共查询到17条相似文献，搜索用时 218 毫秒
1.
运用广义帕雷托分布(GPD)和广义极值分布(GEV),借助于L-矩的参数估计方法,对四川盆地12站的小时极端降水量进行拟合,并对两种模型的拟合效果进行比较。运用Hill图,结合统计量D*来确定GPD的最佳门限值是合适的,选出的样本是独立的。各站的小时极端降水概率分布均符合GPD和GEV,但GPD模型的拟合精度要优于GEV模型。利用两种模型推算出各站给定重现期的最大小时降水量,其中泸州50 a一遇和100 a一遇的降水极值分位数都超过了100 mm,除了遂宁站外,两种模型估计出的极值分位数的相对误差基本都在10%以下。通过分析,GPD推算的结果更加可靠。 相似文献
2.
未来情景下南水北调中线工程水源区极端降水分布特征 总被引：1，自引：0，他引：1
利用南水北调中线工程水源区9个气象站点1961-2008年的日降水资料和IPCC第四次评估报告多模式数据结果,抽取逐年的最大日降水量序列样本,运用广义极值分布（GEV）和广义帕累托分布 (GPD）两种极值统计模型对样本进行拟合,遴选出描述流域最大日降水量分布规律的最优概率模型,推算重现期对应的降水量值,并预估该流域极端降水事件在未来气候变化情景下的响应。研究表明：南水北调中线工程水源区降水极值均符合GEV和GPD分布,但GPD模型更适合用于描述该流域降水极值分布;未来气候变化情景下用GPD分布拟合的降水极值优于使用GEV分布;A2情景下极端降水事件的发生将更频繁、更强烈,A1B情景下次之,B1情景下相对较小,表明未来高排放气候情景对极端降水事件的影响比中、低排放情景大。 相似文献
3.
南京过去100年极端日降水量模拟研究 总被引：2，自引：0，他引：2
在南京过去100年日降水资料的基础上,利用极值理论中的区组模型和阈值模型分析了极端日降水分布特征.首先通过广义极值(GEV)模型模拟了日降水的年极值序列(AMDR),用极大似然估计(MLE)方法计算了模型的参数,并借助轮廓似然函数估计出参数的精确误差区间,同时采用4种较直观的诊断图形对模型的合理性进行全面评估,结果表明Frechet是区组模型中最适合描述极端日降水分布特征的函数.其次,将日降水序列分3种情景构建极值分布的阈值模型(GPD),考察了观测数据的规模对应用该模型的限制,重点讨论了如何针对给定观测样本选择合适的阈值收集极值信息.分析结果认为,长度不小于50年的气候序列,采用24 mm的日降水量作为临界阈值均能进行GPD分析.该阈值处于年降水序列第91个百分位附近,即对目前长度为50年左右的日观测资料,第91个百分位点以上的数据基本能满足GPD研究的需要.另外,根据GEV和GPD对未来极端降水重现水平的推断情况,GPD预测值的置信区间要比GEV的窄,极值推断的不确定性相对也较小,更适合用于研究中国目前规模不大的气候资料.最后,对GPD模型的形状参数和尺度参数进行变换,分别引入描述线性变化的动态变量,分析降水序列中潜在的变异行为对极值理论应用的影响.这种变异包括降水序列中长期的均值变化及百分位变化,从模拟结果看,暂未发现资料变异行为对极值分析产生显著于扰. 相似文献
4.
基于多状态Markov链模式的极端降水模拟试验 总被引：3，自引：2，他引：1
文中建立了基于多状态一阶Markov链的逐日降水量随机模式式结合广义帕雷托分布(GPD)产生夏季逐日极端降水量的模拟资料,结果所显示的各种气候特征表明,绝大多数站点(尤其是中国东部多雨地区)都达到较高的精度.分析表明,该模式对中国东部极端降水特征的模拟能力在某些方面优于两状态一阶Markov链模式.对东部6个代表站模拟试验结果表明,月降水均方差、日降水极大值、月半均降水日数、日降水均方差、日平均降水量等指标与实况比较,均证明该模式对逐日降水量的模拟效果较好,基本模拟出降水量的各种特征.对中同东部78个代表站采用的两种模式模拟结果对比发现,除日平均降水量以外,月半均降水日数、日降水平均极大值都与实际观测结果较为一致,总体上优于两状态模式,说明用该模式在全国范围内模拟逐日降水特征尤其是极端降水特征有较高的町行性.例如,由其中6个代表站模拟资料所拟合的极端降水GPD模式具有较高的拟合优度.无论从门限值或重现期值来看都可发现模拟与实测结果有较好的相似性,且两者门限值的误差越小,重现期极值的差距也越小.证明Markov链模式对极端降水的模拟有广泛的适用性. 相似文献
5.
着重论述极值统计分布在极端天气气候事件和重大工程设计中的重要意义,综述该领域国内外研究进展。例如,基于超门限峰值法（POT）的广义帕累托分布（GPD)和基于单元极大值法（BM）的广义极值分布（GEV）及其参数间的理论关系;采用极值分布模型与多状态一阶Markov链相结合构建降尺度模型模拟局地极端降水事件,推算一定重现期的极端降水量的分位数;探讨极值分布模型分位数估计误差问题,多维极值分布理论及其应用等问题。 相似文献
6.
江淮地区极端降水特征及其变化趋势的研究 总被引：3，自引：1，他引：2
利用1961~2011年江淮地区5~9月无缺测的71站逐日降水资料,做基于POT(Peaks-Over-Threshold)的广义Pareto分布(GPD),研究江淮地区极端降水的分布特征及其变化趋势。结果表明:(1)皖赣交界处阈值最大,西北和东南部较小,且江淮大部分地区阈值的线性趋势系数为正,其中湖北东部和江西北部的站点,趋势达0.8 mm(10 a)-1以上,并通过了显著性水平0.01的MK(Mann-Kendall)检验。(2)江淮地区中东部多存在连续性极端降水,因此文中采用基于极值指数的自动分串技术获得近似独立的极值样本。(3)尺度参数大值区位于江淮南部,西北、东南以及淮河以北较小,且线性趋势系数在大部分地区均表现为正值,表明出现降水极大值的概率增加。(4)皖赣鄂交界处是极端降水发生概率大值区,而西北、东南及安徽中部地区较小,且极端降水在大部分地区有增加的趋势,特别是在大别山附近及河南东部,2年和20年重现水平的趋势分别达6 mm(10 a)-1和20 mm(10 a)-1以上。 相似文献
7.
引进广义帕雷托分布拟合我国东部地区78个测站夏季(5～9月)逐日极端降水量.结果表明,不同门限值条件下的逐日降水量所拟合的降水极值概率分布均符合广义帕雷托分布,与其它极值分布如广义极值(下称GEV)分布模式相比,以GPD模式为最优.根据现代气候条件,分别计算了50年一遇和100年一遇的极端降水量分位数并分析其空间分布特征,两者基本一致,总体上都呈现出由东南向西北方减小的趋势,且南北差异较大,南方的极端降水量值可能达到北方地区的两倍以上.此外,资料年份越长,拟合效果越好. 相似文献
8.
以中国南方诸代表站近40 a(1965—2004年)夏季(5—9月)逐日降水资料为研究对象,探讨了夏半年各站湿期游程及其极端值的概率分布最佳模式。在对各站湿期游程分别验证指数分布的基础上,作耿贝尔(Gumbel)极值分布和广义帕雷托分布(GPD)拟合,进而对两者的拟合效果进行比较。并由此对湿期长度估计其不同重现期(如20 a一遇、50 a一遇和100 a一遇)的极端湿期长度的分位数概率。经K-S方法的统计检验,证明GPD分布拟合效果较好,能更加精确的模拟出中国南方夏季的极端连雨日数及其概率。 相似文献
9.
采用年最大值法（AM）及超阈值峰量法（POT）分别构建基于0.5°×0.5°网格的全国地面日降水极值序列,建立基于广义极值分布（GEV）和广义帕累托分布（GPD）的降水极值统计模型,通过K-S检验评估模型拟合效果,研究全国日降水极值的统计规律及其空间分布特征,提出适用于不同地区极端日降水的极值分布模型与阈值选取标准,结果表明：(1)POT序列比AM序列更符合降水极值序列的要求;(2)为便于比较并提高模型拟合效果,POT序列的阈值由百分位数法确定效果较好;(3)阈值方案优选结果在空间分布上与中国干湿区域的划分有很好的相关性,在湿润地区宜将第90～94百分位数作为阈值,在半湿润和半干旱地区宜将第94～97百分位数作为阈值,在干旱地区则使用第97～99百分位数较为合适。 相似文献
10.
城市化对人类生活息息相关的一些指标(如夏季极端暖夜等)的影响研究尚少.取环渤海地区气象观测站的夏季(6-8月)逐日最低气温资料(1958-2009年),使用广义极值(GEV)分布拟合夏季极端暖夜气温分布,并对拟合函数的3个分布特征参数的年际变化进行分析,根据特征参数变化特征进行城市化对极端暖夜的影响程度的分离.研究结果表明,环渤海地区,在极端暖夜气温分布的3个参数的年际变化中,以位置参数的代表性最好.在城市快速发展时期,城市偏高气温出现的可能性大,但极端气温变化幅度也较大.城市化对环渤海不同类型城市夏季极端暖夜气温的贡献均为上升作用,增温速度最大约为0.3℃/(10a). 相似文献
11.
A newly-discovered GPD-GEV relationship together with comparing their models of extreme precipitation in summer 总被引：3，自引：0，他引：3
It has been theoretically proven that at a high threshold an approximate expression for a quantile of GEV （Generalized Extreme Values） distribution can be derived from GPD （Generalized Pareto Distribution）. Afterwards, a quantile of extreme rainfall events in a certain return period is found using L-moment estimation and extreme rainfall events simulated by GPD and GEV, with all aspects of their results compared. Numerical simulations show that POT （Peaks Over Threshold）-based GPD is advantageous in its simple operation and subjected to practically no effect of the sample size of the primitive series, producing steady high-precision fittings in the whole field of values （including the high-end heavy tailed）. In comparison, BM （Block Maximum）-based GEV is limited, to some extent, to the probability and quantile simulation, thereby showing that GPD is an extension of GEV, the former being of greater utility and higher significance to climate research compared to the latter. 相似文献
12.
This study was conducted using daily precipitation records gathered at 37 meteorological stations in northern Xinjiang, China, from 1961 to 2010. We used the extreme value theory model, generalized extreme value (GEV) and generalized Pareto distribution (GPD), statistical distribution function to fit outputs of precipitation extremes with different return periods to estimate risks of precipitation extremes and diagnose aridity–humidity environmental variation and corresponding spatial patterns in northern Xinjiang. Spatiotemporal patterns of daily maximum precipitation showed that aridity–humidity conditions of northern Xinjiang could be well represented by the return periods of the precipitation data. Indices of daily maximum precipitation were effective in the prediction of floods in the study area. By analyzing future projections of daily maximum precipitation (2, 5, 10, 30, 50, and 100 years), we conclude that the flood risk will gradually increase in northern Xinjiang. GEV extreme value modeling yielded the best results, proving to be extremely valuable. Through example analysis for extreme precipitation models, the GEV statistical model was superior in terms of favorable analog extreme precipitation. The GPD model calculation results reflect annual precipitation. For most of the estimated sites’ 2 and 5-year T for precipitation levels, GPD results were slightly greater than GEV results. The study found that extreme precipitation reaching a certain limit value level will cause a flood disaster. Therefore, predicting future extreme precipitation may aid warnings of flood disaster. A suitable policy concerning effective water resource management is thus urgently required. 相似文献
13.
导线覆冰极值的概率分布模拟及其应用试验 总被引：2，自引：0，他引：2
利用南方地区多个气象站和电力部门观冰站的导线覆冰逐日冰厚资料,将广义极值分布和广义帕雷托分布引入导线覆冰的概率模型研究中,通过超门限覆冰次数的泊松分布拟合检验,结合H ill图解,提出了基于超门限峰值法门限值的确定方法;对两种分布在导线覆冰极值模型拟合的适用性研究表明,广义帕雷托分布对各站覆冰冰厚极值的拟合精度最高;重现期冰厚极值估计随样本长度的变化分析表明,广义帕雷托分布模型极值估计的稳定性比广义极值分布强,一般样本容量达到25 a左右时,广义帕雷托分布重现期冰厚极值的估计趋于稳定,可以作为短序列下估计导线覆冰极值的较好方法。 相似文献
14.
The main goal of this study was to present the statistical analysis of the daily precipitation exceeding 20 mm in Belgrade and their links with the prevailing directions of the air trajectories at 500, 1,500 and 5,000 m. For the extreme precipitation analysis, the generalised extreme value (GEV) distribution and generalised Pareto distribution (GPD) were used. The estimated return levels for 100- and 10-year return periods using GEV and GPD were obtained. Four-day backward trajectory simulations were conducted for days with precipitation exceeding 20 mm to investigate the regional transport of the air moisture towards Belgrade using the hybrid single-particle Lagrangian integrated trajectory model. The air trajectories were classified into 13 trajectory categories by the origin and direction of their approach to Belgrade. Three of the most frequent categories of air flow from south-west, south-east and north-west contributed to more than a half of the observed precipitation. Almost 74.5 % of precipitation totals in Belgrade fell during the warmer part of the year. These were directly connected with the intensive convection of colder and humid, usually maritime, air masses. 相似文献
15.
1960-2005年长江流域降水极值概率分布特征 总被引：7，自引：0，他引：7
摘 要：根据1960-2005年长江流域147个气象站逐日降水观测资料和ECHAM5/ MPI-OM气候模式20世纪试验期（1941-2000年）79个格点逐日降水模拟资料，建立年最大强降水AM（annual maximum）序列及汛期日降水量＜1.27 mm的最长干旱持续天数MI（Munger index）序列，分析了长江流域降水极值序列的时空分布特征和概率分布模式。结果表明：1) 长江流域强降水事件的强度和概率最大的地区位于岷沱江流域中游、洞庭湖湖区、长江中下游干流区与鄱阳湖东南部支流等地区，干旱事件强度和概率最大的地区位于金沙江流域中下游与嘉陵江流域；2) 气候模式模拟的长江流域AM事件的多年平均值普遍高于观测值，但离差系数普遍低于观测值; 3) 气候模式模拟结果与观测的降水极值空间分布有一定的差异，但对气候模式和实际观测的降水极值概率分布的拟合，均证明Wakeby分布函数能够较好地拟合降水极值的概率分布。 相似文献
16.
Based on the daily observational precipitation data of 147 stations in the Yangtze River basin for 1960-2005, and the projected daily data of 79 grids from ECHAM5/MPI-OM in the 20th century, time series of precipitation extremes which contain annual maximum (AM) and Munger index (MI) were constructed. The distribution feature of precipitation extremes was analyzed based on the two index series. Research results show that (1) the intensity and probability of extreme heavy precipitation are higher in the middle Mintuo River sub-catchment, the Dongting Lake area, the mid-lower main stream section of the Yangtze River, and the southeastern Poyang Lake sub-catchment; whereas, the intensity and probability of drought events are higher in the mid-lower Jinsha River sub-catchment and the Jialing River sub-catchment; (2) compared with observational data, the averaged value of AM is higher but the deviation coefficient is lower in projected data, and the center of precipitation extremes moves northwards; (3) in spite of certain differences in the spatial distributions of observed and projected precipitation extremes, by applying General Extreme Value (GEV) and Wakeby (WAK) models with the method of L-Moment Estimator (LME) to the precipitation extremes, it is proved that WAK can simulate the probability distribution of precipitation extremes calculated from both observed and projected data quite well. The WAK could be an important function for estimating the precipitation extreme events in the Yangtze River basin under future climatic scenarios. 相似文献
17.
1960-2005年长江流域降水极值概率分布特征 总被引：1，自引：1，他引：0
Based on the daily observational precipitation data of 147 stations in the Yangtze River basin for 1960-2005,and the projected daily data of 79 grids from ECHAM5/MPI-OM in the 20th century,time series of precipitation extremes which contain annual maximum(AM)and Munger index(MI)were constructed.The distribution feature of precipitation extremes was analyzed based on the two index series.Research results show that(1)the intensity and probability of extreme heavy precipitation are higher in the middle Mintuo River sub-catchment,the Dongting Lake area,the mid-lower main stream section of the Yangtze River,and the southeastern Poyang Lake sub-catchment;whereas,the intensity and probability of drought events are higher in the mid-lower Jinsha River sub-catchment and the Jialing River sub-catchment;(2)compared with observational data,the averaged value of AM is higher but the deviation coefficient is lower in projected data,and the center of precipitation extremes moves northwards;(3)in spite of certain differences in the spatial distributions of observed and projected precipitation extremes,by applying General Extreme Value(GEV)and Wakeby(WAK)models with the method of L-Moment Estimator(LME)to the precipitation extremes,it is proved that WAK can simulate the probability distribution of precipitation extremes calculated from both observed and projected data quite well.The WAK could be an important function for estimating the precipitation extreme events in the Yangtze River basin under future climatic scenarios. 相似文献