCP 8.5, when the total severity of frost events was projected to be increased by a factor of 2.1 compared to the historical climate. The study revealed the possible future increase of vegetation exposure to spring frost in Switzerland and that this phenomenon is noticeable even in the near future under the &lsquo, low concentration&rsquo, RCP 4.5 scenario.

Regional Climate Models (RCMs) are powerful tools to study changes in the climate system on the regional scale. However, the reliability of their simulations has been considerably limited by the longstanding issue that climate models often fail to reproduce various aspects of the historical climate. In our study, we analyse how RCMs from the EURO-CORDEX project are able to reproduce high-impact winter weather. We analyse temporal and spatial characteristics of snowfalls, wind gust, extreme temperatures, late spring frosts, total precipitation, and winter storms. Model outputs are validated against observed data from the gridded European database (EOBS) and the novel ERA5 reanalysis. We focus on the Central European domain (defined roughly between 48–52°N and 10–20°E) over the 1979 – 2017 period. We investigate a set of 12 simulations of 4 different RCMs driven by 3 different global climate models which allow us to analyse the influence of driving data on the RCM’s performance. Since local climate elements are relatively tightly linked to a large-scale atmospheric circulation over Europe in winter, we also evaluate the ability of RCMs to reproduce the atmospheric circulation and its links to selected high-impact winter weather in detail. Investigation of these links can lead to better physical understanding of the climate and to the identification of inadequacies in simulated characteristics of the studied events. All of this is an important step forward in further improving the models and enhancing the credibility of climate change scenarios based on climate model simulations.

Europe experienced several major heat waves in the recent summers, substantially affecting human society and environment. Heat waves are generally related to joint effect of perturbed atmospheric circulation and anomalies in surface energy budget, and they are often linked to hydrological preconditioning. Contributions of these driving mechanisms, however, vary across European climatic zones. Climate models struggle to simulate the spatial differences properly, ultimately leading to large uncertainties in future heat waves’ characteristics. As the first step towards identifying spatial patterns of differences between driving mechanisms of temperature extremes, a pan-European database of observed major heat waves has been created. Heat waves are studied using the E-OBS 20.0e dataset in 0.1° horizontal grid spacing, which is analogous to that used in the ERA5 reanalysis and CORDEX regional climate models. Magnitude of heat waves is defined with respect to local daily maximum temperature (Tmax) variance, using multiples of standard deviation of Tmax summed across individual events. For each heat wave, circulation conditions and surface energy fluxes are analysed using the ERA5 reanalysis, in order to study their links to the heat wave magnitude and geographical location. In the next step, these findings are used for analyzing spatial patterns of heat wave mechanisms and as a source of reference data for evaluation of relevant processes in climate models.

The study examines climate change scenarios of Central European heat waves with a focus on related uncertainties in a large ensemble of regional climate model (RCM) simulations from the EURO-CORDEX and ENSEMBLES projects. Historical runs (1970–1999) driven by global climate models (GCMs) are evaluated against the E-OBS gridded data set in the first step. Although the RCMs are found to reproduce the frequency of heat waves quite well, those RCMs with the coarser grid (25 and 50 km) considerably overestimate the frequency of severe heat waves. This deficiency is improved in higher-resolution (12.5 km) EURO-CORDEX RCMs. In the near future (2020–2049), heat waves are projected to be nearly twice as frequent in comparison to the modelled historical period, and the increase is even larger for severe heat waves. Uncertainty originates mainly from the selection of RCMs and GCMs because the increase is similar for all concentration scenarios. For the late twenty-first century (2070–2099), a substantial increase in heat wave frequencies is projected, the magnitude of which depends mainly upon concentration scenario. Three to four heat waves per summer are projected in this period (compared to less than one in the recent climate), and severe heat waves are likely to become a regular phenomenon. This increment is primarily driven by a positive shift of temperature distribution, but changes in its scale and enhanced temporal autocorrelation of temperature also contribute to the projected increase in heat wave frequencies.

The aim of this study was to evaluate temperature and sea-level pressure (SLP) fields and to analyse a related anomalous flow over midlatitudes simulated by the CNRM-CM5.1 global climate model (GCM). Simulated flow over midlatitudes of the Northern Hemisphere was assessed through flow indices, classified into 11 circulation types. Reference data were taken from the NOAA-CIRES 20th Century Reanalysis, version 2c. CNRM-CM5.1 exhibited analogous temperature biases to those reported for the mean of the CMIP5 GCMs’ ensemble. The most prominent features were an erroneous temperature dipole pattern in the Atlantic Ocean and a warm bias over regions of deep water upwelling (locally exceeding 5°C). The latter feature was associated with negative SLP biases in those regions. Too low pressure was found over midlatitudes of the Northern Hemisphere, and CNRM-CM5.1 simulated too frequent zonal flow in these latitudes. The usage of three ensemble members with different initial conditions did not improve model’s outputs because the bias is found to be considerably larger compared to the ensemble members’ spread. The study showed that temperature and SLP biases are connected in certain regions, suggesting that improvement of GCMs and development of bias correction methods should be carried out with a complex insight.

The European summer of 2013 was characterized by very high temperatures that established a new historical maximum in Austria. The extremity of this summer in Europe is assessed based on the E-OBS and ECA&D data sets. At the continental scale, it is ranked as the fifth warmest summer since 1951, with large positive temperature anomalies over Central Europe. According to seasonal heat wave characteristics, the 2013 summer was unprecedented in Kremsmuenster and Graz (both Austria) and ranked as the second or third at other stations with at least 100 years of measurements in the Czech Republic, Slovakia, Croatia and Slovenia. The most intense 2013 heat wave over Central Europe in early August was driven primarily by anticyclonic conditions and was probably amplified by the preceding precipitation deficit. In combination with major flooding in the Danube and Elbe river basins in early June and severe convective storms at the end of July, the hot 2013 summer in Central Europe may represent an analogue of a future summer climate that will probably be more prone to both temperature and precipitation extremes.

The study examines the capability of regional climate models (RCMs) to reproduce spatial and temporal characteristics of severe Central European heat waves. We analysed an ensemble of seven RCM simulations driven by the ERA-40 reanalysis over the 1961–2000 period, in comparison to observed data from the E-OBS gridded dataset. Heat waves were defined based on regionally significant excesses above the model-specific 95 % quantile of summer daily maximum air temperature distribution and their severity was described using the extremity index. The multi-model mean reflected the observed characteristics of heat waves quite well, but considerable differences were found among the individual RCMs. The RCMs had a tendency to simulate too many heat waves that were shorter but their temperature peak was more pronounced on average compared to E-OBS. Deficiencies were found also in reproducing interannual and interdecadal variability of heat waves. Using as an example the most severe Central European heat wave that occurred in 1994, we demonstrate that its magnitude was underestimated in all RCMs and that this bias was linked to overestimation of precipitation during and before the heat wave. By contrast, a simulated precipitation deficit during summer 1967 in the majority of RCMs contributed to an “erroneous” heat wave. This shows that land–atmosphere coupling is crucial for developing severe heat waves and its proper reproduction in climate models is essential for obtaining credible scenarios of future heat waves.

Heat waves (HWs) and cold spells (CSs) have pronounced impacts on the natural environment and society. The main aim of this study was to identify major Central European HWs and CSs since 1950 and assess their severity not only from the viewpoint of temperature and duration but also as to the affected area. The HWs and CSs were delimited from the E-OBS gridded data set. An extremity index was proposed that captures joint effects of spatial extent, temperature and duration of HWs and CSs. During the 1950–2012 period, we identified 18 major HWs and 24 major CSs over Central Europe. The most severe HW occurred in summer 1994, followed by the 2006 HW; both these events were far more extreme over Central Europe than HWs in the well-known 2003 and 2010 summers. The most severe CSs occurred in the winters of 1955/1956 and 1962/1963. The recent winter of 2011/2012 was found to be the sixth coldest since 1950/1951 according to the seasonal sum of the extremity index. The HWs and CSs were classified through a hierarchical cluster analysis of their characteristics (temperature amplitude, spatial extent of the core and duration) into four basic types. The established list of major Central European HWs and CSs might be utilized in further analyses. The extremity index may be applied over different areas to perform comparative studies and used also for evaluation of regional climate model simulations.

Heat waves are one of the main concerns related to the impacts of climate change, because their frequency and severity are projected to increase in a future climate. The objectives of this work are to study the long-term variability of heat waves over Argentina and to estimate recurrence probability of the most severe 2008 heat wave in Buenos Aires. We used three definitions of heat waves that were based on (1) daily maximum temperature above the 90th percentile (MaxTHW), (2) daily minimum temperature above the 90th percentile (MinTHW) and (3) both maximum and minimum temperatures above the corresponding 90th percentiles (EHW). The minimum length of a heat wave was 3 days, and the analysis was performed over the October–March period. Decadal values in Buenos Aires experienced clear increases in heat waves according to MinTHW and EHW, with the highest frequency for both in the 2001–2010 decade, but at other stations, combinations of different trends and decadal variability resulted in some cases in a decrease of extreme heat waves. In the north-western part of the country, a strong positive change in the last decade was found, mainly due to the increment in the persistence of MinTHW but also accompanied by increases in MaxTHW. In general, other stations show a clear positive trend in MinTHW and decadal variability in MaxTHW, with the largest EHW cases in the last decade. We also estimated recurrence probability of the longest and most severe heat wave in Buenos Aires (over 1909–2010, according to intensity measured by the cumulative excess of maximum daily temperature above the 90th percentile) that occurred from 3 to 14 November 2008, by means of simulations with a stochastic first-order autoregressive model. The recurrence probability of such long and severe heat wave is small in the present climate but it is likely to increase substantially in the near future even under a moderate warming trend. Fil: Rusticucci, Matilde Monica. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Kyselý, Jan. Academy of Sciences of the Czech Republic. Institute of Atmospheric Physics; República Checa. Academy of Sciences of the Czech Republic. Global Change Research Centre; República Checa Fil: Almeira, Gustavo. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina Fil: Lhotka, Ondřej. Academy of Sciences of the Czech Republic. Institute of Atmospheric Physics; República Checa. Academy of Sciences of the Czech Republic. Global Change Research Centre; República Checa. Charles University; República Checa