Archeological evidence for the impact of mega-Niño events on Amazonia during the past two millennia

Recent recognition of teleconnections between El Niño and climatic anomalies elsewhere on the planet identify northern lowland South America as a region experiencing drought. Extensive archeological survey along the major tributaries of the Amazon during the past 15 years has defined the temporal and spatial distributions of numerous ceramic phases and traditions. An unexpected result has been identification of discontinuities in most local sequences. Large numbers of carbon-14 dates establish their contemporaneity ca. 1500, 1000, 700, and 400 B.P. These dates correlate closely with archeological evidence on the north coast of Peru for destructive mega-Niño events. Observations of the impact of milder recent episodes on the flora and fauna imply catastrophic deterioration in local subsistence resources during prehistoric events, forcing the repeated human dispersals reflected in the linguistic and genetic heterogeneity of surviving indigenous lowland South American populations.     

Exploring the impacts of the tropical Pacific SST on the precipitation patterns over South America during ENSO periods

Summary Previous studies on precipitation over South America that strongly support the existence of links between precipitation and SST anomalies in the Pacific Ocean have identified specific regions where the ENSO signal is particularly stronger. Northeast of Brazil and some parts of southern South America are examples of these regions. However, the same attention was not taken to identify which regions in the Central and East Pacific ocean are better correlated with the South America precipitation during extreme ENSO events, and also which are the transition regions of the precipitation signal over South America during these events. Coincident periods of ENSO events for both SST over the tropical Pacific ocean and monthly precipitation sums from many observational stations over South America were selected and analyzed. Two statistical methods were used for the data analysis: Singular Value Decomposition (SVD) and Simple Linear Correlation (SLC). The SVD results for warmer events in the Pacific corroborate previous ones and also clearly identified a transition region between the drier conditions in the Northeast of Brazil and the wetter conditions in the Southeast/South of Brazil. Transition regions were also determined over Peru and central Amazon. The SLC results indicated that the SST anomalies in the tropical east Pacific ocean has the strongest influence in the South American precipitation during El Ni?o events. During La Ni?a events the central area of the Pacific, around 180°, has shown a more significant influence. Received August 10, 2000 Revised August 22, 2001     

Southern Oscillation simulation in the OSU coupled upper ocean-atmosphere GCM

The Southern Oscillation is a major component in the interannual variations of global climate. The Oregon State University global climate model, with a dynamically interactive upper ocean, reproduces in qualitatively correct fashion some of the major characteristics of the Southern Oscillation. This model simulates the observed anti-correlation of annually averaged sea-level pressure (SLP) between the eastern Pacific and the Indonesian region, the primary atmospheric signal of the Southern Oscillation. In the composite of the simulated warm events positive sea-surface temperature (SST) anomalies expand eastward towards South America from the tropical western Pacific during the first half of the calendar year. The SST anomalies develop in conjunction with eastward mixed layer current anomalies in the tropical Pacific. In the late summer and early fall anomalously warm water near South America develops and moves westward to merge with the central Pacific anomalies. This lagged development in the eastern Pacific is analogous to the evolution of the 1982/83 and 1986/87 El Ninos. The temperature of the thermocline layer also increases, with the slope of the equatorial Pacific thermocline decreasing in response to the relaxation of the surface forcing. Enhanced precipitation occurs in the mid-Pacific while in the Indian and Australian monsoon regions a deficit occurs. The peak of the warm phase occurs in late northern fall/early winter, somewhat earlier than during observed El Ninos. The cold phase of the Southern Oscillation, enhancement of the zonal circulation, evolves in a fashion similar to the warm phase with the signs of the anomalies reversed, similar to observations. Occurrence of Southern Oscillation in this coarse resolution GCM indicates that high resolution ocean waves do not play a crucial role in the generation of this phenomenon as suggested by Pacific basin models. These results also show that ocean-atmosphere global climate models are useful tools for investigation of time dependent changes on the interannual timescale in addition to their hitherto accepted use for studying equilibrium properties of climate.     

The Dynamics of ENSO Anomaly as Revealed in Ensemble Climate Simulations-Impact of Mean Stationary Wave

A series of climate ensemble experiments using the climate model from National Centers for Environmental Prediction (NCEP) were performed to exam impact of sea surface temperature (SST) on dynamics of El-Nino/South-crn Oscillation (ENSO).A specific question addressed in this paper is how important the mean stationary wave influences anomalous Rossby wave trains or teleconnection patterns as often observed during ENSO events.Evidences from those ensemble simulations argue that ENSO anomalies,especially over Pacific-North America (PNA) region,appear to be a result of modification for climatological mean stationary wave forced by persistent tropical SST anomalies Therefore,the role of SST forcing in maintaining climate basic state is emphasized.In this argument,the interaction between atmospheric internal dynamics and external forcing,such as SST is a key element to understand and ultimately predict ENSO.     

Influence of ENSO and the South Atlantic Ocean on climate predictability over Southeastern South America

We perform a systematic study of the predictability of surface air temperature and precipitation in Southeastern South America (SESA) using ensembles of AGCM simulations, focusing on the role of the South Atlantic and its interaction with the El Niño-Southern Oscillation (ENSO). It is found that the interannual predictability of climate over SESA is strongly tied to ENSO showing high predictability during the seasons and periods when there is ENSO influence. The most robust ENSO signal during the whole period of study (1949–2006) is during spring when warm events tend to increase the precipitation over Southeastern South America. Moreover, the predictability shows large inter-decadal changes: for the period 1949–1977, the surface temperature shows high predictability during late fall and early winter. On the other hand, for the period 1978–2006, the temperature shows (low) predictability only during winter, while the precipitation shows not only high predictability in spring but also in fall. Furthermore, it is found that the Atlantic does not directly affect the climate over SESA. However, the experiments where air–sea coupling is allowed in the south Atlantic suggest that this ocean can act as a moderator of the ENSO influence. During warm ENSO events the ocean off Brazil and Uruguay tends to warm up through changes in the atmospheric heat fluxes, altering the atmospheric anomalies and the predictability of climate over SESA. The main effect of the air–sea coupling is to strengthen the surface temperature anomalies over SESA; changes in precipitation are more subtle. We further found that the thermodynamic coupling can increase or decrease the predictability. For example, the air–sea coupling significantly increases the skill of the model in simulating the surface air temperature anomalies for most seasons during period 1949–1977, but tends to decrease the skill in late fall during period 1978–2006. This decrease in skill during late fall in 1978–2006 is found to be due to a wrong simulation of the remote ENSO signal that is further intensified by the local air–sea coupling in the south Atlantic. Thus, our results suggest that climate models used for seasonal prediction should simulate correctly not only the remote ENSO signal, but also the local air–sea thermodynamic coupling.     

Anomalies in temperature and rainfall during warm Arctic seasons as a guide to the formulation of climate scenarios

Recently much concern has been expressed regarding the impact of an increased atmospheric CO₂ concentration on climate. Unfortunately, present understanding and models of the climate system are not good enough for reliable prediction of such impacts. This paper presents an analysis of recent climate data in order to illustrate the nature of regional temperature and rainfall changes in different seasons and to provide some guidance with regard to points which might be borne in mind when scenarios of future climate (especially those taking into account human impacts) are being formulated.Since it is believed that an increased atmospheric CO₂ concentration will cause a warming and models and data suggest that the Arctic is more sensitive to climatic change than other latitudes, anomalies associated with warm Arctic seasons have been studied.The regional temperature, precipitation and pressure anomalies in the northern hemisphere for the 10 warmest Arctic winters and 10 warmest Arctic summers during the last 70 years have been investigated. Even when the Arctic area is warm, there are circulation changes such that large coherent anomalies occur elsewhere, with some regions warming and some cooling. The 10 warmest Arctic winters were characterised by larger amplitude anomalies, in the Arctic and elsewhere, than the 10 warmest summers, illustrating the difference in response between seasons. The precipitation differences for the 10 warmest Arctic winters and summers show for North America large coherent areas of increase or decrease, which again differ according to season. However, in winter the differences are not statistically significant, while the differences in two areas are significant in summer.     

Observed (1970–1999) climate variability in Central America using a high-resolution meteorological dataset with implication to climate change studies

High spatial resolution of precipitation (P) and average air temperature (Tavg) datasets are ideal for determining the spatial patterns associated with large-scale atmospheric and oceanic indexes, and climate change and variability studies, however such datasets are not usually available. Those datasets are particularly important for Central America because they allow the conception of climate variability and climate change studies in a region of high climatic heterogeneity and at the same time aid the decisionmaking process at the local scale (municipalities and districts). Tavg data from stations and complementary gridded datasets at 50 km resolution were used to generate a high-resolution (5 km grid) dataset for Central America from 1970 to 1999. A highresolution P dataset was used along with the new Tavg dataset to study climate variability and a climate change application. Consistently with other studies, it was found that the 1970-1999 trends in P are generally non-significant, with the exception of a few small locations. In the case of Tavg, there were significant warming trends in most of Central America, and cooling trends in Honduras and northern Panama. When the sea surface temperature anomalies between the Tropical Pacific and the Tropical Atlantic have different (same) sign, they are a good indicator of the sign of P (Tavg) annual anomalies. Even with non-significant trends in precipitation, the significant warming trends in Tavg in most of Central America can have severe consequences in the hydrology and water availability of the region, as the warming would bring increases in evapotranspiration, drier soils and higher aridity.     

Climatic Change, Wars and Dynastic Cycles in China Over the Last Millennium

In recent years, the phenomenon of global warming and its implications for the future of the human race have been intensively studied. In contrast, few quantitative studies have been attempted on the notable effects of past climatic changes upon human societies. This study explored the relationship between climatic change and war in China by comparing high-resolution paleo-climatic reconstructions with known war incidences in China in the last millennium. War frequencies showed a cyclic pattern that closely followed the global paleo-temperature changes. Strong and significant correlations were found between climatic change, war occurrence, harvest level, population size and dynastic transition. During cold phases, China suffered more often from frequent wars, population decline and dynastic changes. The quantitative analyses suggested that the reduction of thermal energy input during a cold phase would lower the land carrying capacity in the traditional agrarian society, and the population size, with significant accretions accrued in the previous warm phase, could not be sustained by the shrinking resource base. The stressed human-nature relationship generated a ‘push force’, leading to more frequent wars between states, regions and tribes, which could lead to the collapse of dynasties and collapses of human population size. War frequencies varied according to geographical locations (North, Central and South China) due to spatial variations in the physical environment and hence differential response to climatic change. Moreover, war occurrences demonstrated an obvious time lag after an episode of temperature fall, and the three geographical regions experienced different length of time lags. This research also shows that human population increases and collapses were correlated with the climatic phases and the social instabilities that were induced by climate changes during the last millennium. The findings proposed a new interpretation of human-nature relationship in the past, with implications for the impacts of anomalous global warming on future human conflicts.     

The 1877–1878 El Niño episode: associated impacts in South America

At times when attention on climate issues is strongly focused on the assessment of potential impacts of future climate change due to the intensification of the planetary greenhouse effect, it is perhaps pertinent to look back and explore the consequences of past climate variability. In this article we examine a large disruption in global climate that occurred during 1877–1878, when human influence was negligible. The mechanisms explaining this global disturbance are not well established, but there is considerable evidence that the major El Niño episode that started by the end of 1876 and peaked during the 1877–1878 boreal winter contributed significantly to it. The associated regional climate anomalies were extremely destructive, particularly in the Northern Hemisphere, where starvation due to intense droughts in Asia, South-East Asia and Africa took the lives of more than 20 million people. In South America regional precipitation anomalies were typical of El Niño events, with rainfall deficit and droughts in the northern portion of the continent as well as in northeast Brazil and the highlands of the central Andes (Altiplano). In contrast, anomalously intense rainfall and flooding episodes were reported for the coastal areas of southern Ecuador and Northern Perú, as well as along the extratropical West coast of the continent (central Chile, 30° S–40° S), and in the Paraná basin in the southeast region. By far the most devastating impacts in terms of suffering and loss of life occurred in the semiarid region of northeast Brazil where several hundreds of thousands of people died from starvation and diseases during the drought that started in 1877.     

Numerical simulations of anomalies of precipitation and surface air temperature in china in the summer of 1997

1.IntroductionStatisticalstudiesdemonstratedthatinEINinoyearstheprecipitationinsummerintheChangjiangRiverandHuaiheRiverBasinsisprobablyabovethenormalwhileitispossiblybelowthenormalinthenorthernChinaandtheHetao(theGreatBendoftheHuangheRiver)region.ThetemperatureinsummerisusuallylowerthannormalinEastAsia,especiallyinNortheastChina.Therewere6yearswithseverelowtemperaturesince1951,andtheyare1954,1957,1964,1972,1976and1983,whichareallrelatedtotheEINinoyears(seeHuangetal.,1989,1992;Xiangand…     

An essay on the impact of climate change on US agriculture: weather fluctuations, climatic shifts, and adaptation strategies

The impact of climate change on US agriculture has been debated for more than two decades, but the estimates ranged from no damage at the lower end to 80 % losses of grain yields at the higher end. This essay aims to help understand such divergent predictions by clarifying the concepts of weather and climate. First, the widely-read panel fixed effects models capture only the impacts of weather fluctuations but not of climate normals. Random weather fluctuations and climatic shifts are two different meteorological events and they have distinct implications on farming decisions. The former is perceived as random while the latter is perceived as non-random by the farmers. Using the historical corn yield data in the US, I explain the differences between the impact of random weather and that of climate change. Second, adaptation strategies to climatic changes and increased climate risks cannot be accounted for by the panel fixed effects models. Using the farm household data collected in sub-Saharan Africa and Latin America, I discuss quantitative significance of modeling adaptation strategies in the estimates of climate damage. Distinction between random weather fluctuations and climatic shifts is critical in modeling farming decisions, as they are fundamental to climate science, but is poorly understood by the impact researchers.     

The Medieval Warm Period, the Little Ice Age and simulated climatic variability

The CSIRO Mark 2 coupled global climatic model has been used to generate a 10,000-year simulation for ‘present’ climatic conditions. The model output has been analysed to identify sustained climatic fluctuations, such as those attributed to the Medieval Warm Period (MWP) and the Little Ice Age (LIA). Since no external forcing was permitted during the model run all such fluctuations are attributed to naturally occurring climatic variability associated with the nonlinear processes inherent in the climatic system. Comparison of simulated climatic time series for different geographical locations highlighted the lack of synchronicity between these series. The model was found to be able to simulate climatic extremes for selected observations for century timescales, as well as identifying the associated spatial characteristics. Other examples of time series simulated by the model for the USA and eastern Russia had similar characteristics to those attributed to the MWP and the LIA, but smaller amplitudes, and clearly defined spatial patterns. A search for the frequency of occurrence of specified surface temperature anomalies, defined via duration and mean value, revealed that these were primarily confined to polar regions and northern latitudes of Europe, Asia and North America. Over the majority of the oceans and southern hemisphere such climatic fluctuations could not be sustained, for reasons explained in the paper. Similarly, sustained sea–ice anomalies were mainly confined to the northern hemisphere. An examination of mechanisms associated with the sustained climatic fluctuations failed to identify a role for the North Atlantic Oscillation, the El Niño-Southern Oscillation or the Pacific Decadal Oscillation. It was therefore concluded that these fluctuations were generated by stochastic processes intrinsic to the nonlinear climatic system. While a number of characteristics of the MWP and the LIA could have been partially caused by natural processes within the climatic system, the inability of the model to reproduce the observed hemispheric mean temperature anomalies associated with these events indicates that external forcing must have been involved. Essentially the unforced climatic system is unable to sustain the generation of long-term climatic anomalies.     

Archival explorations of climate variability and social vulnerability in colonial Mexico

In this paper, unpublished archival documentary sources are used to explore the vulnerability to–and implications of–climatic variability and extreme weather events in colonial Mexico. Attention focuses on three regions covering a variety of environmental, social, economic, and political contexts and histories and located at key points along a north-south rainfall gradient: Chihuahua in the arid north, Oaxaca in the wetter south and Guanajuato located in the central Mexican highlands. A number of themes are considered. First, the significance of successive, prolonged, or combined climate events as triggers of agrarian crisis. Second, a case study demonstrating the national and regional impacts of a particularly devastating climate induced famine, culminating with the so-called ‘Year of Hunger’ between 1785 and 1786, is presented. The way in which social networks and community engagement were rallied as a means of fortifying social resilience to this and other crises will be highlighted. Third, the impacts of selected historical flood events are explored in order to highlight how the degree of impact of a flood was a function of public expectation, preparedness and also the particular socio-economic and environmental context in which the event took place. An overview of the spatial and temporal variations in vulnerability and resilience to climatic variability and extreme weather events in colonial Mexico is then provided, considering those recorded events that could potentially relate to broader scale, possibly global, climate changes.     

The winter of 1827–1828 over eastern North America: a season of extraordinary climatic anomalies, societal impacts, and false spring

This study reconstructed the weather and its impacts on society for the winter of 1827–1828, focusing on the eastern United States. Data comprise of daily and monthly instrumental records, diaries with both daily and seasonal resolution, newspapers, fur trapper accounts, and tree-rings. Temperature anomalies were calculated and mapped based on the means during the 1820–1840 period to account for different fixed observation times. Precipitation frequencies provided direct comparisons of the 1827–1828 weather with modern climatic normals. Daily plots of temperature also reveal weather variations at daily timeframes. Results indicate that the eastern United States experienced strong positive temperature anomalies that are among the most extreme known in the historical record, particularly its large spatial extent. In contrast, historical evidence reveals strong negative temperature anomalies over northwestern North America, and positive temperature anomalies are evident for coastal Alaska. These temperature anomaly patterns sharply contrast to what is normally experienced during a warm El Niño event. Furthermore, results clearly describe remarkable climatic impacts in the Southeast U.S., including widespread blossoming of fruit trees in mid-winter (false spring) that led to a widespread severe killing frost in early April of 1828. Widespread positive precipitation frequency anomalies are also evident for much of the Southeast U.S., which also played a prominent role on winter vegetation growth. Other weather events and impacts include unusual opening of river traffic in winter in New England, severe flooding in the Mississippi River Valley, and heavy snowfall in northwestern North America.     

Modification of the southern African rainfall variability/ENSO relationship since the late 1960s

Analysis of 149 raingauge series (1946–1988) shows a weak positive correlation between late summer rainfalls (January–March) in tropical southern Africa and the Southern Oscillation Index (SOI). The correlation coefficients have been unstable since World War II. They were close to zero before 1970 and significant thereafter. Before 1970, southern African late summer rainfalls were more specifically correlated with regional patterns of sea surface temperature (SST), mainly over the southwestern Indian Ocean. After 1970, teleconnections with near global SST anomaly patterns, i.e. over the central Pacific and Indian oceans, dominate the regional connections. The increase in the sensitivity of the southern African rainfall to the global SO-related circulation anomalies is simultaneous with the correlation between SOI and more extensive SST anomalies, particularly over the southern Indian Ocean. This feature is part of longer term (decadal), global SST variability, as inferred from statistical analyses. Numerical experiments, using the Météo-France general circulation model ARPEGE-Climat, are performed to test the impact of the observed SST warming in the southern Indian and extratropical oceans during El Niño Southern Oscillation (ENSO) events on southern African rainfall. Simulated results show that ENSO events, which occurred in the relatively cold background of the pre-1970 period in the southern oceans, had a little effect on southern Africa climatic conditions and atmospheric circulation. By contrast, more recent ENSO events, with warmer SST over the southern oceans, lead to a climatic bipolar pattern between continental southern African and the western Indian Ocean, which is characterized by reduced (enhanced) deep convection and rainfall over the subcontinent (the western Indian Ocean). A weaker subtropical high-pressure belt in the southwestern Indian Ocean is also simulated, along with a reduced penetration of the moist southern Indian Ocean trade winds over the southern African plateau. These results are consistent with the strong droughts observed over all southern Africa during ENSO events since 1970.     

2011年海洋和大气环流异常及对中国气候的影响

本文基于实时和历史观测资料,利用气候统计和气候机理诊断方法,对2011年气候异常及成因进行总结分析。结果表明,全球海洋外源强迫和大气内部动力过程共同作用下的大气环流系统组合异常,是造成2011年中国大部地区降水异常偏少,温度明显偏高,呈现暖干型气候特征的主要原因。具体表现为,拉尼娜事件在2011年夏季短暂中断后,9月再次进入拉尼娜状态;西太平洋副热带高压在5月之前异常偏弱、偏东,致使长江中下游出现严重春旱,之后副热带高压有所加强,尤其在6月异常偏强,使长江中下游地区梅雨量偏多、旱涝急转;秋季副热带高压脊线偏北、中高纬度冷空气活动阶段性活跃,致使华西、黄淮地区秋雨异常偏多;热带印度洋海温演变经历负偶极型海温模态后,夏季转为全区一致型暖海温;2010／2011年东亚冬季风偏强,2011年南海夏季风爆发偏早、结束偏晚,东亚夏季风正常偏弱;西北太平洋和南海热带气旋生成数量处于偏少的年代际时段,2011年热带气旋生成数量偏少。     

夏季副高次季节尺度东西变动特征及其与中国西南降水的关系

西北太平洋副热带高压（以下简称副高）是影响中国气候的大尺度环流系统,研究次季节尺度副高东西变动对西南地区降水的影响具有十分重要的意义。本文首先根据副高东西变动的关键区位置分别定义了前夏和后夏副高东西变动指数,指数具有显著的10～30天次季节周期,能够很好表征副高次季节东西变动的特征。根据指数的标准化值,共选取前夏和后夏东西事件195次（1374天）。进一步对东西事件的分析表明次季节尺度上副高东西变动与西南地区降水有十分密切的联系,在副高偏西（东）事件中,副高经历了由东→西→东（西→东→西）逐渐变化的过程,相应西南大部分地区的降水经历了逐渐由少→多→少（多→少→多）的演变,次季节尺度上西南地区降水对副高变化的响应与副高东西变动过程中副高北侧及副高主体区域的水汽和气流的垂直变化有很大的关系。另外,分析发现对于西南地区而言,受副高次季节东西变动的影响,贵州和重庆地区降水变化的一致性比较好,而云南和四川地区降水变化的区域差异较大,尤其是云南。前夏,在副高东西变动过程中云南大部分地区的降水呈现出与西南大部分地区,尤其与贵州和重庆地区的降水变化完全相反的特征,即副高偏西（东）事件中,云南大部分地区的降水偏少（多）,西南其它大部地区降水偏多（少）;后夏,除云南中北部地区,西南大部分地区的降水变化基本一致。     

Climate Change and Cryptosporidiosis: A Qualitative Analysis

The effects of climate change on drinking-waterborne cryptosporidiosis transmission in the United States are analyzed using an influence diagram representation of epidemic development. Results from a systematic qualitative analysis indicate that climate change will have little effect on cryptosporidiosis incidence if the United States continues to be wealthy and maintains its commitment to public health. The major impact will, instead, be the additional costs of adapting to new climate regimes in order to avoid drinking-waterborne disease risk. These costs, for the most part, will be from improved monitoring and treatment of drinking water. The consequences of disaster scenarios are also considered. These, too, suggest that climate change per se will be a poor predictor of waterborne cryptosporidiosis in countries with high standards of living. Rather, the risk of epidemics will depend on the interplay between population, public health investment, infrastructure maintenance, emergency planning/response capabilities, water-treatment technologies, drinking-water regulations, and climate.     

Global characteristics of extreme winters from a multi-millennial simulation

Output from a multi-millennial simulation with the CSIRO Mark 2 coupled global climatic model has been analysed to determine the principal characteristics of extreme winters over the globe for ??present conditions??. Thus, this study is not concerned with possible changes in winter conditions associated with anthropogenically induced climatic change. Defining an extreme winter as having a surface temperature anomaly of below ?2 standard deviations (sd) revealed a general occurrence rate over the globe of between 100 and 200 over a 6,000-year period of the simulation, with somewhat higher values over northwest North America. For temperature anomalies below ?3?sd the corresponding occurrence rate drops to about 10. Spatial correlation studies revealed that extreme winters over regions in Europe, North America or Asia were very limited geographically, with time series of the surface temperature anomalies for these regions having mutual correlation coefficients of about 0.2. The temporal occurrence rates of winters (summers) having sd below ?3 (above +3) were very asymmetric and sporadic, suggesting that such events arise from stochastic influences. Multi-year sequences of extreme winters were comparatively rare events. Detailed analysis revealed that the temporal and spatial evolution of the monthly surface temperature anomalies associated with an individual extreme winter were well replicated in the simulation, as were daily time series of such anomalies. Apart from an influence of the North Atlantic Oscillation on extreme winters in Europe, other prominent climatic oscillations were very poorly correlated with such winters. Rather modest winter temperature anomalies were found in the southern hemisphere.     

Heatwaves in Europe: areas of homogeneous variability and links with the regional to large-scale atmospheric and SSTs anomalies

This work presents a methodology to study the interannual variability associated with summertime months in which extremely hot temperatures are frequent. Daily time series of maximum and minimum temperature fields (T _max and T _min, respectively) are used to define indexes of extreme months based on the number of days crossing thresholds. An empirical orthogonal function (EOF) analysis is applied to the monthly indexes. EOF loadings give information about the geographical areas where the number of days per month with extreme temperatures has the largest variability. Correlations between the EOF principal components and the time series of other fields allow plotting maps highlighting the anomalies in the large scale circulation and in the SSTs that are associated with the occurrence of extreme events. The methodology is used to construct the “climatology” of the extremely hot summertime months over Europe. In terms of both interannual and intraseasonal variability, there are three regions in which the frequency of the extremely hot days per month homogeneously varies: north-west Europe, Euro-Mediterranean and Eurasia region. Although extremes over those regions occur during the whole summer (June to August), the anomalous climatic conditions associated with frequent heatwaves present some intraseasonal variability. Extreme climate events over the north-west Europe and Eurasia are typically related to the occurrence of blocking situations. The intraseasonal variability of those patterns is related to the amplitude of the blocking, the relative location of the action centre and the wavetrain of anomalies downstream or upstream of the blocking. During June and July, blocking situations which give extremely hot climate conditions over north-west Europe are also associated with cold conditions over the eastern Mediterranean sector. The Euro-Mediterranean region is a transition area in which extratropical and tropical systems compete, influencing the occurrence of climate events: blockings tend to be related to extremely hot months during June while baroclinic anomalies dominate the variability of the climate events in July and August. We highlight that our method could be easily applied to other regions of the world, to other fields as well as to model outputs to assess, e.g. the potential change of extreme climate events in a warmer climate.