中国三峡地区汛期降水量的正态性研究

为了分析三峡地区降水量序列的正态性和谱结构,对降水量的常见各种变换进行试验性研究。试验包括单站降水量、降水量的平方根、立方根和Γ分布概率值等非线性变换,以及级别变换。研究区域多站平均降水量、区域降水量的主分量、区域降水量的非线性变换后的主分量和区域降水量的级别变换后的主分量等序列。研究发现三峡地区单站降水量的各种变换不改变序列原始谱结构,仅影响概率分布的偏度和峰度,使其较好地遵从正态分布,其中以Γ分布的变换以及级别变换在分布的偏度上为最好。 区域降水量的各种变换的综合指数(区域平均值和主分量)正态性及谱结构分析表明,除区域平均值变换后不改变原单站序列的谱结构外,主分量的综合指数能改变原单站序列的谱结构,同时也影响概率分布的偏度和峰度,使其能较好地遵从正态分布。其中以降水量的立方根和Γ分布概率变换以及级别变换,在分布的偏度上有较好的效果。     

兰州地区降水量正态分布特征

在对降水资料的分析过程中,要求资料的时间序列呈正态分布。利用兰州地区的兰州、皋兰、榆中和永登4个站点1960~2009年的降水量资料,采用"偏度—峰度系数+W检验"方法,基于SPSS软件,对兰州地区的年、季和月降水量正态特征进行分析。结果表明,兰州地区4个气象站的年降水量均呈正态性分布;兰州、皋兰和永登3站的夏、秋2季降水量为正态性分布,而榆中站只有秋季降水量为正态性分布,且秋季降水量的正态性最好,冬季最差;大多数月降水量不服从正态分布,但对降水序列进行平方根处理后,其正态性得到明显的改善。     

浑太流域降水极值的统计分布特征

基于浑太流域1966-2006年73个雨量站的日降水资料,建立了逐站年最大日降水量(AnnualMaximum,AM)序列和汛期4-9月日降水量<1.27mm.d-1的最长持续干旱天数(Munger Index,MI)序列,并对其时空分布规律进行了分析。采用广义极值(General Extreme Value,GEV)分布、广义帕雷托(General Pareto,GP)分布、韦布尔(Weibull,WB)分布、约翰逊SB(Jonhson SB,J-SB)分布、Burr分布和对数逻辑(Log-Logistic,L-LG)分布等6种极值分布函数对AM和MI序列进行了逐站分布拟合,结果表明,广泛应用的GEV分布整体拟合程度最好,有50个测站的KS检验统计量Dn<0.09,而未曾推广使用的Burr分布的拟合效果也非常好,有36个测站Dn<0.09。用GEV分布对50年一遇的AM和MI进行了估算,发现流域中心地区极端强降水和极端干旱的程度较高,分别为>208mm.d-1和>47d。     

基于风廓线雷达的湖北梅雨期暴雨中小尺度特征

针对2016年湖北梅雨期3次(“6·19”、“7·5”和“7·19”)暴雨过程,首先对比了汉口站探空数据与汉口、咸宁两个风廓线雷达站水平风速、风向,发现“6·19”和“7·5”过程汉口风廓线雷达站3 km以下水平风速和探空数据较为接近,而3次过程中咸宁风廓线雷达站8 km以下水平风向、风速和汉口站探空数据基本吻合。在此基础上利用风廓线雷达资料并结合常规、加密自动气象站资料,对3次过程中水平风场、平均垂直速度及其变率、水平风速垂直切变、大气折射率结构常数(C■)等进行分析。结果表明：(1)降水开始前西南风速明显增大,中层干冷空气入侵和地面冷池形成的中尺度偏东气流是“6·19”过程50站出现大于等于17.2 m·s^-1大风的主要原因,“7·5”和“7·19”过程西南急流长时间维持及1 km以下的偏东气流则是短时强降水持续时间较长的诱因;(2)梅雨期暴雨期间风廓线雷达观测的水平风速垂直切变、平均垂直速度及其变率随高度变化较小,较强上升运动区域主要集中在4 km高度以下;(3)C■显示强降水发生前大气水汽含量有一增加过程,且整层水汽含量深厚,C■大值区的消失对应降水结束。     

Extreme daily precipitation: the case of Serbia in 2014

The extreme daily precipitation in Serbia was examined at 16 stations during the period 1961–2014. Two synoptic situations in May and September of 2014 were analysed, when extreme precipitation was recorded in western and eastern Serbia, respectively. The synoptic situation from 14 to 16 May 2014 remained nearly stationary over the western and central Serbia for the entire period. On 15 May 2014, the daily rainfall broke previous historical records in Belgrade (109.8 mm), Valjevo (108.2 mm) and Loznica (110 mm). Precipitation exceeded 200 mm in 72 h, producing the most catastrophic floods in the recent history of Serbia. In Negotin (eastern Serbia), daily precipitation of 161.3 mm was registered on 16 September 2014, which was the maximum value recorded during the period 1961–2014. The daily maximum in 2014 was registered at 6 out of 16 stations. The total annual precipitation for 2014 was the highest for the period 1961–2014 at almost all stations in Serbia. A non-significant positive trend was found for all precipitation indices: annual daily maximum precipitation, the total precipitation in consecutive 3 and 5 days, the total annual precipitation, and number of days with at least 10 and 20 mm of precipitation. The generalised extreme value distribution was fitted to the annual daily maximum precipitation. The estimated 100-year return levels were 123.4 and 147.4 mm for the annual daily maximum precipitation in Belgrade and Negotin, respectively.

     

Description and validation of a two-step analogue/regression downscaling method

This study describes a two-step analogue statistical downscaling method for daily temperature and precipitation. The first step is an analogue approach: the “n” days most similar to the day to be downscaled are selected. In the second step, a multiple regression analysis using the “n” most analogous days is performed for temperature, whereas for precipitation, the probability distribution of the “n” analogous days is used to define the amount of precipitation. Verification of this method has been carried out for the Spanish Iberian Peninsula and the Balearic Islands. Results show good performance for temperature (BIAS close to 0.1 °C and mean absolute errors around 1.9 °C) and an acceptable skill for precipitation (reasonably low BIAS except in autumn with a mean of ?18 %, mean absolute error lower than for a reference simulation, i.e. persistence and a well-simulated probability distribution according to two non-parametric tests of similarity).     

Probabilistic correction of RCM precipitation in the Basque Country (Northern Spain)

A parametric quantile–quantile transformation is used to correct the systematic errors of precipitation projected by regional climate models. For this purpose, we used two new probability distributions: modified versions of the Gumbel and log-logistic distributions, which fit to the precipitation of both wet and dry days. With these tools, the daily probability distribution of seven regional climate models was corrected: Aladin-ARPEGE, CLM-HadCM3Q0, HIRHAM-HadCM3Q0, HIRHAM-BCM, RECMO-ECHAM5-rt3, REMO-ECHAM-rt3 and PROMES-HadCM3Q0. The implemented method presents an error less than 5 % in the simulation of the average precipitation and 1 % in the simulation of the number of dry days. For the study area, an intensification of daily and subdaily precipitation is expected under the A1B scenario throughout the 21st century. This intensification is interpreted as a consequence of the process of ‘mediterraneanisation’ of the most southern ocean climate.     

Nonparametric kernel estimation of annual precipitation over Iran

In this paper, annual precipitation data sets from five old rain gauge stations (Bushehr, Isfahan, Meshed, Tehran, and Jask) in Iran were fitted to nonparametric kernel function by using rectangular, triangular, and Gaussian or normal as kernel functions. The smoothing parameter was calculated by four methods including rule of thumb, Adamowski criterion, least squares cross-validation, and Sheater and Jones plug-in. The Adamowski criterion showed a better performance compared to other methods due to goodness of fit tests. The results of these proposed nonparametric methods will be then compared to the results of the parametric density functions including normal, two and three parameter log-normal, two parameter gamma, Pearson and log-Pearson type 3, Gumbel or extreme value type 1 and also Fourier series method which were applied by a previous study for the same stations. It was concluded that the annual precipitation data were fitted to nonparametric methods better than parametric methods.     

近38年中国气温和降水的1 km网格数据集

对中国38年的气温和降水进行了空间插值分析,选取最优模型去生成1km网格数据集,为中国大陆的植被分布、气候变化和环境生态等研究提供支持。基于国家气象中心839个气象站的逐日气温和降水数据,用经度、纬度和海拔作为ANUSPLIN软件插值的3个变量,对降水进行开平方预处理,采用3次样条的薄盘光滑样条法,得到了1980—2017年中国大陆月平均气温和月累计降水1km网格插值数据集。数据集的广义交叉验证均方根(RTGCV)和均方根误差(RMSE)具有年周期性和明显的季节变化特征;各站点的平均误差(MBE)的频率分布近似正态分布,绝对误差(MAE)的空间分布也符合中国大陆气候的变化特征。数据集在精准度和时间序列上较新,且提供公共下载服务,可为全国陆地生态系统的研究提供信息支持。     

Evaluation of the weather generator CLIGEN with daily precipitation characteristics in Korea

The ability of the CLImate GENerator (CLIGEN) weather generator to reproduce daily precipitation characteristics for Korea was assessed on the basis of 55-year long historical daily precipitation records from eight weather stations (Seoul, Incheon, Daegu, Ulsan, Gwangju, Busan, Kangneung, and Jeonju) representing different parts of the Korean peninsula. The basic statistics of daily precipitation (mean, standard deviation, skewness of daily precipitation, number of rainy days, and the lengths of wet/dry period), probability distribution characteristics of daily precipitation (percentiles and maximum value), and the spatial covariance statistic generated by CLIGEN were compared with those derived from the observed weather series. Significance tests were conducted on the difference between the historical and generated statistics with the 1% significance level. The results show that CLIGEN simulates most of the daily precipitation characteristics satisfactorily with a tendency to slightly underestimate the mean and variability of daily precipitation. Especially, the number of rainy days is perfectly reproduced with mean relative error of 0.4% across all the stations. It is also found that the spatial covariance statistic from eight different stations is well reproduced by CLIGEN with respect to the leading EOF mode of summer season daily precipitation.     

江淮梅雨区1960—2014年夏季极端降水变化特征及影响因素

利用江淮梅雨区66个测站1960—2014年逐日降水数据和同期NCEP/NCAR再分析资料,基于多个极端降水指数,通过趋势分析、EOF分析和合成分析等手段,探究该区夏季极端降水事件的时空变化特征及影响因素。结果表明：(1)夏季极端降水指数以上升为主,显著上升区主要位于东部。(2)夏季极端降水指数第一特征向量呈全“+”分布形态,北部地区更强,第二特征向量呈“西北+东南-”分布形态;第一模态时间系数呈上升趋势,第二模态时间系数变化趋势不明显。(3)在强（弱）夏季极端降水典型年,西太平洋副热带高压位置偏西（东),中纬度地区表现出经（纬）向型环流分布特征,利于（不利于）江淮地区极端降水发生;同时,对流层中、低层上升运动增强（中层气流辐散增强),水汽通量增强、辐合（减弱、辐散),因此,梅雨区极端降水异常增强（减弱)。     

Using quantile regression to detect relationships between large-scale predictors and local precipitation over northern China

Quantile regression(QR) is proposed to examine the relationships between large-scale atmospheric variables and all parts of the distribution of daily precipitation amount at Beijing Station from 1960 to 2008. QR is also applied to evaluate the relationship between large-scale predictors and extreme precipitation(90th quantile) at 238 stations in northern China.Finally, QR is used to fit observed daily precipitation amounts for wet days at four sample stations. Results show that meridional wind and specific humidity at both 850 h Pa and 500 h Pa(V850, SH850, V500, and SH500) strongly affect all parts of the Beijing precipitation distribution during the wet season(April–September). Meridional wind, zonal wind, and specific humidity at only 850 h Pa(V850, U850, SH850) are significantly related to the precipitation distribution in the dry season(October–March). Impacts of these large-scale predictors on the daily precipitation amount with higher quantile become stronger, whereas their impact on light precipitation is negligible. In addition, SH850 has a strong relationship with wet-season extreme precipitation across the entire region, whereas the impacts of V850, V500, and SH500 are mainly in semi-arid and semi-humid areas. For the dry season, both SH850 and V850 are the major predictors of extreme precipitation in the entire region. Moreover, QR can satisfactorily simulate the daily precipitation amount at each station and for each season, if an optimum distribution family is selected. Therefore, QR is valuable for detecting the relationship between the large-scale predictors and the daily precipitation amount.     

近36年昌都市降水集中度与集中期时空变化特征

本文利用1980~2015年近36a昌都市7个台站的逐日降水资料,计算降水集中度(PCD)与集中期(PCP),采用相关分析、合成分析等统计方法研究对PCD、PCP时空特征及与年降水量关系进行分析。结果表明:昌都市PCD范围在0.53~0.76,多年平均值为0.64,PCP范围在39候(7月中旬)~45候(8月中旬),平均值为41.7侯(7月下旬);空间上,昌都市PCD由北向南,自西向东逐渐增大,PCP呈“北早南晚、西早东晚”分布;昌都市大部地方PCD与年降水量呈显著正相关,年降水越多,降水越集中,出现“先旱后涝”的可能性越大。      

北京两次特大暴雨过程观测对比

本文针对2012年("7·21")和2016年("7·20")北京两次特大暴雨过程,利用多源观测和再分析数据,结合多种分析方法,从多个角度,较为系统地对比揭示了两次特大暴雨过程的差异,结果指出:两次过程降水总量相近,但降水历时和小时雨强不同,"7·21"历时更短、雨势更强;两次过程主导天气系统和演变、对流系统演变以及局...     

European dry spell length distributions, years 1951–2000

Daily precipitation records of 267 European rain gauges are considered to obtain dry spell length (DSL) series along the second half of the twentieth century. A dry spell consists of consecutive days with daily rain amount below a given threshold, R ₀. Four DSL series are obtained for R ₀ values equal to 0.1, 1.0, 5.0, and 10.0 mm/day, and their empirical distributions are properly fitted to different statistical models: Pearson type III (PE3), Weibull (WEI), generalised Pareto, (GPA) and lognormal distributions. The parameters of every model are estimated by L-moments, and the goodness of fit is assessed by quantifying discrepancies between empirical and theoretical distributions in the L-skewness–kurtosis diagrams. The most common best-fitting model is PE3, especially for 0.1 and 1.0 mm/day. Nevertheless, a few stations in southern Europe are better modelled by the WEI distribution. For 5.0 and 10.0 mm/day, the spatial distribution of the best-fitting model is more heterogeneous than for the lowest thresholds. While PE3 is still the preferred model for Western Europe, some DSL series are better fitted to WEI or GPA models. Maps of DSL average and standard deviation and expected lengths for return periods of 2, 5, 10, 25, and 50 years show some common features. Whereas for thresholds of 0.1 and 1.0 mm/day, a N–S gradient is detected, especially in Mediterranean areas; for 5.0 and 10.0 mm/day, a NW–SE gradient is observed in the Iberian Peninsula and a SW–NE gradient in the Scandinavian Peninsula. Then, the vicinity to Atlantic and Arctic Oceans and the Mediterranean Sea, as well as orographic features, are more determining factors than the latitude in patterns associated with the highest R ₀ thresholds. Finally, a regional frequency analysis based on a clustering algorithm is attempted for the four thresholds R ₀, with the PE3 model as the parent distribution for the largest clusters.     

1960-2005年长江流域降水极值概率分布特征

 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。     

近53年江淮流域梅汛期极端降水变化特征

基于1961—2013年江淮流域梅汛期（6—7月）逐日降水资料,利用百分位法确定极端降水阈值,对江淮流域梅汛期极端降水的时空分布及突变特征进行分析,结果表明：95%分位极端降水阈值多在50 mm以上,大值中心主要位于湖北东部到安徽南部一带;平均极端降水强度与阈值大小的空间分布相似。极端降水量和极端降水日数整体呈现由安徽南部向四周递减的空间分布特征,极端降水量约占梅汛期降水总量的1/4~1/3。从季节内分布上看,极端强降水站次在梅汛期呈单峰型分布,各候间差异明显,其中6月第5候到7月第2候最多。极端降水量、极端降水日数以及极端降水量占梅汛期总降水量百分比均具有明显的年际变化,且上升趋势显著;江淮流域梅汛期极端降水量和极端降水站次的这种上升趋势均在1980年发生突变。     

自组织映射神经网络(SOM)降尺度方法对江淮流域逐日降水量的模拟评估

利用1961~2002年ERA-40逐日再分析资料和江淮流域56个台站逐日观测降水量资料,引入基于自组织映射神经网络(Self-Organizing Maps,简称SOM)的统计降尺度方法,对江淮流域夏季(6~8月)逐日降水量进行统计建模与验证,以考察SOM对中国东部季风降水和极端降水的统计降尺度模拟能力。结果表明,SOM通过建立主要天气型与局地降水的条件转换关系,能够再现与观测一致的日降水量概率分布特征,所有台站基于概率分布函数的Brier评分(Brier Score)均近似为0,显著性评分(Significance Score)全部在0.8以上;模拟的多年平均降水日数、中雨日数、夏季总降水量、日降水强度、极端降水阈值和极端降水贡献率区域平均的偏差都低于11%;并且能够在一定程度上模拟出江淮流域夏季降水的时间变率。进一步将SOM降尺度模型应用到BCCCSM1.1(m)模式当前气候情景下,评估其对耦合模式模拟结果的改善能力。发现降尺度显著改善了模式对极端降水模拟偏弱的缺陷,对不同降水指数的模拟较BCC-CSM1.1(m)模式显著提高,降尺度后所有台站6个降水指数的相对误差百分率基本在20%以内,偏差比降尺度前减小了40%~60%;降尺度后6个降水指数气候场的空间相关系数提高到0.9,相对标准差均接近1.0,并且均方根误差在0.5以下。表明SOM降尺度方法显著提高日降水概率分布,特别是概率分布曲线尾部特征的模拟能力,极大改善了模式对极端降水场的模拟能力,为提高未来预估能力提供了基础。     

Periodic variability of surface ozone concentration over western and central Europe from observational data

Characteristics of periodic variability of surface ozone concentration at 98 western and central European stations participating in the EMEP program for at least 7 (up to 14) years are determined. Daily and hourly model concentrations of surface ozone for each station are given in an analytical form that presents a sum of a constant constituent and basic harmonics that determine ozone concentration variability throughout a year and a day. A 12-month harmonic, whose maximum is observed in the spring period (in Northern Europe it is observed 1 to 2 months earlier than in Southern Europe) dominates in the energy spectrum of seasonal variability of daily mean ozone concentration at most stations. The energy part of higher (6-and 4-month) harmonics is the largest at the stations close to the sea and ocean coasts. Higher harmonics largely influence the time of the ozone extremum formation, shifting it towards the summer, or even forming a second (summer) maximum, whose magnitude at a number of stations (in Italy, Hungary, in the south of Germany, and in some others) exceeds the spring maximum. A 24-hour harmonic dominates in the energy spectrum of daily ozone variability. The maps of a “normal” distribution of surface ozone fields and their standard deviations for different seasons and time of the day have been compiled based on the model characteristics. The “norms” derived can be used to detect anomalies in the temporal trend of the surface ozone and to validate its climate changes.     

年最大日雨量极值分布拟合与推算

采用红河州12个站近48～58年的年最大日雨量资料,用PearsonⅢ型分布、耿贝尔分布、对数正态分布等3种概率分布模型分别进行了拟合,选择拟合最好的分布模型来估算最大给定重现期极值.结果表明:3种分布均能较好地拟合年最大日雨量的分布,在红河州12个站的拟合中,有7个站用耿贝尔分布,4个站用Pearson-Ⅲ分布,1个...