Statistical properties of winds near the Taichung Harbour are investigated. The 26 years'incomplete data of wind speeds, measured on an hourly basis, are used as reference. The possibility of imputation using simu...Statistical properties of winds near the Taichung Harbour are investigated. The 26 years'incomplete data of wind speeds, measured on an hourly basis, are used as reference. The possibility of imputation using simulated results of the Auto-Regressive (AR), Moving-Average (MA), and/ or Auto-Regressive and Moving-Average (ARMA) models is studied. Predictions of the 25-year extreme wind speeds based upon the augmented data are compared with the original series. Based upon the results, predictions of the 50- and 100-year extreme wind speeds are then made.展开更多
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...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.展开更多
为获得高层建筑围护结构设计风荷载,通常需要考虑其表面风压系数的概率特征,进而进行极值估计。针对当前基于超越阈值模型的风压系数极值估计方法存在阈值选取困难,需要较大样本的不足,基于高层建筑标准模型进行风洞试验,首先研究其表...为获得高层建筑围护结构设计风荷载,通常需要考虑其表面风压系数的概率特征,进而进行极值估计。针对当前基于超越阈值模型的风压系数极值估计方法存在阈值选取困难,需要较大样本的不足,基于高层建筑标准模型进行风洞试验,首先研究其表面风压系数的概率特征,结果表明迎风区测点接近高斯分布,分离区测点风压系数母体接近Gamma分布,风压系数极小值接近GEV(general extreme value,GEV)分布;提出一种改进的POT(peak over threshold,POT)极值估计方法进行表面风压系数极值估计,进而与几种传统极值估计方法进行对比,结果表明改进POT极值估计方法可实现小样本的风压系数极值估计,其估计结果与大样本容量的标准极值偏差小于5%,且稳定性较好;最后给出了标准高层建筑模型表面极值风压系数。展开更多
随着全球气候变暖,近年来极端降水事件及其引发的洪涝灾害频发,极端降水事件的模拟与精细化研究显得尤为重要。随着区域气象站网的加密建设,为极端降水事件的精细化研究提供可能。为了将区域站短序列数据应用到日极端降水量的研究中,本...随着全球气候变暖,近年来极端降水事件及其引发的洪涝灾害频发,极端降水事件的模拟与精细化研究显得尤为重要。随着区域气象站网的加密建设,为极端降水事件的精细化研究提供可能。为了将区域站短序列数据应用到日极端降水量的研究中,本研究首先基于年最大值法(annual maximum,AM)和超阈值峰值法(peak over threshold,POT)抽样方法与44种概率分布模型,选择最优抽样方法与概率分布模型,并在此基础上提出对于短序列数据计算日极端降水量的订正方案,通过国家站分析论证,优选出最佳订正方案,将该订正方法应用到只有短序列实测数据的区域站中,优选插值参数并比较不同空间插值方法对插值精度的影响,选择最优的插值方法实现日极端降水量的精细化研究。结果表明,POT1抽样方法与广义帕累托模型是最适用于计算河北省日极端降水量的抽样方法与模型;本研究提出的区域站订正与计算日极端降水量方法可行,将区域站考虑进来后与国家站联合插值使得在空间上更加精细。展开更多
基金The project is partly supported by the National Science Council, Contract Nos. NSC-89-261 l-E-019-024 (JZY), and NSC-89-2611-E-019-027 (CRC).
文摘Statistical properties of winds near the Taichung Harbour are investigated. The 26 years'incomplete data of wind speeds, measured on an hourly basis, are used as reference. The possibility of imputation using simulated results of the Auto-Regressive (AR), Moving-Average (MA), and/ or Auto-Regressive and Moving-Average (ARMA) models is studied. Predictions of the 25-year extreme wind speeds based upon the augmented data are compared with the original series. Based upon the results, predictions of the 50- and 100-year extreme wind speeds are then made.
文摘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.
文摘为获得高层建筑围护结构设计风荷载,通常需要考虑其表面风压系数的概率特征,进而进行极值估计。针对当前基于超越阈值模型的风压系数极值估计方法存在阈值选取困难,需要较大样本的不足,基于高层建筑标准模型进行风洞试验,首先研究其表面风压系数的概率特征,结果表明迎风区测点接近高斯分布,分离区测点风压系数母体接近Gamma分布,风压系数极小值接近GEV(general extreme value,GEV)分布;提出一种改进的POT(peak over threshold,POT)极值估计方法进行表面风压系数极值估计,进而与几种传统极值估计方法进行对比,结果表明改进POT极值估计方法可实现小样本的风压系数极值估计,其估计结果与大样本容量的标准极值偏差小于5%,且稳定性较好;最后给出了标准高层建筑模型表面极值风压系数。
文摘随着全球气候变暖,近年来极端降水事件及其引发的洪涝灾害频发,极端降水事件的模拟与精细化研究显得尤为重要。随着区域气象站网的加密建设,为极端降水事件的精细化研究提供可能。为了将区域站短序列数据应用到日极端降水量的研究中,本研究首先基于年最大值法(annual maximum,AM)和超阈值峰值法(peak over threshold,POT)抽样方法与44种概率分布模型,选择最优抽样方法与概率分布模型,并在此基础上提出对于短序列数据计算日极端降水量的订正方案,通过国家站分析论证,优选出最佳订正方案,将该订正方法应用到只有短序列实测数据的区域站中,优选插值参数并比较不同空间插值方法对插值精度的影响,选择最优的插值方法实现日极端降水量的精细化研究。结果表明,POT1抽样方法与广义帕累托模型是最适用于计算河北省日极端降水量的抽样方法与模型;本研究提出的区域站订正与计算日极端降水量方法可行,将区域站考虑进来后与国家站联合插值使得在空间上更加精细。
