Projection of temperature change and extreme temperature events in the Lancang–Mekong River basin

The Lancang–Mekong River basin(LMRB) is under increasing threat from global warming. In this paper, the projection of future climate in the LMRB is explored by focusing on the temperature change and extreme temperature events. First, the authors evaluate the bias of temperature simulated by the Weather Research and Forecasting model. Then, correction is made for the simulation by comparing with observation based on the non-parametric quantile mapping using robust empirical quantiles(RQUANT) method. Furthermore, using the corrected model results, the future climate projections of temperature and extreme temperature events in this basin during 2016–35, 2046–65, and 2080–99 are analyzed. The study shows that RQUANT can effectively reduce the bias of simulation results. After correction, the simulation can capture the spatial features and trends of mean temperature over the LMRB, as well as the extreme temperature events. Besides, it can reproduce the spatial and temporal distributions of the major modes. In the future, the temperature will keep increasing, and the warming in the southern basin will be more intense in the wet season than the dry season. The number of extreme high-temperature days exhibits an increasing trend, while the number of extreme low-temperature days shows a decreasing trend. Based on empirical orthogonal function analysis, the dominant feature of temperature over this basin shows a consistent change. The second mode shows a seesaw pattern.

Human influence on the duration of extreme temperature events in Asia's hotspot regions

Observations and models indicate that human activities exert a considerable impact on the frequency and intensity of extreme temperature events,which are associated with global warming.However,changes in the duration of extreme temperature events and their association with human influence have not been considered in most studies.Thus,the possible relationship between the observed changes in the warm and cold spell duration(WSDI and CSDI)in hotspot regions during 1960-2014 and human influence was investigated based on the NCEP/NCAR reanalysis version 1 and Coupled Model Inter-comparison Project Phase 6(CMIP6)data.Constraint projection based on these attribution results was also performed.The optimal fingerprinting technique was used to compare observed changes in WSDI and CSDI to simulated changes averaged across eight CMIP6 models.Results show that anthropogenic(ANT)forcing contributed to the observed increase in WSDI in the three hotspot regions(West Asia,South Asia and Southeast Asia),with the majority of the changes being attributed to greenhouse gas forcing.However,a generally weak ANT signal can be observed in the decreasing trend of CSDI and can be detected in South and Southeast Asia.The influence of aerosol forcing remains undetected in either WSDI or CSDI,which differs from the results for frequency and intensity of extreme temperatures.The attribution results revealed that the constrained projection of WSDI is lower than the raw projection for 2015-2100 in West Asia and Southeast Asia.However,no differences in future CSDI changes are found in Southeast Asia between the constrained and raw projections.

Spatiotemporal Variability in Extreme Temperature Events in an Arid-Semiarid Region of China and Their Teleconnections with Large-Scale Atmospheric Circulation

With a warming climate,temperature extremes have been a main global issue in recent decades due to their potential influence on the sustainable development of human life and natural ecosystems.In this study,12 indicators of extreme temperature events are used to evaluate the spatiotemporal distribution,periodic structure and teleconnections with large-scale atmospheric circulation in Xinjiang,Northwest China by combining wavelet coherence(WTC) analysis based on continuous wavelet transform(CWT) analysis with the sequential Mann-Kendall test.We find that over the past six decades,the climate in Xinjiang has become warmer and has suffered from increases in the frequency of warm extremes and decreases in the frequency of cold extremes.Warm extremes have mainly occurred in the southern Tianshan Mountains surrounding the Tarim Basin and western part of the Taklamakan Desert,and cold extremes have primarily occurred in the southwestern Altai Mountains and northern foot of the Tianshan Mountains.Extreme temperature events,including warm extremes,cold extremes,and other temperature indices,have significant interannual variability,with the main oscillation periods at smaller(2–4-year band),intermediate(4–7-year band),and greater time scales in recent decades.Furthermore,cold-extreme indices,including frost days,cool days,and cool nights all show a clear changepoint during 1990–1997 at the 95% confidence level,and both ice days and cold spell duration indicator have a potential changepoint during 1981–1986.However,the changing points for warmextreme indices are detected during 1992–1998.The temperature variables are significantly correlated with the EI Ni?o-Southern Oscillation(ENSO) and Arctic Oscillation(AO),but less well correlated with the Pacific Decadal Oscillation(PDO).The phase difference in the WTC spectra is not uniform between temperature extremes and climatic oscillations.Our findings will have important implications for local governments in taking effective measures to mitigate the potential effects of regional climate warming due to human activities in Xinjiang.

Intra-seasonal Features of an Extreme High Temperature Event in 2011 in Eastern China and Its Atmospheric Circulation

Based on the daily maximum air temperature(T_(max))data from the China Meteorological Data Network and the NCEP/DOE reanalysis data,the intra-seasonal circulation and evolution of an extreme high temperature event(EHTE)in the middle reaches of the Yangtze River(MYR)from August 9-21,2011 were explored,as well as the influence of diabatic heating on the position variation of the Western Pacific subtropical high(WPSH).Results show that the daily T_(max) in the MYR exhibits a vigorous intraseasonal oscillation(ISO)of 10-25 days in the extended summer of 1980-2018.The main factors affecting the EHTE in the summer of 2011 are the low-frequency wave train propagating southeastward in the mid-latitude of the upper troposphere and the low-frequency anticyclone moving northwestward in the lowlatitude of the mid-lower troposphere.The diagnosis of 925hPa thermodynamic equation indicates that the ISO features of the T_(max) in the core region is determined by the intra-seasonal variation of the adiabatic variation.In addition,the variations of the WPSH correspond well to the distribution of apparent heat source.In the early stage of the high temperature process,the apparent heat source in the north of the Bay of Bengal is a certain indicator for the westward extension of the WPSH.

Spatial-Temporal Characteristics of Regional Extreme Low Temperature Events in China during 1960-2009

An objective identification technique is used to detect regional extreme low temperature events （RELTE） in China during 1960-2009. Their spatial-temporal characteristics are analyzed. The results indicate that the lowest temperatures of RELTE, together with the frequency distribution of the geometric latitude center, exhibit a double-peak feature. The RELTE frequently happen near the geometric area of 30°N and 42°N before the mid-1980s, but shifted afterwards to 30°N. During 1960-2009, the frequency~ intensity, and the maximum impacted area of RELTE show overall decreasing trends. Due to the contribution of RELTE, with long duratioh and large spatial range, which account for 10% of the total RELTE, there is a significant turning point in the late 1980s. A change to a much more steady state after the late 1990s is identified. In addition, the integrated indices of RELTE are classified and analyzed.

Study on Temporal-spatial Change Characteristics of the Extremely Low Temperature Climate Event in Winter of China

[ Objective] The research aimed to study temporal-spatial change characteristics of the extremely low temperature climate event in winter of China. [MethodI By using actual probability distribution threshold value method, EOF analysis method and the daily minimum temperature data in winter of 1961 -2008 at 195 observatories of China, temporal-spatial change characteristics of the extremely low temperature climate event in win- ter of China in 48 years were analyzed. [ Result] Threshold value calculated by actual probability distribution was higher than that by traditional method, and increase magnitude in east was bigger than that in west, which could describe climatic change situation in China in 48 years better than traditional method. Cold night number in winter of China did not decrease as latitude declined, and it was more in south and north and was less in Yellow River basin and northwest China. Cold night number was the most in northeast Inner Mongolia. Interannual change of the cold night number presented decline tendency. From the 1960s to the eady 1970s, cold night number consistently increased, and change in middle and late periods of the 1960s was severe. From the early 1970s to the middle 1980s, fluctuation of the cold night number was bigger, and increase of the cold night number was the most in 1976. Cold night number from 1986 to the 21= century continuously declined. Change of the cold night number was the most obvious in east region, Guizhou and north Guangxi. Cold night number in northeast China and north Inner Mongolia presented inverting change relationship with that in Yunnan - Kweichow Plateau and Hexi Corridor. [ Conclusion] The research provided reference for eady warning of the extremely low temoerature event in China.

Investigation of Arctic air temperature extremes at north of 60°N in winter

Air temperature is a key index reflecting climate change. Air temperature extremes are very important because they strongly influence the natural environment and societal activities. The Arctic air temperature extremes north of 60°N are investigated in the winter. Daily data from 238 stations at north of 60°N from the global summary of the day for the period 1979–2015 are used to study the trends of cold days, cold nights, warm days and warm nights during the wintertime. The results show a decreasing trend of cold days and nights（rate of –0.2 to –0.3 d/a） and an increasing trend of warm days and nights（rate of ＋0.2 to ＋0.3 d/a） in the Arctic. The mean temperature increases,which contributes to the increasing（decreasing） occurrence of warm（cold） days and nights. On the other hand,the variance at most stations decreased, leading to a reduced number of cold events. A positive AO（Arctic Oscillation） index leads to an increased（decreased） number of warm（cold） days and nights over northern Europe and western Russia and an increased（decreased） number of cold（warm） days and nights over the Bering Strait and Greenland. The lower extent of Arctic autumn sea ice leads to a decreased number of cold days and nights.The occurrences of abrupt changes are detected using the Mann-Kendall method for cold nights occurring in Canada in 1998 and for warm nights occurring in northwestern Eurasia in 1988. This abrupt change mainly resulted from the mean warming induced by south winds and an increased North Atlantic sea surface temperature.

Increases in Anthropogenic Heat Release from Energy Consumption Lead to More Frequent Extreme Heat Events in Urban Cities

With economic development and rapid urbanization,increases in Gross Domestic Product and population in fastgrowing cities since the turn of the 21st Century have led to increases in energy consumption.Anthropogenic heat flux released to the near-surface atmosphere has led to changes in urban thermal environments and severe extreme temperature events.To investigate the effects of energy consumption on urban extreme temperature events,including extreme heat and cold events,a dynamic representation scheme of anthropogenic heat release(AHR)was implemented in the Advanced Research version of the Weather Research and Forecasting(WRF)model,and AHR data were developed based on energy consumption and population density in a case study of Beijing,China.Two simulations during 1999−2017 were then conducted using the developed WRF model with 3-km resolution with and without the AHR scheme.It was shown that the mean temperature increased with the increase in AHR,and more frequent extreme heat events were produced,with an annual increase of 0.02−0.19 days,as well as less frequent extreme cold events,with an annual decrease of 0.26−0.56 days,based on seven extreme temperature indices in the city center.AHR increased the sensible heat flux and led to surface energy budget changes,strengthening the dynamic processes in the atmospheric boundary layer that reduce AHR heating efficiency more in summer than in winter.In addition,it was concluded that suitable energy management might help to mitigate the impact of extreme temperature events in different seasons.

Trends of summertime extreme temperatures in the Arctic

Extreme temperature events can influence the natural environment and societal activities more so than mean temperature events. This study used daily data from 238 stations north of 60°N, obtained from the Global Summary of the Day dataset for the period 1979~015, to investigate the trends of summertime extreme temperature. The results revealed most stations north of 60°N with trends of decrease in the number of cold days （nights） and increase in the number of warm clays （nights）. The regional average results showed trends of consistent decline （rise） of cold days and nights （warm days and nights） in Eurasia and Greenland. Similarly, the trends of the seasonal maximum and minimum values were most significant in these regions. In summer, of three indices considered （i.e., Arctic Oscillation, Arctic dipole, and E1 Nifi^Southem Oscillation）, the largest contributor to the trends of extreme temperature events was the Arctic dipole. Prevailing southerly winds in summer brought warm moist air across northern Eurasia and Greenland, conducive to increased numbers of warm days （nights） and decreased numbers of cold day （nights）. Moreover, we defined extreme events using different thresholds and found the spatial distributions of the trends were similar.

Analysis on Changes of Basic Climatic Elements and Extreme Events in Xinjiang, China during 1961-2010

By using the observation data from 89 weather stations in Xinjiang during 1961-2010, this paper analyzed the basic climatic elements including temperature, precipitation, wind speed, sunshine duration, water vapor pressure, and dust storm in the entire Xinjiang and the subareas: North Xinjiang, Tianshan Mountains, and South Xinjiang. The results indicate that from 1961 to 2010 the annual and seasonal mean temperatures in the entire Xinjiang show an increasing trend with the increasing rate rising from south to north. The increasing rate of annual mean minimum temperature is over twice more than that of the annual mean maximum temperature, contributing much to the increase in the annual averages. The magnitude of the decrease rate of low-temperature days is larger than the increase rate of high-temperature days. The increase of warm days and warm nights and the decrease of cold days and cold nights further reveal that the temperature increasing in Xinjiang is higher. In addition, annual and seasonal rainfalls have been increasing. South Xinjiang experiences higher increase in rainfall amounts than North Xinjiang and Tianshan Mountains. Annual rainy days, longest consecutive rainy days, the daily maximum precipitation and extreme precipitation events, annual torrential rain days and amount, annual blizzard days and amount, all show an increasing trend, corresponding to the increasing in annual mean water vapor pressure. This result shows that the humidity has increased with temperature increasing in the past 50 years. The decrease in annual mean wind speed and gale days lessen the impact of dust storm, sandstorm, and floating dust events. The increase in annual rainy days is the cause of the decrease in annual sunshine duration, while the increase in spring sunshine duration corresponds with the decrease in dust weather. Therefore, the increase in precipitation indicators, the decrease in gales and dust weather, and the increasing in sunshine duration in spring will be beneficial to crops growth.

Distribution Characteristics of Winter Continuous Extreme Low Temperature in China

[Objective] The research aimed to study the distribution characteristics of winter continuous extreme low temperature in China. [Method] Based on the daily minimum temperature data in winter during 1961-2008 in 195 observatories, the continuous extreme low temperature event (cold night) which happened in winter in China and the distribution characteristics of accumulated temperature anomaly in 48 years were analyzed by using the actual probability distribution threshold method. [Result] Besides in Northeast China, Northwest China and Qinghai-Tibet Plateau where the geographical position was northerly, and the altitude was high, the long-time (above 5 d) extreme low temperature event was also easy to happen in the south of Yangtze River, especially in Guizhou, Guangxi, Hunan and so on. The continuous extreme low temperature event in the middle and lower reaches of Yellow River was the least. Started from the metaphase of the 1980s, the frequency trend of continuous extreme low temperature event decreased. But in 1992, 2000 and 2007, the low temperature event which continued above 7 d was more than the average. The accumulated cold in January in 48 years was the strongest. The second one was in February, and the smallest was in December. The accumulated cold in Northeast China and the north of Inner Mongolia was the biggest in December and January. The accumulated cold in the north of Xinjiang was the biggest in February. In the whole winter, the accumulated cold in Qinghai-Tibet Plateau was the smallest. The chilling injury was easier to happen in Guizhou, Guangxi and Hunan than other south areas in December and February. The occurrence probability of chilling injury in most areas of Szechwan Basin, Yunnan and Qinling Mountains in central China was smaller than that in other areas. [Conclusion] The research provided the reference basis for analyzing the influence of chilling injury on the agriculture in China.

MULTIMODEL CONSENSUS FORECASTING OF LOW TEMPERATURE AND ICY WEATHER OVER CENTRAL AND SOUTHERN CHINA IN EARLY 2008

Based on the daily mean temperature and 24-h accumulated total precipitation over central and southern China, the features and the possible causes of the extreme weather events with low temperature and icing conditions,which occurred in the southern part of China during early 2008, are investigated in this study. In addition, multimodel consensus forecasting experiments are conducted by using the ensemble forecasts of ECMWF, JMA, NCEP and CMA taken from the TIGGE archives. Results show that more than a third of the stations in the southern part of China were covered by the extremely abundant precipitation with a 50-a return period, and extremely low temperature with a 50-a return period occurred in the Guizhou and western Hunan province as well. For the 24- to 216-h surface temperature forecasts, the bias-removed multimodel ensemble mean with running training period(R-BREM) has the highest forecast skill of all individual models and multimodel consensus techniques. Taking the RMSEs of the ECMWF 96-h forecasts as the criterion, the forecast time of the surface temperature may be prolonged to 192 h over the southeastern coast of China by using the R-BREM technique. For the sprinkle forecasts over central and southern China, the R-BREM technique has the best performance in terms of threat scores(TS) for the 24- to 192-h forecasts except for the 72-h forecasts among all individual models and multimodel consensus techniques. For the moderate rain, the forecast skill of the R-BREM technique is superior to those of individual models and multimodel ensemble mean.

Changes in Extreme Maximum Temperature Events and Population Exposure in China under Global Warming Scenarios of 1.5 and 2.0°C: Analysis Using the Regional Climate Model COSMO-CLM

We used daily maximum temperature data（1986–2100） from the COSMO-CLM（COnsortium for Small-scale MOdeling in CLimate Mode） regional climate model and the population statistics for China in 2010 to determine the frequency, intensity, coverage, and population exposure of extreme maximum temperature events（EMTEs） with the intensity–area–duration method. Between 1986 and 2005（reference period）, the frequency, intensity, and coverage of EMTEs are 1330–1680 times yr^–1, 31.4–33.3℃, and 1.76–3.88 million km^2, respectively. The center of the most severe EMTEs is located in central China and 179.5–392.8 million people are exposed to EMTEs annually. Relative to 1986–2005, the frequency, intensity, and coverage of EMTEs increase by 1.13–6.84, 0.32–1.50, and15.98%–30.68%, respectively, under 1.5℃ warming; under 2.0℃ warming, the increases are 1.73–12.48, 0.64–2.76,and 31.96%–50.00%, respectively. It is possible that both the intensity and coverage of future EMTEs could exceed the most severe EMTEs currently observed. Two new centers of EMTEs are projected to develop under 1.5℃ warming, one in North China and the other in Southwest China. Under 2.0℃ warming, a fourth EMTE center is projected to develop in Northwest China. Under 1.5 and 2.0℃ warming, population exposure is projected to increase by 23.2%–39.2% and 26.6%–48%, respectively. From a regional perspective, population exposure is expected to increase most rapidly in Southwest China. A greater proportion of the population in North, Northeast, and Northwest China will be exposed to EMTEs under 2.0℃ warming. The results show that a warming world will lead to increases in the intensity, frequency, and coverage of EMTEs. Warming of 2.0℃ will lead to both more severe EMTEs and the exposure of more people to EMTEs. Given the probability of the increased occurrence of more severe EMTEs than in the past, it is vitally important to China that the global temperature increase is limited within 1.5℃.

On Prediction of Record-Breaking Daily Temperature Events

The daily maximum/minimum temperature data at 740 stations in China from 1960 to 2005 were ana-lyzed to reveal the statistical characteristics of record-breaking（RB）daily extreme temperature events in the past 46 yr.It is verified that the observational daily extreme temperatures obey the Gaussian distribution. The expected values of RB extreme temperatures were obtained based on both the Gaussian distribution model and the initial condition of observed historical RB high/low temperature events after tedious the-oretical derivation.The results were then compared with those obtained by the iteration computation of the pure theoretical model.The comparison suggests that the results from the former are more consistent with the observations than those from the latter.Based on the above analyses,prediction of future possible RB high/low temperature events is made,and the spatial distributions of maximum/minimum theoretical values of their intensities are also given.It is indicated that the change amplitudes of future extreme temperatures differ evidently from place to place,showing a remarkable regional feature：the future extremely high temperature events will have a strong rising intensity in Southwest China,and a relatively weak rising intensity in western China;while the largest decrease of the future extremely low temperature events will appear in Northeast China and the north of Northwest China,and the decrease will be maintained relatively stable in space in Central China and Southwest China,in comparison with the historical low temperature pattern.Features in the occurrence time of the future RB temperature events are also illustrated.