Deforestation has a significant influence on the hydrological cycle.Understanding the impact of deforestation on precipitation extremes is crucial for addressing global environmental challenges.This study investigates...Deforestation has a significant influence on the hydrological cycle.Understanding the impact of deforestation on precipitation extremes is crucial for addressing global environmental challenges.This study investigates the impact of deforestation on precipitation extremes(R95p index,which represents the total amount of precipitation exceeding the 95th percentile of the reference period)in China,using outputs from three earth system models(CanESM5,IPSL-CM6A-LR,and MIROC-ES2L).All models,along with their multimodel mean,indicate a general decrease in R95p in Northeast China and southern China,and changes in Northwest China and the Tibetan Plateau are minimal.In contrast,the responses are model-dependent in the Huanghuai and Jianghuai regions.The overall nationwide multimodel mean suggests an annual R95p decrease of 10.7 mm,with individual model variations ranging from-28.0 to 2.0 mm.Further analysis using precipitation extremes scaling reveals a high spatial correlation with direct precipitation extremes changes on both annual and seasonal scales,albeit with slightly smaller magnitudes.Decomposing the response into dynamic and thermodynamic scaling,the authors find that dynamic contributions predominantly drive the changes in precipitation extremes on both annual and seasonal scales.The authors findings highlight the substantial role of dynamic processes in modulating the response of precipitation extremes to deforestation in China.展开更多
Located downstream the Kupang Catchment in Indonesia,Pekalongan faces significant land subsidence issues,leading to severe coastal flooding.This study aimed to assess the impact of climate change on future flow regime...Located downstream the Kupang Catchment in Indonesia,Pekalongan faces significant land subsidence issues,leading to severe coastal flooding.This study aimed to assess the impact of climate change on future flow regimes and hydrological extremes to inform long-term water resources management strategies for the Kupang Catchment.Utilizing precipitation and air temperature data from general circulation models in the Coupled Model Intercomparison Project 6(CMIP6)and employing bias correction techniques,the Soil and Water Assessment Tool(SWAT)hydrological model was employed to analyze climate-induced changes in hydrological fluxes,specifically streamflow.Results indicated a consistent increase in monthly streamflow during the wet season,with a substantial rise of 22.8%,alongside a slight decrease of 18.0%during the dry season.Moreover,both the frequency and severity of extremely low and high flows were projected to intensify by approximately 50%and 70%,respectively,for a 20-year return period,suggesting heightened flood and drought risks in the future.The observed declining trend in low flow,by up to 11%,indicated the potential for long-term groundwater depletion exacerbating the threat of land subsidence and coastal flooding,especially in areas with inadequate surface water management policies and infrastructure.展开更多
This past year, 2024, is on track to be the warmest year, joining 2023 as the two hottest years on record. With the exceptional heat, weather and climate extremes were common across the world. In particular, 2024 has ...This past year, 2024, is on track to be the warmest year, joining 2023 as the two hottest years on record. With the exceptional heat, weather and climate extremes were common across the world. In particular, 2024 has seen a remarkable run of extreme precipitation events and resulting impacts. Here, we provide an overview of the most notable extreme events of the year, including extreme precipitation and floods, tropical cyclones, and droughts. The characteristics and impacts of these extreme events are summarized, followed by discussion on the physical drivers and the role of global warming.Finally, we also discuss the future prospects in extreme event studies, including impact-based perspectives, challenges in attribution of precipitation extremes, and the existing gap to minimize impacts from climate extremes.展开更多
A nonlinear multi-scale interaction(NMI)model was proposed and developed by the first author for nearly 30 years to represent the evolution of atmospheric blocking.In this review paper,we first review the creation and...A nonlinear multi-scale interaction(NMI)model was proposed and developed by the first author for nearly 30 years to represent the evolution of atmospheric blocking.In this review paper,we first review the creation and development of the NMI model and then emphasize that the NMI model represents a new tool for identifying the basic physics of how climate change influences mid-to-high latitude weather extremes.The building of the NMI model took place over three main periods.In the 1990s,a nonlinear Schr?dinger(NLS)equation model was presented to describe atmospheric blocking as a wave packet;however,it could not depict the lifetime(10-20 days)of atmospheric blocking.In the 2000s,we proposed an NMI model of atmospheric blocking in a uniform basic flow by making a scale-separation assumption and deriving an eddyforced NLS equation.This model succeeded in describing the life cycle of atmospheric blocking.In the 2020s,the NMI model was extended to include the impact of a changing climate mainly by altering the basic zonal winds and the magnitude of the meridional background potential vorticity gradient(PVy).Model results show that when PVy is smaller,blocking has a weaker dispersion and a stronger nonlinearity,so blocking can be more persistent and have a larger zonal scale and weaker eastward movement,thus favoring stronger weather extremes.However,when PVy is much smaller and below a critical threshold under much stronger winter Arctic warming of global warming,atmospheric blocking becomes locally less persistent and shows a much stronger westward movement,which acts to inhibit local cold extremes.Such a case does not happen in summer under global warming because PVy fails to fall below the critical threshold.Thus,our theory indicates that global warming can render summer-blocking anticyclones and mid-to-high latitude heatwaves more persistent,intense,and widespread.展开更多
Texas experienced the worst drought in its 100-year history in 2011,resulting in the death of approximately 300 million trees.The high number of sudden deaths had a significant impact on forest ecosystems.This study a...Texas experienced the worst drought in its 100-year history in 2011,resulting in the death of approximately 300 million trees.The high number of sudden deaths had a significant impact on forest ecosystems.This study aimed to gain insight into the long-term and combined impacts of drought-induced forest tree deaths and their effects on biomass.This study used data obtained from 1797 National Forest Inventory(NFI)plots to analyze trends and major causes of changes in tree biomass at the sample plot level in East Texas forests over the past 20 years(2000-2019).In this study,forest trees in East Texas were divided into diameter at breast height(dbh),height,stand types,latitude,elevation,ecological zones,and FIA Unit.Principal component analysis(PCA)was also performed using drought intensity,drought duration,the four competing factor indicators,and the biomass loss rate of forest trees to better understand r drought impacts on forest trees.The results showed the lowest biomass loss rate of Pine species.Similarly,trees with shorter height and smaller dbh experienced a higher biomass loss rate.A higher biomass loss rate was observed in natural forests,West Gulf Coastal Plain and Plain and Southern East Texas ecoregion experienced higher biomass loss.Principal component analyses of drought intensity,drought duration,and the four competing metrics revealed that overall drought was the main contributor to biomass loss rates,and that drought intensity and drought duration had comparable effects on biomass loss rates.展开更多
Climate changes in cold-temperate zones are increasingly altering the state of climatic constraints on photosynthesis and growth,leading to adaptive changes in plant phenology and subsequent seasonal carbon assimilati...Climate changes in cold-temperate zones are increasingly altering the state of climatic constraints on photosynthesis and growth,leading to adaptive changes in plant phenology and subsequent seasonal carbon assimilation.However,the spatio-temporal patterns of climatic constraints and seasonal carbon assimilation are poorly understood.In this study,the timing of peak photosynthetic activity(DOY_(pmax))was employed as a proxy for plant adap-tive state to climatic constraints on growth to examine the spatio-temporal dynamics of DOY_(pmax).By using multiple remote sensing metrics,DOY_(pmax)was characterized with changes in the solar-induced chlorophyll fluorescence(SIF)and leaf area index(LAI)from 2000 to 2018.Based on SIF,the DOY_(pmax)was generally around day 190,while based on LAI was about 10 d later.Peak photosynthetic activity of forests occurs earlier compared to other vegetation types.Overall,the advanced DOY_(pmax)were observed based on both SIF and LAI,with annual rates of 0.2(P=0.31)and 0.3(P<0.05)d,respectively.DOY_(pmax)dynamics were influ-enced by hot temperature extremes and vapor pressure defi-cits(VPD)during the early growing season,regardless of sub-zone and different vegetation type.The generalized lin-ear mixed model(GLMM)showed the largest contribution by hot extremes to DOY_(pmax)dynamics accounted for 55.5%(DOY_(pmax_SIF))and 49.1%(DOY_(pmax_LAI)),respectively,fol-lowed by VPD(DOY_(pmax_SIF):23.1%;DOY_(pmax_LAI):29.5%).These findings highlight the crucial role of climate extremes in shaping seasonal carbon dynamics and regional carbon balance.展开更多
The likelihood of extreme heat occurrence is continuously increasing with global warming.Under high temperatures,humidity may exacerbate the heat impact on humanity.As atmospheric humidity depends on moisture availabi...The likelihood of extreme heat occurrence is continuously increasing with global warming.Under high temperatures,humidity may exacerbate the heat impact on humanity.As atmospheric humidity depends on moisture availability and is constrained by air temperature,it is important to project the changes in the distribution of atmospheric humidity conditional on air temperature as the climate continuously warms.Here,a non-crossing quantile smoothing spline is employed to build quantile regression models emulating conditional distributions of dew point(a measure of humidity)on local temperature evolving with escalating global mean surface temperature.By applying these models to 297 weather stations in seven regions in China,the study analyzes historical trends of humid-heat and dry-hot days,and projects their changes under global warming of 2.0℃ and 4.5℃.In response to global warming,rising trends of humid-heat extremes,while weakening trends of dry-hot extremes,are observed at most stations in Northeast China.Additionally,results indicate an increasing trend in dry-hot extremes at numerous stations across central China,but a rise in humid-heat extremes over Northwest China and coastal regions.These trends found in the current climate state are projected to intensify under 2.0℃ and 4.5℃ warming,possibly influenced by the heterogeneous variations in precipitation,soil moisture,and water vapor fluxes.Requiring much lower computational resources than coupled climate models,these quantile regression models can further project compound humidity and temperature extremes in response to different levels of global warming,potentially informing the risk management of compound humid-heat extremes on a local scale.展开更多
The impact of extreme temperatures on the health of individuals in different organizations remains uncertain.We employed stratified analyses to examine the impacts of summer(April-September)daily maximum temperatures ...The impact of extreme temperatures on the health of individuals in different organizations remains uncertain.We employed stratified analyses to examine the impacts of summer(April-September)daily maximum temperatures and winter(October-March)daily minimum temperatures on blood pressure and lipid profiles across government staff,com-pany employees,and researchers.We examined 209,477 physical examination records from a physical examination center in the First Affiliated Hospital of USTC from 2017 to 2021.Employing a segmented regression model within the frame-work of generalized linear regression(GLM),we examined the causal impact of extreme temperatures on health outcomes.Additionally,sensitivity analyses were conducted via distributed lag nonlinear models(DLNMs),with a focus on ob-serving the long-term effects over a period of 21 days.Our findings indicate that government staff face increased health risks during extremely low temperatures,regardless of the season.Compared with participants experiencing median tem-peratures,government staff exposed to extremely low temperatures(below the 10th percentile,below 24℃)in the sum-mer presented maximum increases of 2.32 mmHg(95%CI:1.542-3.098)in diastolic blood pressure and 6.481 mmHg(95%CI:5.368-7.594)in systolic blood pressure.In winter,government staff exposed to temperatures below the 10th per-centile(below 1℃)demonstrated maximum increases of 0.278 mmol/L(95%CI:0.210-0.346)in total cholesterol,0.153 mmol/L(95%CI:0.032-0.274)in triglycerides,and 0.077 mmol/L(95%CI:0.192-0.134)in low-density lipoprotein.Conversely,warm winters benefit company employees,whereas researchers exhibit lower sensitivity to temperature changes in winter.The maximum temperatures in summer and minimum temperatures in winter had greater impacts on in-dividuals.Small temperature fluctuations impact health more than large changes do.Notably,both the maximum and min-imum temperatures were better predictors of health outcomes than the daily average temperature was.Blood pressure con-sistently displayed significant associations with temperature across all three groups,with extremely low temperatures in-creasing the risk and extremely high temperatures reducing it.However,the relationship between temperature and blood lipids is complex.展开更多
Globally,2023 was the warmest observed year on record since at least 1850 and,according to proxy evidence,possibly of the past 100000 years.As in recent years,the record warmth has again been accompanied with yet more...Globally,2023 was the warmest observed year on record since at least 1850 and,according to proxy evidence,possibly of the past 100000 years.As in recent years,the record warmth has again been accompanied with yet more extreme weather and climate events throughout the world.Here,we provide an overview of those of 2023,with details and key background causes to help build upon our understanding of the roles of internal climate variability and anthropogenic climate change.We also highlight emerging features associated with some of these extreme events.Hot extremes are occurring earlier in the year,and increasingly simultaneously in differing parts of the world(e.g.,the concurrent hot extremes in the Northern Hemisphere in July 2023).Intense cyclones are exacerbating precipitation extremes(e.g.,the North China flooding in July and the Libya flooding in September).Droughts in some regions(e.g.,California and the Horn of Africa)have transitioned into flood conditions.Climate extremes also show increasing interactions with ecosystems via wildfires(e.g.,those in Hawaii in August and in Canada from spring to autumn 2023)and sandstorms(e.g.,those in Mongolia in April 2023).Finally,we also consider the challenges to research that these emerging characteristics present for the strategy and practice of adaptation.展开更多
Summer weather extremes(e.g.,heavy rainfall,heat waves)in China have been linked to anomalies of summer monsoon circulations.The East Asian subtropical westerly jet(EASWJ),an important component of the summer monsoon ...Summer weather extremes(e.g.,heavy rainfall,heat waves)in China have been linked to anomalies of summer monsoon circulations.The East Asian subtropical westerly jet(EASWJ),an important component of the summer monsoon circulations,was investigated to elucidate the dynamical linkages between its intraseasonal variations and local weather extremes.Based on EOF analysis,the dominant mode of the EASWJ in early summer is characterized by anomalous westerlies centered over North China and anomalous easterlies centered over the south of Japan.This mode is conducive to the occurrence of precipitation extremes over Central and North China and humid heat extremes over most areas of China except Northwest and Northeast China.The centers of the dominant mode of the EASWJ in late summer extend more to the west and north than in early summer,and induce anomalous weather extremes in the corresponding areas.The dominant mode of the EASWJ in late summer is characterized by anomalous westerlies centered over the south of Lake Baikal and anomalous easterlies centered over Central China,which is favorable for the occurrence of precipitation extremes over northern and southern China and humid heat extremes over most areas of China except parts of southern China and northern Xinjiang Province.The variability of the EASWJ can influence precipitation and humid heat extremes by driving anomalous vertical motion and water vapor transport over the corresponding areas in early and late summer.展开更多
Modification signs in extreme weather events may be directly related to alterations in the thermodynamic panorama of the atmosphere that need to be better understood. This study aimed to make a first interconnection b...Modification signs in extreme weather events may be directly related to alterations in the thermodynamic panorama of the atmosphere that need to be better understood. This study aimed to make a first interconnection between climate extremes and thermodynamic patterns in the city of Rio de Janeiro. Maximum and minimum air temperature and precipitation extreme indices from two surface meteorological stations (ABOV and STCZ) and instability indices based on temperature and humidity from radiosonde observations (SBGL) were employed to investigate changes in the periods 1964-1980 (P1), 1981-2000 (P2), and 2001-2020 (P3). Statistical tests were adopted to determine the significance and magnitude of trends. The frequency of warm (cold) days and warm (cold) nights are increasing (decreasing) in the city. Cold (Warm) extremes are changing with greater magnitude in ABOV (STCZ) than in STCZ (ABOV). In ABOV, there is a significant increase of +84 mm/decade in the rainfall volume associated with severe precipitation (above the 95<sup>th</sup> percentile) and most extreme precipitation indices show an increase in frequency and intensity. In STCZ, there is a decrease in extreme precipitation until the 1990s, and from there, an increase, showing a wetter climate in the most recent years. It is also verified in SBGL that there is a statistically significant increase (decrease) in air temperature of +0.1°C/decade (-0.2°C/decade) and relative humidity of +1.2%/decade (-3%/decade) at the low and middle (high) troposphere. There is a visible rising trend in most of the evaluated instability indices over the last few decades. The increasing trends of some extreme precipitation indices are probably allied to the precipitable water increasing trend of +1.2 mm/decade.展开更多
Based on climate extreme indices calculated from a high-resolution daily observational dataset in China during 1961–2005,the performance of 12 climate models from phase 6 of the Coupled Model Intercomparison Project(...Based on climate extreme indices calculated from a high-resolution daily observational dataset in China during 1961–2005,the performance of 12 climate models from phase 6 of the Coupled Model Intercomparison Project(CMIP6),and 30 models from phase 5 of CMIP(CMIP5),are assessed in terms of spatial distribution and interannual variability.The CMIP6 multi-model ensemble mean(CMIP6-MME)can simulate well the spatial pattern of annual mean temperature,maximum daily maximum temperature,and minimum daily minimum temperature.However,CMIP6-MME has difficulties in reproducing cold nights and warm days,and has large cold biases over the Tibetan Plateau.Its performance in simulating extreme precipitation indices is generally lower than in simulating temperature indices.Compared to CMIP5,CMIP6 models show improvements in the simulation of climate indices over China.This is particularly true for precipitation indices for both the climatological pattern and the interannual variation,except for the consecutive dry days.The arealmean bias for total precipitation has been reduced from 127%(CMIP5-MME)to 79%(CMIP6-MME).The most striking feature is that the dry biases in southern China,very persistent and general in CMIP5-MME,are largely reduced in CMIP6-MME.Stronger ascent together with more abundant moisture can explain this reduction in dry biases.Wet biases for total precipitation,heavy precipitation,and precipitation intensity in the eastern Tibetan Plateau are still present in CMIP6-MME,but smaller,compared to CMIP5-MME.展开更多
Interannual variations in the number of winter extreme warm and cold days over eastern China （EC） and their relationship with the Arctic Oscillation （AO） and E1 Nifio-Southern Oscillation （ENSO） were investigate...Interannual variations in the number of winter extreme warm and cold days over eastern China （EC） and their relationship with the Arctic Oscillation （AO） and E1 Nifio-Southern Oscillation （ENSO） were investigated using an updated temperature dataset comprising 542 Chinese stations during the period 1961- 2011. Results showed that the number of winter extreme warm （cold） days across EC experienced a significant increase （decrease） around the mid-1980s, which could be attributed to interdecadal variation of the East Asian Winter Monsoon （EAWM）. Probability distribution functions （PDFs） of winter temperature extremes in different phases of the AO and ENSO were estimated based on Generalized Extreme Value Distribution theory. Correlation analysis and the PDF technique consistently demonstrated that interannual variation of winter extreme cold days in the northern part of EC （NEC） is closely linked to the AO, while it is most strongly related to the ENSO in the southern part （SEC）. However, the number of winter extreme warm days across EC has little correlation with both AO and ENSO. Furthermore, results indicated that, whether before or after the mid-1980s shift, a significant connection existed between winter extreme cold days in NEC and the AO. However, a significant connection between winter extreme cold days in SEC and the ENSO was only found after the mid-1980s shift. These results highlight the different roles of the AO and ENSO in influencing winter temperature extremes in different parts of EC and in different periods, thus providing important clues for improving short-term climate prediction for winter temperature extremes.展开更多
China is physically and socio-economically susceptible to global warming-derived high temperature extremes because of its vast area and high urban population density. This article presents a scenario-based analysis me...China is physically and socio-economically susceptible to global warming-derived high temperature extremes because of its vast area and high urban population density. This article presents a scenario-based analysis method for high temperature extremes aimed at illustrating the latter＇s hazardous potential and exposure across China. Based on probability analysis, high temperature extreme scenarios with return periods of 5, 10, 20, and 50 years were designed, with a high temperature hazard index calculated by integrating two differen- tially-weighted extreme temperature indices （maximum temperature and high temperature days）. To perform the exposure analysis, a land use map was employed to determine the spatial distribution of susceptible human activities under the different scenarios. The results indicate that there are two heat-prone regions and a sub-hotspot occupying a relatively small land area. However, the societal and economic consequences of such an environmental im- pact upon the North China Plain and middle/lower Yangtze River Basin would be substantial due to the concentration of human activities in these areas.展开更多
The long-term goal of the 2015 Paris Agreement is to limit global warming to well below 2 ℃above pre-industrial levels and to pursue efforts to limit it to 1.5 ℃. However, for climate mitigation and adaption efforts...The long-term goal of the 2015 Paris Agreement is to limit global warming to well below 2 ℃above pre-industrial levels and to pursue efforts to limit it to 1.5 ℃. However, for climate mitigation and adaption efforts, further studies are still needed to understand the regional consequences between the two global warming limits. Here we provide an assessment of changes in temperature extremes over China （relative to 1986-2005） at 1.5 ℃ and 2 ℃ warming levels （relative to 1861-1900） by using the 5th phase of the Coupled Model Intercomparison Project （CMIP5） models under three RCP scenarios （RCP2.6, RCP4.5, RCP8.5）. Results show that the increases in mean temperature and temperature extremes over China are greater than that in global mean temperature. With respect to 1986-2005, the temperature of hottest day （TXx） and coldest night （TNn） are projected to increase about 1/1.6 ℃ and 1.1/1.8 ℃, whereas warm days （TX90p） and warm spell duration （WSDI） will increase about 7.5/13.8% and 15/30 d for the 1.5/2 ℃ global warming target, respectively. Under an additional 0.5 ℃ global warming, the projected increases of temperature in warmest day/night and coldest day/night are both more than 0.5 ℃ across almost the whole China. In Northwest China, Northeast China and the Tibetan Plateau, the projected changes are particularly sensitive to the additional 0.5 ℃ global warming, for example, multi-model mean increase in coldest day （TXn） and coldest night （TNn） will be about 2 times higher than a change of 0.5 ℃ global warming. Although the area-averaged changes in temperature extremes are very similar for different scenarios, spatial hotspot still exists, such as in Northwest China and North China, the increases in temperatures are apparently larger in RCP8.5 than that in RCP4.5.展开更多
This study investigated the drivers and physical processes for the abrupt decadal summer surface warming and increases in hot temperature extremes that occurred over Northeast Asia in the mid-1990s. Observations indic...This study investigated the drivers and physical processes for the abrupt decadal summer surface warming and increases in hot temperature extremes that occurred over Northeast Asia in the mid-1990s. Observations indicate an abrupt increase in summer mean surface air temperature （SAT） over Northeast Asia since the mid-1990s. Accompanying this abrupt surface wanning, significant changes in some temperature extremes, characterized by increases in summer mean daily maximum temperature （Tmax）, daily minimum temperature （Train）, annual hottest day temperature （TXx）, and annual warmest night temperature （TNx） were observed. There were also increases in the frequency of summer days （SU） and tropical nights （TR）. Atmospheric general circulation model experiments forced by changes in sea surface temperature （SST）/sea ice extent （SIE）, anthropogenic greenhouse gas （GHG） concentrations, and anthropogenic aerosol （AA） forcing, relative to the period 1964- 93, reproduced the general patterns of observed summer mean SAT changes and associated changes in temperature extremes, although the abrupt decrease in precipitation since the mid-1990s was not simulated. Additional model experiments with different forcings indicated that changes in SST/SIE explained 76% of the area-averaged summer mean surface warming signal over Northeast Asia, while the direct impact of changes in GHG and AA explained the remaining 24% of the surface warming signal. Analysis of physical processes indicated that the direct impact of the changes in AA （through aerosol- radiation and aerosol-cloud interactions）, mainly related to the reduction of AA precursor emissions over Europe, played a dominant role in the increase in TXx and a similarly important role as SST/SIE changes in the increase in the frequency of SU over Northeast Asia via AA-induced coupled atmosphere-land surface and cloud feedbacks, rather than through a direct impact of AA changes on cloud condensation nuclei. The modelling results also imply that the abrupt summer surface warming and increases in hot temperature extremes over Northeast Asia since the mid-1990s will probably sustain in the next few decades as GHG concentrations continue to increase and AA precursor emissions over both North America and Europe continue to decrease.展开更多
Recent trends in seasonal cycles in China are analyzed, based on a homogenized dataset of daily temperatures at 541 stations during the period 1960–2008. Several indices are defined for describing the key features of...Recent trends in seasonal cycles in China are analyzed, based on a homogenized dataset of daily temperatures at 541 stations during the period 1960–2008. Several indices are defined for describing the key features of a seasonal cycle, including local winter/summer （LW/LS） periods and local spring/autumn phase （LSP/LAP）. The Ensemble Empirical Mode Decomposition method is applied to determine the indices for each year. The LW period was found to have shortened by 2–6 d （10 yr）-1, mainly due to an earlier end to winter conditions, with the LW mean temperature having increased by 0.2°C–0.4°C （10 yr）？1, over almost all of China. Records of the most severe climate extremes changed less than more typical winter conditions did. The LS period was found to have lengthened by 2–4 d （10 yr）？1, due to progressively earlier onsets and delayed end dates of the locally defined hot period. The LS mean temperature increased by 0.1°C–0.2°C （10 yr）-1 in most of China, except for a region in southern China centered on the mid-lower reaches of the Yangtze River. In contrast to the winter cases, the warming trend in summer was more prominent in the most extreme records than in those of more typical summer conditions. The LSP was found to have advanced significantly by about 2 d （10 yr）-1 in most of China. Changes in the autumn phase were less prominent. Relatively rapid changes happened in the 1980s for most of the regional mean indices dealing with winter and in the 1990s for those dealing with summer.展开更多
Under the impacts of climate change and human activities, great uncertainties still exist in the response of climate extremes, especially in Central Asia (CA). In this study, we investigated spatial-temporal variation...Under the impacts of climate change and human activities, great uncertainties still exist in the response of climate extremes, especially in Central Asia (CA). In this study, we investigated spatial-temporal variation trends and abrupt changes in 17 indices of climate extremes, based on daily climate observations from 55 meteorological stations in CA during 1957-2005. We also speculated as to which atmospheric circulation factors had the greatest impacts on climate extremes. Our results indicated that the annual mean temperature (Tav), mean maximum and minimum temperature significantly increased at a rate of 0.32ºC/10a, 0.24ºC/10a and 0.41ºC/10a, respectively, which was far higher than the increasing rates either globally or across the Northern Hemisphere. Other temperature extremes showed widespread significant warming trends, especially for those indices derived from daily minimum temperature. All temperature extremes exhibited spatially widespread rising trends. Compared to temperature changes, precipitation extremes showed higher spatial and temporal variabilities. The annual total precipitation significantly increased at a rate of 4.76 mm/10a, and all precipitation extremes showed rising trends except for annual maximum consecutive dry days (CDD), which significantly decreased at a rate of -3.17 days/10a. On the whole, precipitation extremes experienced slight wetter trends in the Tianshan Mountains, Kazakhskiy Melkosopochnik (Hill), the Kyzylkum Desert and most of Xinjiang. The results of Cumulative Deviation showed that Tav and Txav had a significant abrupt change around 1987, and all precipitation indices experienced abrupt changes in 1986. Spearman’s correlation analysis pointed to Siberian High and Tibetan Plateau Index_B as possibly being the most important atmospheric circulation factors affecting climate extremes in CA. A full quantitative understanding of these changes is crucial for the management and mitigation of natural hazards in this region.展开更多
Given that climate extremes in China might have serious regional and global consequences, an increasing number of studies are examining temperature extremes in China using the Coupled Model Intercomparison Project Pha...Given that climate extremes in China might have serious regional and global consequences, an increasing number of studies are examining temperature extremes in China using the Coupled Model Intercomparison Project Phase 5 （CMIP5） models. This paper investigates recent changes in temperature extremes in China using 25 state-of-the-art global climate models participating in CMIP5. Thirteen indices that represent extreme temperature events were chosen and derived by daily maximum and minimum temperatures, including those representing the intensity （absolute indices and threshold indices）, duration （duration indices）, and frequency （percentile indices） of extreme temperature. The overall performance of each model is summarized by a ＂portrait＂ diagram based on relative root-mean-square error, which is the RMSE relative to the median RMSE of all models, revealing the multi-model ensemble simulation to be better than individual model for most indices. Compared with observations, the models are able to capture the main features of the spatial distribution of extreme temperature during 1986-2005. Overall, the CMIP5 models are able to depict the observed indices well, and the spatial structure of the ensemble result is better for threshold indices than frequency indices. The spread amongst the CMIP5 models in different subregions for intensity indices is small and the median CMIP5 is close to observations; however, for the duration and frequency indices there can be wide disagreement regarding the change between models and observations in some regions. The model ensemble also performs well in reproducing the observational trend of temperature extremes. All absolute indices increase over China during 1961-2005.展开更多
Trends in the frequencies of four temperature extremes （the occurrence of warm days, cold days, warm nights and cold nights） with respect to a modulated annual cycle （MAC）, and those associated exclusively with we...Trends in the frequencies of four temperature extremes （the occurrence of warm days, cold days, warm nights and cold nights） with respect to a modulated annual cycle （MAC）, and those associated exclusively with weather-intraseasonal fluctuations （WIF） in eastern China were investigated based on an updated homogenized daily maximum and minimum temperature dataset for 1960–2008. The Ensemble Empirical Mode Decomposition （EEMD） method was used to isolate the WIF, MAC, and longer-term components from the temperature series. The annual, winter and summer occurrences of warm （cold） nights were found to have increased （decreased） significantly almost everywhere, while those of warm （cold） days have increased （decreased） in northern China （north of 40°N）. However, the four temperature extremes associated exclusively with WIF for winter have decreased almost everywhere, while those for summer have decreased in the north but increased in the south. These characteristics agree with changes in the amplitude of WIF. In particular, winter WIF of maximum temperature tended to weaken almost everywhere, especially in eastern coastal areas （by 10%–20%）; summer WIF tended to intensify in southern China by 10%–20%. It is notable that in northern China, the occurrence of warm days has increased, even where that associated with WIF has decreased significantly. This suggests that the recent increasing frequency of warm extremes is due to a considerable rise in the mean temperature level, which surpasses the effect of the weakening weather fluctuations in northern China.展开更多
基金supported by National Natural Science Foundation of China[grant number 42305041].
文摘Deforestation has a significant influence on the hydrological cycle.Understanding the impact of deforestation on precipitation extremes is crucial for addressing global environmental challenges.This study investigates the impact of deforestation on precipitation extremes(R95p index,which represents the total amount of precipitation exceeding the 95th percentile of the reference period)in China,using outputs from three earth system models(CanESM5,IPSL-CM6A-LR,and MIROC-ES2L).All models,along with their multimodel mean,indicate a general decrease in R95p in Northeast China and southern China,and changes in Northwest China and the Tibetan Plateau are minimal.In contrast,the responses are model-dependent in the Huanghuai and Jianghuai regions.The overall nationwide multimodel mean suggests an annual R95p decrease of 10.7 mm,with individual model variations ranging from-28.0 to 2.0 mm.Further analysis using precipitation extremes scaling reveals a high spatial correlation with direct precipitation extremes changes on both annual and seasonal scales,albeit with slightly smaller magnitudes.Decomposing the response into dynamic and thermodynamic scaling,the authors find that dynamic contributions predominantly drive the changes in precipitation extremes on both annual and seasonal scales.The authors findings highlight the substantial role of dynamic processes in modulating the response of precipitation extremes to deforestation in China.
基金supported by the funding Riset Unggulan Daerah 2022 of the Bureau of Development Planning and Research in Central Java Province(BAPPEDA Provinsi Jawa Tengah).
文摘Located downstream the Kupang Catchment in Indonesia,Pekalongan faces significant land subsidence issues,leading to severe coastal flooding.This study aimed to assess the impact of climate change on future flow regimes and hydrological extremes to inform long-term water resources management strategies for the Kupang Catchment.Utilizing precipitation and air temperature data from general circulation models in the Coupled Model Intercomparison Project 6(CMIP6)and employing bias correction techniques,the Soil and Water Assessment Tool(SWAT)hydrological model was employed to analyze climate-induced changes in hydrological fluxes,specifically streamflow.Results indicated a consistent increase in monthly streamflow during the wet season,with a substantial rise of 22.8%,alongside a slight decrease of 18.0%during the dry season.Moreover,both the frequency and severity of extremely low and high flows were projected to intensify by approximately 50%and 70%,respectively,for a 20-year return period,suggesting heightened flood and drought risks in the future.The observed declining trend in low flow,by up to 11%,indicated the potential for long-term groundwater depletion exacerbating the threat of land subsidence and coastal flooding,especially in areas with inadequate surface water management policies and infrastructure.
基金jointly supported by the National Natural Science Foundation of China (Grant Nos.42422502 and 42275038)the China Meteorological Administration Climate Change Special Program (Grant No.QBZ202306)funded by the Met Office Climate Science for Service Partnership (CSSP) China project under the International Science Partnerships Fund (ISPF)。
文摘This past year, 2024, is on track to be the warmest year, joining 2023 as the two hottest years on record. With the exceptional heat, weather and climate extremes were common across the world. In particular, 2024 has seen a remarkable run of extreme precipitation events and resulting impacts. Here, we provide an overview of the most notable extreme events of the year, including extreme precipitation and floods, tropical cyclones, and droughts. The characteristics and impacts of these extreme events are summarized, followed by discussion on the physical drivers and the role of global warming.Finally, we also discuss the future prospects in extreme event studies, including impact-based perspectives, challenges in attribution of precipitation extremes, and the existing gap to minimize impacts from climate extremes.
基金supported by the National Natural Science Foundation of China(Grant Nos.42150204 and 2288101)supported by the China National Postdoctoral Program for Innovative Talents(BX20230045)the China Postdoctoral Science Foundation(2023M730279)。
文摘A nonlinear multi-scale interaction(NMI)model was proposed and developed by the first author for nearly 30 years to represent the evolution of atmospheric blocking.In this review paper,we first review the creation and development of the NMI model and then emphasize that the NMI model represents a new tool for identifying the basic physics of how climate change influences mid-to-high latitude weather extremes.The building of the NMI model took place over three main periods.In the 1990s,a nonlinear Schr?dinger(NLS)equation model was presented to describe atmospheric blocking as a wave packet;however,it could not depict the lifetime(10-20 days)of atmospheric blocking.In the 2000s,we proposed an NMI model of atmospheric blocking in a uniform basic flow by making a scale-separation assumption and deriving an eddyforced NLS equation.This model succeeded in describing the life cycle of atmospheric blocking.In the 2020s,the NMI model was extended to include the impact of a changing climate mainly by altering the basic zonal winds and the magnitude of the meridional background potential vorticity gradient(PVy).Model results show that when PVy is smaller,blocking has a weaker dispersion and a stronger nonlinearity,so blocking can be more persistent and have a larger zonal scale and weaker eastward movement,thus favoring stronger weather extremes.However,when PVy is much smaller and below a critical threshold under much stronger winter Arctic warming of global warming,atmospheric blocking becomes locally less persistent and shows a much stronger westward movement,which acts to inhibit local cold extremes.Such a case does not happen in summer under global warming because PVy fails to fall below the critical threshold.Thus,our theory indicates that global warming can render summer-blocking anticyclones and mid-to-high latitude heatwaves more persistent,intense,and widespread.
基金supported by a Forest Health Monitoring(FHM)award from the USDA Forest Service(Grant No.:19-DG-11083150-030)to Dr.Weimin Xi。
文摘Texas experienced the worst drought in its 100-year history in 2011,resulting in the death of approximately 300 million trees.The high number of sudden deaths had a significant impact on forest ecosystems.This study aimed to gain insight into the long-term and combined impacts of drought-induced forest tree deaths and their effects on biomass.This study used data obtained from 1797 National Forest Inventory(NFI)plots to analyze trends and major causes of changes in tree biomass at the sample plot level in East Texas forests over the past 20 years(2000-2019).In this study,forest trees in East Texas were divided into diameter at breast height(dbh),height,stand types,latitude,elevation,ecological zones,and FIA Unit.Principal component analysis(PCA)was also performed using drought intensity,drought duration,the four competing factor indicators,and the biomass loss rate of forest trees to better understand r drought impacts on forest trees.The results showed the lowest biomass loss rate of Pine species.Similarly,trees with shorter height and smaller dbh experienced a higher biomass loss rate.A higher biomass loss rate was observed in natural forests,West Gulf Coastal Plain and Plain and Southern East Texas ecoregion experienced higher biomass loss.Principal component analyses of drought intensity,drought duration,and the four competing metrics revealed that overall drought was the main contributor to biomass loss rates,and that drought intensity and drought duration had comparable effects on biomass loss rates.
基金supported by the National Key R&D Program of China(2021YFD2200405)the National Natural Science Foundationof China(Nos.U23A2002,31930078,and 31670450)the Fundamental Research Funds for ICBR(1632021023,1632019006,and1630032023002).
文摘Climate changes in cold-temperate zones are increasingly altering the state of climatic constraints on photosynthesis and growth,leading to adaptive changes in plant phenology and subsequent seasonal carbon assimilation.However,the spatio-temporal patterns of climatic constraints and seasonal carbon assimilation are poorly understood.In this study,the timing of peak photosynthetic activity(DOY_(pmax))was employed as a proxy for plant adap-tive state to climatic constraints on growth to examine the spatio-temporal dynamics of DOY_(pmax).By using multiple remote sensing metrics,DOY_(pmax)was characterized with changes in the solar-induced chlorophyll fluorescence(SIF)and leaf area index(LAI)from 2000 to 2018.Based on SIF,the DOY_(pmax)was generally around day 190,while based on LAI was about 10 d later.Peak photosynthetic activity of forests occurs earlier compared to other vegetation types.Overall,the advanced DOY_(pmax)were observed based on both SIF and LAI,with annual rates of 0.2(P=0.31)and 0.3(P<0.05)d,respectively.DOY_(pmax)dynamics were influ-enced by hot temperature extremes and vapor pressure defi-cits(VPD)during the early growing season,regardless of sub-zone and different vegetation type.The generalized lin-ear mixed model(GLMM)showed the largest contribution by hot extremes to DOY_(pmax)dynamics accounted for 55.5%(DOY_(pmax_SIF))and 49.1%(DOY_(pmax_LAI)),respectively,fol-lowed by VPD(DOY_(pmax_SIF):23.1%;DOY_(pmax_LAI):29.5%).These findings highlight the crucial role of climate extremes in shaping seasonal carbon dynamics and regional carbon balance.
基金supported by the National Natural Science Foundation of China[grant number 42175066]the Shanghai International Science and Technology Partnership Project[grant number 21230780200].
文摘The likelihood of extreme heat occurrence is continuously increasing with global warming.Under high temperatures,humidity may exacerbate the heat impact on humanity.As atmospheric humidity depends on moisture availability and is constrained by air temperature,it is important to project the changes in the distribution of atmospheric humidity conditional on air temperature as the climate continuously warms.Here,a non-crossing quantile smoothing spline is employed to build quantile regression models emulating conditional distributions of dew point(a measure of humidity)on local temperature evolving with escalating global mean surface temperature.By applying these models to 297 weather stations in seven regions in China,the study analyzes historical trends of humid-heat and dry-hot days,and projects their changes under global warming of 2.0℃ and 4.5℃.In response to global warming,rising trends of humid-heat extremes,while weakening trends of dry-hot extremes,are observed at most stations in Northeast China.Additionally,results indicate an increasing trend in dry-hot extremes at numerous stations across central China,but a rise in humid-heat extremes over Northwest China and coastal regions.These trends found in the current climate state are projected to intensify under 2.0℃ and 4.5℃ warming,possibly influenced by the heterogeneous variations in precipitation,soil moisture,and water vapor fluxes.Requiring much lower computational resources than coupled climate models,these quantile regression models can further project compound humidity and temperature extremes in response to different levels of global warming,potentially informing the risk management of compound humid-heat extremes on a local scale.
基金supported by the National Natural Science Foundation of China(72072169)the Fundamental Re-search Funds for the Central Universities(YD2040002015).
文摘The impact of extreme temperatures on the health of individuals in different organizations remains uncertain.We employed stratified analyses to examine the impacts of summer(April-September)daily maximum temperatures and winter(October-March)daily minimum temperatures on blood pressure and lipid profiles across government staff,com-pany employees,and researchers.We examined 209,477 physical examination records from a physical examination center in the First Affiliated Hospital of USTC from 2017 to 2021.Employing a segmented regression model within the frame-work of generalized linear regression(GLM),we examined the causal impact of extreme temperatures on health outcomes.Additionally,sensitivity analyses were conducted via distributed lag nonlinear models(DLNMs),with a focus on ob-serving the long-term effects over a period of 21 days.Our findings indicate that government staff face increased health risks during extremely low temperatures,regardless of the season.Compared with participants experiencing median tem-peratures,government staff exposed to extremely low temperatures(below the 10th percentile,below 24℃)in the sum-mer presented maximum increases of 2.32 mmHg(95%CI:1.542-3.098)in diastolic blood pressure and 6.481 mmHg(95%CI:5.368-7.594)in systolic blood pressure.In winter,government staff exposed to temperatures below the 10th per-centile(below 1℃)demonstrated maximum increases of 0.278 mmol/L(95%CI:0.210-0.346)in total cholesterol,0.153 mmol/L(95%CI:0.032-0.274)in triglycerides,and 0.077 mmol/L(95%CI:0.192-0.134)in low-density lipoprotein.Conversely,warm winters benefit company employees,whereas researchers exhibit lower sensitivity to temperature changes in winter.The maximum temperatures in summer and minimum temperatures in winter had greater impacts on in-dividuals.Small temperature fluctuations impact health more than large changes do.Notably,both the maximum and min-imum temperatures were better predictors of health outcomes than the daily average temperature was.Blood pressure con-sistently displayed significant associations with temperature across all three groups,with extremely low temperatures in-creasing the risk and extremely high temperatures reducing it.However,the relationship between temperature and blood lipids is complex.
基金jointly supported by the National Natural Science Foundation of China (42275038)China Meteorological Administration Climate Change Special Program (QBZ202306)Robin CLARK was funded by the Met Office Climate Science for Service Partnership (CSSP) China project under the International Science Partnerships Fund (ISPF)
文摘Globally,2023 was the warmest observed year on record since at least 1850 and,according to proxy evidence,possibly of the past 100000 years.As in recent years,the record warmth has again been accompanied with yet more extreme weather and climate events throughout the world.Here,we provide an overview of those of 2023,with details and key background causes to help build upon our understanding of the roles of internal climate variability and anthropogenic climate change.We also highlight emerging features associated with some of these extreme events.Hot extremes are occurring earlier in the year,and increasingly simultaneously in differing parts of the world(e.g.,the concurrent hot extremes in the Northern Hemisphere in July 2023).Intense cyclones are exacerbating precipitation extremes(e.g.,the North China flooding in July and the Libya flooding in September).Droughts in some regions(e.g.,California and the Horn of Africa)have transitioned into flood conditions.Climate extremes also show increasing interactions with ecosystems via wildfires(e.g.,those in Hawaii in August and in Canada from spring to autumn 2023)and sandstorms(e.g.,those in Mongolia in April 2023).Finally,we also consider the challenges to research that these emerging characteristics present for the strategy and practice of adaptation.
基金supported by the National Natural Science Foundation of China[grant numbers 42175066,41875087,42030601,and 42105017]the Shanghai Municipal Natural Science Fund[grant number 20ZR1407400]the Shanghai Pujiang Program[grant number 20PJ1401600]。
文摘Summer weather extremes(e.g.,heavy rainfall,heat waves)in China have been linked to anomalies of summer monsoon circulations.The East Asian subtropical westerly jet(EASWJ),an important component of the summer monsoon circulations,was investigated to elucidate the dynamical linkages between its intraseasonal variations and local weather extremes.Based on EOF analysis,the dominant mode of the EASWJ in early summer is characterized by anomalous westerlies centered over North China and anomalous easterlies centered over the south of Japan.This mode is conducive to the occurrence of precipitation extremes over Central and North China and humid heat extremes over most areas of China except Northwest and Northeast China.The centers of the dominant mode of the EASWJ in late summer extend more to the west and north than in early summer,and induce anomalous weather extremes in the corresponding areas.The dominant mode of the EASWJ in late summer is characterized by anomalous westerlies centered over the south of Lake Baikal and anomalous easterlies centered over Central China,which is favorable for the occurrence of precipitation extremes over northern and southern China and humid heat extremes over most areas of China except parts of southern China and northern Xinjiang Province.The variability of the EASWJ can influence precipitation and humid heat extremes by driving anomalous vertical motion and water vapor transport over the corresponding areas in early and late summer.
文摘Modification signs in extreme weather events may be directly related to alterations in the thermodynamic panorama of the atmosphere that need to be better understood. This study aimed to make a first interconnection between climate extremes and thermodynamic patterns in the city of Rio de Janeiro. Maximum and minimum air temperature and precipitation extreme indices from two surface meteorological stations (ABOV and STCZ) and instability indices based on temperature and humidity from radiosonde observations (SBGL) were employed to investigate changes in the periods 1964-1980 (P1), 1981-2000 (P2), and 2001-2020 (P3). Statistical tests were adopted to determine the significance and magnitude of trends. The frequency of warm (cold) days and warm (cold) nights are increasing (decreasing) in the city. Cold (Warm) extremes are changing with greater magnitude in ABOV (STCZ) than in STCZ (ABOV). In ABOV, there is a significant increase of +84 mm/decade in the rainfall volume associated with severe precipitation (above the 95<sup>th</sup> percentile) and most extreme precipitation indices show an increase in frequency and intensity. In STCZ, there is a decrease in extreme precipitation until the 1990s, and from there, an increase, showing a wetter climate in the most recent years. It is also verified in SBGL that there is a statistically significant increase (decrease) in air temperature of +0.1°C/decade (-0.2°C/decade) and relative humidity of +1.2%/decade (-3%/decade) at the low and middle (high) troposphere. There is a visible rising trend in most of the evaluated instability indices over the last few decades. The increasing trends of some extreme precipitation indices are probably allied to the precipitable water increasing trend of +1.2 mm/decade.
基金This research was supported by the National Key Research and Development Program of China(Grant Nos.2017YFA0603804 and 2018YFC1507704)the Natural Science Foundation of China(Grant No.41805048).
文摘Based on climate extreme indices calculated from a high-resolution daily observational dataset in China during 1961–2005,the performance of 12 climate models from phase 6 of the Coupled Model Intercomparison Project(CMIP6),and 30 models from phase 5 of CMIP(CMIP5),are assessed in terms of spatial distribution and interannual variability.The CMIP6 multi-model ensemble mean(CMIP6-MME)can simulate well the spatial pattern of annual mean temperature,maximum daily maximum temperature,and minimum daily minimum temperature.However,CMIP6-MME has difficulties in reproducing cold nights and warm days,and has large cold biases over the Tibetan Plateau.Its performance in simulating extreme precipitation indices is generally lower than in simulating temperature indices.Compared to CMIP5,CMIP6 models show improvements in the simulation of climate indices over China.This is particularly true for precipitation indices for both the climatological pattern and the interannual variation,except for the consecutive dry days.The arealmean bias for total precipitation has been reduced from 127%(CMIP5-MME)to 79%(CMIP6-MME).The most striking feature is that the dry biases in southern China,very persistent and general in CMIP5-MME,are largely reduced in CMIP6-MME.Stronger ascent together with more abundant moisture can explain this reduction in dry biases.Wet biases for total precipitation,heavy precipitation,and precipitation intensity in the eastern Tibetan Plateau are still present in CMIP6-MME,but smaller,compared to CMIP5-MME.
基金supported by the National Natural Science Foundation of China(Grant Nos.41230527,41025017 and 41175041)
文摘Interannual variations in the number of winter extreme warm and cold days over eastern China （EC） and their relationship with the Arctic Oscillation （AO） and E1 Nifio-Southern Oscillation （ENSO） were investigated using an updated temperature dataset comprising 542 Chinese stations during the period 1961- 2011. Results showed that the number of winter extreme warm （cold） days across EC experienced a significant increase （decrease） around the mid-1980s, which could be attributed to interdecadal variation of the East Asian Winter Monsoon （EAWM）. Probability distribution functions （PDFs） of winter temperature extremes in different phases of the AO and ENSO were estimated based on Generalized Extreme Value Distribution theory. Correlation analysis and the PDF technique consistently demonstrated that interannual variation of winter extreme cold days in the northern part of EC （NEC） is closely linked to the AO, while it is most strongly related to the ENSO in the southern part （SEC）. However, the number of winter extreme warm days across EC has little correlation with both AO and ENSO. Furthermore, results indicated that, whether before or after the mid-1980s shift, a significant connection existed between winter extreme cold days in NEC and the AO. However, a significant connection between winter extreme cold days in SEC and the ENSO was only found after the mid-1980s shift. These results highlight the different roles of the AO and ENSO in influencing winter temperature extremes in different parts of EC and in different periods, thus providing important clues for improving short-term climate prediction for winter temperature extremes.
基金National Natural Science Foundation of China, No.41071324 No.41201550+5 种基金 No.40730526 Humanities and Social Sciences Project from the Ministry of Education, No.12YJCZtt257 The Innovation Program of Shanghai Municipal Education Commission, No. 13YZ061 No.13ZZ035 Open Fund of Key Laboratory of Geographic Information Science, East China Normal University, No.KLGIS2011A04 The Fundamental Re- search Funds for the Central Universities, and the Key Subject Development Project of the Shanghai Munici- pal Education Commission, No.J50402
文摘China is physically and socio-economically susceptible to global warming-derived high temperature extremes because of its vast area and high urban population density. This article presents a scenario-based analysis method for high temperature extremes aimed at illustrating the latter＇s hazardous potential and exposure across China. Based on probability analysis, high temperature extreme scenarios with return periods of 5, 10, 20, and 50 years were designed, with a high temperature hazard index calculated by integrating two differen- tially-weighted extreme temperature indices （maximum temperature and high temperature days）. To perform the exposure analysis, a land use map was employed to determine the spatial distribution of susceptible human activities under the different scenarios. The results indicate that there are two heat-prone regions and a sub-hotspot occupying a relatively small land area. However, the societal and economic consequences of such an environmental im- pact upon the North China Plain and middle/lower Yangtze River Basin would be substantial due to the concentration of human activities in these areas.
基金We acknowledge the World Climate Research Programme＇s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups （listed in Table l） for producing and making available their model output. This research is supported by the National Key Research and Development Program of China （2017YFA0603804） and the State Key Program of National Natural Science Foundation of China （41230528）.
文摘The long-term goal of the 2015 Paris Agreement is to limit global warming to well below 2 ℃above pre-industrial levels and to pursue efforts to limit it to 1.5 ℃. However, for climate mitigation and adaption efforts, further studies are still needed to understand the regional consequences between the two global warming limits. Here we provide an assessment of changes in temperature extremes over China （relative to 1986-2005） at 1.5 ℃ and 2 ℃ warming levels （relative to 1861-1900） by using the 5th phase of the Coupled Model Intercomparison Project （CMIP5） models under three RCP scenarios （RCP2.6, RCP4.5, RCP8.5）. Results show that the increases in mean temperature and temperature extremes over China are greater than that in global mean temperature. With respect to 1986-2005, the temperature of hottest day （TXx） and coldest night （TNn） are projected to increase about 1/1.6 ℃ and 1.1/1.8 ℃, whereas warm days （TX90p） and warm spell duration （WSDI） will increase about 7.5/13.8% and 15/30 d for the 1.5/2 ℃ global warming target, respectively. Under an additional 0.5 ℃ global warming, the projected increases of temperature in warmest day/night and coldest day/night are both more than 0.5 ℃ across almost the whole China. In Northwest China, Northeast China and the Tibetan Plateau, the projected changes are particularly sensitive to the additional 0.5 ℃ global warming, for example, multi-model mean increase in coldest day （TXn） and coldest night （TNn） will be about 2 times higher than a change of 0.5 ℃ global warming. Although the area-averaged changes in temperature extremes are very similar for different scenarios, spatial hotspot still exists, such as in Northwest China and North China, the increases in temperatures are apparently larger in RCP8.5 than that in RCP4.5.
基金supported by the UK– China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) of China, as part of the Newton Fundsupported by the UK National Centre for Atmospheric Science–Climate (NCAS– Climate) at the University of Reading
文摘This study investigated the drivers and physical processes for the abrupt decadal summer surface warming and increases in hot temperature extremes that occurred over Northeast Asia in the mid-1990s. Observations indicate an abrupt increase in summer mean surface air temperature （SAT） over Northeast Asia since the mid-1990s. Accompanying this abrupt surface wanning, significant changes in some temperature extremes, characterized by increases in summer mean daily maximum temperature （Tmax）, daily minimum temperature （Train）, annual hottest day temperature （TXx）, and annual warmest night temperature （TNx） were observed. There were also increases in the frequency of summer days （SU） and tropical nights （TR）. Atmospheric general circulation model experiments forced by changes in sea surface temperature （SST）/sea ice extent （SIE）, anthropogenic greenhouse gas （GHG） concentrations, and anthropogenic aerosol （AA） forcing, relative to the period 1964- 93, reproduced the general patterns of observed summer mean SAT changes and associated changes in temperature extremes, although the abrupt decrease in precipitation since the mid-1990s was not simulated. Additional model experiments with different forcings indicated that changes in SST/SIE explained 76% of the area-averaged summer mean surface warming signal over Northeast Asia, while the direct impact of changes in GHG and AA explained the remaining 24% of the surface warming signal. Analysis of physical processes indicated that the direct impact of the changes in AA （through aerosol- radiation and aerosol-cloud interactions）, mainly related to the reduction of AA precursor emissions over Europe, played a dominant role in the increase in TXx and a similarly important role as SST/SIE changes in the increase in the frequency of SU over Northeast Asia via AA-induced coupled atmosphere-land surface and cloud feedbacks, rather than through a direct impact of AA changes on cloud condensation nuclei. The modelling results also imply that the abrupt summer surface warming and increases in hot temperature extremes over Northeast Asia since the mid-1990s will probably sustain in the next few decades as GHG concentrations continue to increase and AA precursor emissions over both North America and Europe continue to decrease.
基金supported bythe National Basic Research Program of China (Grant No.2009CB421401)Qian was supported by the National Natural Science Foundation of China (Grant No. 41005039)The work of Xia and Zhou was partly supported by astrategic research grant from the City University of HongKong (Grant No. SRG-Fd 7002505)
文摘Recent trends in seasonal cycles in China are analyzed, based on a homogenized dataset of daily temperatures at 541 stations during the period 1960–2008. Several indices are defined for describing the key features of a seasonal cycle, including local winter/summer （LW/LS） periods and local spring/autumn phase （LSP/LAP）. The Ensemble Empirical Mode Decomposition method is applied to determine the indices for each year. The LW period was found to have shortened by 2–6 d （10 yr）-1, mainly due to an earlier end to winter conditions, with the LW mean temperature having increased by 0.2°C–0.4°C （10 yr）？1, over almost all of China. Records of the most severe climate extremes changed less than more typical winter conditions did. The LS period was found to have lengthened by 2–4 d （10 yr）？1, due to progressively earlier onsets and delayed end dates of the locally defined hot period. The LS mean temperature increased by 0.1°C–0.2°C （10 yr）-1 in most of China, except for a region in southern China centered on the mid-lower reaches of the Yangtze River. In contrast to the winter cases, the warming trend in summer was more prominent in the most extreme records than in those of more typical summer conditions. The LSP was found to have advanced significantly by about 2 d （10 yr）-1 in most of China. Changes in the autumn phase were less prominent. Relatively rapid changes happened in the 1980s for most of the regional mean indices dealing with winter and in the 1990s for those dealing with summer.
基金National Natural Science Foundation of China,No.41630859The CAS "Light of West China" Program,No.2015-XBQN-B-17
文摘Under the impacts of climate change and human activities, great uncertainties still exist in the response of climate extremes, especially in Central Asia (CA). In this study, we investigated spatial-temporal variation trends and abrupt changes in 17 indices of climate extremes, based on daily climate observations from 55 meteorological stations in CA during 1957-2005. We also speculated as to which atmospheric circulation factors had the greatest impacts on climate extremes. Our results indicated that the annual mean temperature (Tav), mean maximum and minimum temperature significantly increased at a rate of 0.32ºC/10a, 0.24ºC/10a and 0.41ºC/10a, respectively, which was far higher than the increasing rates either globally or across the Northern Hemisphere. Other temperature extremes showed widespread significant warming trends, especially for those indices derived from daily minimum temperature. All temperature extremes exhibited spatially widespread rising trends. Compared to temperature changes, precipitation extremes showed higher spatial and temporal variabilities. The annual total precipitation significantly increased at a rate of 4.76 mm/10a, and all precipitation extremes showed rising trends except for annual maximum consecutive dry days (CDD), which significantly decreased at a rate of -3.17 days/10a. On the whole, precipitation extremes experienced slight wetter trends in the Tianshan Mountains, Kazakhskiy Melkosopochnik (Hill), the Kyzylkum Desert and most of Xinjiang. The results of Cumulative Deviation showed that Tav and Txav had a significant abrupt change around 1987, and all precipitation indices experienced abrupt changes in 1986. Spearman’s correlation analysis pointed to Siberian High and Tibetan Plateau Index_B as possibly being the most important atmospheric circulation factors affecting climate extremes in CA. A full quantitative understanding of these changes is crucial for the management and mitigation of natural hazards in this region.
基金supported by the National Basic Key Project (also called 973 Project, Grant Nos. 2010CB950501 and 2010CB950102)the R&D Special Fund for Public Welfare Industry (meteorology) (Grant No. GYHY 201306019)the National Natural Science Foundation of China (Grant No. 41275078)
文摘Given that climate extremes in China might have serious regional and global consequences, an increasing number of studies are examining temperature extremes in China using the Coupled Model Intercomparison Project Phase 5 （CMIP5） models. This paper investigates recent changes in temperature extremes in China using 25 state-of-the-art global climate models participating in CMIP5. Thirteen indices that represent extreme temperature events were chosen and derived by daily maximum and minimum temperatures, including those representing the intensity （absolute indices and threshold indices）, duration （duration indices）, and frequency （percentile indices） of extreme temperature. The overall performance of each model is summarized by a ＂portrait＂ diagram based on relative root-mean-square error, which is the RMSE relative to the median RMSE of all models, revealing the multi-model ensemble simulation to be better than individual model for most indices. Compared with observations, the models are able to capture the main features of the spatial distribution of extreme temperature during 1986-2005. Overall, the CMIP5 models are able to depict the observed indices well, and the spatial structure of the ensemble result is better for threshold indices than frequency indices. The spread amongst the CMIP5 models in different subregions for intensity indices is small and the median CMIP5 is close to observations; however, for the duration and frequency indices there can be wide disagreement regarding the change between models and observations in some regions. The model ensemble also performs well in reproducing the observational trend of temperature extremes. All absolute indices increase over China during 1961-2005.
基金sponsored by the National Basic Research Program of China (GrantNo. 2011CB952000)the National Natural Science Foundation of China (Grant Nos. 41005039 and40810059003)+1 种基金Yan and Tu were sponsored by the National Basic Research Program of China (Grant No.2009CB421401)Wu was sponsored by the National Science Foundation of USA (ATM-0653136, ATM-0917743)
文摘Trends in the frequencies of four temperature extremes （the occurrence of warm days, cold days, warm nights and cold nights） with respect to a modulated annual cycle （MAC）, and those associated exclusively with weather-intraseasonal fluctuations （WIF） in eastern China were investigated based on an updated homogenized daily maximum and minimum temperature dataset for 1960–2008. The Ensemble Empirical Mode Decomposition （EEMD） method was used to isolate the WIF, MAC, and longer-term components from the temperature series. The annual, winter and summer occurrences of warm （cold） nights were found to have increased （decreased） significantly almost everywhere, while those of warm （cold） days have increased （decreased） in northern China （north of 40°N）. However, the four temperature extremes associated exclusively with WIF for winter have decreased almost everywhere, while those for summer have decreased in the north but increased in the south. These characteristics agree with changes in the amplitude of WIF. In particular, winter WIF of maximum temperature tended to weaken almost everywhere, especially in eastern coastal areas （by 10%–20%）; summer WIF tended to intensify in southern China by 10%–20%. It is notable that in northern China, the occurrence of warm days has increased, even where that associated with WIF has decreased significantly. This suggests that the recent increasing frequency of warm extremes is due to a considerable rise in the mean temperature level, which surpasses the effect of the weakening weather fluctuations in northern China.
