淮河流域极值降水的统计参数特征及在水文频率分析中的意义

以淮河流域为研究区域,利用线性矩精确求解极值降水统计特征值,为极值降水频率估计值的计算提供理论基础和依据.主要结果表明：淮河流域各站点的年最大日降雨量（Annual Maximum Precipitation,AMP）的均值和离差范围分别为92.79~130.28 mm和0.193~0.266;各站点的AMP分布都为右偏分布,即至少有一半以上的AMP值是小于平均值的,有少数的AMP值远大于平均值,且对平均值的影响较大;各站点的分布相对于正态分布而言,都属于尖峰厚尾.极值降水统计特征值的空间分布表明：大值主要分布在流域的西南山区和东部丘陵地带,即这些地方具有更多更强的AMP极值.极值降水统计参数不仅能够反映AMP的一般平均水平和年际AMP的波动情况,还能更好地掌握AMP的两端分布情况,特别是尾端的暴雨极值.因此分析极值降水统计参数可以给洪涝灾害提供很好的指导.     

双极值模糊集研究综述

大数据时代背景下,不但数据的不确定性愈发明显,数据的冲突性(不相容)现象亦越来越突出.两极性和模糊性一样是事物的本质属性,模糊集虽然是处理不确定信息的有力工具,却一直忽略了不相容两极性问题.双极值模糊集首次将不相容两极性引入到模糊集理论中,为分析和解决带有不相容特性的大数据问题提供了新的思路和方法,其研究渐渐成为热点.综述首先阐述了两极性的种类与特点,以及双极值模糊集的相关概念、理论,特别是和其他已有模糊集的区别;接着分析了双极值模糊集国内外发展现状;最后分析了双极值模糊集未来的发展方向.通过综述,将对双极值模糊集有一个全面的认识,为下一步研究打下基础.     

淮河流域水文极值预测模型研究

为探索气候变化影响下水文极值的非平稳性和预测方法,建立了水文极值非平稳广义极值（GEV）分布的统计预测模型。利用1952-2010年淮河上游流域累计面雨量和流量年最大值资料、同期500 hPa环流特征量资料以及17个CMIP5模式对环流特征量的模拟结果,筛选出对水文极值影响显著的年平均北半球极涡强度指数作为GEV分布参数的预测因子。分析了在RCP2.6、RCP4.5和RCP8.5情景下2006-2050年淮河上游流域水文极值对气候变化的响应。结果表明,10年以下与10年以上重现期的水文极值在非平稳过程中呈现前者下降而后者上升的相反变化趋势;多模型预测的集合平均在未来情景中均呈现上升趋势,情景排放量越大增幅越大,重现期越长增幅也越大。与极值的常态相比,极值的极端态更易受气候变化影响。     

中国格点化日降水极值统计模型及阈值的选取

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。     

我国地面气温极值和地面风速极值的渐近分布

利用1951—1982年期间我国173个测站的地面最高气温年极值记录,158个测站的地面最低气温年极值记录和83个测站的地面最大风速年极值记录,通过统计推断,找出了我国地面最高、最低气温年极值和地面最大风速年极值遵循的渐近分布——Weibull分布和Gumbel分布,并简要讨论了它们的形状。     

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。     

湛江近海台风风速复合极值分析

采用Poisson-Weibull复合极值分布方法对湛江近海36年的风暴过程资料进行统计分析。推算出湛江近海的多年一遇设计风速,并单一因素设计方法进行比较。计算结果表明,复合极值统计模式计算结果较稳定。     

广西三十年气候极值特征分析

本文根据“气象异常年表”规定的统计项目,对广西近三十年(1961—1990年)气候极值进行了分析,得出气温、降水、日照等要素气侯极值的时空分布特征。     

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。     

广西三十年气候极值特征分析

本文根据“气象异常年表”规定的统计项目,对广西近三十年(1961—1990年)气候极值进行了分析,得出气温、降水、日照等要素气候极值的时空分布特征。     

A comparison of climatological observing windows and their impact on detecting daily temperature extrema

Climatological observing window (COW) is defined as a time frame over which continuous or extreme air temperature measurements are collected. A 24-h time interval, ending at 00UTC or shifted to end at 06UTC, has been associated with difficulties in characterizing daily temperature extrema. A fixed 24-h COW used to obtain the temperature minima leads to potential misidentification due to fragmentation of “nighttime” into two subsequent nighttime periods due to the time discretization interval. The correct identification of air temperature extrema is achievable using a COW that identifies daily minimum over a single nighttime period and maximum over a single daytime period, as determined by sunrise and sunset. Due to a common absence of hourly air temperature observations, the accuracy of the mean temperature estimation is dependent on the accuracy of determination of diurnal air temperature extrema. Qualitative and quantitative criteria were used to examine the impact of the COW on detecting daily air temperature extrema. The timing of the 24-h observing window occasionally affects the determination of daily extrema through a mischaracterization of the diurnal minima and by extension can lead to errors in determining daily mean temperature. Hourly air temperature data for the time period from year 1987 to 2014, obtained from Toronto Buttonville Municipal Airport weather station, were used in analysis of COW impacts on detection of daily temperature extrema and calculation of annual temperature averages based on such extrema.     

Statistical estimation of high-resolution surface air temperature from MODIS over the Yangtze River Delta,China

High-resolution surface air temperature data are critical to regional climate modeling in terms of energy balance, urban climate change, and so on. This study demonstrates the feasibility of using Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) to estimate air temperature at a high resolution over the Yangtze River Delta region, China. It is found that daytime LST is highly correlated with maximum air temperature, and the linear regression coefficients vary with the type of land surface. The air temperature at a resolution of 1 km is estimated from the MODIS LST with linear regression models. The estimated air temperature shows a clear spatial structure of urban heat islands. Spatial patterns of LST and air temperature differences are detected, indicating maximum differences over urban and forest regions during summer. Validations are performed with independent data samples, demonstrating that the mean absolute error of the estimated air temperature is approximately 2.5°C, and the uncertainty is about 3.1°C, if using all valid LST data. The error is reduced by 0.4°C (15%) if using best-quality LST with errors of less than 1 K. The estimated high-resolution air temperature data have great potential to be used in validating high-resolution climate models and other regional applications.     

福建区域性暴雨过程综合强度定量化评估方法

该文以福建省为例,探讨了区域性暴雨过程的识别方法和综合强度评估模型。采用福建省66个国家级气象观测站1961—2010年逐日降水量资料,首先在给定区域性暴雨过程识别方法的基础上,筛选出941次区域性暴雨过程;其次选取区域最大日降水量、区域最大过程降水量、区域暴雨范围和区域暴雨持续时间4项暴雨过程指标,采用百分位数方法分别确定4项指标的等级划分标准;采用相关系数法确定各指标权重,构建福建区域性暴雨过程的综合强度评估模型,并给出福建区域性暴雨过程的综合强度等级划分标准。业务服务和历史事件验证表明:采用该方法的评估结果较为合理,且与历史重大暴雨事件具有良好的一致性。     

非随机化人工增雨作业功效数值分析和效果评估

用自然复随机化方法对北京市人工增雨作业非随机化试验进行功效数值分析.结果表明不同统计检验方案功效差别较大,序列试验功效最差,当作业样本数较多时对比试验功效较高,其次为区域历史回归试验和双比分析方案,当作业样本数较少时区域历史回归试验功效比其他两种方案更高.功效与增雨效果、历史样本数、作业样本数都有关系,当作业样本数或历史样本数增多时,功效都会增大,但是增大的程度会随着样本数目的增多而趋缓.分类统计不一定可以提高检验功效值,要采用分类统计方案首先就要保证分类后的作业样本数下的功效值大于合并后作业样本数下的功效值.在综合分析影响功效的各种因素基础上选择区域对比试验、双比分析和区域历史回归试验对北京市2002～2007年人工增雨作业进行效果总评价,结果均表明相对增雨效果在10％左右,采用复随机化方案进行显著度检验,结果表明3种方案下显著度水平均达0.05.     

Wavelet entropy-based investigation into the daily precipitation variability in the Yangtze River Delta, China, with rapid urbanizations

In this paper, the daily precipitation data measured at 58 meteorological stations were used, and the spatial and temporal variability of daily precipitation and precipitation extrema in the Yangtze River Delta (YRD) during 1958–2007 was investigated using the indicator of discrete wavelet entropy; then, the urbanization effects were further analyzed. Results indicate that the daily precipitation variability in YRD, especially in the mid YRD with highly urbanized city clusters, is determined by the comprehensive impacts of atmospheric circulation, urbanizations, and the Taihu Lake. Compared with the results in 1958–1985, the variability of daily precipitation and precipitation extrema becomes more complex in 1986–2007, and daily precipitation variability is more complex in the mid YRD relative to the north and south. The precipitation extrema with bigger magnitudes show more complex variability. Urbanizations cause more complexity and fluctuations of daily precipitation in the mid YRD in 1986–2007, reflecting more uncertainty of daily precipitation variability, while the urbanization effects vary with regions and precipitation magnitudes. The variability of precipitation extrema with maximum values is mainly determined by natural atmospheric circulation but has little relationship with urbanizations; however, the variability of those precipitation extrema with general values is determined by both urbanizations and the Taihu Lake in YRD over the last three decades.     

A cautionary note on automated statistical downscaling methods for climate change

The urge for higher resolution climate change scenarios has been widely recognized, particularly for conducting impact assessment studies. Statistical downscaling methods have shown to be very convenient for this task, mainly because of their lower computational requirements in comparison with nested limited-area regional models or very high resolution Atmosphere–ocean General Circulation Models. Nevertheless, although some of the limitations of statistical downscaling methods are widely known and have been discussed in the literature, in this paper it is argued that the current approach for statistical downscaling does not guard against misspecified statistical models and that the occurrence of spurious results is likely if the assumptions of the underlying probabilistic model are not satisfied. In this case, the physics included in climate change scenarios obtained by general circulation models, could be replaced by spatial patterns and magnitudes produced by statistically inadequate models. Illustrative examples are provided for monthly temperature for a region encompassing Mexico and part of the United States. It is found that the assumptions of the probabilistic models do not hold for about 70 % of the gridpoints, parameter instability and temporal dependence being the most common problems. As our examples reveal, automated statistical downscaling “black-box” models are to be considered as highly prone to produce misleading results. It is shown that the Probabilistic Reduction approach can be incorporated as a complete and internally consistent framework for securing the statistical adequacy of the downscaling models and for guiding the respecification process, in a way that prevents the lack of empirical validity that affects current methods.     

威宁县乡镇最高最低气温分析与预报方法探讨

基于贵州省威宁县2012年12月-2018年8月国家基准气候站(以下简称“国家站”)和52个区域自动观测站(以下简称“区域站”)的逐日最高最低气温资料,采用统计学方法和加权最小二乘法,分析威宁县近几年来最高最低气温的变化特征及国家站和部分区域站最高最低气温的相关性。结果表明:四季中,最低气温存在稳定的低值中心和高值中心,而最高气温只存在稳定的高值中心。春、夏、秋季的最高最低气温和冬季的最低气温分布与地形基本一致,但冬季的最高气温分布受地形和滇黔静止锋共同影响却有所变化。根据拟合方程得出的各乡镇气温预报值比直接用EC模式的预报值准确率更高,其误差值≤|2|℃。随着方程相关系数的减小,预报准确率相应降低,误差范围对应增大,预报准确率的高低与相关系数的变化具有一致性。     

Using Statistical Downscaling to Quantify the GCM-Related Uncertainty in Regional Climate Change Scenarios： A Case Study of Swedish Precipitation

There are a number of sources of uncertainty in regional climate change scenarios. When statistical downscaling is used to obtain regional climate change scenarios, the uncertainty may originate from the uncertainties in the global climate models used, the skill of the statistical model, and the forcing scenarios applied to the global climate model. The uncertainty associated with global climate models can be evaluated by examining the differences in the predictors and in the downscaled climate change scenarios based on a set of different global climate models. When standardized global climate model simulations such as the second phase of the Coupled Model Intercomparison Project （CMIP2） are used, the difference in the downscaled variables mainly reflects differences in the climate models and the natural variability in the simulated climates. It is proposed that the spread of the estimates can be taken as a measure of the uncertainty associated with global climate models. The proposed method is applied to the estimation of global-climate-model-related uncertainty in regional precipitation change scenarios in Sweden. Results from statistical downscaling based on 17 global climate models show that there is an overall increase in annual precipitation all over Sweden although a considerable spread of the changes in the precipitation exists. The general increase can be attributed to the increased large-scale precipitation and the enhanced westerly wind. The estimated uncertainty is nearly independent of region. However, there is a seasonal dependence. The estimates for winter show the highest level of confidence, while the estimates for summer show the least.     

石家庄极端冷暖天气气候事件及其与气候变暖

用石家庄市1955～2002年逐日气温资料，取其第95个和第5个百分位值作为确定极端高(低)温日的阈值来检测极端冷暖事件。对发生在2002年的极端冷暖事件进行检测分析证明，上述方法能比较有效地检测极端冷暖事件的发生。计算气温趋势变率表明，石家庄气候有明显的增暖趋势，随气候变暖夏季持续性强高温和破记录高温事件的出现频次增加；寒冷期趋于缩短；极端冷日趋于减少，极端暖日趋于增加。用季极端冷(暖)日数与气温求取相关的方法，分析各季极端冷暖事件与气候变暖的联系发现，气候变暖对冬季极端冷日减少的影响最甚。城市化效应使城市变暖趋势速率高于郊区，尤以最低气温表现明显；暖事件增多、冷事件减少的趋势速率也是城市高于郊区，且冷事件减少速率高于暖事件增多速率。在气候变暖背景下应特别重视冬季冷事件减少给人类带来的潜在影响。     

由最高最低气温求算的平均气温对我国年平均气温序列影响

针对研究全国近百年平均气温长期变化的实际需要，利用603个测站1961—2002年气温观测资料，比较分析了最高最低平均气温距平序列和4次观测记录平均气温距平序列的差异，讨论了最高、最低气温变化趋势。结果表明:两种统计方法得到的平均气温距平序列及增温速率的差异均不明显，在一定条件下两者可以互相替换。此外，最高、最低气温变化普遍存在不对称现象，且可分为4种类型，这种不对称性对平均气温变化速率并没有明确一致的影响。