Runoff change in the Yellow River Basin of China from 1960 to 2020 and its driving factors

Analysing runoff changes and how these are affected by climate change and human activities is deemed crucial to elucidate the ecological and hydrological response mechanisms of rivers.The Indicators of Hydrologic Alteration and the Range of Variability Approach(IHA-RVA)method,as well as the ecological indicator method,were employed to quantitatively assess the degree of hydrologic change and ecological response processes in the Yellow River Basin from 1960 to 2020.Using Budyko's water heat coupling balance theory,the relative contributions of various driving factors(such as precipitation,potential evapotranspiration,and underlying surface)to runoff changes in the Yellow River Basin were quantitatively evaluated.The results show that the annual average runoff and precipitation in the Yellow River Basin had a downwards trend,whereas the potential evapotranspiration exhibited an upwards trend from 1960 to 2020.In approximately 1985,it was reported that the hydrological regime of the main stream underwent an abrupt change.The degree of hydrological change was observed to gradually increase from upstream to downstream,with a range of 34.00%-54.00%,all of which are moderate changes.However,significant differences have been noted among different ecological indicators,with a fluctuation index of 90.00%at the outlet of downstream hydrological stations,reaching a high level of change.After the mutation,the biodiversity index of flow in the middle and lower reaches of the Yellow River was generally lower than that in the base period.The research results also indicate that the driving factor for runoff changes in the upper reach of the Yellow River Basin is mainly precipitation,with a contribution rate of 39.31%-54.70%.Moreover,the driving factor for runoff changes in the middle and lower reaches is mainly human activities,having a contribution rate of 63.70%-84.37%.These results can serve as a basis to strengthen the protection and restoration efforts in the Yellow River Basin and further promote the rational development and use of water resources in the Yellow River.

Not in Control,but Liable?Attributing Human Responsibility for Fully Automated Vehicle Accidents

Human agency has become increasingly limited in complex systems with increasingly automated decision-making capabilities.For instance,human occupants are passengers and do not have direct vehicle control in fully automated cars(i.e.,driverless cars).An interesting question is whether users are responsible for the accidents of these cars.Normative ethical and legal analyses frequently argue that individuals should not bear responsibility for harm beyond their control.Here,we consider human judgment of responsibility for accidents involving fully automated cars through three studies with seven experiments(N=2668).We compared the responsibility attributed to the occupants in three conditions:an owner in his private fully automated car,a passenger in a driverless robotaxi,and a passenger in a conventional taxi,where none of these three occupants have direct vehicle control over the involved vehicles that cause identical pedestrian injury.In contrast to normative analyses,we show that the occupants of driverless cars(private cars and robotaxis)are attributed more responsibility than conventional taxi passengers.This dilemma is robust across different contexts(e.g.,participants from China vs the Republic of Korea,participants with first-vs third-person perspectives,and occupant presence vs absence).Furthermore,we observe that this is not due to the perception that these occupants have greater control over driving but because they are more expected to foresee the potential consequences of using driverless cars.Our findings suggest that when driverless vehicles(private cars and taxis)cause harm,their users may face more social pressure,which public discourse and legal regulations should manage appropriately.

Understanding the Low Predictability of the 2015/16 El Niño Event Based on a Deep Learning Model

The 2015/16 El Niño event ranks among the top three of the last 100 years in terms of intensity,but most dynamical models had a relatively low prediction skill for this event before the summer months.Therefore,the attribution of this particular event can help us to understand the cause of super El Niño–Southern Oscillation events and how to forecast them skillfully.The present study applies attribute methods based on a deep learning model to study the key factors related to the formation of this event.A deep learning model is trained using historical simulations from 21 CMIP6 models to predict the Niño-3.4 index.The integrated gradient method is then used to identify the key signals in the North Pacific that determine the evolution of the Niño-3.4 index.These crucial signals are then masked in the initial conditions to verify their roles in the prediction.In addition to confirming the key signals inducing the super El Niño event revealed in previous attribution studies,we identify the combined contribution of the tropical North Atlantic and the South Pacific oceans to the evolution and intensity of this event,emphasizing the crucial role of the interactions among them and the North Pacific.This approach is also applied to other El Niño events,revealing several new precursor signals.This study suggests that the deep learning method is useful in attributing the key factors inducing extreme tropical climate events.

Improving Optimal Fingerprinting Methods Requires a Viewpoint beyond Statistical Science

While being successful in the detection and attribution of climate change,the optimal fingerprinting method(OFM)may have some limitations from a physics-and-dynamics-based viewpoint.Here,an analysis is made on the linearity,noninteraction,and stationary-variability assumptions adopted by OFM.It is suggested that furthering OFM needs a viewpoint beyond statistical science,and the method should be combined with theoretical tools in the dynamics and physics of the Earth system,so as to be applied for the detection and attribution of nonlinear climate change including tipping elements within the Earth system.

Is Peer Victimization Associated with Higher Online Trolling among Adolescents?The Mediation of Hostile Attribution Bias and the Moderation of Trait Mindfulness

Background:In recent years,online trolling has garnered significant attention due to its detrimental effects on mental health and social well-being.The current study examined the influence of peer victimization on adolescent online trolling behavior,proposing that hostile attribution bias mediated this relationship and that trait mindfulness moderated both the direct and indirect effects.Methods:A total of 833 Chinese adolescents completed the measurements of peer victimization,hostile attribution bias,trait mindfulness,and online trolling.Moderated mediation analysis was performed to examine the relationships between these variables.Results:After controlling for gender and residential address,the study found a significant positive correlation between peer victimization and online trolling,with hostile attribution bias serving as a mediator.In addition,trait mindfulness moderated the direct relationship between peer victimization and online trolling.Specifically,the effect of peer victimization on online trolling was attenuated when adolescents had high levels of trait mindfulness.The results of the study emphasized the joint role of peer and personal factors in adolescents’online trolling behavior and provide certain strategies for intervening in adolescents’online trolling behavior.Conclusion:The results of the study suggest that strategies focusing on peer support and mindfulness training can have a positive impact on reducing online trolling behavior,promoting adolescents’mental health,and their long-term development.

Identity and Identification: William Langland Wrote The Romance of William of Palerne

This essay shows that William Langland/Longe Wille wrote The Romance of William of Palerne.It brings forward evidence from its text in two main ways:(1).synchronically,i.e.across the text;and(2).diachronically,‘across time’.There is a comparison between this c.1360-61 work and the previous 1191-4 NE Old French/Picard poem Le Roman de Guillaume de Palerne specifically of three passages from each.

Trend Analysis of the Burden of Hypertensive Heart Disease in China from 1990 to 2021

Objective:To quantitatively analyze the burden of hypertensive heart disease(HHD)in China and provide a scientific basis for prevention and control strategies.Methods:Data from the Global Burden of Disease 2021 database were used to assess the disease burden,deaths,years lived with disability(YLDs),and risk factors for HHD in the Chinese population from 1990 to 2021.Results:From 1990 to 2021,HHD cases in China increased from 1.5 million to 3.9 million,with an average annual growth rate of 2.83%.Prevalence rose from 127.76/100,000 to 259.00/100,000,while age-standardized prevalence decreased by 0.68%annually.HHD deaths increased from 232,478 to 320,247,with a mortality rate rise from 19.76/100,000 to 22.56/100,000,though age-standardized mortality decreased by 2.68%annually.YLDs rose from 124,386 to 301,426,with the rate increasing by 2.20%annually,while age-standardized YLDs decreased by 0.67%annually.High sodium intake and low fruit consumption were key risk factors for HHD deaths.Deaths related to low vegetable intake decreased until 2005 and then rose,while deaths from lead exposure showed a similar pattern.Conclusion:HHD cases and prevalence increased significantly,but age-standardized prevalence and mortality rates declined,reflecting the impact of an aging population and improved health interventions.The rise in YLDs highlights the long-term impact on patients’quality of life.Key risk factors included high sodium intake and low fruit consumption,emphasizing the importance of dietary improvements in HHD prevention.HHD remains a significant public health challenge in China,requiring continuous research and targeted prevention strategies.

Distribution of high-risk human papillomavirus genotype prevalence and attribution to cervical precancerous lesions in rural North China

Objective: Precise prevention is more desired for cervical cancer due to the huge population, high prevalence of human papillomavirus(HPV) infection in China and the vision of screen-and-treat strategies in low-and middleincome countries(LMICs). Considerations of combining type-specific prevalence and attribution proportion to high-grade cervical intraepithelial neoplasia are informative to more precise and effective region-specific cervical cancer prevention and control programs. The aim of the current study was to determine the genotype distribution of HPV and attribution to cervical precancerous lesions among women from rural areas in North China.Methods: A total of 9,526 women participated in the cervical cancer screening project in rural China. The samples of women who tested positive for HPV were retested with a polymerase chain reaction(PCR)-based HPV genotyping test. The attribution proportion of specific high-risk human papillomavirus(HR-HPV) types for different grades of cervical lesions was calculated by using the type contribution weighting method.Results: A total of 22.2%(2,112/9,526) of women were HR-HPV positive and HPV52(21.7%) was the most common HR-HPV genotype, followed by HPV58(18.2%), HPV53(18.2%) and HPV16(16.2%). The top three genotypes detected in HR-HPV-positive cervical intraepithelial neoplasia(CIN)1 were HPV16(36.7%), HPV58(20.4%), HPV56(15.3%). Among CIN2+, the most frequent genotypes were HPV16(75.6%), HPV52(17.8%),HPV58(16.7%). HPV16, 56, 58, 53, 52, 59, 68, and 18 combined were attributed to 84.17% of all CIN1 lesions,and HPV16, 58, and 52 combined were attributed to 86.98% of all CIN2+ lesions.Conclusions: The prevalence of HR-HPV infection among women from rural areas in North China was high and HPV16, HPV58, HPV52 had paramount attributable fraction in CIN2+. Type-specific HPV prevalence and attribution proportion to cervical precancerous lesions should be taken into consideration in the development of vaccines and strategy for screening in this population.

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.

Documented changes in annual runoff and attribution since the 1950s within selected rivers in China

To enable local water resource management and maintenance of ecosystem integrity and to protect and mitigate against flood and drought, it is necessary to determine changes in long-term series of streamflow and to distinguish the roles that climate change and human disturbance play in these changes. A review of previous research on the detection and attribution of observed changes in annual runoff in China shows a decrease in annual runoff since the 1950s in northern China in areas such as the Songhuajiang River water resources zone, the Liaohe River water resources zone, the Haihe River water resources zone, the Yellow River water resources zone, and the Huaihe River water resources Zone. Furthermore, abrupt changes in annual runoff occurred mostly in the 1970s and 1980s in all the above zones, except for some of the sub-basins in the middle Yellow River where abrupt change occurred in the 1990s. Changes in annual runoff are found to be mainly caused by climate change in the western Songhuajiang River basin, the upper mainstream of the Yangtze River, and the western Pearl River basin, which shows that studies on the impact of climate change on future water resources under different climate change scenarios are required to enable planning and management by agencies in these river basins. However, changes in annual runoff were found to be mainly caused by human activities in most of the catchments in northern China (such as the southern Songhuajiang River, Liaohe River, Haihe River, the lower reach and some of the catchments within the middle Yellow River basin) and in middle-eastern China, such as the Huaihe River and lower mainstream of the Yangtze River. This suggests that current hydro-climatic data can continue to be used in water-use planning and that policymakers need to focus on water resource management and protection.

2021:A Year of Unprecedented Climate Extremes in Eastern Asia,North America,and Europe

The year 2021 was recorded as the 6th warmest since 1880.In addition to large-scale warming,2021 will be remembered for its unprecedented climate extremes.Here,a review of selected high-impact climate extremes in 2021,with a focus on China,along with an extension to extreme events in North America and Europe is presented.Nine extreme events that occurred in 2021 in China are highlighted,including a rapid transition from cold to warm extremes and sandstorms in spring,consecutive drought in South China and severe thunderstorms in eastern China in the first half of the year,extremely heavy rainfall over Henan Province and Hubei Province during summer,as well as heatwaves,persistent heavy rainfall,and a cold surge during fall.Potential links of extremes in China to four global-scale climate extremes and the underlying physical mechanisms are discussed here,providing insights to understand climate extremes from a global perspective.This serves as a reference for climate event attribution,process understanding,and high-resolution modeling of extreme events.

Attribution of the Langshan Tectonic Belt: Evidence from zircon U-Pb ages and Hf isotope compositions

This study describes a previously unidentified Neoproterozoic mafic dyke emplaced in the northern flank of the Langshan Tectonic Belt. This dyke intruded into the micaquartz schist of the Zhaertaishan Group, and yielded an age of 908 ± 8 Ma. The youngest U-Pb ages of micaquartz schist from the Zhaertaishan Group in the Langshan area were 1118 ± 33 Ma,1187 ± 3 Ma and 1189 ± 39 Ma,suggesting that the depositional age of the protolith of the schist was between 908 ± 8 Ma and 1118 ± 33 Ma. In addition, 436 U-Pb age data and 155 Lu-Hf isotopic data from six samples in the Langshan Tectonic Belt and one Permian greywacke from the Wuhai area show distinct differences between the northern and southern flanks of the Main Langshan area. The U-Pb ages of the northern flank are primarily Meso-Neoproterozoic; similar ages have not been identified in the southern flank to date.Moreover, two-stage Hf model ages of the northern flank feature three age peaks at ～900 Ma,～1700 Ma and ～2600 Ma; this differs from Hf model ages of the southern flank, which feature one strong age peak at ～2700 Ma. These results suggest that the northern and southern flanks of the Main Langshan area have different geochronologic characteristics and should be divided further. Based on the U-Pb ages and Hf model ages, the northern and southern flanks of the Main Langshan area are named the North and South Langshan Tectonic Belts. Comparison of the U-Pb age and two-stage Hf model age distributions from the North Langshan Tectonic Belt, South Langshan Tectonic Belt, Alxa Block and the North China Craton(NCC) reveal that the North Langshan Tectonic Belt is similar to the Alxa Block and that the South Langshan Tectonic Belt is similar to the NCC. In addition, the zircon U-Pb age of 860 ±7 Ma commonly observed in the Alxa Block was detected in the Permian greywacke from the Wuhai area of the NCC, which suggests that the amalgamation of the North and South Langshan Tectonic belts(i.e.,the amalgamation of the Alxa Block and the NCC), occurred between Devonian and late Permian.

Another Record: Ocean Warming Continues through 2021 despite La Nina Conditions

The increased concentration of greenhouse gases in the atmosphere from human activities traps heat within the climate system and increases ocean heat content(OHC). Here, we provide the first analysis of recent OHC changes through 2021 from two international groups. The world ocean, in 2021, was the hottest ever recorded by humans, and the 2021 annual OHC value is even higher than last year’s record value by 14 ± 11 ZJ(1 zetta J = 1021 J) using the IAP/CAS dataset and by16 ± 10 ZJ using NCEI/NOAA dataset. The long-term ocean warming is larger in the Atlantic and Southern Oceans than in other regions and is mainly attributed, via climate model simulations, to an increase in anthropogenic greenhouse gas concentrations. The year-to-year variation of OHC is primarily tied to the El Nino-Southern Oscillation(ENSO). In the seven maritime domains of the Indian, Tropical Atlantic, North Atlantic, Northwest Pacific, North Pacific, Southern oceans,and the Mediterranean Sea, robust warming is observed but with distinct inter-annual to decadal variability. Four out of seven domains showed record-high heat content in 2021. The anomalous global and regional ocean warming established in this study should be incorporated into climate risk assessments, adaptation, and mitigation.

Attribution retraining group therapy for outpatients with major depression disorder,generalized anxiety disorder,and obsessive-compulsive disorder:a pilot study

The aim of this present study is to examine the efficacy of attribution retraining group therapy （ARGT） and to compare the responses of outpatients with major depression disorder （MDD）, generalized anxiety disorder （GAD） and obsessive-compulsive disorder （OCD）. We carried out a prospective uncontrolled intervention study with a 8-weeks of ARGT on sixty three outpatients with MDD, GAD or OCD. Hamilton rating scale for depression, Hamilton rating scale for anxiety, Yale-Brown obsessive-compulsive scale, attribution style questionnaire, self-esteem scale, index of well-being, and social disability screening schedule were administered before and after treatment. Significant improvement in symptoms and psychological and social functions from pre- to posttreatment occurred for all participants. The changes favored MDD patients. Our study suggested that ARGT may improve the symptoms and psychological-social functions of MDD, GAD, and OCD patients. MDD patients showed the best response.

Forest disturbances and the attribution derived from yearly Landsat time series over 1990–2020 in the Hengduan Mountains Region of Southwest China

Background:Natural forests in the Hengduan Mountains Region(HDMR)have pivotal ecological functions and provide diverse ecosystem services.Capturing long-term forest disturbance and drivers at a regional scale is crucial for sustainable forest management and biodiversity conservation.Methods:We used 30-m resolution Landsat time series images and the LandTrendr algorithm on the Google Earth Engine cloud platform to map forest disturbances at an annual time scale between 1990 and 2020 and attributed causal agents of forest disturbance,including fire,logging,road construction and insects,using disturbance properties and spectral and topographic variables in the random forest model.Results:The conventional and area-adjusted overall accuracies(OAs)of the forest disturbance map were 92.3% and 97.70%±0.06%,respectively,and the OA of mapping disturbance agents was 85.80%.The estimated disturbed forest area totalled 3313.13 km^(2)(approximately 2.31% of the total forest area in 1990)from 1990 to 2020,with considerable interannual fluctuations and significant regional differences.The predominant disturbance agent was fire,which comprised approximately 83.33% of the forest area disturbance,followed by logging(12.2%),insects(2.4%)and road construction(2.0%).Massive forest disturbances occurred mainly before 2000,and the post-2000 annual disturbance area significantly dropped by 55% compared with the pre-2000 value.Conclusions:This study provided spatially explicit and retrospective information on annual forest disturbance and associated agents in the HDMR.The findings suggest that China’s logging bans in natural forests combined with other forest sustainability programmes have effectively curbed forest disturbances in the HDMR,which has implications for enhancing future forest management and biodiversity conservation.

Understanding and Attribution of Extreme Heat and Drought Events in 2022: Current Situation and Future Challenges

Extreme weather events and their consequential impacts have been a key feature of the climate in recent years in many parts of the world,with many partly attributed to ongoing global-scale warming.The past year,2022,has been no exception,with further records being broken.The year was marked by unprecedented heatwaves and droughts with highly unusual spatial extent,duration and intensity,with one measure indicating an aggregated and overall intensity of extreme heat events worldwide not seen since at least 1950.The extreme drought measured by surface soil moisture covered 47.3%of global land areas in 2022,which was the second most widespread year since 1980.Here,we examine notable events of the year in five major regions of the world:China’s Yangtze River region,western Europe,the western U.S.,the Horn of Africa and central South America.For each event,we review the potential roles of circulation,oceanic forcing(especially the“triple-dip”La Niña)and anthropogenic climate change,with an aim of understanding the extreme events in 2022 from a global perspective.This will serve as a reference for mechanism understanding,prediction and attribution of extreme events.

Attributing Analysis on the Model Bias in Surface Temperature in the Climate System Model FGOALS-s2 through a Process-Based Decomposition Method

This study uses the coupled atmosphere–surface climate feedback–response analysis method（CFRAM） to analyze the surface temperature biases in the Flexible Global Ocean–Atmosphere–Land System model, spectral version 2（FGOALS-s2）in January and July. The process-based decomposition of the surface temperature biases, defined as the difference between the model and ERA-Interim during 1979–2005, enables us to attribute the model surface temperature biases to individual radiative processes including ozone, water vapor, cloud, and surface albedo; and non-radiative processes including surface sensible and latent heat fluxes, and dynamic processes at the surface and in the atmosphere. The results show that significant model surface temperature biases are almost globally present, are generally larger over land than over oceans, and are relatively larger in summer than in winter. Relative to the model biases in non-radiative processes, which tend to dominate the surface temperature biases in most parts of the world, biases in radiative processes are much smaller, except in the sub-polar Antarctic region where the cold biases from the much overestimated surface albedo are compensated for by the warm biases from nonradiative processes. The larger biases in non-radiative processes mainly lie in surface heat fluxes and in surface dynamics,which are twice as large in the Southern Hemisphere as in the Northern Hemisphere and always tend to compensate for each other. In particular, the upward/downward heat fluxes are systematically underestimated/overestimated in most parts of the world, and are mainly compensated for by surface dynamic processes including the increased heat storage in deep oceans across the globe.

Quantifying the attribution of model bias in simulating summer hot days in China with IAP AGCM 4.1

Using lAP AGCM simulation results for the period 1961-2005, summer hot days in China were calculated and then compared with observations. Generally, the spatial pattern of hot days is reasonably reproduced, with more hot days found in northern China, the Yangtze and Huaihe River basin, the Chuan-Yu region, and southern Xinjiang. However, the model tends to overestimate the number of hot days in the above-mentioned regions, particularly in the Yangtze and Huaihe River basin where the simulated summer-mean hot days is 13 days more than observed when averaged over the whole region, and the maximum overestimation of hot days can reach 23 days in the region. Analysis of the probability distribution of daily maximum temperature （Trnax） suggests that the warm bias in the model-simulated Tmax contributes largely to the overestimation of hot days in the model. Furthermore, the discrepancy in the simulated variance of the Tmax distribution also plays a non- negligible role in the overestimation of hot days. Indeed, the latter can even account for 22% of the total bias of simulated hot days in August in the Yangtze and Huaihe River basin. The quantification of model bias from the mean value and variability can provide more information for further model improvement.

Impact of environmental change on runoff in a transitional basin:Tao River Basin from the Tibetan Plateau to the Loess Plateau,China

Quantification of the impacts of environmental changes on runoff in the transitional area from the Tibetan Plateau to the Loess Plateau is of critical importance for regional water resources management.Trends and abrupt change points of the hydro-climatic variables in the Tao River Basin were investigated during 1956-2015.It also quantitatively separates the impacts of climate change and human activities on runoff change in the Tao River by using RCC-WBM model.Results indicate that temperature presented a significant rising trend(0.2℃per decade)while precipitation exhibited an insignificant decreasing trend(3.8 mm per decade)during 1956-2015.Recorded runoff in the Tao River decreased significantly with a magnitude of-13.7 mm per decade and abrupt changes in 1968 and 1986 were identified.Relative to the baseline period(1956-1968),runoff in the two anthropogenic disturbed periods of 1969-1986 and 1987-2015 decreased by 27.8 mm and 76.5 mm,respectively,which can be attributed to human activities(accounting for 69%)and climate change(accounting for 31%).Human activities are the principal drivers of runoff reduction in the Tao River Basin.However,the absolute influences on runoff reductions by the both drivers tend to increase,from 7.7 mm in 1969-1986 to 24.4 mm in 1987-2015 by climate change and from 20.2 mm to 52.2 mm by human activities.

Contribution of Global Warming and Atmospheric Circulation to the Hottest Spring in Eastern China in 2018

The spring of 2018 was the hottest on record since 1951 over eastern China based on station observations,being 2.5°C higher than the 1961−90 mean and with more than 900 stations reaching the record spring mean temperature.This event exerted serious impacts in the region on agriculture,plant phenology,electricity transmission systems,and human health.In this paper,the contributions of human-induced climate change and anomalous anticyclonic circulation to this event are investigated using the newly homogenized observations and updated Met Office Hadley Centre system for attribution of extreme events,as well as CanESM2(Second Generation Canadian Earth System Model)simulations.Results indicate that both anthropogenic influences and anomalous anticyclonic circulation played significant roles in increasing the probability of the 2018 hottest spring.Quantitative estimates of the probability ratio show that anthropogenic forcing may have increased the chance of this event by ten-fold,while the anomalous circulation increased it by approximately two-fold.The persistent anomalous anticyclonic circulation located on the north side of China blocked the air with lower temperature from high latitudes into eastern China.Without anthropogenic forcing or without the anomalous circulation in northern China,the occurrence probability of the extreme warm spring is significantly reduced.