基于芝加哥法的桂林市短历时暴雨特征分析

利用桂林气象站1957-2014年逐分钟降雨资料,运用线性倾向估计、M-K突变检验方法分析了桂林市短历时暴雨变化特征,采用芝加哥法推算了重现期2a,历时30-180min的暴雨雨型。结果表明:(1)桂林市各短历时最大降雨量均呈增加趋势,30-90min最大降雨量增加趋势较为显著,120-180min最大降雨量增加趋势不明显;(2)各历时前10个降雨极值在1986-2014年间出现的个数大于1957-1985年间,降雨极端值均出现在1978年以后,各历时年最大降雨量变化均未有明显的突变;(3)桂林市短历时暴雨雨型为单峰型,30-90min雨峰位置降雨量随着历时的增加而增加,90-150min雨峰位置降雨量随着历时的增加先减少后增加,雨峰位置基本处于整场降雨过程的1/3分位;(4)30min和60min降雨过程的累积降雨量一开始出现激增变化,随后增速趋于平缓,历时90-180min降雨过程的累积降雨量经过平缓增加-激烈增加-平缓增加的过程。     

南京过去100年极端日降水量模拟研究

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.     

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。     

长江三峡地区宜昌、巴东短历时极值降水特征分析

利用长江三峡库首宜昌站及库区巴东站1955—2008年分钟降水强度资料,采用广义极值分布和线性矩参数估计方法,拟合两站7个短历时(60min以内)年最大降水量概率分布,推断各历时有关重现期降水极值,计算各历时暴雨频次及年最大降水量气候倾向率,分析各历时降水广义极值分布的参数随时间变化规律。结果表明:宜昌、巴东两站7个短历时年最大降水量采用广义极值分布拟合,其效果较好;两站短历时降水平均值趋势变化不明显,而不同百分位数降水量变化趋势差异较大,其中中位数的降水量呈下降趋势,较高百分位数的降水量增加趋势显著,达20%～30%。     

陕西短历时降水极值特征和致灾性分析

利用陕西95个气象站1980—2013年的短历时(1h、3h、6h、12h、24h)降水极值及相应县域1984—2013年的气象地质灾害记录,对陕西短历时降水极值、气象地质灾害发生的时空分布特征及两者间的关联度进行分析,并通过耿贝尔(Gumbel)极值分布模型拟合短历时降水百年极值。结果表明:陕北的子长、佳县,关中的彬县、华阴、武功、千阳,陕南的镇巴、商南、佛坪为短历时降水极值中心。超过一半的站降水极值呈缓慢增大趋势,降水极值与灾害均集中出现在4—10月,两者发生时间有较好的对应关系。陕北54.62%、关中48.5%、陕南68.97%的短历时降水极值出现的当天,当地发生了气象地质灾害。利用耿贝尔极值分布模型拟合5个短历时降水百年极值发现,百年一遇降水极值的空间分布特征与历史极值特征相似,这对短历时降水极值的预测与可能引发的暴雨洪涝地质灾害的预防有一定的借鉴意义。     

重庆多历时极值降水的概率型优选及应用

基于重庆34个国家气象站1981—2016年5 min,24 h至3 d的过程最大雨量共18个年极值降水序列,利用线性矩法计算6种常用概率分布函数的模型参数,通过备选最优模型筛选法客观选取各站各历时极值降水的最优概率模型,并将优选结果应用于重庆不同历时百年重现期降水的计算。结果表明:模型优选方法得到的重庆各站不同历时极值降水的最优线型略有差异,广义极值分布占比最大,三参数Weibull分布次之,三参数对数正态分布第三,皮尔逊Ⅲ型和Gumbel分布相当,指数分布最差。最优线型计算的重庆不同历时百年重现期降水的空间分布大值区由短历时的点状分布向长历时的片状分布转变,渝东北的大值中心受地形影响不断向北移动。基于线性矩法的概率模型参数估计及客观的线型优选过程具有较强的可操作性和适应性,可应用于其他工程气象参数的推算中。     

对两种不同取样方法Pilgrim&Cordery设计雨型的比较研究

选取北京市观象台1941—2013年共73 a的逐分钟降雨量资料,以60 min和120 min两个历时一年一遇的降雨量作为临界阈值,提取降水场次样本,采用PilgrimCordery法推求北京市短历时设计暴雨雨型。各历时的雨型样本选样分别采用自然降雨过程(方法一)和最大历时过程(方法二)。结果表明:两种方法的60 min和120 min雨型分布形状一致,均为单峰型,雨峰位置靠前;但在降雨量分配比例上,两种方法存在差异,自然降雨过程的60 min和120 min雨型雨峰所在时刻降雨量占总雨量的比例比最大历时过程的分别高3.79%和5.83%。     

海河流域降水极值的时空演变特征

利用海河流域104个测站逐日降水资料,研究了海河流域过去47年中降水极值时空变化趋势,从降水极值变化的角度解释了海河流域旱涝的演变特征。结果表明:近47年来,海河流域的降雨量、小雨日数、暴雨日数、湿涝事件、日最大降水量均表现出明显减少趋势,干旱事件表现出显著增加趋势,加剧了海河流域干旱化程度。海河流域降水极值空间变化趋势在大部分区域表现为干旱化倾向,尤其是在海河流域东南部区域干旱化程度最为显著。降水的极值变化致使降水时空分布变得更加不均匀,使得海河流域干旱事件发生频率和强度增加,从而对流域内生态、环境和社会经济系统产生深远的影响。     

南宁市短历时暴雨演变特征分析

利用南宁气象站1953—2014年的短历时暴雨资料,运用线性倾向估计、M-K突变检验、集中度等方法分析了南宁市短历时暴雨演变特征。结果表明:(1)南宁市短历时最大降雨量呈增加趋势,时段越短增加越明显。(2)短历时暴雨月变化呈单峰型,6月为峰值,一天中短历时暴雨多发生在下午时段。(3)短历时年最大降雨量未出现突变。     

近40年来中国降水时空分布特征分析

本文基于中国的726个气象站点（1961年-2000年）的逐句降雨量数据和726个站点（1995年-2002年）的逐日降雨量数据,利用数理统计方法分析了研究区年降水变率、年降水距平、降水空间变化趋势、3d降雨量极值等降雨量特征值,发现近40年来,研究区春、夏两季的降雨量均有明显的增多趋势,秋季则有大幅的减少趋势,冬季的变幅相对来说最小。整体表现出降雨量变化幅度大、降雨量逐年减少、气候暖干化趋势的特点。     

Storylines: an alternative approach to representing uncertainty in physical aspects of climate change

Investigating the relationships between climate extremes and crop yield can help us understand how unfavourable climatic conditions affect crop production. In this study, two statistical models, multiple linear regression and random forest, were used to identify rainfall extremes indices affecting wheat yield in three different regions of the New South Wales wheat belt. The results show that the random forest model explained 41–67% of the year-to-year yield variation, whereas the multiple linear regression model explained 34–58%. In the two models, 3-month timescale standardized precipitation index of Jun.–Aug. (SPI_JJA), Sep.–Nov. (SPI_SON), and consecutive dry days (CDDs) were identified as the three most important indices which can explain yield variability for most of the wheat belt. Our results indicated that the inter-annual variability of rainfall in winter and spring was largely responsible for wheat yield variation, and pre-growing season rainfall played a secondary role. Frequent shortages of rainfall posed a greater threat to crop growth than excessive rainfall in eastern Australia. We concluded that the comparison between multiple linear regression and machine learning algorithm proposed in the present study would be useful to provide robust prediction of yields and new insights of the effects of various rainfall extremes, when suitable climate and yield datasets are available.     

The Effects of Climatic Variability on US Irrigation Adoption

This paper contributes to the literature underscoring the importance of climatic variance by developing a framework for incorporating the means and tails of the distributions of rainfall and temperature into empirical models of agricultural production. The methodology is applied to estimate the impact of climate change on the discrete choice decision to adopt irrigation since it is an important adaptation to climate change. We develop a discrete choice model for the decision to install irrigation capacity that captures the effects of both climate means and extremes. Climatic means and frequencies of climatic events in the upper tails of the temperature and precipitation distributions are used to estimate the parameters of a normal distribution for temperature and a Weibull distribution for precipitation. Using estimates from a probit model, we examine the independent effects of changing climatic mean and variance on the probability of adopting irrigation. Increasing the mean temperature, holding variance constant, shifts the entire distribution toward warmer temperatures—increasing the frequency of extreme temperatures. For precipitation, the specification captures the separate effects of mean rainfall, frequency of rainfall, and frequency of extreme events. The results show that the tails of the temperature and precipitation distributions, not the means, are the dominant climatic determinants in irrigation adoption. The results also show that water availability, soil characteristics, farm size and operator demographics are important determinants of irrigation.     

Preservation of rainfall properties in stochastic disaggregation by a simple random cascade model

We analyse properties of a simple discrete multiplicative random cascade model for rainfall disaggregation in urban hydrology. Two types of cascade models (canonical and microcanonical) are applied to the stochastic fine graining of rainfall observations into high resolution data. In particular, we analyse the disaggregation of 1280-min into 10-min data for a 20-year record period (Zurich raingauge, 1979–1998). Differences between the models and parameter estimation techniques are explored on simulated data with a special focus on three important properties of observed rainfall: distribution, intermittency, and extremes. The canonical models are overall better at preserving the distribution of rainfall at the 10-min scale. It is demonstrated that the growth of intermittency across scales is preserved well with all studied models. The ability of the models to reproduce rainfall extremes is a fundamental requirement in disaggregation. The studied models preserved annual rainfall maxima satisfactorily for short durations; however, the performance deteriorated for longer durations. The canonical models performed substantially better in capturing the variability in rainfall. The results are encouraging considering the parsimonious nature of the models and simple parameter estimation.     

Assessing future climatic changes of rainfall extremes at small spatio-temporal scales

Climate change is expected to influence the occurrence and magnitude of rainfall extremes and hence the flood risks in cities. Major impacts of an increased pluvial flood risk are expected to occur at hourly and sub-hourly resolutions. This makes convective storms the dominant rainfall type in relation to urban flooding. The present study focuses on high-resolution regional climate model (RCM) skill in simulating sub-daily rainfall extremes. Temporal and spatial characteristics of output from three different RCM simulations with 25 km resolution are compared to point rainfall extremes estimated from observed data. The applied RCM data sets represent two different models and two different types of forcing. Temporal changes in observed extreme point rainfall are partly reproduced by the RCM RACMO when forced by ERA40 re-analysis data. Two ECHAM forced simulations show similar increases in the occurrence of rainfall extremes of over a 150-year period, but significantly different changes in the magnitudes. The physical processes behind convective rainfall extremes generate a distinctive spatial inter-site correlation structure for extreme events. All analysed RCM rainfall extremes, however, show a clear deviation from this correlation structure for sub-daily rainfalls, partly because RCM output represents areal rainfall intensities and partly due to well-known inadequacies in the convective parameterization of RCMs. The results highlight the problem urban designers are facing when using RCM output. The paper takes the first step towards a methodology by which RCM performance and other downscaling methods can be assessed in relation to the simulation of short-duration rainfall extremes.     

Combining climatological and participatory approaches for assessing changes in extreme climatic indices at regional scale

This paper combines the climatological and societal perspectives for assessing future climatic extremes over Kangasabati River basin in India using an ensemble of four high resolution (25 km) regional climate model (RCM) simulations from 1970 to 2050. The relevant extreme indices and their thresholds are defined in consultation with stakeholders and are then compared using RCM simulations. To evaluate the performance of RCM in realistically representing atmospheric processes in the basin, model simulations driven with ERAInterim global re-analysis data from 1989 to 2008 are compared with observations. The models perform well in simulating seasonality, interannual variability and climatic extremes. Future climatic extremes are evaluated based on RCM simulations driven by GCMs, for present (1970–1999) and for the SRES A1B scenario for future (2021–2050) period. The analysis shows an intensification of majority of extremes as projected by future ensemble mean. The study suggests that there is a marked consistency in stakeholder observed changes in climate extremes and future predicted trends.     

Changes of Frequency of Summer Precipitation Extremes over the Yangtze River in Association with Large-scale Oceanic-atmospheric Conditions

Changes of the frequency of precipitation extremes (the number of days with daily precipitation exceeding the 90th percentile of a daily climatology,referred to as R90N) in summer (June-August) over the mid-lower reaches of the Yangtze River are analyzed based on daily observations during 1961-2007.The first singular value decomposition (SVD) mode of R90N is linked to an ENSO-like mode of the sea surface temperature anomalies (SSTA) in the previous winter.Responses of different grades of precipitation events to the climatic mode are compared.It is notable that the frequency of summer precipitation extremes is significantly related with the SSTA in the Pacific,while those of light and moderate precipitation are not.It is suggested that the previously well-recognized impact of ENSO on summer rainfall along the Yangtze River is essentially due to a response in summer precipitation extremes in the region,in association with the East Asia-Pacific (EAP) teleconnection pattern.A negative relationship is found between the East Asian Summer Monsoon (EASM) and precipitation extremes over the mid-lower reaches of the Yangtze River.In contrast,light rainfall processes are independent from the SST and EASM variations.     

Assessment of a climate model to reproduce rainfall variability and extremes over Southern Africa

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UK Meteorological Office Hadley Centre’s climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with extremes from the MIRA dataset. The results suggest that the model reproduces the number and spatial distribution of rainfall extremes with some accuracy, but that mean rainfall and rainfall variability is under-estimated (over-estimated) over wet (dry) regions of southern Africa.     

6.25 km高分辨率降尺度数据对21世纪长江经济带极端气候事件及其风险的集合预估

使用基于动力降尺度和统计降尺度方法得到的RCP4.5情景下的6.25 km高分辨率联合降尺度预估数据集,对长江经济带未来极端气候事件及其造成的风险展开评估和预估。结果表明：降尺度预估数据能较好的再现各极端温度指数和大部分极端降水指数的空间分布,但一些极端降水指数的偏差略大。未来长江经济带极端热事件将增加,冷事件减少;长江中游东部和下游的极端降水事件将增加,上游地区东南部发生干旱事件的可能性大。长江经济带以及上游、中游和下游3个分区的高温事件和强降水事件的国内生产总值（GDP）暴露度都将增加;人口暴露度呈先增后降的变化趋势。高温事件的GDP暴露度的分布因子和非线性因子的贡献同样重要,人口暴露度中分布因子的影响更大;强降水事件的暴露度主要取决于GDP或人口分布因子。     

An intercomparison of observed and simulated extreme rainfall and temperature events during the last half of the twentieth century: part 2: historical trends

We analyze historical simulations of variability in temperature and rainfall extremes in the twentieth century, as derived from various global models run informing the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR4). On the basis of three indices of climate extremes, we compare observed and modeled trends in time and space, including the direction and significance of the changes at the scale of South America south of 10° S. The climate extremes described warm nights, heavy rainfall amounts and dry spells. The reliability of the GCM simulations is suggested by similarity between observations and simulations in the case of warm nights and extreme rainfall in some regions. For any specific extreme temperature index, minor differences appear in the spatial distribution of the changes across models in some regions, while substantial differences appear in regions in the interior of tropical and subtropical South America. The differences are in the relative magnitude of the trends. Consensus and significance are less strong when regional patterns are considered, with the exception of the La Plata Basin, where observed and simulated trends in warm nights and extreme rainfall are evident.     

广义极值分布理论在重现期计算的应用

在气候统计学上,常用Weibull、Gumbel、Frechet统计分布函数对极端气候要素的分布进行拟合,广义极值分布理论综合了以上三种极值分布模型,在气候分析中得到了广泛应用。以南昌市年汛期日最大降水量为例,利用广义极值分布理论对其分布进行拟合,并对重现值及其置信区间进行计算,为气候要素极值的统计分析提供了一种新的手段。