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。     

基于高分辨率区域气候模式的三峡库区降水变化模拟与预估

基于三峡库区1961—2005年逐日降水格点数据,评估由BCC_CSM1.1模式驱动的RegCM4区域气候模式、MPI—ESM—LR模式驱动的CCLM区域气候模式对三峡库区年平均降水量、极端降水的模拟能力,筛选出与观测更为接近的区域气候模式模拟数据,预估在RCP4.5温室气体排放情景下未来2016—2050年三峡库区降水变化特征。结果表明:RegCM4和CCLM模式能够模拟出三峡库区降水量和暴雨日数的季节、年际变化特征和空间分布形态,但在库区东南部模拟的数值均偏少,而对暴雨强度不具备模拟能力。总体而言,CCLM模式对三峡库区降水的模拟效果好于RegCM4。在RCP4.5情景下,2016—2050年三峡库区年降水量未表现出明显变化趋势,而年暴雨日数将显著增加,平均较当代(1986—2005年)增加1.2 d。     

长江流域气候变化高分辨率模拟与RCP4.5情景下的预估

基于长江流域142个气象站1986—2005年月降水和气温数据,评估由MPI-ESM-LR模式驱动的CCLM区域气候模式对长江流域气温和降水的模拟能力,并采用EDCDF法对气温和降水预估数据进行偏差校正。结果表明：该区域气候模式能较好地模拟出长江流域平均气温的季节变化和空间分布特征,但模拟值无论在季节还是年际尺度上均高于观测值。对降水而言,该模式不能较好地模拟出降水的季节分布特征,导致春季、冬季及年模拟值高于观测值,而夏季和秋季模拟值低于观测值。总体而言,该模式对气温的模拟效果相对较好。偏差校正后的预估结果表明：在RCP4.5情景下,长江流域未来（2016—2035年）平均气温相对于基准期（1986—2005年）将升高0.66℃,年降水量将减少2.2%。     

湖南省短历时降水极值分布拟合与应用

选择适宜的极值分布模型有助于提高极值序列再现期极值的准确度。基于1981—2010年湖南省97个地面气象观测站逐时降水观测资料,构建逐站年和季1 h、3 h、12 h最大降水量序列,运用Pearson-Ⅲ型、Gumbel、对数正态、Cauchy和Weibull 5种分布函数对湖南省3种短历时最大降水量序列进行极值分布拟合。结果表明：1981—2010年湖南省中北部地区3种短历时降水极值分布符合Gumbel分布模型,Weibull分布次之;湖南省南部地区3种短历时降水极值分布则仅符合Gumbel分布模型。在此基础上,应用Gumbel分布模型估算湖南省各站重现期为百年的降水极值,结果表明1 h、3 h、12 h的年降水极值高值中心分别位于湘东南地区、湖南省西部地区和湘西北地区;各季降水极值中心与年极值中心略有不同。     

2011—2050年长江流域气候变化预估问题的探讨

利用长江流域1961—2008年观测气象资料,对IPCC 第四次评估报告中12个全球气候模式及所有模式集合平均进行比较验证,结果表明：MIUB_ECHO_G模式对该地区降水模拟能力较强,NCAR_CCSM3模式对温度模拟效果较好。进一步利用MIUB_ECHO_G模式和NCAR_CCSM3模式结果在SRES-A2、-A1B、-B1 3种排放情景下的降水和温度数据,分析2011—2050年3种排放情景下长江流域降水和温度变化特征。结果表明,2011—2050年长江流域降水变化趋势不明显,温度呈增加趋势,增幅在2℃内。     

基于PRECIS模式对珠江流域降水的模拟与分析

该文使用区域气候模式PRECIS的A1B情景,模拟1961—1990年珠江流域降水平均值、区域分布和概率分布,并对订正方法的效果进行了检验,检验结果表明PRECIS模式模拟的结果与观测值接近,对模拟结果进行概率订正后模拟结果得到了改善。在模式效果可信的基础上,对珠江流域2021—2050年降水量进行了模拟和分析,模拟结果表明未来时段珠江流域的降水总体稍微增加,珠江流域全年下游降水增多,上游降水减少,降水的波动性增加,未来降水量趋于两极化,可能导致极端多雨和极端少雨事件的增加,更易导致干旱和洪涝的发生;未来珠江流域降水在时空分布上将更加不均匀,即冬季和春季南部沿海降水增多,北部降水减少;夏季和秋季北部降水增多,南部降水减少。     

三峡库区气温变化高精度区域气候模式模拟与预估

基于三峡库区1961—2005年气温逐日格点数据,评估由BCC_CSM1.1模式驱动的RegCM4区域气候模式、MPI-ESM-LR模式驱动的CCLM区域气候模式对三峡库区平均气温、极端高温的模拟能力,选用与观测值更为接近的区域气候模式模拟结果,预估三峡库区在RCP4.5温室气体排放情景下2016—2035年气温变化。结果表明:RegCM4和CCLM模式均能模拟出三峡库区多年平均气温、高温日数和高温强度的季节变化和空间分布形态,但均在库区东北部模拟的年平均气温偏低、高温日数偏少、高温强度偏小。同时,模式均能较好地反映出三峡库区年平均气温、年高温日数的年际变化,但对高温强度的年际变化模拟较差。总体而言,CCLM模式对三峡库区气温的模拟效果好于RegCM4。RCP4.5情景下,三峡库区2016—2035年平均气温、高温日数比当代(1986—2005年)分别增加0.6℃和5d,高温强度变化不明显。     

BCC_CSM1.0模式对20世纪降水及其变率的模拟

应用国家气候中心气候系统模式 (BCC_CSM1.0),在给定温室气体、太阳常数、硫酸盐气溶胶、火山灰等外强迫数据的条件下,对19世纪末到20世纪气候进行模拟。对降水模拟结果的检验表明:BCC_CSM1.0模式能够模拟出全球降水的基本气候状态、季节变化、季节内振荡、年际变化等特征。模拟结果显示:与CMAP及CRU观测分析资料相比基本一致,全球陆地降水在过去一个多世纪中存在上升趋势。同时,模式也存在不足和需要改进之处:模拟降水的时空分布与观测不一致;我国东部地区的雨带季节转变较观测偏快;主要雨带位置较观测偏西、偏北;夏季青藏高原东北侧有虚假的降水中心;热带季节内振荡较实际偏弱;降水年际变率较观测略大,主要发生在降水较明显的热带。BCC_CSM1.0模式模拟的全球陆地降水以及欧亚、亚洲、中国大陆 (中国东部、江南、华北等地区) 平均降水与近105年由观测所得的CRU资料基本一致,但多数地区比观测略偏低。模拟的全球陆地、中国东部、江南、华北等地区的降水趋势也与CRU资料一致;模拟的全球陆地降水在过去105年中有明显的上升趋势,与CRU资料相比,上升趋势更强,但在欧亚、亚洲、中国范围内模拟的降水趋势与观测有一定的差异。     

1961-2014年新疆降水极值概率特征及拟合不确定性分析

本文采用多种函数初步探讨了1961—2014 年新疆地区日降水极值概率拟合分析中的不确定性。结果表明：新疆气候在暖干向暖湿转变背景下,更易出现极端强降水事件,由此影响极端降水拟合的不确定性;在统计函数选择以及重现期极值拟合中存在不确定性,因此建议在进行新疆区域降水极值分析时选择整体表现较好的GEV、Gen.Logistic、Log-Pearson 3、Pearson 6 和Wakeby 函数进行合成分析,在进行单站分析时给出具有界限范围的降水极值综合曲线图,以此减少来自函数方面的不确定性。     

CMIP5全球气候模式对中国地区干旱变化模拟能力评估

利用东亚地区1961～2005年高分辨率（0．5°×0．5°）降水格点数据和参加CMIP5的42个全球气候模式数值模拟结果,通过对简单降水强度指数（降水距平百分率）的计算,对比分析了观测和多模式集合的中国地区干旱面积、干旱频率的时空分布以及干旱分布型的变化,评估了全球气候模式的模拟能力。结果表明：多个全球气候模式的集合结果对中国区域的干旱变化特征有一定的模拟能力,能较好地模拟出中国年平均干旱指数的时间变化趋势,但模拟的干旱强度偏弱;多模式集合模拟的严重干旱面积与观测值的变化趋势基本一致,与观测相比,模拟的长江以南干旱强度偏强,西北干旱强度偏弱;通过EOF的分析表明,多模式集合可以较好地模拟出西北与长江以南呈反位相及我国东部地区的“旱-涝-旱”或“涝-旱-涝”的分布型。     

Simulation of extreme precipitation over the Yangtze River Basin using Wakeby distribution

Based on the daily observational precipitation data at 147 stations in the Yangtze River Basin during 1960–2005 and projected daily data of 79 grid cells from the ECHAM5/ MPI-OM model in the 20th and 21st century, time series of precipitation extremes which contain AM (Annual Maximum) and MI (Munger Index) are constructed. The distribution feature of precipitation extremes is analyzed based on the two index series. Three principal results were obtained, as stated in the sequel. (i) In the past half century, the intensity of extreme heavy precipitation and drought events was higher in the mid-lower Yangtze than in the upper Yangtze reaches. Although the ECHAM5 model still can’t capture the precipitation extremes over the Yangtze River Basin satisfactorily, spatial pattern of the observed and the simulated precipitation extremes are much similar to each other. (ii) For quantifying the characteristics of extremely high and extremely low precipitation over the Yangtze River Basin, four probability distributions are used, namely: General Extreme Value (GEV), General Pareto (GPA), General Logistic (GLO), and Wakeby (WAK). It was found that WAK can adequately describe the probability distribution of precipitation extremes calculated from both observational and projected data. (iii) Return period of precipitation extremes show spatially different changes under three greenhouse gas emission scenarios. The 50-year heavy precipitation and drought events from simulated data during 1951–2000 will become more frequent, with return period below 25 years, for the most mid-lower Yangtze region in 2001–2050. The changing character of return periods of precipitation extremes should be taken into account for the hydrological design and future water resources management.     

1960-2005年长江流域降水极值概率分布特征

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.     

Probability Distribution of Precipitation Extremes over the Yangtze River Basin

 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.     

Changing climate extremes in the Northeast United States: observations and projections from CMIP5

Climate extremes indices are evaluated for the northeast United States and adjacent Canada (Northeast) using gridded observations and twenty-three CMIP5 coupled models. Previous results have demonstrated observed increases in warm and wet extremes and decreases in cold extremes, consistent with changes expected in a warming world. Here, a significant shift is found in the distribution of observed total annual precipitation over 1981-2010. In addition, significant positive trends are seen in all observed wet precipitation indices over 1951-2010. For the Northeast region, CMIP5 models project significant shifts in the distributions of most temperature and precipitation indices by 2041-2070. By the late century, the coldest (driest) future extremes are projected to be warmer (wetter) than the warmest (wettest) extremes at present. The multimodel interquartile range compares well with observations, providing a measure of confidence in the projections in this region. Spatial analysis suggests that the largest increases in heavy precipitation extremes are projected for northern, coastal, and mountainous areas. Results suggest that the projected increase in total annual precipitation is strongly influenced by increases in winter wet extremes. The largest decreases in cold extremes are projected for northern and interior portions of the Northeast, while the largest increases in summer warm extremes are projected for densely populated southern, central, and coastal areas. This study provides a regional analysis and verification of the latest generation of CMIP global models specifically for the Northeast, useful to stakeholders focused on understanding and adapting to climate change and its impacts in the region.     

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。     

Changes of precipitation and extremes and the possible effect of urbanization in the Beijing metropolitan region during 1960–2012 based on homogenized observations

Daily precipitation series at 15 stations in the Beijing metropolitan region (BMR) during 1960-2012 were homogenized using the multiple analysis of series for homogenization method, with additional adjustments based on analysis of empirical cumulative density function (ECDF) regarding climate extremes. The cumulative density functions of daily precipitation series, the trends of annual and seasonal precipitation, and summer extreme events during 1960-2012 in the original and final adjusted series at Beijing station were comparatively analyzed to show the necessity and efficiency of the new method. Results indicate that the ECDF adjustments can improve the homogeneity of high-order moments of daily series and the estimation of climate trends in extremes. The linear trends of the regional-mean annual and seasonal (spring, summer, autumn, and winter) precipitation series are -10.16, 4.97, -20.04, 5.02, and -0.11 mm (10 yr)-1, respectively. The trends over the BMR increase consistently for spring/autumn and decrease for the whole year/summer; however, the trends for winter decrease in southern parts and increase in northern parts. Urbanization affects local trends of precipitation amount, frequency, and intensity and their geographical patterns. For the urban-influenced sites, urbanization tends to slow down the magnitude of decrease in the precipitation and extreme amount series by approximately -10.4% and -6.0%, respectively; enhance the magnitude of decrease in precipitation frequency series by approximately 5.7%; reduce that of extremes by approximately -8.9%; and promote the decreasing trends in the summer intensity series of both precipitation and extremes by approximately 6.8% and 51.5%, respectively.     

Assessment of CMIP3 climate models and projected changes of precipitation and temperature in the Yangtze River Basin, China

The projected changes of precipitation and temperature in the Yangtze River Basin in the 20th Century from 20 models of the CMIP3 (phase 3 of the Coupled Model Inter-comparison Project) dataset are analyzed based on the observed precipitation and temperature data of 147 meteorological stations in the Yangtze River Basin. The results show that all models tend to underestimate the annual mean temperature over the Yangtze River Basin, and to overestimate the annual mean precipitation. The temporal changes of simulated annual mean precipitation and temperature are broadly comparable with the observations, but with large variability among the results of the models. Most of the models can reproduce maximum precipitation during the monsoon season, while all models tend to underestimate the mean temperature of each month over the Yangtze River Basin. The Taylor diagram shows that the differences between modeled and observed temperature are relatively smaller as compared to differences in precipitation. For a detailed investigation of regional characteristics of climate change in the Yangtze River Basin during 2011–2050, the multi-model ensembles produced by an upgraded REA method are carried out for more reliable projections. The projected precipitation and temperature show large spatial variability in the Yangtze River Basin. Mean precipitation will increase under the A1B and B1 scenarios and decrease under the A2 scenario, with linear trends ranging from ?21 to 28.5?mm/decade. Increasing mean temperature can be found in all scenarios with linear trends ranging from 0.15 to 0.48°C/decade. Grids in the head region of the Jingshajiang catchment show distinct increasing trends for all scenarios. Some physical processes associated with precipitation are not well represented in the models.     

Changes in precipitation extremes over arid to semiarid and subhumid Punjab,Pakistan

Asymmetrical monsoons during the recent past have resulted into spatially variable and devastating floods in South Asia. Analysis of historic precipitation extremes record may help in formulating mitigation strategies at local level. Eleven indices of precipitation extremes were evaluated using RClimDex and daily time series data for analysis period of 1981–2010 from five representative cities across Punjab province of Pakistan. The indices include consecutive dry days, consecutive wet days, number of days above daily average precipitation, number of days with precipitation ≥10 mm, number of days with precipitation ≥20 mm, very wet days, extremely wet days, simple daily intensity index, maximum 1-day precipitation quantity, maximum 5 consecutive day precipitation quantity, and annual total wet-day precipitation. Mann-Kendall test and Sen’s slope extremes were used to detect trends in indices. Droughts and excessive precipitation were dictated by elevation from mean sea level with prolonged dry spells in southern Punjab and vice versa confirming spatial trends for precipitation extremes. However, no temporal trend was observed for any of the indices. Summer in the region is the wettest season depicting contribution of monsoons during June through August toward devastating floods in the region.     

RCP4.5情景下长江上游流域未来气候变化及其对径流的影响

基于1961—2010年长江寸滩以上流域50个气象站的逐日观测数据和寸滩水文控制站的逐日径流数据,结合流域的地形、土地利用和土壤信息,采用HBV和SWAT水文模型,模拟了流域降水径流定量关系,并利用CCLM区域气候模式,开展了气候变化背景下,寸滩未来径流的可能演变趋势分析。结果表明:HBV和SWAT水文模型都适用于位于湿润地区的长江寸滩以上流域,月径流的模拟Nash-Sutcliffe效率系数都在0.90以上。相比较,SWAT水文模型对于枯水径流的模拟较差,HBV水文模型峰值流量的模拟高于实测。相对于基准期(1986—2005年),RCP4.5情景下,2011—2040年寸滩以上流域平均气温、最高气温、最低气温将明显增加,并呈持续上升趋势;流域降水也有一定的增加,但2030年后呈弱减少趋势。从两类水文模型对径流模拟的集合结果来看,2011—2040年年径流将上升14.2%;而径流量的概率分布尾部特征及径流分位数变化进一步表明,流域的未来峰值流量预计将有所增大。