Changes In Extreme Temperature Events Research Articles

Exploring Climate Change Impacts on Temperature Extremes in the South Saskatchewan River Watershed, Alberta, Canada

In recent years, the frequency and intensity of extreme temperature events have escalated, posing unprecedented challenges to ecosystems, economies, and human health. As global temperatures rise, these events are emerging as critical threats; therefore, understanding their changes is essential for developing strategies to mitigate their growing risks under global warming. In this study, we used ETCCDI (Expert Team on Climate Change Detection, Monitoring, and Indices) temperature indices to analyze future changes in extreme temperature events in the South Saskatchewan River Watershed (SSRW) in Southern Alberta, Canada, a critical area for irrigation, agriculture, and food production. This analysis is based on an ensemble of 26 Global Circulation Models (GCMs) and three Shared Socio-economic Pathway (SSP) scenarios, in three periods (2015–2030, 2041–2060, 2071–2100), compared against the base period of 1951–1990. The results suggest substantial changes in most of the studied indices towards higher temperatures, with a significant rise in both the numbers of days with extreme temperatures and the magnitude of the temperature itself, as well as a notable drop in the number of cold days. As a result of warming, the growing season length is 16 days longer in 2015–2030 compared to the base period and is projected to increase substantially by the end of the century. A longer growing season might seem favourable for agriculture, but it can disrupt water availability and cause unpleasant environmental consequences. Overall, the scenarios considered in this research suggest that the SSRW could experience warming at a significant rate. This finding underscores the urgent need for adaptation and mitigation actions to enhance resilience and sustainability.

Analyzing Extreme Temperature Patterns in Subtropical Highlands Climates: Implications for Disaster Risk Reduction Strategies

This study utilized hot and cold indices to evaluate the changes in extreme temperature events that occurred in subtropical highland climates from 1991 to 2020. The modified Mann–Kendall (MMK) test and the Theil–Sen (TS) slope estimator were used to analyze the linear trends in the time series of the extreme temperature indices. The northern highlands of Pakistan (NHP) were considered as a case study region. The results showed that the annual maximum temperature had a slightly increasing tendency (at the rate of 0.14 °C/decade), while the annual minimum temperature had a slightly decreasing tendency (at the rate of −0.02 °C/decade). However, these trends were not significant at the 5% significance level. The decadal averages of the hot indices were the highest in the second decade (2000s), while they were the lowest in the subsequent decade (2010s). In comparison, all the cold indices except the annual minimum value of the maximum temperature (TXn) showed a persistent decline in their decadal averages throughout the 2000s and 2010s. Overall, the frequency of hot days significantly increased in the NHP during the study period. This study found that the hot days and coldest days increased over the past three decades in the NHP. However, there was a decreasing trend in the cold spell duration, cold nights, and the coldest nights over the past three decades, as demonstrated by the trends of the cold spell duration index (CSDI), the temperature of cold nights (TN10p), and the annual minimum value of the minimum temperature (TNn) indices. These changes may impact the environment, human health, and agricultural operations. The findings provide useful insights into the shifting patterns of extreme temperature events in northern Pakistan and have crucial implications for the climate-change-adaptation and resilience-building initiatives being undertaken in the region. It is suggested that the continuous monitoring of extreme temperature events is necessary to comprehend their effects on the region and devise strategies for sustainable development.

Analysis of Frost Probabilities in Aydın, Türkiye

Frost events are of particular importance for plants. Its occurrence determines growing season. Early or late frost events may cause injuries and damage in plants which have not yet entered dormancy in fall/winter, and for plants in flowering period in winter/spring. Global average temperature increase has been accompanied by changes in extreme temperature events. Observations have shown that there has been a decreasing pattern in frequencies and intensities of frost events. In this sense, it is aimed in this study to analyse probabilities of frost occurrences within the latest 30-year climatic normal period, from the cold period of 1991-1992 to that of 2020-2021, at five locations (Aydın, Kuşadası, Nazilli, Söke ve Sultanhisar) in the province Aydın, western Türkiye. Six frost indices were selected, and three temperature thresholds to define frost were considered when daily minimum temperature (TMIN) being equal to or less than 0.0, -1.2 or -2.3°C.The selected frost indices are first fall frost (FFF), last spring frost (LSF), frost period (FP), number of frost days (NFD), dates of frost occurrences (DFO) and consecutive frost days (CFD). The results revealed that Nazilli and Sultanhisar are characterized by the highest probabilities of frost in terms of frequency, intensity and duration, along with the earliest occurrence of first fall frost and latest occurrences of last spring frost, and with longest duration of frost period. On the other hand, Kuşadası and Söke have opposite characteristics in comparison to Nazilli an Sultanhisar. Aydın lies in between them. The results are expected to provide information to schedule the agricultural activities, and to avoid detrimental impacts of frost events.

Changes in Extreme Temperature Events and Their Contribution to Mean Temperature Changes during Historical and Future Periods over Mainland China

Extreme climate events undoubtedly have essential impacts on terrestrial ecosystems, but the spatiotemporal patterns of extreme climate events at regional scales are unclear. In this study, based on observations and 14 CMIP6 global climate models, we analyzed the spatiotemporal changes in extreme temperature events at the mainland China scale and different basin scales in historical and future periods, and their relative importance for the changes in mean temperature (Tmean). The results show that at the mainland China scale in the historical period, extreme cold days and extreme cold nights significantly decreased, while Tmean, extreme warm days, and extreme warm nights significantly increased. However, the rates of increase in Tmean and extreme temperature events in the Continental Basin, Southwest Basin and Yellow River Basin are higher than that at the mainland China scale. The multi-model ensemble is the best model for simulating extreme temperature events in mainland China. At the mainland China scale in the future, the trends of Tmean and extreme temperature events are slow, rapid, and extremely rapid under SSP1-2.6, SSP2-4.5 and SSP5-8.5, respectively. In addition, the changes in the Continental Basin and Songhua and Liaohe River Basin are larger than those at the mainland China scale. In the historical and future periods, the extreme temperature events that have a great influence on the Tmean at the Chinese mainland scale and different basin scales are all related to the minimum temperature. The findings from this study can provide references for formulating scientific and reasonable regional-scale climate change policies.

Warming signals emerging from the analysis of daily changes in extreme temperature events over Pampas (Argentina)

Warming signals emerging from the analysis of daily changes in extreme temperature events over Pampas (Argentina)

Changes in extreme temperature events over Africa under 1.5 and 2.0°C global warming scenarios

AbstractFollowing the December 2015 Paris Agreement, there is an international effort to limit global warming at 1.5 and 2.0°C relative to the pre‐industrial level. However, there is inadequate research quantifying the difference in extreme temperature between the two target levels, especially in Africa. This study used historical and future low‐warming projections of NCAR‐CESM to assess the differences in extreme temperature events under 1.5 and 2.0°C future scenarios relative to the recent climate taken from 1976 to 2005 over Africa. The results show that compared with the present day, the magnitude of the highest temperature (TXx) will increase by approximately 1.6/2.2°C in 1.5/2.0°C warming worlds, with more substantial warming in Sahara and Southern Africa. The lowest temperature (TNn) will increase by ∼1.9/2.5°C in 1.5/2.0°C future climates, where SAH and SAF will experience a higher intensity of warming followed by Eastern Africa and Western Africa regions. The frequency of hot days (TX90p) is projected to increase with global warming across the continent, with a high increase in SAF and SAH. The frequency of cold days (TN10p) is expected to decrease with global warming in many parts of Africa except in WAF. In most regions, there were no apparent changes revealed in the Warm Spell Duration Indicator relative to the recent climate across the continent except SAH in 1.5 and 2.0°C warming levels, while a decrease in Cold Spell Duration Indicator will be in SAH. Assessment of the avoided impacts in 1.5 relative to 2.0°C indicates that limiting global warming at 1.5 rather than 2.0°C could reduce the intensity, frequency and duration of extreme temperatures from 3 to 81%. However, the magnitude of avoided impacts differs among indices and sub‐regions. Hence, it is paramount for the African continent to limit global warming at 1.5 instead of 2.0°C.

CMIP5-Based Spatiotemporal Changes of Extreme Temperature Events during 2021–2100 in Mainland China

The increasing number of extreme climate events is having a great impact on the terrestrial ecosystem. In this study, we applied a Taylor diagram to evaluate the 7 extreme temperature indices (ETI) of 12 models and the multi-model ensemble (MME) mean from phase 5 of the Coupled Model Intercomparison Project (CMIP5) during 1961–2005, and found that the MME has the best simulation effect. Warm indices and warm duration indices increase slowly, rapidly, and extremely under the representative concentration pathway 2.6 (RCP2.6), RCP4.5, and RCP8.5 scenarios, respectively. In contrast, the decrease in cold indices and cold duration indices are slow, rapid and extreme, respectively. The ETI from 2021–2100 under the RCP2.6 and RCP4.5 scenarios have primary periods ranging from 1–16 years. Under the RCP2.6 and RCP4.5 scenarios, the changes of warm indices are relatively largest in the basin of the central, and southeastern, while, under the RCP8.5 scenario, the changes are relatively significant, except for basin of northeast. The cold indices have the most significant decreasing trend in the Tibetan Plateau and its surrounding areas, under the three RCP scenarios. The findings from this study can provide reference for the risk management and prevention of climate disasters in the context of climate change in mainland China.

Estimating Changes in Temperature Distributions in a Large Ensemble of Climate Simulations Using Quantile Regression

Understanding future changes in extreme temperature events in a transient climate is inherently challenging. A single model simulation is generally insufficient to characterize the statistical properties of the evolving climate, but ensembles of repeated simulations with different initial conditions greatly expand the amount of data available. We present here a new approach for using ensembles to characterize changes in temperature distributions based on quantile regression that more flexibly characterizes seasonal changes. Specifically, our approach uses a continuous representation of seasonality rather than breaking the dataset into seasonal blocks; that is, we assume that temperature distributions evolve smoothly both day to day over an annual cycle and year to year over longer secular trends. To demonstrate our method’s utility, we analyze an ensemble of 50 simulations of the Community Earth System Model (CESM) under a scenario of increasing radiative forcing to 2100, focusing on North America. As previous studies have found, we see that daily temperature bulk variability generally decreases in wintertime in the continental mid- and high latitudes (>40°). A more subtle result that our approach uncovers is that differences in two low quantiles of wintertime temperatures do not shrink as much as the rest of the temperature distribution, producing a more negative skew in the overall distribution. Although the examples above concern temperature only, the technique is sufficiently general that it can be used to generate precise estimates of distributional changes in a broad range of climate variables by exploiting the power of ensembles.

Projected changes of temperature extremes over nine major basins in China based on the CMIP5 multimodel ensembles

Based on the outputs of 27 global climate models (GCMs) from the Coupled Model Inter-comparison Project Phase 5 (CMIP5), projected changes of extreme temperature events have been analyzed over nine river basins in China by the end of the twenty-first century relative to the reference period 1961–1990. The temporal and spatial changes and their projection uncertainty are studied using the extreme temperature indices defined by the Expert Team of Climate Change Detection and Indices (ETCCDI) under two Representative Concentration Pathways (RCPs). The model simulations predict a general increasing (decreasing) trend in warm (cold) extremes over China in the twenty-first century, with more pronounced warming trend under a higher emission scenario. The projected changes in cold and warm extremes exhibit a large difference in spatial patterns. The high-latitude and high-elevation regions of China (e.g., Continental and Southwest basins) are projected to respond more strongly to changes in cold extremes, while eastern and southern China (e.g., Yangtze River and Pearl River basins) tend to be more sensitive to the increases in warm extremes. In general, projected changes in cold indices based on minimum temperature tend to be more pronounced than in warm indices based on maximum temperature. Uncertainty analysis shows a large difference among the 27 GCMs under 2 RCP scenarios, and the uncertainty ranges tend to be larger under a higher emission scenario. Overall, the uncertainties in the emission scenarios are smaller than those from the climate models in the near future period. However, for the long-term climate projections (e.g., by the end of the twenty-first century), the projected difference under various emission scenarios tends to be larger than those by different climate models and hence can be the dominant contributor to the projection uncertainty of temperature indices.

Investigation of temperature and its indices under climate change scenarios over different regions of Rajasthan state in India

Abstract The ongoing increases in concentrations of atmospheric greenhouse gas will most likely affect global climate for the rest of this century. Global warming brings a huge provocation to society and human beings. Single extreme events and increased climate variability have a greater impact than long-term changes in the mean of climatic variables. This study analyzed the temperature projections for Rajasthan state, India using data obtain from two General Circulation Models (GFCM21 and HadCM3) for three Intergovernmental Panel on Climate Change (IPCC) Special Range of Emission Scenarios (SRES) A1B, A2, and B1. A 30 years of maximum (Tmax) and minimum (Tmin) temperature for the period 1976–2005 has been obtained from India Meteorological Department (IMD) and by using LARS-WG5 to generate the long-term weather series for three different periods i.e. 2011–2040 (2025s), 2041–2070 (2055s), and 2071–2100 (2085s). Further to determine the changes in extreme temperature events, the data for the baseline period and the future periods was represented by eight extreme temperature indices. Results illustrate that an increase in minimum and the maximum temperature are observed in all the three future periods. The average mean temperature for base period and three future periods over four regions of Rajasthan was observed highest in region 3 which shows an incessantly increased in mean temperature about 2.6 °C i.e. north-east and north-west part of Rajasthan. Two GCMs depicts that the incessant temperatures may be increase in the future and future maximum temperature in all the seasons varies from 2.43 °C to 4.27 °C in the direction from south to north of Rajasthan during 2071–2100. While for minimum temperature, the range of temperature changes varies from 0.23 °C to 1.42 °C from south-east to north-west of Rajasthan during 2011–2040. In the temperature indices, the number of tropical nights (TR20), warmest day (TX90p), warmest night (TN90p) and summer days (SU25) is expected to increase during all three future periods. The maximum changes was found in region 2 (39.4 days) and region 1 (38.8 days) during the 2071–2100 periods, followed by 2041–2070 and 2011–2040. In all the four regions, the annual occurrence of Cold Spells Duration Indicator (CSDI) decreased and Warm Spells Duration Indicator (WSDI) increased for all three future periods.

Changes in extreme temperature events over the Hindu Kush Himalaya during 1961–2015

This study uses the CMA (China Meteorological Administration) global land-surface daily air temperature dataset V1.0 (GLSATD V1.0) to analyze long-term changes in extreme temperature events over the Hindu Kush Himalaya (HKH) during 1961–2015. Results show there was a significant decrease in the number of extreme cold events (cold nights, cold days, and frost days) but a significant increase in the number of extreme warm events (warm nights, warm days, and summer days) over the entire HKH during 1961–2015. For percentile-based indices, trends of extreme events related to minimum temperature (Tmin) were greater in magnitude than those related to maximum temperature (Tmax). For absolute-value based indices, maximum Tmax, minimum Tmin, and summer days all show increasing trends, while frost days and the diurnal temperature range (DTR) show significant decreasing trends. In addition, there was a decrease in extreme cold events in most parts of east HKH, particularly in Southwest China and the Tibetan Plateau, while there was a general increase in extreme warm events over the entire HKH. Finally, the change in extreme cold events in the HKH appears to be more sensitive to elevation (with cold nights and cold days decreasing with elevation), whereas the change in warm extremes (warm nights, warm days, and maximum Tmax) shows no detectable relationship with elevation. Frost days and minimum Tmin also have a good relationship with elevation, and the trend in frost days decreases with an increase in elevation while the trend in minimum Tmin increases with an increase in elevation.

长江三角洲地区极端气温事件变化特征及其与ENSO的关系

PDF HTML阅读 XML下载 导出引用 引用提醒 长江三角洲地区极端气温事件变化特征及其与ENSO的关系 DOI: 10.5846/stxb201607091409 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（41561024）；高校博士学科点专项科研基金项目（20136203110002）；山西省高等学校哲学社会科学研究项目（2015265）。 Correlation analysis of variation of extreme temperature events and El Niño Southern Oscillation(ENSO) in Yangtze River Delta region during 1960-2014 Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:基于1960-2014年65个气象站点逐日最高、最低气温和平均气温资料，分析了长江三角洲地区极端气温事件的变化规律和ENSO事件强度对极端气温指数变化趋势的影响。结果表明：近55年长江三角洲地区夏季日数（SU）、热夜日数（TR）、暖昼日数（TX90）、暖夜日数（TN90）、异常暖昼持续指数（WSDI）、生长期（GSL）均呈增加趋势，其中暖夜日数（TN90）增加幅度最大，增幅为8.55d/10a；极值指数也呈上升趋势，其中月最低气温极小值（TNn）上升幅度最大为（0.53℃/10a）；冰冻日数（ID）、霜冻日数（FD）、冷昼日数（TX10）、冷夜日数（TN10）、异常冷昼持续指数（CSDI）均呈减少趋势，其中冷夜日数（TN10）减少幅度最大（-6.06d/10a）；月平均日较差（DTR）以0.11℃/10a的速率呈下降趋势。空间上，所有站点SU、TXn、TNx呈增加趋势；TR、TX90、TN90、TNn、TXx、WSDI、GSL分别有97%、85%、98%、95%、78%、92%、94%的站点呈增加趋势；所有站点ID、FD、TX10、TN10呈减少趋势；CSDI、DTR分别有87%、77%的站点呈减少趋势。多数极端气温指数与纬度、经度、海拔显著相关。气候变暖突变后，极端暖指数明显增加，极端冷指数明显减少。总体上，厄尔尼诺对极端气温指数的影响大于拉尼娜的影响。 Abstract:Based on daily temperature (maximum, minimum, and average) data of 65 stations, spatial and temporal changes of extreme temperature events and the El Niño Southern Oscillation (ENSO) influence on the extreme temperature threshold over Yangtze River Delta were analyzed for the period 1960-2014. The results showed that in the last 55 years, the extreme temperature indices, i.e. summer days (SU), tropical nights (TR), warm days (TX90), warm nights (TN90), warm spell duration days (WSDI), and growing season length (GSL) have all increased significantly, and TN90 showed an increasing rate of 8.55d per decade. The extremal indices (TXn, TNn, TXx, and TNx) had increasing trends in the Yangtze River Delta region, and TNn showed an increasing rate of 0.53℃ per decade. The ice days (ID), frost days (FD), cold days (TX10), cold nights (TN10), and cold spell duration days (CSDI) have decreased significantly by 0.40 d, 4.03 d, 2.56 d, 6.06 d and 0.33 d per decade, respectively, and TN10 showed a decreasing rate of 6.06 d per decade. DTR has decreased by 0.11℃ per decade. For the spatial distribution of SU, TXn and TNx, all meteorological stations showed increasing trends during 1960-2014. TR, TX90, TN90, TNn, TXx, WSDI, and GSL showed increasing trends at 97%, 85%, 98%, 95%, 78%, 92%, and 94% of meteorological stations, respectively. ID, FD, TX10, and TN10 showed decreasing trends for all stations. For CSDI and DTR, 87% and 77% stations showed decreasing trend. Most extreme temperature indices show good correlation with latitude, longitude, and altitude. After the detected abrupt climate changes, extreme warm indices increased, and extreme cold indices decreased significantly. Overall, the effect of El Nifio on extreme temperature indices was greater than the effect of La Nina. 参考文献 相似文献 引证文献

Projected changes in extreme temperature events based on the NARCCAP model suite

AbstractOnce‐per‐year (annual) maximum temperature extremes in North American Regional Climate Change Assessment Program (NARCCAP) models are projected to increase more (less) than mean daily maximum summer temperatures over much of the eastern (western) United States. In contrast, the models almost everywhere project greater warming of once‐per‐year minimum temperatures as compared to mean daily minimum winter temperatures. Under projected changes associated with extremes of the temperature distribution, Baltimore's maximum temperature that was met or exceeded once per year historically is projected to occur 17 times per season by midcentury, a 28% increase relative to projections based on summer mean daily maximum temperature change. Under the same approach, historical once‐per‐year cold events in Baltimore are projected to occur once per decade. The models are generally able to capture observed geopotential height anomalies associated with temperature extremes in two subregions. Projected changes in extreme temperature events cannot be explained by geopotential height anomalies or lower boundary conditions as reflected by soil moisture anomalies or snow water equivalent.

Assessment of climate variations in temperature and precipitation extreme events over Iran

In this study, changes in the spatial and temporal patterns of climate extreme indices were analyzed. Daily maximum and minimum air temperature, precipitation, and their association with climate change were used as the basis for tracking changes at 50 meteorological stations in Iran over the period 1975–2010. Sixteen indices of extreme temperature and 11 indices of extreme precipitation, which have been quality controlled and tested for homogeneity and missing data, are examined. Temperature extremes show a warming trend, with a large proportion of stations having statistically significant trends for all temperature indices. Over the last 15 years (1995–2010), the annual frequency of warm days and nights has increased by 12 and 14 days/decade, respectively. The number of cold days and nights has decreased by 4 and 3 days/decade, respectively. The annual mean maximum and minimum temperatures averaged across Iran both increased by 0.031 and 0.059 °C/decade. The probability of cold nights has gradually decreased from more than 20 % in 1975–1986 to less than 15 % in 1999–2010, whereas the mean frequency of warm days has increased abruptly between the first 12-year period (1975–1986) and the recent 12-year period (1999–2010) from 18 to 40 %, respectively. There are no systematic regional trends over the study period in total precipitation or in the frequency and duration of extreme precipitation events. Statistically significant trends in extreme precipitation events are observed at less than 15 % of all weather stations, with no spatially coherent pattern of change, whereas statistically significant changes in extreme temperature events have occurred at more than 85 % of all weather stations, forming strongly coherent spatial patterns.

Modelling extreme temperatures in Ireland under global warming using a hybrid peak-over-threshold and generalised Pareto distribution approach

In the present paper, modelling extreme temperature to assess risk of global warming in Ireland is addressed. The approach used is a combination of peak–over–threshold (POT) - generalised Pareto distribution (GPD) in which the parameter of distribution is allowed to vary with a dominant feature of climate at the location. The dominant climatic feature at a location is approximated by climatic variables derived from the National Centre for Environmental Prediction (NCEP) reanalysis data. Data from six stations were used to develop seasonal models for winter, spring, summer and autumn. Future changes in extreme temperature values are generated by using climate variables derived from (HadCM3) GCM for the A2 emissions scenario. The software extRemes was used to develop the models as it serves the proposed modelling approach. Results indicate that significant changes in extreme temperature events are projected to occur in Ireland over the course of the present century. These include hotter summers and mild winters.

Future change of extreme temperature climate indices over East Asia with uncertainties estimation in the CMIP5

How well the climate models simulate extreme temperature over East Asia and how the extreme indices would change under anthropogenic global warming are investigated. The indices studied include hot days (HD), tropical nights (TN), growing degree days (GDD), and cooling degree days (CDD) in summer and heating degree days (HDD) and frost days (FD) in winter. The representative concentration pathway 4.5 (RCP 4.5) experiments for the period of 2075–2099 are compared with historical simulations for the period of 1979–2005 from 15 coupled models that are participated in phase 5 of the Coupled Model Intercomparison Project (CMIP5). To optimally estimate future change and its uncertainty, groups of best models are selected based on Taylor diagrams, relative entropy, and probability density function (PDF) methods previously suggested. Overall, the best models’ multi-model ensemble based on Taylor diagrams has the lowest errors in reproducing temperature extremes in the present climate among three methods. Selected best models in three methods tend to project considerably different changes in the extreme indices from each other, indicating that the selection of reliable models are of critical importance to reduce uncertainties. Three groups of best models show significant increase of summerbased indices but decrease of the winter-based indices. Over East Asia, the most significant increase is seen in the HD (336 ± 23.4% of current climate) and the most significant decrease is appeared in the HDD (82 ± 4.2%). It is suggested that the larger future change in the HD is found over in the Southeastern China region, probably due to a higher local maximum temperature in the present climate. All of the indices show the largest uncertainty over Southeastern China, particularly in the TN (~3.9 times as large as uncertainty over East Asia) and in the HD (~2.4). It is further noted that the TN reveals the largest uncertainty over three East Asian countries (~1.7 and 1.4 over Korea and Japan, respectively). These future changes in extreme temperature events have an important implication for energy-saving applications and human molarity in the future.

Future changes in extreme temperature events using the statistical downscaling model (SDSM) in the trans-boundary region of the Jhelum river basin

In the 21st century, climate change is considered to be one of the greatest environmental threats to the world, and the changes in climate extremes are estimated to have greater negative impacts on human society and the natural environment than the changes in mean climate. This study presents the projections of future changes in extreme temperature events under A2 and B2 SRES scenarios using the statistical downscaling model (SDSM) in the trans-boundary region of the Jhelum River basin. This area is located in Pakistan and India. In order to get realistic results, bias correction was also applied to downscale the daily maximum and minimum temperature values before calculating 8 intensity and 4 frequency indices. Validation (1991–2000) showed great reliability of SDSM in ascertaining changes for the periods 2011–2040, 2041–2070 and 2071–2099, relative to 1961–1990.The intensity of the highest and the lowest night time temperatures is simulated to be higher than the highest and lowest day time temperatures. In contrast, the intensity of high night time temperature (hot nights) is projected to be lower than high day time temperature (hot days). The number of hot days and hot nights is predicted to increase, and by contrast, the frequency of cold days and cold night is predicted to decrease in all three future periods. Almost all the seasons will witness warming effects in the basin. However, these effects are much more serious in spring (hot days and nights) and in winter (cold and frosty days).On the whole in the Jhelum basin, the intensity and frequency of warm temperature extremes are likely to be higher and the intensity and frequency of cold temperature extremes to be lower in the future.

Characteristics of Observed Atmospheric Circulation Patterns Associated with Temperature Extremes over North America

Abstract Motivated by a desire to understand the physical mechanisms involved in future anthropogenic changes in extreme temperature events, the key atmospheric circulation patterns associated with extreme daily temperatures over North America in the current climate are identified. The findings show that warm extremes at most locations are associated with positive 500-hPa geopotential height and sea level pressure anomalies just downstream with negative anomalies farther upstream. The orientation, physical characteristics, and spatial scale of these circulation patterns vary based on latitude, season, and proximity to important geographic features (i.e., mountains, coastlines). The anomaly patterns associated with extreme cold events tend to be similar to, but opposite in sign of, those associated with extreme warm events, especially within the westerlies, and tend to scale with temperature in the same locations. Circulation patterns aloft are more coherent across the continent than those at the surface where local surface features influence the occurrence of and patterns associated with extreme temperature days. Temperature extremes may be more sensitive to small shifts in circulation at locations where temperature is strongly influenced by mountains or large water bodies, or at the margins of important large-scale circulation patterns making such locations more susceptible to nonlinear responses to future climate change. The identification of these patterns and processes will allow for a thorough evaluation of the ability of climate models to realistically simulate extreme temperatures and their future trends.

Changes of extreme temperature events in Three Gorges area, China

Meteorological data and heat stress indices from 1958 to 2007 in the Three Gorges area were investigated in this study. It is found that there is a (1) mild augmentation of the diurnal temperature range in the region (2) antithetical trends in mean\maximum\minimum temperatures, indicated by warmer winters and slightly cooler summers and (3) declining linear trends of the number of (very) hot days and annual frequencies of (long) heat waves, despite rising frequencies of (very) hot days and annual short heat waves. A U-shape was detected for all the climatic indices, with low values occurring mostly in the 1980s. However, spatial variations exist. Decreasing trends of hot days and frequency of heat waves were more evident in areas like Shapingba, where high annual temperatures were recorded. The finding also suggests a positive impact of the subtropical high on high temperatures and extreme temperature events.

Changes in means and extreme events of temperature and precipitation in the Asia‐Pacific Network region, 1955–2007

AbstractIn this study, spatial and temporal patterns of changes in extreme events of temperature and precipitation at 143 weather stations in ten Asia‐Pacific Network (APN) countries and their associations with changes in climate means are examined for the 1955–2007 period. Averaged over the APN region, annual frequency of cool nights (days) has decreased by 6.4 days/decade (3.3 days/decade), whereas the frequency of warm nights (days) has increased by 5.4 days/decade (3.9 days/decade). The change rates in the annual frequency of warm nights (days) over the last 20 years (1988–2007) have exceeded those over the full 1955–2007 period by a factor of 1.8 (3.4). Seasonally, the frequencies of summer warm nights and days are changing more rapidly per unit change in mean temperatures than the corresponding frequencies for cool nights and days. However, normalization of the extreme and mean series shows that the rate of changes in extreme temperature events are generally less than that of mean temperatures, except for winter cold nights which are changing as rapidly as the winter mean minimum temperature. These results indicate that there have been seasonally and diurnally asymmetric changes in extreme temperature events relative to recent increases in temperature means in the APN region.There are no systematic, regional trends over the study period in total precipitation, or in the frequency and duration of extreme precipitation events. Statistically significant trends in extreme precipitation events are observed at fewer than 30% of all weather stations, with no spatially coherent pattern of change, whereas statistically significant changes in extreme temperature events have occurred at more than 70% of all weather stations, forming strongly coherent spatial patterns. Copyright © 2009 Royal Meteorological Society