Trends and uncertainties in surface air temperature over the Tibetan Plateau, 1951–2013

Trends and uncertainties of surface air temperature over the Tibetan Plateau (TP) are evaluated by using observations at 100 meteorological stations during the period 1951–2013. The sampling error variances of gridded monthly data are estimated for every month and every grid box of data. The gridded data and their sampling error variances are used to calculate TP averages, their trends, and associated uncertainties. It is shown that large sampling error variances dominate northern and western TP, while small variances appear over southern and eastern TP. Every month from January to December has a positive linear trend during the study period. February has the largest trend of 0.34 ± 0.18°C (10 yr)^–1, and April the smallest at 0.15 ± 0.11°C (10 yr)^–1. The uncertainties decrease steadily with time, implying that they are not large enough to alter the TP warming trend.     

Analysis of Sampling Error Uncertainties and Trends in Maximum and Minimum Temperatures in China简

In this paper we report an analysis of sampling error uncertainties in mean maximum and minimum temperatures （Tmax and Tmin） carried out on monthly,seasonal and annual scales,including an examination of homogenized and original data collected at 731 meteorological stations across China for the period 1951-2004.Uncertainties of the gridded data and national average,linear trends and their uncertainties,as well as the homogenization effect on uncertainties are assessed.It is shown that the sampling error variances of homogenized Tmax and Tmin,which are larger in winter than in summer,have a marked northwest-southeast gradient distribution,while the sampling error variances of the original data are found to be larger and irregular.Tmax and Tmin increase in all months of the year in the study period 1951-2004,with the largest warming and uncertainties being 0.400℃ （10 yr）-1 ＋ 0.269℃ （10 yr）-1 and 0.578℃ （10 yr）-1 ＋ 0.211℃ （10 yr）-1 in February,and the least being 0.022℃ （10 yr）-1 ＋ 0.085℃ （10 yr）-1 and 0.104℃ （10 yr）-1 ＋0.070℃ （10 yr）-1 in August.Homogenization can remove large uncertainties in the original records resulting from various non-natural changes in China.     

Future changes and uncertainties in temperature and precipitation over China based on CMIP5 models

Climate changes in future 21 st century China and their uncertainties are evaluated based on 22 climate models from the Coupled Model Intercomparison Project Phase 5(CMIP5). By 2081–2100, the annual mean surface air temperature(SAT) is predicted to increase by 1.3℃± 0.7℃, 2.6℃± 0.8℃ and 5.2℃± 1.2℃ under the Representative Concentration Pathway(RCP) scenarios RCP2.6, RCP4.5 and RCP8.5, relative to 1986–2005, respectively. The future change in SAT averaged over China increases the most in autumn/winter and the least in spring, while the uncertainty shows little seasonal variation.Spatially, the annual and seasonal mean SAT both show a homogeneous warming pattern across China, with a warming rate increasing from southeastern China to the Tibetan Plateau and northern China, invariant with time and emissions scenario.The associated uncertainty in SAT decreases from northern to southern China. Meanwhile, by 2081–2100, the annual mean precipitation increases by 5% ± 5%, 8% ± 6% and 12% ± 8% under RCP2.6, RCP4.5 and RCP8.5, respectively. The national average precipitation anomaly percentage, largest in spring and smallest in winter, and its uncertainty, largest in winter and smallest in autumn, show visible seasonal variations. Although at a low confidence level, a homogeneous wetting pattern is projected across China on the annual mean scale, with a larger increasing percentage in northern China and a weak drying in southern China in the early 21 st century. The associated uncertainty is also generally larger in northern China and smaller in southwestern China. In addition, both SAT and precipitation usually show larger seasonal variability on the sub-regional scale compared with the national average.     

Assessment of surface air warming in northeast China, with emphasis on the impacts of urbanization

Based on homogenized land surface air temperature (SAT) data (derived from China Homogenized Historical Temperature (CHHT) 1.0), the warming trends over Northeast China are detected in this paper, and the impacts of urban heat islands (UHIs) evaluated. Results show that this region is undergoing rapid warming: the trends of annual mean minimum temperature (MMIT), mean temperature (MT), and mean maximum temperature (MMAT) are 0.40 C decade^?1, 0.32 C decade^?1, and 0.23 C decade^?1, respectively. Regional average temperature series built with these networks including and excluding “typical urban stations” are compared for the periods of 1954–2005. Although impacts of UHIs on the absolute annual and seasonal temperature are identified, UHI contributions to the long-term trends are less than 10% of the regional total warming during the period. The large warming trend during the period is due to a regime shift in around 1988, which accounted for about 51% of the regional warming.     

Recent Progress in Studies of Climate Change in China

An overview of basic research on climate change in recent years in China is presented. In the past 100 years in China, average annual mean surface air temperature (SAT) has increased at a rate ranging from 0.03℃ (10 yr)-1 to 0.12℃ (10 yr)-1 . This warming is more evident in northern China and is more significant in winter and spring. In the past 50 years in China, at least 27% of the average annual warming has been caused by urbanization. Overall, no significant trends have been detected in annual and/or summer precipitation in China on a whole for the past 100 years or 50 years. Both increases and decreases in frequencies of major extreme climate events have been observed for the past 50 years. The frequencies of extreme temperature events have generally displayed a consistent pattern of change across the country, while the frequencies of extreme precipitation events have shown only regionally and seasonally significant trends. The frequency of tropical cyclone landfall decreased slightly, but the frequency of sand/dust storms decreased significantly. Proxy records indicate that the annual mean SAT in the past a few decades is the highest in the past 400-500 years in China, but it may not have exceeded the highest level of the Medieval Warm Period (1000-1300 AD). Proxy records also indicate that droughts and floods in eastern China have been characterized by continuously abnormal rainfall periods, with the frequencies of extreme droughts and floods in the 20th century most likely being near the average levels of the past 2000 years. The attribution studies suggest that increasing greenhouse gas (GHG) concentrations in the atmosphere are likely to be a main factor for the observed surface warming nationwide. The Yangtze River and Huaihe River basins underwent a cooling trend in summer over the past 50 years, which might have been caused by increased aerosol concentrations and cloud cover. However, natural climate variability might have been a main driver for the mean and extreme precipitation variations observed over the past century. Climate models generally perform well in simulating the variations of annual mean SAT in China. They have also been used to project future changes in SAT under varied GHG emission scenarios. Large uncertainties have remained in these model-based projections, however, especially for the projected trends of regional precipitation and extreme climate events.     

The Role of Changes in the Annual Cycle in Earlier Onset of Climatic Spring in Northern China

Climatic changes in the onset of spring in northern China associated with changes in the annual cycle and with a recent warming trend were quantified using a recently developed adaptive data analysis tool, the Ensemble Empirical Mode Decomposition. The study was based on a homogenized daily surface air temperature (SAT) dataset for the period 1955–2003. The annual cycle here is referred to as a refined modulated annual cycle (MAC). The results show that spring at Beijing has arrived significantly earlier by about 2.98 d (10 yr)-1, of which about 1.85 d (10 yr)-1 is due to changes in the annual cycle and 1.13 d (10 yr)-1 due to the long-term warming trend. Variations in the MAC component explain about 92.5% of the total variance in the Beijing daily SAT series and could cause as much as a 20-day shift in the onset of spring from one year to another. The onset of spring has been advancing all over northern China, but more significant in the east than in the west part of the region. These differences are somehow unexplainable by the zonal pattern of the warming trend over the whole region, but can be explained by opposite changes in the spring phase of the MAC, i.e. advancing in the east while delaying in the west. In the east of northern China, the change in the spring phase of MAC explains 40%–60% of the spring onset trend and is attributable to a weakening Asian winter monsoon. The average sea level pressure in Siberia (55°–80°N, 50°–110°E), an index of the strength of the winter monsoon, could serve as a potential short-term predictor for the onset of spring in the east of northern China.     

Stratospheric radiative feedback limited by the tropospheric influence in global warming

Whether the stratospheric radiative feedback amplifies the global warming remains under debate. The stratospheric water vapor (SWV), one of the primary feedbacks in the stratosphere, is argued to be an important contributor to the global warming. On the other hand, the overall stratospheric feedback, which consists of both the SWV feedback and the stratospheric temperature (ST) feedback, does not amount to a significant value. The key to reconciling these seemingly contradictory arguments is to understand the ST change. Here, we develop a method to decompose the ST change and to quantify the decomposed feedbacks. We find that the SWV feedback, which consists of a 0.04 W m⁻² K⁻¹ direct impact on the top-of-the-atmosphere radiation and 0.11 W m⁻² K⁻¹ indirect impact via ST cooling, is offset by a negative ST feedback of − 0.13 W m⁻² K⁻¹ that is radiatively driven by the tropospheric warming. This compensation results in an insignificant overall stratospheric feedback.

     

Urban heat island effect on annual mean temperature during the last 50 years in China

Summary Based on Chinas fifth population survey (2000) data and homogenized annual mean surface air temperature data, the urban heat island (UHI) effect on the warming during the last 50 years in China was analyzed in this study. In most cities with population over 10⁴, where there are national reference stations and principal stations, most of the temperature series are inevitably affected by the UHI effect. To detect the UHI effect, the annual mean surface air temperature (SAT) time series were firstly classified into 5 subregions by using Rotated Principal Components Analysis (RPCA) according to its high and low frequency climatic change features. Then the average UHI effect on each subregions regional annual mean STA was studied. Results indicate that the UHI effect on the annual mean temperatures includes three aspects: increase of the average values, decrease of variances and change of the climatic trends. The effect on the climatic trends is different from region to region. In the Yangtze River Valley and South China, the UHI effect enhances the warming trends by about 0.011°C/decade. In the other areas, such as Northeast, North-China, and Northwest, UHI has little impact on the warming trends of the regional annual temperature; while in the Southwest of China, introducing UHI stations slows down the warming trend by –0.006°C/decade. But no matter what subregion it is, the total warming/cooling of these effects is much smaller than the background change in regional temperature. The average UHI effect for the entire country, during the last 50 years is less than 0.06°C, which agrees well with the IPCC (2001). This suggests that we cannot conclude that urbanization during the last 50 years has had much obvious effect on the observed warming in China.     

A Kriging-based Estimate of the Survey Quality in Biomonitoring of Trace Element Air Pollution

The present paper addresses Kriging-based approaches to estimate survey quality, thereby using data on biomonitoring surveys of trace element air pollution. Data were used of a 1995 moss monitoring study in The Netherlands, thereby taking sodium (Na), arsenic (As) and bromium (Br) to illustrate the points made. Survey quality was expressed as the survey signal-to-noise ratio (SSNR), with the survey variance as the signal and the local variance as the noise. The Kriging approaches were regarded in parallel to direct approaches where local variances are determined from multi-fold local sampling.The paper addresses the uncertainties in SSNR associated to the uncertainties in local values and variances if based on pooled samples and a limited 5-fold sub-sampling in a restricted number of sampling sites. It further introduces a Kriging approach to SSNR_K (_K for Kriging), by Kriging-assisted recalculation of local values and variances, in turn based on fitted experimental variograms. The outcomes suggest that the Kriging approach may yield reliable SSNR_K values; the approach implies that SSNR_K depends on survey set-up, site density and sampling grid characteristics. The discussion of the paper addresses the points made and further suggests the use of large sample analytical facilities to permit a change in survey approach from mixing and milling of pooled sub-samples to bulk analyses of all sampled material in higher site-density surveys.     

Probabilistic climate change projections using neural networks

Anticipated future warming of the climate system increases the need for accurate climate projections. A central problem are the large uncertainties associated with these model projections, and that uncertainty estimates are often based on expert judgment rather than objective quantitative methods. Further, important climate model parameters are still given as poorly constrained ranges that are partly inconsistent with the observed warming during the industrial period. Here we present a neural network based climate model substitute that increases the efficiency of large climate model ensembles by at least an order of magnitude. Using the observed surface warming over the industrial period and estimates of global ocean heat uptake as constraints for the ensemble, this method estimates ranges for climate sensitivity and radiative forcing that are consistent with observations. In particular, negative values for the uncertain indirect aerosol forcing exceeding –1.2 Wm^–2 can be excluded with high confidence. A parameterization to account for the uncertainty in the future carbon cycle is introduced, derived separately from a carbon cycle model. This allows us to quantify the effect of the feedback between oceanic and terrestrial carbon uptake and global warming on global temperature projections. Finally, probability density functions for the surface warming until year 2100 for two illustrative emission scenarios are calculated, taking into account uncertainties in the carbon cycle, radiative forcing, climate sensitivity, model parameters and the observed temperature records. We find that warming exceeds the surface warming range projected by IPCC for almost half of the ensemble members. Projection uncertainties are only consistent with IPCC if a model-derived upper limit of about 5 K is assumed for climate sensitivity.     

Evaluation of Surface Air Temperature Change over China and the Globe during the Twentieth Century in IAP AGCM4.0

Based on time series and linear trend analysis, the authors evaluated the performance of the fourth generation atmospheric general circulation model developed at the Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP AGCM4.0), in simulating surface air temperature (SAT) during the twentieth century over China and the globe. The numerical experiment is conducted by driving the model with the observed sea surface temperature and sea ice. It is shown that IAP AGCM4.0 can simulate the warming trend of the global SAT, with the major warming regions in the high latitudes of the Northern Hemisphere and the mid-latitudes of the Southern Hemisphere. While the simulated trend over the whole globe is close to the observation, the model under-estimates the observed trend over the continents. More-over, the model simulates the spatial distribution of SAT in China, with a bias of approximately-2°C in eastern China, but with a more serious bias in western China. Compared with the global mean, however, the correlation coefficient between the simulation and observation in China is significantly lower, indicating that there is large uncertainty in simulating regional climate change.     

Projected Changes in Surface Air Temperature and Surface Wind in the Gulf of St. Lawrence

Abstract

The impacts of climate change on surface air temperature (SAT) and winds in the Gulf of St. Lawrence (GSL) are investigated by performing simulations from 1970 to 2099 with the Canadian Regional Climate Model (CRCM), driven by a five-member ensemble. Three members are from Canadian Global Climate Model (CGCM3) simulations following scenario A1B from the Intergovernmental Panel on Climate Change (IPCC); one member is from the Community Climate System Model, version 3 (CCSM3) simulation, also following the A1B scenario; and one member is from the CCSM4 (version 4) simulation following the Representative Concentration Pathway (RCP8.5) scenario. Compared with North America Regional Reanalysis (NARR) data, it is shown that CRCM can reproduce the observed SAT spatial patterns; for example, both CRCM simulations and NARR data show a warm SAT tongue along the eastern Gulf; CRCM simulations also capture the dominant northwesterly winds in January and the southwesterly winds in July. In terms of future climate scenarios, the spatial patterns of SAT show plausible seasonal variations. In January, the warming is 3°–3.5°C in the northern Gulf and 2.5°–3°C near Cabot Strait during 2040–2069, whereas the warming is more uniform during 2070–2099, with SAT increases of 4°–5°C. In summer, the warming gradually decreases from the western side of the GSL to the eastern side because of the different heat capacities between land and water. Moreover, the January winds increase by 0.2–0.4?m?s^?1 during 2040–2069, related to weakening stability in the atmospheric planetary boundary layer. However, during 2070–2099, the winds decrease by 0.2–0.4?m?s^?1 over the western Gulf, reflecting the northeastward shift in northwest Atlantic storm tracks. In July, enhanced baroclinicity along the east coast of North America dominates the wind changes, with increases of 0.2–0.4?m?s^?1. On average, the variance for the SAT changes is about 10% of the SAT increase, and the variance for projected wind changes is the same magnitude as the projected changes, suggesting uncertainty in the latter.     

近100年中国地表平均气温变化的误差分析

误差问题是气候变化研究中必须考虑的一个重要因素,利用全国616个气象观测站的气温资料对近100年中国地表平均气温变化中的4类误差及其造成的不确定性范围进行了定量计算和综合分析。结果表明,20世纪60年代以前覆盖误差影响最大;70年代开始由于中国城市化进程的加快,城市化影响导致的偏差误差呈上升趋势。由此可见,从准确检测近100年中国区域气候变化信号的角度来看,减少覆盖误差是减小早期不确定性的关键,同时近年来城市化的影响也值得注意。综合来看,近100年来中国地表平均气温变化的误差及其所引起的不确定性随时间不断减小。比较分析表明,近100年中国地表平均气温变化不确定性的主要变化特征与全球基本一致,均为早期大、后期小。因此,无论是全球还是中国都应该注意由误差引起的不确定性影响,特别是在早期。     

A decadal shift of summer surface air temperature over Northeast Asia around the mid-1990s

This study identifies a decadal shift of summer surface air temperature （SAT） over Northeast Asia,including southeastern parts of Russia,Mongolia and northern China,around the mid-1990s.The results suggest that the SAT over the Northeast Asia experienced a significant warming after 1994 relative to that before 1993.This decadal shift also extends to northern China,and leads to a warmer summer over Northeast China and North China after the mid-1990s.The decadal warming over Northeast Asia is found to concur with the enhancement of South China rainfall around the mid-1990s.On the one hand,both the Northeast Asian SAT and South China rainfall exhibit this mid-1990s decadal shift only in summer,but not in other seasons.On the other hand,both the Northeast Asian SAT and South China rainfall exhibit this mid-1990s decadal shift not only in the summer seasonal mean,but also in each month of summer （June,July and August）.Furthermore,the decadal warming is found to result from an anticyclonic anomaly over Northeast Asia,which can be interpreted as the response to the increased precipitation over South China,according to previous numerical results.Thus,we conclude that the warming shift of summer Northeast Asian SAT around the mid-1990s was a remote response to the increased precipitation over South China.     

Summertime land–sea thermal contrast and atmospheric circulation over East Asia in a warming climate—Part II: Importance of CO2-induced continental warming

In this the second of a two-part study, we examine the physical mechanisms responsible for the increasing contrast of the land–sea surface air temperature (SAT) in summertime over the Far East, as observed in recent decades and revealed in future climate projections obtained from a series of transient warming and sensitivity experiments conducted under the umbrella of the Coupled Model Intercomparison Project phase 5. On a global perspective, a strengthening of land–sea SAT contrast in the transient warming simulations of coupled atmosphere–ocean general circulation models is attributed to an increase in sea surface temperature (SST). However, in boreal summer, the strengthened contrast over the Far East is reproduced only by increasing atmospheric CO₂ concentration. In response to SST increase alone, the tropospheric warming over the interior of the mid- to high-latitude continents including Eurasia are weaker than those over the surrounding oceans, leading to a weakening of the land–sea SAT contrast over the Far East. Thus, the increasing contrast and associated change in atmospheric circulation over East Asia is explained by CO₂-induced continental warming. The degree of strengthening of the land–sea SAT contrast varies in different transient warming scenarios, but is reproduced through a combination of the CO₂-induced positive and SST-induced negative contributions to the land–sea contrast. These results imply that changes of climate patterns over the land–ocean boundary regions are sensitive to future scenarios of CO₂ concentration pathways including extreme cases.     

近百年中国气候变暖趋势之再评估

基于均一化的气温观测序列集,1900年以来中国气温升高趋势1.3—1.7℃/（100 a）。这个已用于新近的中国国家气候变化评估报告的结果,远高于早期的评估结果（0.5—0.8℃/（100 a））。回顾了始于20世纪80年代的中国百年气温序列的研究,指出其中关键进展在于近年来研发了均一化的长期站点气温观测序列集。早年构建的中国气温序列中,20世纪40年代前异常偏高,除了战乱期间观测缺失严重及记录代表性问题外,主要是50年代前后很多台站迁址导致早期气温观测值系统性偏高所致,从而低估长期变暖趋势。40年代前后部分区域确实偏暖,但由于不同区域气温波动位相不一致,因而大范围平均序列中并不明显。这一事实可与近年发展的“北极暖-大陆冷”等气候变化动力学理论以及一些区域气温代用资料相印证。近几十年城市化对中国气温变化趋势之贡献大小尚存争议,但远非主导因素。      

气候变化趋势分析中自相关的检验与去除

受资料本身、分析方法及未来排放情景假设等因素影响, 气候变暖幅度尚存在较大的不确定性。从分析方法入手, 探讨气象观测序列可能存在的自相关及其对气候变化趋势分析的不确定性影响。引入了Durbin-Watson一阶自相关检验方法对气象观测序列进行检验, 并用Cochrane-Orcutt方法去除存在的自相关。分析发现:浙江省平湖市气温序列存在的自相关放大了该站气温的升温趋势, 并且虚高了气温变化趋势的显著性水平。因此, 对资料序列进行自相关检验与去除是十分必要的。     

气候变化的归因与预估模拟研究

本文总结了近五年来中国科学院大气物理研究所在气候变暖的归因模拟与预估研究上的主要进展。研究表明,利用海温、太阳辐射和温室气体等实际强迫因子驱动大气环流模式,能够较为合理地模拟全球平均地表气温在20世纪的演变,但是难以模拟出包括北大西洋涛动／北极涛动和南极涛动在内的高纬度环流的长期变化趋势。利用温室气体和硫酸盐气溶胶等“历史资料”驱动气候系统模式,能够较好地模拟出20世纪后期的全球增暖,但如果要再现20世纪前期(1940年代)的变暖,还需同时考虑太阳辐射等自然外强迫因子。20世纪中国气温演变的耦合模式模拟技巧,较之全球平均情况要低;中国气候在1920年代的变暖机理目前尚不清楚。对于近50年中国东部地区“南冷北暖”、“南涝北旱”的气候变化,基于大气环流模式特别是区域气候模式的数值试验表明,夏季硫酸盐气溶胶的负辐射效应超过了温室气体的增暖效应,从而对变冷产生贡献。但现有的数值模拟证据,不足以说明气溶胶增加对“南涝北旱”型降水异常有贡献。20世纪中期以来,青藏高原主体存在明显增温趋势,温室气体浓度的增加对这种增暖有显著贡献。多模式集合预估的未来气候变化表明,21世纪全球平均温度将继续增暖,增温幅度因不同排放情景而异;中国大陆年均表面气温的增暖与全球同步,但增幅在东北、西部和华中地区较大,冬季升温幅度高于夏季、日最低温度升幅要强于日最高温度;全球增暖有可能对我国中东部植被的地理分布产生影响。伴随温室气体增加所导致的夏季平均温度升高,极端温度事件增多;在更暖的气候背景下,中国大部分地区总降水将增多,极端降水强度加大且更频繁发生,极端降水占总降水的比例也将增大。全球增暖有可能令大洋热盐环流减弱,但是减弱的幅度因模式而异。全球增暖可能不是导致北太平洋副热带－热带经圈环流自20世纪70年代以来变弱的原因。文章同时指出了模式预估结果中存在的不确定性。     

Evaluation and projection of daily maximum and minimum temperatures over China using the high-resolution NEX-GDDP dataset

A new bias-corrected, statistically downscaled product, the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset, has been developed and released to help in understanding climate change at local to regional scales. Here, we evaluate the performance of the NEX-GDDP data in simulating daily maximum temperature (TX) and daily minimum temperature (TN) in the historical period 1961–2005 over China at national and regional scales. Projected future changes in TX and TN are assessed under the Representative Concentration Pathways (RCPs) 4.5 and 8.5 emissions scenarios. Results show that the NEX-GDDP data can capture the basic spatial patterns of TX and TN, but these results underestimate the warming trends of TX and TN from 1961 to 2005 over China. The largest biases are found in western China due to its complex terrain conditions; these biases are 2.33 and 2.21 times larger than those found in eastern China for TX and TN, respectively. The climate projections show that the difference in uncertainties is small between the east and the west, and higher warming changes correspond to greater uncertainties. The increasing trends under the RCP8.5 are 2.22 and 2.31 times the size found under the RCP4.5 by the end of the twenty-first century for TX and TN, respectively. The Tibetan plateau has the fastest warming trend under the two scenarios.

     

Drivers of the Severity of the Extreme Hot Summer of 2015 in Western China

Western China experienced an extreme hot summer in 2015, breaking a number of temperature records. The summer mean surface air temperature (SAT) anomaly was twice the interannual variability. The hottest daytime temperature (T_Xx) and warmest night-time temperature (T_Nx) were the highest in China since 1964. This extreme hot summer occurred in the context of steadily increasing temperatures in recent decades. We carried out a set of experiments to evaluate the extent to which the changes in sea surface temperature (SST)/sea ice extent (SIE) and anthropogenic forcing drove the severity of the extreme summer of 2015 in western China. Our results indicate that about 65%–72% of the observed changes in the seasonal mean SAT and the daily maximum (T_max) and daily minimum (T_min) temperatures over western China resulted from changes in boundary forcings, including the SST/SIE and anthropogenic forcing. For the relative role of individual forcing, the direct impact of changes in anthropogenic forcing explain about 42% of the SAT warming and 60% (40%) of the increase in T_Nx and Tmin (T_Xx and T_max) in the model response. The changes in SST/SIE contributed to the remaining surface warming and the increase in hot extremes, which are mainly the result of changes in the SST over the Pacific Ocean, where a super El Niño event occurred. Our study indicates a prominent role for the direct impact of anthropogenic forcing in the severity of the extreme hot summer in western China in 2015, although the changes in SST/SIE, as well as the internal variability of the atmosphere, also made a contribution.