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1.
A complete picture of changes in climate extremes has been presented for Shanxi Province, China using data from all 61 available stations. The results reveal large spatial coherence of trends for the majority of extremes, especially for temperature extremes. Significant and symmetric increasing trends of the annual mean maximum and mean minimum temperatures (TXam, TNam) are detected over the past 50 years. Significant positive trends are detected for warm days and nights (TX90p, TN90p), the highest and lowest maximum and minimum temperatures (TXx, TXn, TNx, TNn), and the growing season length (GSL). Significant negative trends are revealed for cold days and nights (TX10p, TN10p) and frost days (FD). Significant decreases are found in the number of heavy precipitation days (R10mm) and wet day precipitation (PRCPTOT). Although Shanxi and the northern half of North China Plain (NNCP) have been grouped into the North China region and assessed together in previous studies for China, the changes in climate extremes in the NNCP have some pronounced differences in comparison with Shanxi. Noticeably, the increase of the TNam is at a rate nearly three times that of the TXam during 1959–2008 over the NNCP. The warming for the nighttime indices TN90p, TN10p, TNx, and TNn is stronger, but the warming for the daytime indices TX10p, TX90p, and TXx is weaker in the NNCP. There is no significant decrease for R10mm and PRCPTOT in the NNCP.  相似文献   

2.
利用秦巴山区88个气象站1975—2016年的逐日气温数据,结合16个极端气温指数分析了秦巴山区极端气温阈值的空间分布及极端气温事件变化趋势的海拔依赖性。结果表明：极端气温阈值存在明显的空间分布差异,表现为极端低温阈值与极端高温阈值由西北向东南均有增温趋势;总体来看,极端气温暖事件（SU25、TR20、TX90P、TN90P、WSDI）增加幅度大于冷事件（FD0、ID0、TX10P、TN10P、CSDI）减少幅度,且变化趋势较冷事件更显著;全区霜冻日数、夏日日数、冷夜日数、暖昼日数及高温极值（TXx、TXn）变化均比较显著;区域作物生长期西部增长趋势较东部显著,多数站点变化幅度在3~6 d/10a之间;海拔越高发生极端低温事件的气温越低,极端低温阈值变化趋势为-0.36℃/100m;海拔越低发生极端高温事件的气温越高,极端高温变化趋势达0.5℃/100m,且均通过99%的信度检验;区域极端气温极值指数的变化趋势与海拔呈显著正相关,具有明显的海拔依赖性,表现为海拔越高,极值指数增加趋势越明显。  相似文献   

3.
黑龙江省1961—2009年极端气温事件变化特征分析   总被引：3，自引：0，他引：3       下载免费PDF全文
选用世界气象组织公布的极端气候指数方法对1961—2009年黑龙江省8个极端气温指数进行计算和分析,得到黑龙江省极端气温事件的事实和变化特征。结果表明：黑龙江省近49年来夏日天数、极端最低气温、极端最高气温、暖夜指数和暖昼日数均呈上升趋势,而霜冻日数、冷夜指数和冷昼日数呈下降趋势。极端气温指数的变化存在明显的年际变化特征,并有突变发生。对黑龙江省气温升高来说,最低气温升高主要发生在20世纪80年代中期以后,而最高气温则在90年代以后上升明显。空间分布方面,极端气温指数在全区基本都呈一致的增大或减小分布。夜间增暖的幅度要大于白天增暖的幅度,夜间气温的上升对增暖的贡献更大。  相似文献   

4.
This study assesses the performance of temperature extremes over China in two regional climate models(RCMs),RegCM4 and WRF, driven by the ECMWF's 20 th century reanalysis. Based on the advice of the Expert Team on Climate Change Detection and Indices(ETCCDI), 12 extreme temperature indices(i.e., TXx, TXn, TNx, TNn, TX90 p, TN90 p,TX10 p, TN10 p WSDI, ID, FD, and CSDI) are derived from the simulations of two RCMs and compared with those from the daily station-based observational data for the period 1981–2010. Overall, the two RCMs demonstrate satisfactory capability in representing the spatiotemporal distribution of the extreme indices over most regions. RegCM performs better than WRF in reproducing the mean temperature extremes, especially over the Tibetan Plateau(TP). Moreover, both models capture well the decreasing trends in ID, FD, CSDI, TX10 p, and TN10 p, and the increasing trends in TXx, TXn, TNx, TNn, WSDI, TX90 p,and TN90 p, over China. Compared with observation, RegCM tends to underestimate the trends of temperature extremes,while WRF tends to overestimate them over the TP. For instance, the linear trends of TXx over the TP from observation,RegCM, and WRF are 0.53?C(10 yr)-1, 0.44?C(10 yr)-1, and 0.75?C(10 yr)-1, respectively. However, WRF performs better than RegCM in reproducing the interannual variability of the extreme-temperature indices. Our findings are helpful towards improving our understanding of the physical realism of RCMs in terms of different time scales, thus enabling us in future work to address the sources of model biases.  相似文献   

5.
The aims of this study are to identify the trend of warm days and cold nights over the Iberian Peninsula and to connect the variations with large-scale variables. The reasons for performing this analysis are the effects that extremes events have on different ecosystems. Here, we present the results on spatial and temporal variability of warm days (TX90), or those exceeding the 90th percentile of maximum temperature, and cold nights (TN10), or those falling below the 10th percentile of minimum temperature. The extreme indices were derived from daily observations at stations and gridded data over land area for the period 1950 to 2006. Significant trends of more warm days and fewer cold nights were found. The trend to fewer cold nights is within the interval of global results given by the IPCC AR4 report; however, the trend to warm days is greater than the corresponding global trend. The influence of large-scale variables on these extreme indices was examined by means of the Empirical Orthogonal Function, correlation, composite maps and multiple regression analyses. Changes in TX90 are connected with the Scandinavian teleconnection index and a preferred mode of geopotential height at 500 hPa over the North Atlantic. Changes in TN10 are connected with the East Atlantic teleconnection index and the leading mode of Sea Surface Temperature (SST) variability over the North Atlantic area. Based on the links between the extreme indices and the large-scale variables we derived statistical models to describe the response of TX90 and TN10 to atmospheric circulation and SST variations. The models characterized the observed variations of TX90 and TN10 reasonably well. The results of this study encourage us to analyze, in further work, how temperature extremes might change over the Iberian Peninsula under warmer climate conditions.  相似文献   

6.
根据广州国家基本气象站1951—2020年的逐日气温资料,采用线性趋势法、距平及累积距平法和Mann-Kendall检验法,对WMO推荐的16种极端气温指数中的13种以及2种结合本地实际的新的极端气温指数共计15种指数进行计算,从月尺度和年尺度分析广州地区各极端气温指数随时间变化的趋势和突变年份,并对以往研究中较少探究的基期的选择对相对极端气温指数的结果影响进行了对比分析。(1) 从年尺度看,广州地区近70 a的夏日日数SU25、酷热日数SU35、热夜日数TR20、非常热夜日数TR26、最高气温TXx、最低气温TNn、最低气温最大值TNx、相对暖夜日数TN90p、暖昼日数TX90p、显著偏暖持续指数WSDI均呈现明显的上升趋势,相对冷夜日数TN10p、冷昼日数TX10p和偏冷持续指数CSDI呈现下降趋势,气温日较差DTR和最高气温最小值TXn变化趋势不明显;(2) 新的极端气温指数SU35和TR26的上升速率明显大于SU25和TR20的上升速率,能更好地反映近70 a昼夜体感炎热日数呈现极显著的上升趋势,更加符合评估气候变化对当地生产生活的影响;(3) 从月尺度来看近70 a广州地区的暖系列极值气温指数TXx和TNx在夏季出现了明显的上升;相对极端气温指数TX90p在广州地区气候学意义的夏季(4—10月)的上升趋势除了5月以外均达到极显著水平;广州地区夏季相对暖(热)昼的上升是导致全年相对暖(热)昼上升的主要因素, 这与国内大部分地区冬季升温较为明显的结论有所不同;(4) 以三个不同基期(1961—1990年/1971—2000年/1981—2010年)的选择对相对极端气温指数的计算结果影响发现,基期的不同选择对相对极端气温指数的计算结果有一定影响,但不影响其变化趋势;(5) 突变分析显示广州地区近70 a的SU25、SU35、TMAXmean(平均最高气温)、TXx和TX90p的突变发生在1997年前后;TR20、TR26、TMINmean(平均最低气温)、TNn、TNx、TN10p、TX10p和TN90p的突变发生在1985年前后;结果符合全球气候变化的大趋势,可以为广州地区应对气候变化和预防极端天气灾害提供科学的理论依据和参考。   相似文献   

7.
利用CORDEX-EA计划11个区域模式模拟结果,集合预估了中国西部干旱区16个极端温度指数未来的变化趋势及空间分布。结果表明:1)区域模式基本上能够再现近30 a西部干旱区极端温度的空间分布。2)多模式集合预估的西部干旱区21世纪中期霜冻日数(FD)和冰封日数(ID)呈现显著的下降趋势,而热夜日数(TR)和夏季日数(SU)则呈现明显的上升趋势。3)未来异常暖昼持续指数(WSDI)和生长期(GSL)呈现增加趋势,异常冷昼持续指数(CSDI)和日较差(DTR)则呈现下降趋势。4)未来气候增温导致冷昼日数(TX90p)、暖夜日数(TN90p)增加,而暖昼日数(TX10p)和冷夜日数(TN10p)减少。5)未来月最高温度极大值(TXx)、月最低温度极大值(TNx)、月最高温度极小值(TXn)和月最低温度极小值(TNn)都呈现增加的趋势。因此,西部干旱区未来发生极端低温事件的概率减小,发生极端高温事件的概率则会增大,但不同的极端温度指数变化的空间分布并不均一,存在明显的区域差异。  相似文献   

8.
陈海山  周晶 《大气科学》2013,37(1):1-13
利用NCARCAM3.1大气环流模式,设计了有、无土壤湿度年际异常的两组数值试验,探讨了土壤湿度年际异常对极端气候事件模拟的可能影响。结果表明,模式模拟的极端气候事件对土壤湿度异常十分敏感,土壤湿度异常对极端气候指标的多年平均空间分布、年际变率以及年际变化均具有重要影响。当不考虑土壤湿度的年际异常时:(1)模拟的暖夜日数、暖昼日数和热浪持续指数的发生频次在全国范围内均明显减少,而霜冻日数则明显增加。极端降水指标的响应表现出明显的空间差异,极端降水频次在江淮流域明显减小,而极端降水强度则表现为东北减弱、长江流域增强;中雨日数和持续湿期在我国大部分地区减少。(2)极端气温指标的年际变率在我国大部分地区呈减小趋势;而极端降水事件的变化则较为复杂,极端降水频次和极端降水强度的年际变率在长江以南有所增强,而北方地区则有所减弱。中雨日数和持续湿期的年际变率在我国呈现出较为一致的减少趋势。(3)模式对暖夜日数、霜冻日数的年际变化的模拟能力明显下降,并对4个极端降水指标的年际变化的模拟能力在全国多数区域均有不同程度的下降。  相似文献   

9.
Extreme temperature events are simulated by using the Beijing Climate Center Atmospheric General Circulation Model (BCC AGCM) in this paper. The model has been run for 136 yr with the observed external forcing data including solar insolation, greenhouse gases, and monthly sea surface temperature (SST). The daily maximum and minimum temperatures are simulated by the model, and 16 indices representing various extreme temperature events are calculated based on these two variables. The results show that the maximum of daily maximum temperature (TXX), maximum of daily minimum (TNX), minimum of daily maximum (TXN), minimum of daily minimum (TNN), warm days (TX90p), warm nights (TN90p), summer days (SU25), tropical nights (TR20), and warm spell duration index (WSDI) have increasing trends during the 20th century in most regions of the world, while the cold days (TX10p), cold nights (TN10p), and cold spell duration index (CSDI) have decreasing trends. The probability density function (PDF) of warm/cold days/nights for three periods of 1881-1950, 1951- 1978, and 1979-2003 is examined. It is found that before 1950, the cold day/night has the largest probability, while for the period of 1979-2003, it has the smallest probability. In contrast to the decreasing trend of cold days/nights, the PDF of warm days/nights exhibits an opposite trend. In addition, the frost days (FD) and ice days (ID) have decreasing trends, the growing season has lengthened, and the diurnal temperature range is getting smaller during the 20th century. A comparison of the above extreme temperature indices between the model output and NCEP data (taken as observation) for 1948-2000 indicates that the mean values and the trends of the simulated indices are close to the observations, and overall there is a high correlation between the simulated indices and the observations. But the simulated trends of FD, ID, growing season length, and diurnal temperature range are not consistent with the observations and their correlations are low or even negative. This indicates that the model is incapable to simulate these four indices although it has captured most indices of the extreme temperature events.  相似文献   

10.
Exploring the characteristic of the extreme climatic events, especially future projection is considerably important in assessing the impacts of climatic change on hydrology and water resources system. We investigate the future patterns of climate extremes (2001–2099) in the Haihe River Basin (HRB) derived from Coupled General Circulation Model (CGCM) multimodel ensemble projections using the Bayesian Model Average (BMA) approach, under a range of emission scenarios. The extremes are depicted by three extreme temperature indices (i.e., frost days (FD), growing season length (GSL), and T min >90th percentile (TN90)) and five extreme precipitation indices (i.e., consecutive dry days (CDD), precipitation ≥10 mm (R10), maximum 5-day precipitation total (R5D), precipitation >95th percentile (R95T), and simple daily intensity index (SDII)). The results indicate frost days display negative trend over the HRB in the 21st century, particularly in the southern basin. Moreover, a greater season length and more frequent warm nights are also projected in the basin. The decreasing CDD, together with the increasing R10, R5D, R95T, and SDII in the 21st century indicate that the extreme precipitation events will increase in their intensity and frequency in the basin. Meanwhile, the changes of all eight extremes climate indices under A2 and A1B scenarios are more pronounced than in B1. The results will be of practical significance in mitigation of the detrimental effects of variations of climatic extremes and improve the regional strategy for water resource and eco-environment management, particularly for the HRB characterized by the severe water shortages and fragile ecological environment.  相似文献   

11.
Using an ensemble of four high resolution (~25 km) regional climate models, this study analyses the future (2021–2050) spatial distribution of seasonal temperature and precipitation extremes in the Ganges river basin based on the SRES A1B emissions scenario. The model validation results (1989–2008) show that the models simulate seasonality and spatial distribution of extreme temperature events better than precipitation. The models are able to capture fine topographical detail in the spatial distribution of indices based on their ability to resolve processes at a higher regional resolution. Future simulations of extreme temperature indices generally agree with expected warming in the Ganges basin, with considerable seasonal and spatial variation. Significantly warmer summers in the central part of the basin along with basin-wide increase in night temperature are expected during the summer and monsoon months. An increase in heavy precipitation indices during monsoon, coupled with extended periods without precipitation during the winter months; indicates an increase in the incidence of extreme events.  相似文献   

12.
基于ETCCDI指数2017年中国极端温度和降水特征分析   总被引：1，自引：0，他引：1  
利用中国1961—2017年2419站均一化逐日气候数据,计算了气候变化检测和指数联合专家组定义的26个极端气候指数,分析2017年中国极端温度和降水特征。结果表明：2017年中国区域平均的所有极端高温指数均高于1961—1990年30年平均,所有极端低温指数均低于1961—1990年30年平均。中国区域平均的多个极端温度指数达到或者接近历史极值,其中年最小日最高气温(TXn)和年最小日最低气温(TNn)均达到历史最高值,冷夜(TN10p)、冷昼(TX10p)和持续冷日日数(CSDI)达到历史最低值。年最大日最高气温(TXx)、年最大日最低气温(TNx)、暖夜(TN90p)、霜冻(FD)、冰冻(ID)、热夜(TR)、生长期长度(GSL)排在1961年以来的第2或第3位,其余极端温度指数全部排在了1961年以来前10位。2017年中国区域平均的10个极端降水指数中,有7个指数值处于1961—2017年1个标准差范围内,指示2017年的极端降水接近正常年。  相似文献   

13.
利用1986—2005年中国地面气象台站观测的格点化逐日气温资料（CN05.1）评估了高分辨率统计降尺度数据集NASA Earth Exchange/Global Daily Downscaled Projections（NEX-GDDP）中21个全球气候模式对中国极端温度指数的模拟能力。在选用了日最低温度最大值（TNx）、日最高温度最大值（TXx）、暖夜指数（TN90p）和暖昼指数（TX90p）来研究极端温度事件的变化。结果显示:（1）除MRI-CGCM3模拟的日最高温度最大值外,其余模式对4个指数的模拟结果均表现出与观测一致的上升趋势,但模拟结果的平均值相对观测平均低0.26℃/（10 a）（日最低温度最大值）、0.19℃/（10 a）（日最高温度最大值）、2.21%/（10 a）（暖夜指数）、1.04%/（10 a）（暖昼指数）。（2）不同模式对各指数变化趋势空间分布特征的模拟存在较大差别,对日最低温度最大值、日最高温度最大值、暖夜指数和暖昼指数模拟能力最优模式分别为CCSM4、CESM1-BGC、MIROC-ESM-CHEM和bcc-csm1-1。模式模拟的日最低温度最大值和日最高温度最大值气候态平均值与观测值的相关系数在0.97以上。暖夜指数和暖昼指数模拟结果与观测值的标准差比值为0.34—1.58,均方根误差变化为1.6%—3.47%,对这两个指数模拟能力较优的模式分别为MIROC-ESM-CHEM（暖夜指数）和CESM1-BGC（暖昼指数）。（3）综合模式对4个指数在气候态平均值和变化趋势模拟能力的评估结果来看,CanESM2、CESM1-BGC和MIROC-ESM-CHEM显示了相对较高的模拟能力。因此,在利用GDDP-NEX研究未来极端温度事件时,建议将它们作为优选模式。   相似文献   

14.
We evaluate the capacity of a regional climate model to represent observed extreme temperature and precipitation events and also examine the impact of increased resolution, in an effort to identify added value in this respect. Two climate simulations of western Canada (WCan) were conducted with the Canadian Regional Climate Model (version 4) at 15 (CRCM15) and 45?km (CRCM45) horizontal resolution driven at the lateral boundaries by data from the European Centre for Medium-range Weather Forecasts (ECMWF) 40-year Reanalysis (ERA-40) for the period 1973–1995. The simulations were evaluated using the spline-interpolated dataset ANUSPLIN, a daily observational gridded surface temperature and precipitation product with a nominal resolution of approximately 10?km. We examine a range of climate extremes, comprising the 10th and 90th percentiles of daily maximum (TX) and minimum (TN) temperatures, the 90th percentile of daily precipitation (PR90), and the 27 core Climate Daily Extremes (CLIMDEX) indices.

Both simulations exhibit cold biases compared with observations over WCan, with the bias exacerbated at higher resolution, suggesting little added value for temperature overall. There are instances, however, of regional improvement in the spatial pattern of temperature extremes at the higher resolution of CRCM15 (e.g., the CLIMDEX index for the annual number of days when TX?>?25°C). The high-resolution simulations also reveal similarly localized features in precipitation (e.g., rain shadows) that are not resolved at the 45?km resolution. With regard to precipitation extremes, although both simulations generally display wet biases, CRCM15 features a reduced bias in PR90 in all seasons except winter. This improvement occurs despite the fact that spatial and interannual variability of PR90 in CRCM15 is significantly overestimated relative to both CRCM45 and ANUSPLIN. We posit that these characteristics are the result of demonstrable differences between corresponding topographical datasets used in the gridded observations and CRCM, the resulting errors propagated to physical variables tied to elevation and the beneficial effect of subsequent spatial averaging. Because topographical input is often discordant between simulations and gridded observations, it is argued that a limited form of spatial averaging may contribute added value beyond that which has already been noted in previous studies with respect to small-scale climate variability.  相似文献   

15.
气候变化背景下,频发的暴雨事件造成城市内涝、人员伤亡和财产损失,已经成为全社会广泛关注的焦点问题之一。为了诊断中国暴雨的时空变化及其与不同自然因子的关联性,采用1961—2015年中国659个降水站点数据,采用线性趋势、EOF分析等多种统计方法诊断了中国暴雨时空变化特征,结果表明,中国暴雨雨量、雨日和雨强在1961—2015年以胡焕庸线为界呈现出东南高-西北低的气候态空间分布格局;线性趋势分析表明1961—2015年中国暴雨雨量和雨日从东南沿海向西北内陆呈明显“增-减-增”的空间分布格局,且呈增长趋势的站点占主导,分别高达80.88%和79.81%;从西北内陆到东南沿海的年代剖面分析表明中国暴雨雨量和雨日随着年代推移在迅速增长;对低通滤波后的中国暴雨进行EOF分析表明中国暴雨雨量和雨日的增长东南沿海快,内陆地区慢。根据IPCC等已有研究中筛选出对中国地区有影响的28个气候因子,并将其与659个站点的暴雨进行相关分析,结果表明不同气候因子与不同区域暴雨呈现出错综复杂的相关性特征,其中与暴雨雨量呈现以正相关和负相关为主的气候因子分别为15和13个,全局相关因子包含AAO(Antarctic Oscillation)、Pacific Warmpool,而其它气候因子在七大分区中与暴雨的关联性各有突出,表现出明显的空间异质性。   相似文献   

16.
基于RCP4.5情景下6.25 km高分辨率统计降尺度数据,使用国际上通用的极端气候事件指数,分析雄安新区及整个京津冀地区未来极端气候事件的可能变化。首先对当代模拟结果进行评估,结果表明,集合平均模拟可以较好地再现大部分极端气候事件指数的分布,且对与气温有关的极端气候事件指数模拟效果较好。但也存在一定偏差,特别是对连续干旱日数(CDD)的模拟效果相对较差。集合平均的预估结果表明,未来在全球变暖背景下,雄安新区及整个京津冀地区均表现为极端暖事件增多,极端冷事件减少,连续干旱日数减少,极端强降水事件增多。具体来看,到21世纪末期,日最高气温最高值(TXx)和日最低气温最低值(TNn)在整个区域上都是增加的,大部分地区增加值分别超过2.4℃和3.2℃;夏季日数(SU)和热带夜数(TR)也都表现为增加,但两者的变化分布基本相反,其中SU在山区增加幅度较大,平原地区增加幅度较小,而TR在平原地区的增加值较山区更显著,两个指数未来增加值分别为20~40 d和5~40 d;霜冻日数(FD)和冰冻日数(ID)都表现为减少,减少值分别超过10 d和5 d;与降水有关的极端气候事件指数,CDD、降雨日数(R1mm)和中雨日数(R10mm)的变化均以减少为主,但数值较小,一般都在?10%~0之间;最大5 d降水量(RX5day)、降水强度(SDII)和大雨日数(R20mm)主要表现为增加,增加值一般在0~25%之间。从区域平均的变化来看,与气温有关的极端气候事件指数的变化趋势较为显著,与降水有关的极端气候事件指数变化趋势较小。两个区域对比来看,雄安新区模式间的不确定性更大,反映出模式对较小区域模拟的不足。  相似文献   

17.
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.  相似文献   

18.
In this study, the influence of the East Atlantic Oscillation (EAO) on the climate indices based on the daily minimum temperature at eight stations in Serbia was examined. The following climate indices were analyzed: frost days (FD), cold nights (TN10p), warm nights (TN90p), minimum value of daily minimum temperature (TNn), tropical nights (TR), and cold spell duration indice (CSDI). Analysis of correlation between the East Atlantic Index (EAI) and the geopotential at 500 hPa, as well as between the EAI and climate indices was realized for all seasons and months during the period 1950–2009. Two characteristic situations for the extreme positive and negative values of the EAI were analyzed. Seasonal and monthly trend analyses of climate indices were performed. Decreases of FD and TN10p and increases of TN90p and TR were observed. It was found that the negative correlation prevailed between the EAI and TN10p/FD, and positive one between the EAI and TN90p/TR for all seasons and months. The highest correlation was observed between the EAI and TN90p in February.  相似文献   

19.
Going to the Extremes   总被引：8，自引：1，他引：8  
Projections of changes in climate extremes are critical to assessing the potential impacts of climate change on human and natural systems. Modeling advances now provide the opportunity of utilizing global general circulation models (GCMs) for projections of extreme temperature and precipitation indicators. We analyze historical and future simulations of ten such indicators as derived from an ensemble of 9 GCMs contributing to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR4), under a range of emissions scenarios. Our focus is on the consensus from the GCM ensemble, in terms of direction and significance of the changes, at the global average and geographical scale. The climate extremes described by the ten indices range from heat-wave frequency to frost-day occurrence, from dry-spell length to heavy rainfall amounts. Historical trends generally agree with previous observational studies, providing a basic sense of reliability for the GCM simulations. Individual model projections for the 21st century across the three scenarios examined are in agreement in showing greater temperature extremes consistent with a warmer climate. For any specific temperature index, minor differences appear in the spatial distribution of the changes across models and across scenarios, while substantial differences appear in the relative magnitude of the trends under different emissions rates. Depictions of a wetter world and greater precipitation intensity emerge unequivocally in the global averages of most of the precipitation indices. However, consensus and significance are less strong when regional patterns are considered. This analysis provides a first overview of projected changes in climate extremes from the IPCC-AR4 model ensemble, and has significant implications with regard to climate projections for impact assessments. An erratum to this article is available at . An erratum to this article can be found at  相似文献   

20.
基于中国均一化气温数据集CN05.1的观测数据,结合暖昼指数（TX90）、冷昼指数（TX10）、暖夜指数（TN90）、冷夜指数（TN10）、暖日持续指数（WSDI）和冷日持续指数（CSDI）6个极端温度指数,从气候平均、概率分布、年际变率和年际趋势方面,系统评估区域气候模式（Climate–Weather Research and Forecasting model, CWRF）对1980～2015年间我国极端温度指数区域分布和年际变化的模拟能力,为改进并利用模式研究我国未来区域极端温度的预测提供科学依据。结果显示:观测的冷暖指数在北方的年际变率幅度高于南方,其中暖指数在我国大部分地区为增暖趋势,冷指数在北方地区的变冷趋势显著,尤其暖夜增暖、冷夜变冷,极端暖事件（WSDI）的持续性比冷事件（CSDI）显著。CWRF模式较好再现了极端温度指数的年均分布和年际变化趋势特征,尤其对暖日和冷日持续指数的模拟优势显著,但仍存在系统性的区域偏差,如低估暖昼和冷夜的极值强度;对华东地区暖（冷）指数变暖（冷）的趋势存在低（高）估;尤其是低估青藏高原地区暖、冷指数的强度,并且高估其暖昼变冷、暖夜变暖的年际变化趋势。因此,该模式对华东及高原地区极端温度的强度和年际变率的模拟仍亟需改善。  相似文献   

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