江苏省近45a极端气候的变化特征

利用江苏省35个测站1960—2004年45 a的逐日最高温度、最低温度、日降水量资料集,分析了近45 a江苏省极端高温、极端低温以及极端降水的基本变化特征。结果表明:(1)多年平均年极端高温的空间分布表现为西高东低,而极端低温则表现为自北向南的显著增加,极端降水的发生频次自南向北逐渐减少;(2)极端高温在江苏中部以及南部大部分地区有上升趋势,而西北地区则有弱的下降趋势;全省极端低温表现为显著的升高趋势;极端降水频次在南部地区有增加的趋势,北部减少趋势,中部则无变化趋势。(3)江苏极端高温、低温和极端降水的年际和年代际变化具有区域性差异,其中极端降水频次变化的区域性差异最为明显。     

Temperature Extremes from Canadian Regional Climate Model (CRCM) Climate Change Projections

Future climate projections of extreme events can help forewarn society of high-impact events and allow the development of better adaptation strategies. In this study a non-stationary model for Generalized Extreme Value (GEV) distributions is used to analyze the trend in extreme temperatures in the context of a changing climate and compare it with the trend in average temperatures.

The analysis is performed using the climate projections of the Canadian Regional Climate Model (CRCM), under an IPCC SRES A2 greenhouse gas emissions scenario, over North America. Annual extremes in daily minimum and maximum temperatures are analyzed. Significant positive trends for the location parameter of the GEV distribution are found, indicating an expected increase in extreme temperature values. The scale parameter of the GEV distribution, on the other hand, reveals a decrease in the variability of temperature extremes in some continental regions. Trends in the annual minimum and maximum temperatures are compared with trends in average winter and summer temperatures, respectively. In some regions, extreme temperatures exhibit a significantly larger increase than the seasonal average temperatures.

The CRCM projections are compared with those of its driving model and framed in the context of the Coupled Model Intercomparison Project, phase 3 (CMIP3) Global Climate Model projections. This enables us to establish the CRCM position within the CMIP3 climate projection uncertainty range. The CRCM is validated against the HadEX2 dataset in order to assess the CRCM representation of temperature extremes in the present climate. The validation is also framed in the context of CMIP3 validation results. The CRCM cold extremes validate better and are closer to the driving model and CMIP3 projections than the hot extremes.     

Future change in the frequency of warm and cold spells over Pakistan simulated by the PRECIS regional climate model

Climate change caused by anthropogenic activities has generated a variety of research focusing on investigating the past climate, predicting the future climate and quantifying the change in climate extreme events by using different climate models. Climate extreme events are valuable to evaluate the potential impact of climate change on human activities, agriculture and economy and are also useful to monitor the climate change on global scale. Here, a Regional Climate Model (RCM) simulation is used to study the future variations in the temperature extreme indices, particularly change in frequency of warm and cold spells duration over Pakistan. The analyses are done on the basis of simulating two 30 years simulations with the Hadley Center’s RCM PRECIS, at a horizontal resolution of 50 km. Simulation for the period 1961–1990 represents the recent climate and simulation for the period 2071–2100 represents the future climate. These simulations are driven by lateral boundary conditions from HadAM3P GCM of Hadley centre UK. For the validation of model, observed mean, maximum and minimum temperatures for the period 1961–1990 at all the available stations in Pakistan are first averaged and are then compared with the PRECIS averaged grid-box data. Also the observed monthly gridded data set of Climate Research Unit (UK) data is used to validate the model. Temperature indices in the base period as well as in future are then calculated and the corresponding change is observed. Percentile based spatial change of temperature shows that in summer, increase in daily minimum temperature is more as compared to the increase of daily maximum temperature whereas in winter, the change in maximum temperature is high. The occurrence of annual cold spells shows significantly decreasing trend while for warm spells there is slight increasing trend over Pakistan.     

Simulation of regional climate change under the IPCC A2 scenario in southeast China

A variable-grid atmospheric general circulation model, LMDZ, with a local zoom over southeast China is used to investigate regional climate changes in terms of both means and extremes. Two time slices of 30?years are chosen to represent, respectively, the end of the 20th century and the middle of the 21st century. The lower-boundary conditions (sea-surface temperature and sea-ice extension) are taken from the outputs of three global coupled climate models: Institut Pierre-Simon Laplace (IPSL), Centre National de Recherches Météorologiques (CNRM) and Geophysical Fluid Dynamics Laboratory (GFDL). Results from a two-way nesting system between LMDZ-global and LMDZ-regional are also presented. The evaluation of simulated temperature and precipitation for the current climate shows that LMDZ reproduces generally well the spatial distribution of mean climate and extreme climate events in southeast China, but the model has systematic cold biases in temperature and tends to overestimate the extreme precipitation. The two-way nesting model can reduce the ??cold bias?? to some extent compared to the one-way nesting model. Results with greenhouse gas forcing from the SRES-A2 emission scenario show that there is a significant increase for mean, daily-maximum and minimum temperature in the entire region, associated with a decrease in the number of frost days and an increase in the heat wave duration. The annual frost days are projected to significantly decrease by 12?C19?days while the heat wave duration to increase by about 7?days. A warming environment gives rise to changes in extreme precipitation events. Except two simulations (LMDZ/GFDL and LMDZ/IPSL2) that project a decrease in maximum 5-day precipitation (R5d) for winter, other precipitation extremes are projected to increase over most of southeast China in all seasons, and among the three global scenarios. The domain-averaged values for annual simple daily intensity index (SDII), R5d and fraction of total rainfall from extreme events (R95t) are projected to increase by 6?C7, 10?C13 and 11?C14%, respectively, relative to their present-day values. However, it is clear that more research will be needed to assess the uncertainties on the projection in future of climate extremes at local scale.     

Recent trends in observed temperature and precipitation extremes in the Yangtze River basin,China

Summary The present study is an analysis of the observed extreme temperature and precipitation trends over Yangtze from 1960 to 2002 on the basis of the daily data from 108 meteorological stations. The intention is to identify whether or not the frequency or intensity of extreme events has increased with climate warming over Yangtze River basin in the last 40 years. Both the Mann-Kendall (MK) trend test and simple linear regression were utilized to detect monotonic trends in annual and seasonal extremes. Trend tests reveal that the annual and seasonal mean maximum and minimum temperature trend is characterized by a positive trend and that the strongest trend is found in the winter mean minimum in the Yangtze. However, the observed significant trend on the upper Yangtze reaches is less than that found on the middle and lower Yangtze reaches and for the mean maximum is much less than that of the mean minimum. From the basin-wide point of view, significant increasing trends are observed in 1-day extreme temperature in summer and winter minimum, but there is no significant trend for 1-day maximum temperature. Moreover, the number of cold days ≤0 °C and ≤10 °C shows significant decrease, while the number of hot days (daily value ≥35 °C) shows only a minor decrease. The upward trends found in the winter minimum temperature in both the mean and the extreme value provide evidence of the warming-up of winter and of the weakening of temperature extremes in the Yangtze in last few decades. The monsoon climate implies that precipitation amount peaks in summer as does the occurrence of heavy rainfall events. While the trend test has revealed a significant trend in summer rainfall, no statistically significant change was observed in heavy rain intensity. The 1-day, 3-day and 7-day extremes show only a minor increase from a basin-wide point of view. However, a significant positive trend was found for the number of rainstorm days (daily rainfall ≥50 mm). The increase of rainstorm frequency, rather than intensity, on the middle and lower reaches contributes most to the positive trend in summer precipitation in the Yangtze.     

北京1841年以来均一化最高和最低气温日值序列的构建

长期连续的日值观测资料是研究百年来极端气候事件及其变化特征的重要基础支撑.目前中外由于缺乏可靠的逐日百年尺度气候资料,使得20世纪50年代以前的极端气候变化规律仍然没有得到很好的认识.基于国家气象信息中心收集整理的日最高和最低气温观测资料,构建北京1841—2019年气温日值序列.首先,通过数据质量控制剔除原始基础资料...     

新、旧气候态差异及对中国地区气候和极端事件评估业务的影响

利用1961—2020年中国区域2089个地面观测站资料,分析了1991—2020年和1981—2010年新、旧气候态下,平均气温、最高气温、最低气温和降水量等变量的空间变化特征,探讨对气候距平值、极端事件等评估结果的影响。结果表明：新气候态下,全国三类气温年和季节平均均一致升高,年降水增加,空间上气温偏高（低）、降水偏多（少）的特征将弱（强）化;华北东部、华东中部和北部以及青海西南部的年平均风速和日照时数距平增加;极端高温年减少,低温年增多,其中平均气温和最低气温受到的影响较最高气温更大;夏季南北方两条雨带极端强降水年的发生概率降低,冬季东北中部和南部、华北、华东北部、西北东部极端弱降水年概率显著增加;全国超过一半的站点极端日高温、低温和强降水事件的历史频次发生改变;新气候态还减弱了极端日高温事件的增速,加快了极端日低温事件的降速。     

攀枝花市区33年气温变化趋势研究

本文利用攀枝花市区1977~2009年年平均气温、年平均极端最高气温、年平均极端最低气温以及逐日最高气温资料,运用气候趋势系数、累计距平、MK突变检验等方法研究分析了攀枝花市区气温变化趋势,主要结论有:(1)33年来该地区年平均气温呈现弱的下降趋势,与全球升温趋势相悖。(2)年平均极端最低气温升温趋势率为0.24℃/(10a),大大高于年平均极端最高气温升温趋势率0.09℃/(10a)。(3)高温日数及热积温均呈下降趋势,其中热积温下降趋势率为8.4℃/(10a)。(4)市区炳草岗年平均气温相对稳定,不存在突变现象。      

新旧气候态的差异及其对江西气候业务的影响

利用1961—2022年江西74个气象站平均气温、最高气温、最低气温、降水量、相对湿度、平均风速和日照时数资料,对比分析了1991—2020年和1981—2010年新、旧气候态下气象要素差异,探讨气候平均值改变对气候影响评价和预测业务的影响。结果表明：新气候态下,江西省三类气温的年和季节平均值均上升,年降水量总体增加将弱化气温偏高、降水偏多的变化特征。年和季节平均风速距平山区减小而平原地区增大;年日照时数距平总体增加。极端高温年份减少,极端低温年份增多,其中平均气温和最低气温的极端高（低）温年发生概率的降幅（增幅）比最高气温更大。极端强降水年发生概率在赣西北、赣中大部、赣南西北部等地区夏季减少,赣南中南部地区冬季增大。全省历年极端日高温、低温和强降水事件发生站次总体减少。新、旧气候态的更替会对气候业务产生影响,如冬季气温偏冷的年份增加,偏暖的年份减少,需对冷、暖冬事件进行重新评估,夏季降水增多的变化特征减弱,将导致夏季降水预测量级和趋势发生改变。     

8个CMIP5模式对中国极端气温的模拟和预估

利用8个耦合模式比较计划第五阶段（CMIP5）模式结果,采用加权平均方法进行多模式集合,并与NCEP再分析资料进行对比分析,评估了CMIP5模式对中国极端气温的模拟效果,在此基础上,对未来极端气温进行预估。CMIP5模式对中国8个极端气温指数和20年一遇最高（低）气温有模拟能力,所有极端气温指数模拟和观测结果的时间相关均达到0.10显著性水平,20年一遇最高、最低气温模拟和观测结果空间相关系数均超过0.98。在中等排放RCP4.5情景下,未来中国极暖（冷）日数增多（减少）,到21世纪中期热浪指数增加2.6倍,到21世纪末期寒潮指数减少71%,20年一遇最高（低）气温在中国地区均呈现升高趋势,局部升温幅度达到4℃。     

Detecting abrupt climate changes on different time scales

Two concepts are introduced for detecting abrupt climate changes. In the first case, the sampling frequency of climate data is high as compared to the frequency of climate events examined. The method is based on a separation of trend and noise in the data and is applicable to any dataset that satisfies some mild smoothness and statistical dependence conditions for the trend and the noise, respectively. We say that an abrupt change occurs when the first derivative of the trend function has a discontinuity and the task is to identify such points. The technique is applied to Northern Hemisphere temperature data from 1850 to 2009, Northern Hemisphere temperature data from proxy data, a.d. 200?C1995 and Holocene ??¹⁸O values going back to 11,700 years BP. Several abrupt changes are detected that are, among other things, beneficial for determining the Medieval Warm Period, Little Ice Age and Holocene Climate Optimum. In the second case, the sampling frequency is low relative to the frequency of climate events studied. A typical example includes Dansgaard?COeschger events. The methodology used here is based on a refinement of autoregressive conditional heteroscedastic models. The key element of this approach is the volatility that characterises the time-varying variance, and abrupt changes are defined by high volatilities. The technique applied to ??¹⁸O values going back to 122,950 years BP is suitable for identifying DO events. These two approaches for the two cases are closely related despite the fact that at first glance, they seem quite different.     

近50年来乌兰乌苏多种天气事件变化特征研究

利用乌兰乌苏镇1964～2012年的气象资料,选取逐年平均气温、极端最高气温、极端最低气温、大风、雷暴、沙尘暴、沙尘天气及大雾、轻雾天气出现的天数作为分析对象,运用3年移动平均法、回归分析法、非参数检验方法的Mann-Kendall趋势检验和突变检验法以及小波分析法,进行了多种天气事件的年纪变化趋势分析.结果表明：（1）大雾天气的发生日数呈增加趋势,沙尘天气、沙尘暴天气、轻雾天气、大风天气和雷暴天气的发生日数都呈减少趋势,其中大风天气发生日数减少趋势最为明显.（2）平均气温、年极端最高气温、年极端最低气温、大雾天气、轻雾天气、沙尘暴天气、雷暴天气和沙尘天气在研究时段都出现了突变,且平均气温、轻雾天气、沙尘天气和雷暴天气在突变之后不久都达到了极显著的上升或者下降变化趋势.（3）平均气温、年极端最低气温、年极端最高气温、大雾天气、雷暴天气和大风天气有明显的周期性,但是不同的气象要素周期性长短是不同的,沙尘、沙尘暴和轻雾天气则没有明显的周期性.     

An intercomparison of model-simulated in extreme rainfall and temperature events during the last half of the twentieth century. Part 1: mean values and variability

In this study we examine the performance of eight of the IPCC AR4 global coupled climate models used in the WCRP CMIP3 Multimodel Dataset, as well as their ensemble mean, in simulating annual indices of extreme temperature and precipitation climate events in South America. In this first part we focus on comparing observed and modeled mean values and interannual variability. Two extreme temperature indices based on minimum temperature (warm nights and frost days) and three indices of extreme precipitation (R95t, R10 and consecutive dry days), obtained both from meteorological stations during 1961–2000 and model outputs, were compared. The number of warm nights are better represented by models than the FD. The interannual variability pattern is also in good agreement with the observed values. For precipitation, the index that is best represented by the models is the R95t, which relates the extreme precipitation to local climate. The maximum of dryness observed over the central Argentinian Andes or the extensive dry season of the Amazon region could not be represented by any model.     

1961~2015年青藏高原极端气温事件的气候变化特征

利用1961~2015年CN05.1高分辨率的逐日最高、最低气温格点资料,计算6个极端气温指数（极端最高气温、极端最低气温、结冰日数、霜冻日数、暖日日数、冷夜日数）,通过趋势分析和Mann-Kendall突变检验,考察青藏高原极端气温事件的时空变化规律。结果表明:青藏高原极端最高气温、极端最低气温的总体分布呈现西冷东暖的特征,与地形西高东低一致;该地区极端最高气温、极端最低气温及暖日日数均呈上升趋势,倾向率分别为0.25℃/10a、0.42℃/10a、2.14d/10a,极端最低气温的线性增温趋势较极端最高气温更为明显;而结冰日数、霜冻日数及冷夜日数均呈下降趋势,倾向率分别为?3.09d/10a、?4.75d/10a、?2.31d/10a;从空间分布看,青海地区极端最高气温的增温趋势最为显著,柴达木盆地是明显的升温中心;在时间变化上,极端最高气温、结冰日数、暖日日数均在1997年发生了突变。      

1951—2017年鞍山市气温变化特征及城市热岛变化

利用建站以来鞍山站和海城乡村站的一日四次观测数据和逐日平均、最低和最高气温资料,对1951—2017年鞍山市年、四季和各月平均气温和极端气温变化特征及其变率进行了分析,并对鞍山城市热岛变化进行探讨.结果表明:1951—2017年鞍山市年平均最低气温的递增趋势最强、平均气温次之、平均最高气温最弱,且均通过显著性检验.19...     

利用随机模拟研究极值天气的预报模型试验

将随机过程的交叉理论应用于天气气候极值分析，以长江三角洲地区逐月最高最低气温为例，说明了交叉理论在极值研究中的作用。基于该理论，对上海市近100a一月气温序列，用随机模拟的方法讨论了极端温度出现的频数、持续时间、时间间隔等参数对于气候变化的敏感性，并根据气候变化趋势，预测了未来气候极值统计特征的变化规律。     

云南不同气候带极端气温变化趋势

利用1975-2008年云南6个气候代表站的最高气温、最低气温和平均气温资料,分析了气温序列的变化趋势,探讨了可能的形成原因.结果显示,各代表站的气温总体上呈上升趋势,但气温变化率的大小与其所处的气候带之间没有明显的规律性差异.代表高原气候的香格里拉站其气温增暖趋势最突出,代表北亚热带、中亚热带和南亚热带站点的气温与其有相似的变化趋势,主要表现为最低气温增温速率最大,平均气温次之,最高气温最小,而气温日较差(DTR:Differenceof Temperature Range)有明显减小趋势.温带和北热带代表站气温的变化则有不同的特征,温带的变化表现为最高气温显著上升,最低气温上升速率略小于平均气温的上升速率,DTR变化不显著;北热带的变化表现为平均气温增温速率最大,最低气温次之,最高气温最小,DTR变化不显著.对各站相对暖日、冷日、暖夜、冷夜和霜日的逐年统计分析表明,总体上云南的冷事件在减少,而暖事件增多.     

Trends in extreme summer temperatures at Belgrade

Summary Trends in extreme temperatures have been investigated for the Belgrade temperature record (1975–2003) to assess how an increase in the mean summer temperatures is related to changes in the extreme maximum and minimum temperatures. The rising mean summer temperatures at Belgrade are associated with a substantial increase in the occurrence of extreme maximum temperatures. Two statistical models for climate change (changing mean with constant standard deviation, and changing mean and standard deviation) indicated that the changing mean was dominant, because the observed trend in standard deviation was small.     

Nonstationary analysis of the extreme temperatures in Turkey

Record-breaking extreme temperatures have been measured in the last two decades all over Turkey, with recent studies detecting positive trends in extreme temperature time series. In this study, nonstationary extreme value analysis was performed on extreme temperature time series obtained from fifty stations scattered over the seven geographical regions of Turkey. Basic characterization of the data set was defined through outlier detection, homogeneity, trend detection, and stationarity tests. Trend-including non-stationary extreme temperature time series were analyzed with non-stationary Generalized Extreme Value distribution. Three main physical drivers were considered as the leading causes that trigger the observed trends in extreme temperatures over Turkey: time, teleconnection patterns of the Arctic Oscillations, and those of the North Atlantic Oscillations. The results showed that most of the absolute annual minimum and maximum temperature time series are inhomogeneous while the possible breakpoints date back to the1970s and 1990s, respectively. More than half of the absolute annual maximum time series (26/50 and many of the absolute annual minimum time series (21/50) showed a positive trend. No negative trend was detected in the extreme temperature time series. Based on the frequency analysis of the 21 annual maximum time series, the non-stationary estimations of 50-year return levels were detected to be higher than in the stationary model (between 0.44 °C and 3.73 °C). The return levels in 15 of the 20 minimum temperature time series increased from 0.11 °C up to 12.28 °C. Elevation increases the nonstationarity impact on absolute minimum temperatures and decreases it on absolute maximums. The findings in this study indicate that the consideration of non-stationarity in extreme temperature time series is a necessity during return level estimations over the study area.     

基于改进的EMD的运城市持续极端气温的初步分析

采用每日最高（最低）气温的历史同期序列的分位数作为该日的极端阈值,运用改进的经验模态分解（empirical mode decomposition,EMD）方法对山西省运城市1971—2005年每年发生的持续（3 d及3 d以上）极端气温频数进行了初步分析。结果表明,1971—2005年运城市每年的持续极端高温频数（frequency of sustained extreme-high temperature,FSEHT）和持续极端低温频数（frequen-cy of sustained extreme-lowtemperature,FSELT）序列均存在线性下降趋势;在0.05的水平下,运城市的FSEHT序列与该地区的年平均气温序列的线性相关性不显著,而该地区的FSELT序列与年平均气温序列的负线性相关关系是显著的;此外,这两个频数序列分别存在不同的周期振荡。从主要周期看,运城市的FSEHT和FSELT序列与厄尔尼诺现象的周期相一致。