2023: Weather and Climate Extremes Hitting the Globe with Emerging Features

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.

Evaluation and Projection of Population Exposure to Temperature Extremes over the Beijing−Tianjin−Hebei Region Using a High-Resolution Regional Climate Model RegCM4 Ensemble

Temperature extremes over rapidly urbanizing regions with high population densities have been scrutinized due to their severe impacts on human safety and economics.First of all,the performance of the regional climate model RegCM4 with a hydrostatic or non-hydrostatic dynamic core in simulating seasonal temperature and temperature extremes was evaluated over the historical period of 1991–99 at a 12-km spatial resolution over China and a 3-km resolution over the Beijing−Tianjin−Hebei(JJJ)region,a typical urban agglomeration of China.Simulations of spatial distributions of temperature extremes over the JJJ region using RegCM4 with hydrostatic and non-hydrostatic cores showed high spatial correlations of more than 0.8 with the observations.Under a warming climate,temperature extremes of annual maximum daily temperature(TXx)and summer days(SU)in China and the JJJ region showed obvious increases by the end of the 21st century while there was a general reduction in frost days(FD).The ensemble of RegCM4 with different land surface components was used to examine population exposure to temperature extremes over the JJJ region.Population exposure to temperature extremes was found to decrease in 2091−99 relative to 1991−99 over the majority of the JJJ region due to the joint impacts of increases in temperature extremes over the JJJ and population decreases over the JJJ region,except for downtown areas.Furthermore,changes in population exposure to temperature extremes were mainly dominated by future population changes.Finally,we quantified changes in exposure to temperature extremes with temperature increase over the JJJ region.This study helps to provide relevant policies to respond future climate risks over the JJJ region.

Response of drought to climate extremes in a semi-arid inland river basin in China

Against the backdrop of global warming,climate extremes and drought events have become more severe,especially in arid and semi-arid areas.This study forecasted the characteristics of climate extremes in the Xilin River Basin(a semi-arid inland river basin)of China for the period of 2021–2100 by employing a multi-model ensemble approach based on three climate Shared Socioeconomic Pathway(SSP)scenarios(SSP1-2.6,SSP2-4.5,and SSP5-8.5)from the latest Coupled Model Intercomparison Project Phase 6(CMIP6).Furthermore,a linear regression,a wavelet analysis,and the correlation analysis were conducted to explore the response of climate extremes to the Standardized Precipitation Evapotranspiration Index(SPEI)and Streamflow Drought Index(SDI),as well as their respective trends during the historical period from 1970 to 2020 and during the future period from 2021 to 2070.The results indicated that extreme high temperatures and extreme precipitation will further intensify under the higher forcing scenarios(SSP5-8.5>SSP2-4.5>SSP1-2.6)in the future.The SPEI trends under the SSP1-2.6,SSP2-4.5,and SSP5-8.5 scenarios were estimated as–0.003/a,–0.004/a,and–0.008/a,respectively,indicating a drier future climate.During the historical period(1970–2020),the SPEI and SDI trends were–0.003/a and–0.016/a,respectively,with significant cycles of 15 and 22 a,and abrupt changes occurring in 1995 and 1996,respectively.The next abrupt change in the SPEI was projected to occur in the 2040s.The SPEI had a significant positive correlation with both summer days(SU)and heavy precipitation days(R10mm),while the SDI was only significantly positively correlated with R10mm.Additionally,the SPEI and SDI exhibited a strong and consistent positive correlation at a cycle of 4–6 a,indicating a robust interdependence between the two indices.These findings have important implications for policy makers,enabling them to improve water resource management of inland river basins in arid and semi-arid areas under future climate uncertainty.

Towards a Link between Climate Extremes and Thermodynamic Patterns in the City of Rio de Janeiro-Brazil: Climatological Aspects and Identified Changes

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 95th 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.

Projection of precipitation extremes over South Asia from CMIP6 GCMs

Extreme precipitation events are one of the most dangerous hydrometeorological disasters,often resulting in significant human and socio-economic losses worldwide.It is therefore important to use current global climate models to project future changes in precipitation extremes.The present study aims to assess the future changes in precipitation extremes over South Asia from the Coupled Model Intercomparison Project Phase 6(CMIP6)Global Climate Models(GCMs).The results were derived using the modified Mann-Kendall test,Sen's slope estimator,student's t-test,and probability density function approach.Eight extreme precipitation indices were assessed,including wet days(RR1mm),heavy precipitation days(RR10mm),very heavy precipitation days(RR20mm),severe precipitation days(RR50mm),consecutive wet days(CWD),consecutive dry days(CDD),maximum 5-day precipitation amount(RX5day),and simple daily intensity index(SDII).The future changes were estimated in two time periods for the 21^(st) century(i.e.,near future(NF;2021-2060)and far future(FF;2061-2100))under two Shared Socioeconomic Pathway(SSP)scenarios(SSP2-4.5 and SSP5-8.5).The results suggest increases in the frequency and intensity of extreme precipitation indices under the SSP5-8.5 scenario towards the end of the 21^(st) century(2061-2100).Moreover,from the results of multimodel ensemble means(MMEMs),extreme precipitation indices of RR1mm,RR10mm,RR20mm,CWD,and SDII demonstrate remarkable increases in the FF period under the SSP5-8.5 scenario.The spatial distribution of extreme precipitation indices shows intensification over the eastern part of South Asia compared to the western part.The probability density function of extreme precipitation indices suggests a frequent(intense)occurrence of precipitation extremes in the FF period under the SSP5-8.5 scenario,with values up to 35.00 d for RR1mm and 25.00-35.00 d for CWD.The potential impacts of heavy precipitation can pose serious challenges to the study area regarding flooding,soil erosion,water resource management,food security,and agriculture development.

HadISDH.extremes Part Ⅱ:Exploring Humid Heat Extremes Using Wet Bulb Temperature Indices

Heat events may be humid or dry.While several indices incorporate humidity,such combined indices obscure identification and exploration of heat events by their different humidity characteristics.The new HadISDH.extremes global gridded monitoring product uniquely provides a range of wet and dry bulb temperature extremes indices.Analysis of this new data product demonstrates its value as a tool for quantifying exposure to humid verses dry heat events.It also enables exploration into“stealth heat events”,where humidity is high,perhaps enough to affect productivity and health,while temperature remains moderate.Such events may not typically be identified as“heat events”by temperature-focused heat indices.Over 1973-2022,the peak magnitude of humid extremes(maximum daily wet bulb temperature over a month;T_(w)X)for the global annual mean increased significantly at 0.13±0.04℃(10 yr)^(−1),which is slightly slower than the global annual mean T_(w) increase of 0.22±0.04℃(10 yr)^(−1).The frequency of moderate humid extreme events per year(90th per-centile daily maxima wet bulb temperature exceedance;T_(w)X90p)also increased significantly at 4.61±1.07 d yr^(−1)(10 yr)^(−1).These rates were slower than for temperature extremes,TX and TX90p,which respectively increased significantly at 0.27±0.04℃(10 yr)^(−1) and 5.53±0.72 d yr^(−1)(10 yr)^(−1).Similarly,for the UK/Europe focus region,JJA-mean T_(w)X increased significantly,again at a slower rate than for TX and mean T_(w).HadISDH.extremes shows some evidence of“stealth heat events”occurring where humidity is high but temperature remains more moderate.

HadISDH.extremes Part Ⅰ:A Gridded Wet Bulb Temperature Extremes Index Product for Climate Monitoring

HadISDH.extremes is an annually updated global gridded monthly monitoring product of wet and dry bulb temperature–based extremes indices,from January 1973 to December 2022.Data quality,including spatial and temporal stability,is a key focus.The hourly data are quality controlled.Homogeneity is assessed on monthly means and used to score each gridbox according to its homogeneity rather than to apply adjustments.This enables user-specific screening for temporal stability and avoids errors from inferring adjustments from monthly means for the daily maximum values.For general use,a score(HQ Flag)of 0 to 6 is recommended.A range of indices are presented,aligning with existing standardised indices.Uniquely,provision of both wet and dry bulb indices allows exploration of heat event character—whether it is a“humid and hot”,“dry and hot”or“humid and warm”event.It is designed for analysis of long-term trends in regional features.HadISDH.extremes can be used to study local events,but given the greater vulnerability to errors of maximum compared to mean values,cross-validation with independent information is advised.

Erratum to: A Two-plume Convective Model forPrecipitation Extremes

Erratum to:Yin,Z.H.,P.X.Dai,and J.Nie,2021:A two-plume convective model for precipitation extremes.Adv.Atmos.Sci.,38(6),957−965,https://doi.org/10.1007/s00376-021-0404-8.

Evaluation of IMERG, TMPA, ERA5, and CPC precipitation products over China's Mainland: Spatiotemporal patterns and extremes

A comprehensive assessment of representative satellite-retrieved(Integrated Multi-satellite Retrievals for Global Precipitation Measurement(IMERG)and Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis(TMPA)),reanalysis-based(fifth generation of atmospheric reanalysis by the European Centre for Medium Range Weather Forecasts(ERA5)),and gauge-estimated(Climate Prediction Center(CPC))precipitation products was conducted using the data from 807 meteorological stations across China's Mainland from 2001 to 2017.Error statistical metrics,precipitation distribution functions,and extreme precipitation indices were used to evaluate the quality of the four precipitation products in terms of multi-timescale accuracy and extreme precipitation estimation.When the timescale increased from daily to seasonal scales,the accuracy of the four precipitation products first increased and then decreased,and all products performed best on the monthly timescale.Their accuracy ranking in descending order was CPC,IMERG,TMPA,and ERA5 on the daily timescale and IMERG,CPC,TMPA,and ERA5 on the monthly and seasonal timescales.IMERG was generally superior to its predecessor TMPA on the three timescales.ERA5 exhibited large statistical errors.CPC provided stable estimated values.For extreme precipitation estimation,the quality of IMERG was relatively consistent with that of TMPA in terms of precipitation distribution and extreme metrics,and IMERG exhibited a significant advantage in estimating moderate and heavy precipitation.In contrast,ERA5 and CPC exhibited poor performance with large systematic underestimation biases.The findings of this study provide insight into the performance of the latest IMERG product compared with the widely used TMPA,ERA5,and CPC datasets,and points to possible directions for improvement of multi-source precipitation data fusion algorithms in order to better serve hydrological applications.

Corrigendum to:“Spectrum-tailored random fiber laser towards ICF laser facility”[Matter and Radiation at Extremes 8,025902(2023)]

The third paragraph in Sec.IV REGENERATIVE AMPLIFICATION erroneously states“In other words,the distribution of spectral components is time-dependent,and the spectral distortion in the amplification process will not change the time-domain shape.”

The impacts of the East Asian subtropical westerly jet on weather extremes over China in early and late summer

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.

Does CMIP6 Inspire More Confidence in Simulating Climate Extremes over China?

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.

Recent Trends in Winter Temperature Extremes in Eastern China and their Relationship with the Arctic Oscillation and ENSO

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.

Changes in temperature extremes over China under 1.5 ℃ and 2 ℃ global warming targets

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.

Abrupt Summer Warming and Changes in Temperature Extremes over Northeast Asia Since the Mid-1990s: Drivers and Physical Processes

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.

Changes in Seasonal Cycle and Extremes in China during the Period 1960–2008

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.

Assessment of Indices of Temperature Extremes Simulated by Multiple CMIP5 Models over China

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.

Trends in Temperature Extremes in Association with Weather-Intraseasonal Fluctuations in Eastern China

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.

Trends of Temperature Extremes in China and their Relationship with Global Temperature Anomalies

Changes of temperature extremes over China were evaluated using daily maximum and minimum temperature data from 591 stations for the period 1961-2002. A set of indices of warm extremes, cold extremes and daily temperature range （DTR） extremes was studied with a focus on trends. The results showed that the frequency of warm extremes （F WE） increased obviously in most parts of China, and the intensity of warm extremes （I WE） increased significantly in northern China. The opposite distribution was found in the frequency and intensity of cold extremes. The frequency of high DTR extremes was relatively uniform with that of intensity： an obvious increasing trend was located over western China and the east coast, while significant decreases occurred in central, southeastern and northeastern China; the opposite distribution was found for low DTR extreme days. Seasonal trends illustrated that both F WE and I WE showed signifi- cant increasing trends, especially over northeastern China and along the Yangtze Valley basin in spring and winter. A correlation technique was used to link extreme temperature anomalies over China with global temperature anomalies. Three key regions were identified, as follows： northeastern China and its coastal areas, the high-latitude regions above 40~0N, and southwestern China and the equatorial eastern Pacific.

Changes of Temperature and Precipitation Extremes in Hengduan Mountains,Qinghai-Tibet Plateau in 1961-2008

Variations and trends in extreme climate events are more sensitive to climate change than the mean values, and so have received much attention. In this study, twelve indices of temperature extremes and 11 indices of precipita- tion extremes at 32 meteorological stations in Hengduan Mountains were examined for the period 1961-2008. The re- suits reveal statistically significant increases in the temperature of the warmest and coldest nights and in the frequen- cies of extreme warm days and nights. Decreases of the diurnal temperature range and the numbers of frost days and ice days are statistically significant. Regional averages of growing season length also display the trends consistent and significant with warming. At a large proportion of the stations, patterns of temperature extremes are consistent with warming since 1961： warming trends in minimum temperature indices are greater than those relating to maximum temperature. As the center of the Shaluli Mountain, the warming magnitudes decrease from inner to outer. Changes in precipitation extremes is low： trends are difficult to detect against the larger inter-annual and decadal-scale variability of precipitation, and only the wet day precipitation and the regional trend in consecutive dry days are significant at the 0.05 level. It can be concluded that the variation of extreme precipitation events is not obvious in the Hengduan Mountains, however, the regional trends generally decrease from the south to the north. Overall, the spatial distribution of temporal changes of all extreme climate indices in the Hengduan Mountains illustrated here reflects the climatic complexity in mountainous regions.