Decadal Changes in Dry and Wet Heatwaves in Eastern China:Spatial Patterns and Risk Assessment

Under global warming,understanding the long-term variation in different types of heatwaves is vital for China’s preparedness against escalating heat stress.This study investigates dry and wet heatwave shifts in eastern China over recent decades.Spatial trend analysis displays pronounced warming in inland midlatitudes and the Yangtze River Valley,with increased humidity in coastal regions.EOF results indicate intensifying dry heatwaves in northern China,while the Yangtze River Valley sees more frequent dry heatwaves.On the other hand,Indochina and regions north of 25°N also experience intensified wet heatwaves,corresponding to regional humidity increases.Composite analysis is conducted based on different situations:strong,frequent dry or wet heatwaves.Strong dry heatwaves are influenced by anticyclonic circulations over northern China,accompanied by warming SST anomalies around the coastal midlatitudes of the western North Pacific(WNP).Frequent dry heatwaves are related to strong subsidence along with a strengthened subtropical high over the WNP.Strong and frequent wet heatwaves show an intensified Okhotsk high at higher latitudes in the lower troposphere,and a negative circumglobal teleconnection wave train pattern in the upper troposphere.Decaying El Niño SST patterns are observed in two kinds of wet heatwave and frequent dry heatwave years.Risk analysis indicates that El Niño events heighten the likelihood of these heatwaves in regions most at risk.As global warming continues,adapting and implementing mitigation strategies toward extreme heatwaves becomes crucial,especially for the aforementioned regions under significant heat stress.

Electricity Generation from Heatwaves

We chose a definition of heatwaves (HWs) that has ~4-year recurrence frequency at world hot spots. We first examined the 1940-2022 HWs climatology and trends in lifespan, severity, spatial extent, and recurrence frequency. HWs are becoming more frequent and more severe for extratropical mid- and low-latitudes. To euphemize HWs, we here propose a novel clean energy-tapping concept that utilizes the available nano-technology, micro-meteorology knowledge of temperature distribution within/without buildings, and radiative properties of earth atmosphere. The key points for a practical electricity generation scheme from HWs are defogging, insulation, and minimizing the absorption of infrared downward radiation at the cold legs of the thermoelectric generators. One sample realization is presented which, through relay with existing photovoltaic devices, provides all-day electricity supply sufficient for providing air conditioning requirement for a residence (~2000-watt throughput). The provision of power to air conditioning systems, usually imposes a significant stress on traditional city power grids during heatwaves.

The 2022 Extreme Heatwave in Shanghai,Lower Reaches of the Yangtze River Valley:Combined Influences of Multiscale Variabilities

In the summer of 2022,China(especially the Yangtze River Valley,YRV)suffered its strongest heatwave(HW)event since 1961.In this study,we examined the influences of multiscale variabilities on the 2022 extreme HW in the lower reaches of the YRV,focusing on the city of Shanghai.We found that about 1/3 of the 2022 HW days in Shanghai can be attributed to the long-term warming trend of global warming.During mid-summer of 2022,an enhanced western Pacific subtropical high(WPSH)and anomalous double blockings over the Ural Mountains and Sea of Okhotsk,respectively,were associated with the persistently anomalous high pressure over the YRV,leading to the extreme HW.The Pacific Decadal Oscillation played a major role in the anomalous blocking pattern associated with the HW at the decadal time scale.Also,the positive phase of the Atlantic Multidecadal Oscillation may have contributed to regulating the formation of the double-blocking pattern.Anomalous warming of both the warm pool of the western Pacific and tropical North Atlantic at the interannual time scale may also have favored the persistency of the double blocking and the anomalously strong WPSH.At the subseasonal time scale,the anomalously frequent phases 2-5 of the canonical northward propagating variability of boreal summer intraseasonal oscillation associated with the anomalous propagation of a weak Madden-Julian Oscillation suppressed the convection over the YRV and also contributed to the HW.Therefore,the 2022 extreme HW originated from multiscale forcing including both the climate warming trend and air-sea interaction at multiple time scales.

The Forecast Skills and Predictability Sources of Marine Heatwaves in the NUIST-CFS1.0 Hindcasts

Using monthly observations and ensemble hindcasts of the Nanjing University of Information Science and Technology Climate Forecast System(NUIST-CFS1.0) for the period 1983–2020, this study investigates the forecast skill of marine heatwaves(MHWs) over the globe and the predictability sources of the MHWs over the tropical oceans. The MHW forecasts are demonstrated to be skillful on seasonal-annual time scales, particularly in tropical oceans. The forecast skill of the MHWs over the tropical Pacific Ocean(TPO) remains high at lead times of 1–24 months, indicating a forecast better than random chance for up to two years. The forecast skill is subject to the spring predictability barrier of El Nino-Southern Oscillation(ENSO). The forecast skills for the MHWs over the tropical Indian Ocean(TIO), tropical Atlantic Ocean(TAO), and tropical Northwest Pacific(NWP) are lower than that in the TPO. A reliable forecast at lead times of up to two years is shown over the TIO, while a shorter reliable forecast window(less than 17 months) occurs for the TAO and NWP.Additionally, the forecast skills for the TIO, TAO, and NWP are seasonally dependent. Higher skills for the TIO and TAO appear in boreal spring, while a greater skill for the NWP emerges in late summer-early autumn. Further analyses suggest that ENSO serves as a critical source of predictability for MHWs over the TIO and TAO in spring and MHWs over the NWP in summer.

Evaluation and projection of marine heatwaves in the South China Sea: insights from CMIP6 multi-model ensemble

This study evaluates the performance of 16 models sourced from the coupled model intercomparison project phase 6(CMIP6)in simulating marine heatwaves(MHWs)in the South China Sea(SCS)during the historical period(1982−2014),and also investigates future changes in SCS MHWs based on simulations from three shared socioeconomic pathway(SSP)scenarios(SSP126,SSP245,and SSP585)using CMIP6 models.Results demonstrate that the CMIP6 models perform well in simulating the spatial-temporal distribution and intensity of SCS MHWs,with their multi-model ensemble(MME)results showing the best performance.The reasonable agreement between the observations and CMIP6 MME reveals that the increasing trends of SCS MHWs are attributed to the warming sea surface temperature trend.Under various SSP scenarios,the year 2040 emerges as pivotal juncture for future shifts in SCS MHWs,marked by distinct variations in changing rate and amplitudes.This is characterized by an accelerated decrease in MHWs frequency and a notably heightened increase in mean intensity,duration,and total days after 2040.Furthermore,the projection results for SCS MHWs suggest that the spatial pattern of MHWs remains consistent across future periods.However,the intensity shows higher consistency only during the near-term period(2021−2050),while notable inconsistencies are observed during the medium-term(2041−2070)and long-term(2071−2100)periods under the three SSP scenarios.During the nearterm period,the SCS MHWs are characterized by moderate and strong events with high frequencies and relatively shorter durations.In contrast,during the medium-term period,MHWs are also characterized by moderate and strong events,but with longer-lasting and more intense events under the SSP245 and SSP585 scenarios.However,in the long-term period,extreme MHWs become the dominant feature under the SSP585 scenario,indicating a substantial intensification of SCS MHWs,effectively establishing a near-permanent state.

Long-term ocean temperature trend and marine heatwaves

Marine heatwaves(MHWs)can cause irreversible damage to marine ecosystems and livelihoods.Appropriate MHW characterization remains difficult,because the choice of a sea surface temperature(SST)temporal baseline strongly influences MHW identification.Following a recent work suggesting that there should be a communicating baseline for long-term ocean temperature trends(LTT)and MHWs,we provided an effective and quantitative solution to calculate LTT and MHWs simultaneously by using the ensemble empirical mode decomposition(EEMD)method.The long-term nonlinear trend of SST obtained by EEMD shows superiority over the traditional linear trend in that the data extension does not alter prior results.The MHWs identified from the detrended SST data exhibited low sensitivity to the baseline choice,demonstrating the robustness of our method.We also derived the total heat exposure(THE)by combining LTT and MHWs.The THE was sensitive to the fixed-period baseline choice,with a response to increasing SST that depended on the onset time of a perpetual MHW state(identified MHW days equal to the year length).Subtropical areas,the Indian Ocean,and part of the Southern Ocean were most sensitive to the long-term global warming trend.

Linkage Between European and East Asian Heatwaves on Synoptic Scales

Concurrent extreme weather events in geographically distant areas potentially cause high-end risks for societies.By using network analysis,the present study managed to identify significant nearly-simultaneous occurrences of heatwaves between the grid cells in East Asia and Eastern Europe,even though they are geographically far away from each other.By further composite analysis,this study revealed that hot events first occurred in Eastern Europe,typically with a time lag of3-4 days before the East Asian heatwave events.An eastward propagating atmospheric wave train,known as the circumglobal teleconnection(CGT)pattern,bridged the sequent occurrences of extreme events in these two remote regions.Atmospheric blockings,amplified by surface warming over Eastern Europe,not only enhanced local heat extremes but also excited a CGT-like pattern characterized by alternative anomalies of high and low pressures.Subsequent downstream anticyclones in the middle and upper troposphere reduced local cloud cover and increased downward solar radiation,thereby facilitating the formation of heatwaves over East Asia.Nearly half of East Asian heatwave events were preceded by Eastern European heatwave events in the 10-day time range before East Asian heatwave events.This investigation of heatwave teleconnection in the two distant regions exhibits strong potential to improve the prediction accuracy of East Asian heatwaves.

Unprecedented Heatwave in Western North America during Late June of 2021: Roles of Atmospheric Circulation and Global Warming

An extraordinary and unprecedented heatwave swept across western North America(i.e.,the Pacific Northwest)in late June of 2021,resulting in hundreds of deaths,a massive die-off of sea creatures off the coast,and horrific wildfires.Here,we use observational data to find the atmospheric circulation variabilities of the North Pacific and Arctic-Pacific-Canada patterns that co-occurred with the development and mature phases of the heatwave,as well as the North America pattern,which coincided with the decaying and eastward movement of the heatwave.Climate models from the Coupled Model Intercomparison Project(Phase 6)are not designed to simulate a particular heatwave event like this one.Still,models show that greenhouse gases are the main reason for the long-term increase of average daily maximum temperature in western North America in the past and future.

Geographical Patterns and Temporal Variations of Regional Dry and Wet Heatwave Events in China during 1960–2008

Daily maximum/minimum temperatures and relative humidity records from 510 stations in China for the period 1960–2008 were used to investigate geographical patterns and temporal variations of heatwave （HW） events. Dry and wet HW events were compared by different definitions. Regionally, both dry and wet HW events are commonly located in southeastern China in the monsoon area, with neither type occurring in the northeast part of Northeast China and Southwest China, while the north-northwest region of the country experiences dry HW events and a few wet HW events. In the southeast of the country, site dry HW events occurred from April to September and mostly in June, while site wet HW events occurred from April to October and mostly in September. In total, 163 regional wet HW events were identified. The ten longest regional wet HW events lasted for more than 20 days, while the mean duration for 163 events was about 11 days. For the top ten events, six occurred after the 1990s, compared with four before this time. Global surface warming was clear since 1979, but the frequency and severity of regional wet HW events were relatively low in the 1980s, increasing remarkably since the 1990s. Possible reasons for this might be the strong interdecadal and interannual variations in regional atmospheric circulations, as well as water transport related directly to temperature contrasts in different regions, rather than global-mean temperature changes.

Sources of Subseasonal Prediction Skill for Heatwaves over the Yangtze River Basin Revealed from Three S2S Models

Based on the reforecast data(1999–2010)of three operational models[the China Meteorological Administration(CMA),the National Centers for Environmental Prediction of the U.S.(NCEP)and the European Centre for Medium-Range Weather Forecasts(ECMWF)]that participated in the Subseasonal to Seasonal Prediction(S2S)project,we identified the major sources of subseasonal prediction skill for heatwaves over the Yangtze River basin(YRB).The three models show limited prediction skills in terms of the fraction of correct predictions for heatwave days in summer;the Heidke Skill Score drops quickly after a 5-day forecast lead and falls down close to zero beyond the lead time of 15 days.The superior skill of the ECMWF model in predicting the intensity and duration of the YRB heatwave is attributable to its fidelity in capturing the phase evolution and amplitude of high-pressure anomalies associated with the intraseasonal oscillation and the dryness of soil moisture induced by less precipitation via the land–atmosphere coupling.The effects of 10–30-day and 30–90-day circulation prediction skills on heatwave predictions are comparable at shorter forecast leads(10 days),while the biases in 30–90-day circulation amplitude prediction show close connection with the degradation of heatwave prediction skill at longer forecast leads(>15–20 days).The biases of intraseasonal circulation anomalies further affect precipitation anomalies and thus land conditions,causing difficulty in capturing extremely hot days and their persistence in the S2S models.

Observed Frequent Occurrences of Marine Heatwaves in Most Ocean Regions during the Last Two Decades

Marine heatwaves(MHWs)are prolonged high-temperature extreme events in the ocean that can be devastating to marine life and seriously impact climate systems and economies.This paper describes the accessibility,content,characteristics,and potential applications of an MHW dataset to facilitate its use in scientific research.Daily intensities of global MHWs from 1982 to 2020 were analyzed using gridded SST data sourced from the National Oceanic and Atmospheric Administration(NOAA)Optimum Interpolation(OI)SST V2 high-resolution(0.25°)dataset.The analysis shows a linear increase in the frequency of MHWs in most ocean regions of the world as well as significant interdecadal changes.This data product can be used as a basic dataset to study the seasonal to decadal changes in extreme ocean events and explore the effects of global warming on the surface layers of oceans during the last 40 years.

Analysis of lower-boundary climate factors contributing to the summer heatwave frequency over eastern Europe using a machine-learning model

A machine-learning(ML)model,the light gradient boosting machine(LightGBM),was constructed to simulate the variation in the summer(June-July-August)heatwave frequency(HWF)over eastern Europe(HWFUR)and to analyze the contributions of various lower-boundary climate factors to the HWFUR variation.The examined lower-boundary climate factors were those that may contribute to the HWFUR variation—namely,the sea surface temperature,soil moisture,snow-cover extent,and sea-ice concentration from the simultaneous summer,preceding spring,and winter.These selected climate factors were significantly correlated to the summer HWFUR variation and were used to construct the ML model.Both the hindcast simulation of HWF EUR for the period 1981-2020 and its real-time simulation for the period 2011-2020,which used the constructed ML model,were investigated.To evaluate the contributions of the climate factors,various model experiments using different combinations of the climate factors were examined and compared.The results indicated that the LightGBM model had comparatively good performance in simulating the HWFUR variation.The sea surface temperature made more contributions to the ML model simulation than the other climate factors.Further examination showed that the best ML simulation was that which used the climate factors in the preceding winter,suggesting that the lower-boundary conditions in the preceding winter may be critical in forecasting the summer HWFUR variation.

Role of adaptation measures in addressing heatwave exposure in China

Heatwave exposure has increased dramatically because of climate warming and population growth,along with their interactive effects.However,effective adaptation measures can reduce these impacts.Nonetheless,the dynamic changes,regional inequality in adaptive capacity and their potential contributions to reducing exposure in the future remain unclear.This study quantifies the impact of adaptive capacity and underscores regional variations in heatwave magnitudes,population exposure and adaptation levels in China.We projected the future adaptive capacity using air-conditioner penetration,factoring in climate cooling requirements and individuals'purchasing power.Utilising population and gross domestic product(GDP)data from four Shared Socioeconomic Pathways(SSP1,SSP2,SSP3 and SSP5)and daily temperature data from four SSP-based emission scenarios(SSP1-2.6,SSP2-4.5,SSP3-7.0 and SSP5-8.5),we estimated heatwave duration,population exposure and avoided impacts through adaptation across China and its sub-regions.Results show a substantial increase in heatwave duration in Southwest and Southern China,especially under the SSP5-8.5 scenario,with a projection of 163.2±36.7 d during 2081-2100.Under the SSP3|SSP3-7.0 scenario,total exposure reaches 156.4±76.8 billion person d per year,which is the highest among all scenarios and 23 times greater than that in 1986-2005 without adaptation.Upon considering adaptation measures,a noteworthy reduction in population exposure is observed,especially in the SSP3|SSP3-7.0 and SSP5JSSP5-8.5 scenarios,with reductions of(62.6±3.9)%and(65.8±5.1)%,respectively,compared with the scenario without adaptation during 2081-2100.Remarkable regional disparities in avoided impacts are also evident,with variations of up to 50%across different regions.The implementation of effective and environmentally friendly adaptation measures can notably address climate change,thereby alleviating the profound threats posed to human well-being.

Effects of the urban landscape on heatwave-mortality associations in Hong Kong: comparison of different heatwave definitions

Despite increased attention given to potential modifiers of temperature-mortality associations, evidence for variations between different urban landscape characteristics remains limited. It is in this context that in this paper effect modifications of multiple urban landscape characteristics are explored under different heatwave definitions for different age groups and gender in Hong Kong, China. Daily meteorological data and heatwave-related mortality counts from 2008 to 2017 were collected from the Hong Kong Census and Statistics Department, China. A case-only design was adopted, combined with logistic regression models to examine the modification effects of five urban landscape characteristics under six heatwave definitions. Stratified analyses were conducted to investigate age- and gender-specific effect modifications. It is found that individuals living in greener areas experienced lower levels of mortality during or immediately after heatwaves. In contrast, a higher building density and nighttime land surface temperature (LST) were associated with a higher heatwave-related mortality risk. Pronounced effect modifications of these urban landscape characteristics were observed under hotter and longer heatwaves, and in older adults (age ≥ 65 years) and males. The findings provide a scientific basis for policymakers and practitioners when considering measures for coping with hotter, longer, and more frequent heatwaves in the context of global climate change.

Coping with the concurrent heatwaves and ozone extremes in China under a warming climate

Intensive human activity has brought about unprecedented climate and environmental crises, in which concurrent heatwaves and ozone extremes pose the most serious threats. However, a limited understanding of the comprehensive mechanism hinders our ability to mitigate such compound events, especially in densely populated regions like China. Here, based on field observations and climate-chemistry coupled modelling, we elucidate the linkage between human activities and the climate system in heatrelated ozone pollution. In China, we have observed that both the frequency and intensity of heatwaves have almost tripled since the beginning of this century. Moreover, these heatwaves are becoming more common in urban clusters with serious ozone pollution. Persistent heatwaves during the extremely hot and dry summers of 2013 and 2022 accelerated photochemical ozone production by boosting anthropogenic and biogenic emissions, and aggravated ozone accumulation by suppressing dry deposition due to water-stressed vegetation, leading to a more than 30% increase in ozone pollution in China's urban areas. The sensitivity of ozone to heat is demonstrated to be substantially modulated by anthropogenic emissions, and China's clean air policy may have altered the relationship between ozone and temperature. Climate model projections further highlight that the high-emission climate-socioeconomic scenario tends to intensify the concurrent heat and ozone extremes in the next century. Our results underscore that the implementation of a strict emission strategy will significantly reduce the co-occurrence of heatwaves and ozone extremes, achieving climate and environmental co-benefits.

Factor analysis of recent major heatwaves in East Asia

Heatwaves(HWs)present a major hazard to our society and more extreme heatwaves are expected with future climatic changes.Hence,it is important to improve our understanding of the underlying processes that drive HWs,in order to boost our socioeconomic-ecological resilience.In this study,we quantified the influences of key driving factors(large-scale atmospheric circulation,soil moisture,and sea surface temperature)and their synergies on recent heatwaves in East Asia.We conducted a factor separation analysis for three recent HW events by constraining the key factors in the regional Weather Research and Forecasting model with their climatologies or pseudo-observations in different combinations.Our study showed distinct spatial variations in the HW-controlling factors in East Asia.The synergistic interaction of large-scale circulation and soil moisture was the most important factors in the 2013 Chinese HW.During the 2018 HWs in Korea and Japan,the same stagnant large-scale atmospheric circulation played a dominant role in driving the HW events.The land-atmosphere coupling via soil moisture,its interaction with circulation,and SST exhibited stronger influences during the Korean HW than the Japanese HW.Our analysis also revealed temporal variations in the factors driving Korean and Chinese HWs due to typhoon passage and other multiple processes over heterogeneous surfaces(i.e.,topographically induced Foehn winds,large-scale warm advection from the warm ocean,spatial differences in soil moisture).Our findings suggest that future heatwave-related studies should consider interactive contributions of key factors,their interplay with surface heterogeneities of complex terrain.

Will the 2022 compound heatwaveedrought extreme over the Yangtze River Basin become Grey Rhino in the future?

The increasingly frequent and severe regional-scale compound heatwave-drought extreme events(CHDEs),driven by global warming,present formidable challenges to ecosystems,residential livelihoods,and economic conditions.However,uncertainty persists regarding the future trend of CHDEs and their insights into regional spatiotemporal heterogeneity.By integrating daily meteorological data from observations in 1961-2022 and global climate models(GCMs)based on the Shared Socioeconomic Pathways,the evolution patterns of CHDEs were compared and examined among three sub-catchments of the Yangtze River Basin,and the return periods of CHDE in 2050s and 210Os were projected.The findings indicate that the climate during the 2022 CHDE period was the warmest and driest recorded in 1961-2022,with precipitation less than 154.5 mm and a mean daily maximum temperature 3.4°C higher than the average of 1981-2010,whereas the char-acteristics in the sub-catchments exhibited temporal and spatial variation.In July-August 2022,the most notable feature of CHDE was its extremeness since 1961,with return periods of~200-year in upstream,80-year in midstream,and 40-year in downstream,respectively.By 2050,the return periods witnessed 2022 CHDE would likely be reduced by one-third.Looking towards 2100,under the highest emission scenario of SSP585,it was projected to substantially increase the frequency of CHDEs,with return periods reduced to one-third in the upstream and downstream,as well as halved in the midstream.These findings provide valuable insights into the changing risks associated with forthcoming climate extremes,emphasizing the urgency of addressing these challenges in regional management and sustainable development.

Compound events of heatwave and dust storm in the Taklamakan Desert

Taklamakan Desert(TD)has been characterized by numerous heatwaves and dust storms,leading to negative effects on societies and ecosystems at regional and global scales.However,the association between heatwaves and dust storms is poorly known.In this study,we describe the association between heatwaves and dust events and propose a mechanism for such compound events in the TD.The results show that,from 1993 to 2022,the frequency and intensity of heatwaves in the TD have increased at a rate of 0.21 days year^(-1)and 0.02℃ year^(-1),respectively.More than 40% of heatwaves existed with dust events,which significantly lagged behind heatwaves.Mechanically,the higher the air temperature,the hotter and drier the soil,leading to more dust emissions in the TD.In high-occurrence heatwave years,a large-scale wave train of“cyclone-anticyclone-cyclone”in the northwest-southeast direction was found,with the anticyclone of which hovered over the TD region.The anomalous anticyclones favored the formation and maintenance of heatwaves,and subsequent anomalous cyclones in the wave train triggered strong dust events followed by heatwaves.With climate warming,the compound events of heatwave and dust storm are becoming bigger hazards threatening the socioeconomic and ecological security in the TD,the profound study of which is critical to understanding regional extreme responses.

Heatwave exacerbates air pollution in China through intertwined climate-energy-environment interactions

Climate change is increasing the frequency and intensity of heatwaves, raising concerns about their detrimental effects on air quality. However, a role for heatwave-human-environment interactions in air pollution exacerbation has not been established. In the summer of 2022, record-breaking heatwaves struck China and Europe. In this study, we use integrated observational data and machine learning to elucidate the formation mechanism underlying one of the most severe ozone pollution seasons on record in central eastern China, an area that encompasses approximately half of China's total population and sown land.Our findings reveal that the worsened ozone and nitrogen dioxide pollution resulted from a mismatch between energy demand and supply, which was driven by both heatwaves and energy policy-related factors. The observed adverse heatwave-energy-environment feedback loop highlights the need for the diversification of clean energy sources, more resilient energy structures and power policies, and further emission control to confront the escalating climate challenge in the future.

Physical mechanism of the rapid increase in intense and long-lived extreme heatwaves in the Northern Hemisphere since 1980

Since 1980,both the intensity and duration of summer heatwaves in the middle and high latitudes of the Northern Hemisphere have significantly increased,leading this region to become a critical area for a significant increase in the frequency of intense and long-lived extreme heatwaves.We found that stronger and more persistent high-pressure systems and lower soil moisture before the events were the main drivers of intense and long-lived extreme heatwaves in western Europe and the middle and high latitudes of North America.However,in eastern Europe and Siberia,lower cloud cover before events is also a main driver of this type of extreme heatwave,in addition to the above drivers.These factors are coupled with each other and can change heatwave intensity and duration by influencing surface radiation processes during events.Using the self-organizing map classification method,we found that 6 weather patterns with increased frequency,intensity,and duration were the main dynamic reasons leading to the increase in intense and long-lived extreme heatwaves after 1980.In addition,the decrease in summer average soil moisture in most areas of the mid-high latitudes of the Northern Hemisphere and the decrease in average cloud cover in eastern Europe and Siberia are found to be the main thermodynamic reasons leading to the increase in these extreme heatwaves.