近40年中国平均气候与极值气候变化的概述

随着中国气象局对近50年来逐日气象观测资料的释放,人们从不同的角度对中国平均气候和极端气候的分布特征有了更多的了解.从目前研究的结果来看,这些认识需要有一个集成,即需要有一个总体的归纳和解释.通过中国近40年来的温度极值和降水极值事件的分析认识到全球增暖和区域环流异常决定着气候极值事件的分布格局.与全球增暖相联系的是:我国微量降水在空间上表现为一致的减少趋势,我国北方寒潮事件显著减少,冷夜和冷日的减少与暖夜和暖日的增多并存,以及极端强降水有增多的趋势.与东亚季风气流和西风带气流异常对应的我国有效降水在区域分布上发生了显著变化,东部季风区中的"北涝南旱"从1970年代末转型为"南涝北旱",与华南的偏干一起形成了东部季风区降水从华南、长江到华北的"-、 、-"异常分布型,但华南在1991年出现了转湿的突变;东北和西北先后从1983年和1987年前后转为暖湿气候.极端温度和极端降水趋势的空间分布与平均温度和平均降水趋势的空间分布一致.     

1961-2012年辽宁省极端气温事件气候变化特征

利用辽宁省52个气象台站逐日平均气温、 最高气温和最低气温数据, 使用国际通用的10种极端气候指数, 研究了1961-2012年辽宁省极端气温事件的气候变化特征. 结果表明: 年平均极端气温事件空间分布存在明显的地区差异. 时间尺度上, 1961-2012年辽宁省年及四季极端暖事件(暖昼日数、 暖夜日数、 夏季日数、 热带夜数和热浪持续指数)呈增加趋势, 极端冷事件(冷昼日数、 冷夜日数、 结冰日数、 霜冻日数和寒潮持续指数)呈减少趋势; 极端暖事件在20世纪90年代中期开始明显增加, 极端冷事件在20世纪80年代末期开始显著减少; 极端暖事件的变化速率要小于极端冷事件. 辽宁省气温日较差有增大的趋势, 极端暖(冷)事件的增加(减少)在秋季(冬季)最为显著. 空间变化上, 极端气温事件在全省基本都呈一致的增加或减少的分布. 多数极端气温事件均存在8 a左右的周期, 检测到的突变的时间大致在20世纪80年代中期到90年代末期. 20世纪80年代末期辽宁省气候变暖后, 极端暖事件和冷事件均有明显的增加和减少.     

天山南坡高冰川覆盖率的木扎提河流域水文过程对气候变化的响应

木扎提河是天山南坡冰川面积覆盖率最大（48.2%）的河流, 流域径流过程对气候变化极为敏感, 为了合理管理和规划水资源, 确保水资源的可持续利用, 亟需定量评估气候变化对该流域水文过程的影响。以VIC-CAS分布式水文模型为计算平台, 利用实测的径流和两次冰川编目间的冰川面积变化数据开展了模型的多目标参数化校正和验证, 有效提高了模拟结果的“真实性”, 然后通过数值模拟结果结合观测数据定量解析了流域径流的组成、 变化特征及对气候变化的响应机理。结果表明： 木扎提河总径流集中在暖季（5 - 9月）, 占全年总径流量的77.9%, 冰川径流、 融雪径流和降雨径流分别占总径流量的66.6%、 26.4%和7.0%。1971 - 2010年木扎提河流域气温和降水呈显著增加趋势, 由于降水的增加, 降雨和融雪径流均呈增加趋势, 但冰川径流呈现明显减少趋势, 导致总径流呈现下降趋势。在RCP4.5情景下, 未来该流域气温呈现明显升高趋势, 降水表现为微弱下降趋势; 气候变暖后, 更多降水以降雨形式发生, 未来降雨径流将明显增加, 降雪和融雪径流已于20世纪90年代达到峰值, 随后明显减少; 冰川面积将持续萎缩, 冰川径流于21世纪10年代达到拐点, 随后明显减少, 导致河道总径流量也将明显减少。     

Analysis of rainfall and temperature time series to detect long-term climatic trends and variability over semi-arid Botswana

Arid and semi-arid environments have been identified with locations prone to impacts of climate variability and change. Investigating long-term trends is one way of tracing climate change impacts. This study investigates variability through annual and seasonal meteorological time series. Possible inhomogeneities and years of intervention are analysed using four absolute homogeneity tests. Trends in the climatic variables were determined using Mann–Kendall and Sen’s Slope estimator statistics. Association of El Niño Southern Oscillation (ENSO) with local climate is also investigated through multivariate analysis. Results from the study show that rainfall time series are fully homogeneous with 78.6 and 50% of the stations for maximum and minimum temperature, respectively, showing homogeneity. Trends also indicate a general decrease of 5.8, 7.4 and 18.1% in annual, summer and winter rainfall, respectively. Warming trends are observed in annual and winter temperature at 0.3 and 1.5% for maximum temperature and 1.7 and 6.5% for minimum temperature, respectively. Rainfall reported a positive correlation with Southern Oscillation Index (SOI) and at the same time negative association with Sea Surface Temperatures (SSTs). Strong relationships between SSTs and maximum temperature are observed during the El Niño and La Niña years. These study findings could facilitate planning and management of agricultural and water resources in Botswana.     

Statistical detection and no-detection of rainfall change trends and breaks in semiarid Tunisia—50+ years over the Merguellil agro-hydro-climatic reference basin

Rainfall variability is an important feature of semiarid climates with major effects on hydrology, and beyond on key water-dependent societal aspects. Eventual changes in rainfall variability are a strong driver of change of hydrological processes, resources, and hazards, up to catchment signatures and spatial arrangements. We deal with observed precipitations and subsequent statistical coefficients available from a network of 15 rainfall gauges over and around the Merguellil catchment (1175 km²), with series ranging up to the 1961–2013 period. We look for eventual annual trends and breakpoints with a set of methods: Mann Kendall test, Pettitt test, Hubert segmentation procedure, Buishand U statistic, and Lee Heghinian Bayesian procedure. The results underline oscillation of dry and wet periods; several studied rain gauges (Tella, Oueslatia forêt, Majbar, Kesra forêt, Henchir Bhima, and Haffouz DGRE) denote significant trends in annual precipitation. Some breaks are detected but they are not synchronous. These methods reveal the variability of rainfall regimes in the semiarid region and provide a synoptic view of detection and no-detection of symptoms of change. This work gives opportunities to water stakeholders and climate experts in understanding the relationships between climate variability and water availability.     

Impact of climate change on extreme rainfall events and flood risk in India

The occurrence of exceptionally heavy rainfall events and associated flash floods in many areas during recent years motivate us to study long-term changes in extreme rainfall over India. The analysis of the frequency of rainy days, rain days and heavy rainfall days as well as one-day extreme rainfall and return period has been carried out in this study to observe the impact of climate change on extreme rainfall events and flood risk in India. The frequency of heavy rainfall events are decreasing in major parts of central and north India while they are increasing in peninsular, east and north east India. The study tries to bring out some of the interesting findings which are very useful for hydrological planning and disaster managements. Extreme rainfall and flood risk are increasing significantly in the country except some parts of central India.     

Identification of trends in rainfall,rainy days and 24 h maximum rainfall over subtropical Assam in Northeast India

Trends in rainfall, rainy days and 24 h maximum rainfall are investigated using the Mann-Kendall non-parametric test at twenty-four sites of subtropical Assam located in the northeastern region of India. The trends are statistically confirmed by both the parametric and non-parametric methods and the magnitudes of significant trends are obtained through the linear regression test. In Assam, the average monsoon rainfall (rainy days) during the monsoon months of June to September is about 1606 mm (70), which accounts for about 70% (64%) of the annual rainfall (rainy days). On monthly time scales, sixteen and seventeen sites (twenty-one sites each) witnessed decreasing trends in the total rainfall (rainy days), out of which one and three trends (seven trends each) were found to be statistically significant in June and July, respectively. On the other hand, seventeen sites witnessed increasing trends in rainfall in the month of September, but none were statistically significant. In December (February), eighteen (twenty-two) sites witnessed decreasing (increasing) trends in total rainfall, out of which five (three) trends were statistically significant. For the rainy days during the months of November to January, twenty-two or more sites witnessed decreasing trends in Assam, but for nine (November), twelve (January) and eighteen (December) sites, these trends were statistically significant. These observed changes in rainfall, although most time series are not convincing as they show predominantly no significance, along with the well-reported climatic warming in monsoon and post-monsoon seasons may have implications for human health and water resources management over bio-diversity rich Northeast India.     

Spatial contribution of one-day precipitations variability to rainy days and rainfall amounts in Iran

Rainfalls with short persistency are the tangible characteristics of arid and semiarid regions such as Iran. Iran is an arid and semiarid region with dramatic tempo-spatial changes of rainfall. In this regard, the short persistency of rainfall is approximately observed from 1 to 7 days in whole parts, while the greater ones are only separated in eastern parts of Iran. According to the results, the rainfall persistency is ranged from 1 to 45 days, but the maximum amount and rainy days are generated by rainfalls with short persistency. So, the rainfall events with long persistency are considered as an extreme event with extreme variability. One-day precipitations generate the maximum rainy days and rainfall amounts, especially in eastern parts of Iran. Decrease in the one-day precipitations contribution to eastern parts may indicate to decrease in regional precipitation. However, decrease in contribution in western parts may indicate to increased amounts of rainfall at other persistency rates. Our results revealed that the contribution of the one-day precipitation to general rainfall has reductive trends in almost 17.5 % of the whole Iran. The most integrated and significant reductive trend of one-day precipitation contribution to rainfall spreads northeastern and eastern parts of Iran. However, in the western parts of Iran, decreasing one-day precipitation contribution to rainy days affects to increase in the diurnal rainfall. The mentioned variability can be considered as the climate change signals in respect of one-day precipitation.     

Analyses of precipitation,temperature and evapotranspiration in a French Mediterranean region in the context of climate change

This study is focused on the western part of the French Mediterranean area, namely the Pyrénées-Orientales and Aude administrative departments. The water resources (surface and groundwater) in the region are sensitive to climate change. The study addresses the question of whether any trend in the annual and monthly series of temperature, rainfall and potential evapotranspiration (PET) already appears at the scale of this region. Two data sources have been used: (a) direct local measurements using the meteorological network; and (b) spatially interpolated data from the French weather service model SAFRAN for the period 1970–2006. The non-parametric Mann–Kendall test was applied to identify significant trends at the local scale and, because of the natural spatial variability of the Mediterranean climate, regional interpretation was also performed. The trends observed in the 13 catchments of interest are consistent with those observed at a larger scale. An increase in annual mean temperature and annual PET was observed throughout the study area, whereas annual precipitation has not exhibited any trend. The monthly scale has revealed strong seasonal variability in trend. The trend for an increase in monthly PET has been observed mainly in the spring, and has not been seen in the coastal areas. A trend for an increase in monthly temperature has been observed in June and in the spring throughout the entire area. Monthly rainfall has been found to decrease in June and increase in November throughout the area. The significant trends observed in rainfall and temperature seem to be consistent between the different data sources.     

Rainfall variability and indices of extreme rainfall-analysis and perception study for two stations over Central Himalaya,India

The analysis of rainfall pattern and indices of extreme rainfall events is performed for two meteorological stations located in the Central Himalayan Region which is highly vulnerable to rain-induced hazards. The records of these rain-induced disasters suggest that such events are generally observed in later part of monsoon season, when soil is saturated after monsoon rains. An attempt is made here to test trends of 19 different extreme rainfall indices that have been widely used in the literature, using daily rainfall data for two urban centres (Nainital and Almora) over the period 1992–2005. We have used statistical tools such as Sen’s method and Mann–Kendall test for detection of trend in annual rainfall, monsoon rainfall, number of rainy days and 1-day extreme rainfall. Principal component analysis gives the correlation between different extreme rainfall indices. Time series of principal components are representing the trends of extreme indices, their variation and interrelation between different indices. The perception study conducted in the same sites indicates that extreme rainfall events and change in rainfall amount and timing are well perceived by the local people.     

Climate extreme and its linkage to regional drought over Idaho, USA

To investigate consequences of climate extreme and variability on agriculture and regional water resource, twenty-seven climatic indices of temperature and precipitation over Idaho, USA, were computed. Precipitation, mean temperature and maximum temperature, self-calibrated Palmer Drought Index and Standardized Precipitation Index for 1-, 3-, 6- and 12-month time scales were used to identify spatial and temporal distribution of climatic extreme and variability as well as drought frequency and magnitude. Seven oceanic indices were also used to detect teleconnections between climatic indices and regional droughts. The analyses were conducted for 56 meteorological stations, during 1962?C2008, characterized by a long-term and high-quality data set. The result indicates that decreasing trends and increasing trends are identified for precipitation and temperature, respectively. Consequently, it appears that frost and ice days dwindle as growing season (May?CAugust) length, tropical nights and summer days increase. Given current climate conditions, the results also imply that these trends will continue in the future possibly driven by uncertain climate variability. We anticipate that these indices explained by teleconnections will improve drought-forecasting capability in this region.     

Hydrologic behavior and flood probability for selected arid basins in Makkah area, western Saudi Arabia

In arid regions, flash floods often occur as a consequence of excessive rainfall. Occasionally causing major loss of property and life, floods are large events of relatively short duration. Makkah area in western Saudi Arabia is characterized by high rainfall intensity that leads to flash floods. This study quantifies the hydrological characteristics and flood probability of some major wadis in western Saudi Arabia, including Na’man, Fatimah, and Usfan. Flood responses in these wadis vary due to the nature and rainfall distribution within these wadis. Rainfall frequency analysis was performed using selected annual maximums of 24-h rainfall from eight stations located in the area. Two of the most applied methods of statistical distribution, Gumbel’s extreme value distribution and log Pearson type III distribution, were applied to maximum daily rainfall data over 26 to 40 years. The Gumbel’s model was found to be the best fitting model for identifying and predicting future rainfall occurrence. Rainfall estimations from different return periods were identified. Probable maximum floods of the major wadis studied were also estimated for different return periods, which were extrapolated from the probable maximum precipitation.     

1961-2016年四川地区不同量级不同持续时间降水的 时空特征分析

利用四川地区122站逐日降水数据,采用均值、气候趋势系数等统计方法,对1961-2016年不同量级不同持续时间降水的空间和时间变化特征进行了分析,结果表明：盆地和攀西地区小雨、中雨、大雨和总暴雨所占年降水量比例接近,高原地区小雨降水量约占50%以上,中雨约40%,大雨约10%;整个四川地区小雨日数占总降水日数75%以上,量级越高降水日数越少。年降水量在盆地和攀西地区为减少趋势,高原则相反,年降水日数除了在高原局部微弱增加外其他地区皆减少且大部分区域减少趋势通过99%的显著性水平检验,这种趋势显著性主要体现在小雨量级降水。随着降水量级的增加,高原、盆地东北、攀西和盆地东南的部分地区出现了降水量和降水次数增加趋势,这可能说明高原地区年降水量的增加由小雨量级降水效率以及中雨和大雨降水次数增加导致,盆地和攀西部分地区年降水量的增加主要由降水量级大的降水次数增加导致。     

1960—2017年河西地区降水时空变化特征

利用1960—2017年日降水量资料,采用线性倾向趋势分析、滑动分析和泰森多边形法等,对河西地区多年降水时空变化特征及不同量级降水日数及降水强度的变化趋势进行了研究。结果表明：河西地区年均降水量为99.0 mm,呈现明显的逐年上升趋势,平均倾向率为8.72 mm?（10a）^-1,月降水量为单峰分布,5—10月夏秋汛期降水量占年降水量的89.2%,各季节降水量均呈现显著上升趋势;年均降水日数为36.7天,呈现明显的上升趋势,增幅为3.18 d?（10a）^-1,降水日数主要分布在夏季,约占总降水日数的54.6%;平均降水强度为2.70 mm?d^-1,呈现减弱趋势,变化速率为-0.04 mm?d^-1?（10a）^-1;零星小雨和小雨降水日数均呈现增加趋势,而二者平均降水强度均为下降趋势,小到中雨降水日数和降水强度呈现增加趋势,中雨及以上的降水变化趋势不明显。     

青海省极端气温事件的气候变化特征研究

选用青海省37个气象站点1961-2011年近51 a, 逐日气温(最高、 最低、 平均)资料, 采用国际通用的极端气温指数定义计算了9种极端气温指数, 并分析其主要气候特征.结果表明: 近51 a青海省极端气温呈明显上升趋势, 极端冷指标(霜冻、 结冰日数、 冷夜、 冷昼指数)呈下降趋势, 而极端暖指标(夏天日数、 暖夜、 暖昼指数)呈上升趋势, 且极端冷指标的减少幅度高于极端暖指标的增加幅度.空间分布上, 极端气温指数在全省呈一致的上升(下降)趋势分布.在近51 a的时间尺度上各种极端气温指数都存在多个较明显的周期, 如较短的3~8 a的准周期, 以及13 a、 17 a、 27 a的年代际周期特征.青海省年平均气温与极端气温指数有很高的相关性, 气候变暖突变前后极端气温指数表现出明显差异: 在变暖突变发生后, 霜冻日数、 冷夜指数、 冷昼指数、 结冰日数明显减少, 夏天日数、 暖夜指数及暖昼指数明显增加, 其中相对指数几乎呈倍数显著变化, 表明极端气温指数对气候变暖有很好的响应.     

Assessing the impacts of rainfall intensity and urbanization on storm runoff in an arid catchment

In the past few decades, rapid urbanization has occurred in many regions of the Kingdom of Saudi Arabia due to increasing population and urban development. Additionally, the effects of global warming on rainfall characteristics have been observed. This rapid change in urbanization and climate change has cause significant changes in the nature of land surfaces and rainfall patterns, which affect the runoff process and the amount of surface runoff during floods. This study investigated the effect of urbanization and rainfall intensity for Hafr Al-Batin watershed located in Saudi Arabia. For this purpose, a hydrologic model, HEC-HMS, was adopted to simulate the flow of different rainfall intesities and urbanization levels. Simulated results showed that for a 100-year storm, a 24-h duration, and an urbanization level of 80%, the peak flow was 213% higher than the estimated current peak and the runoff volume was 112% higher than the current runoff volume. These results show a strong linear correlation between the level of urbanization and both peak discharge and runoff volume. Furthermore, the results indicate that for short return periods, the peak flow is more sensitive to the level of urbanization compared to long periods.     

Spatial variability of rainfall trends in Iran

The main objective of this paper is to analyze the spatial variability of rainfall trends using the spatial variability methods of rainfall trend patterns in Iran. The study represents a method on the effectiveness of spatial variability for predicting rainfall trend patterns variations. In rainfall trend analysis and spatial variability methods, seven techniques were used: Mann–Kendall test, Sen’s slope method, geostatistical tools as a global polynomial interpolation and the spatial autocorrelation (Global Moran’s I), high/low clustering (Getis-Ord General G), precipitation concentration index, generate spatial weights matrix tool, and activation functions of semiliner, sigmoid, bipolar sigmoid, and hyperbolic tangent in the artificial neural network technique .For the spatial variability of monthly rainfall trends, trend tests were used in 140 stations of spatial variability of rainfall trends in the 1975–2014 period. We analyzed the long and short scale spatial variability of rainfall series in Iran. Spatial variability distribution of rainfall series was depicted using geostatistical methods (ordinary kriging). Relative nugget effect (RNE) predicted from variograms which showed weak, moderate, and strong spatial variability for seasonal and annual rainfall series. Moreover, the rainfall trends at each station were examined using the trend tests at a significance level of 0.05. The results show that temporal and spatial trend patterns are different in Iran and the monthly rainfall had a downward (decreasing) trend in most stations, and the trend was statistically significant for most of the series (73.5% of the stations demonstrated a decreasing trend with 0.5 significance level). Rainfall downward trends are generally temporal-spatial patterns in Iran. The monthly variations of rainfall decreased significantly throughout eastern and central Iran, but they increased in the west and north of Iran during the studied interval. The variability patterns of monthly rainfall were statistically significant and spatially random. Activation functions in the artificial neural network models, in annual time scale, had spatially dispersed distribution with other clustering patterns. The results of this study confirm that variability of rainfall revealing diverse patterns over Iran should be controlled mainly by trend patterns in the west and north parts and by random and dispersed patterns in the central, southern, and eastern parts.     

Spatio-temporal variations in precipitation on the Huang-Huai-Hai Plain from 1963 to 2012

Spatio-temporal variations in precipitation are affecting agricultural production in China in the context of climate change. Based on daily precipitation data from 63 national meteorological stations on the Huang-Huai-Hai Plain from 1963 to 2012, this paper analysed the spatio-temporal variations in precipitation in terms of precipitation days and intensity, using spatial interpolation, linear trend estimation and wavelet analysis. The results indicated that: (i) from 1963 to 2012, the number of annual precipitation days and intensity decreased gradually from the southeast to the northwest. Additionally, the distribution of the extreme precipitation index was similar to that of the annual precipitation index; (ii) the number of annual precipitation days and heavy precipitation days gradually decreased, while precipitation intensity and extreme precipitation days and extreme rainfall intensity remained relatively stable or decreased. The spatial patterns of annual variation trends were considerably different. The annual precipitation days and intensity trends are consistent with the overall trend, while that of the extreme rainfall index in some regions differs from the overall trend; (iii) the precipitation index displayed different periodic oscillations during the period, and the precipitation index values differed at different time scales. However, all the precipitation index values exhibited a 28-yr oscillation.     

南京市强降水天气长期动态及变异性规律

基于南京市1951～2016年汛期(6～9月)各月降水资料,分析研究区强降水天气的长期动态及变异性规律。长期动态结果表明,近66年来南京市强降水天气发生频率显著增加,平均每10年增加0.31次;不同规模强降水中,暴雨、大暴雨天气发生频率均呈增加趋势,其中暴雨天气呈显著增加。多年(7a、10a、15a)月际排序值滑动标准差均通过置信度99%显著性检验,强降水天气变异性呈显著下降趋势;强降水天气汛期盛行月份趋于集中(7月),月间格局趋于稳定,与多年的月际排序值滑动标准差得出强降水天气变异性呈下降趋势的结论相吻合。     

Changes in annual temperature extremes in the Carpathians since AD 1961

The Carpathian Mountains region cover areas from seven countries of central and southeastern Europe, the mountain chain having major regional influences on the temperate climate, specific to latitudes between 43°N and 49°N. In order to identify changes in the annual temperature extremes, the Mann–Kendall nonparametric trend test has been applied to several thermal indices, recommended by the expert team on climate change detection and indices. The indices were computed from gridded daily datasets of minimum and maximum temperature at 0.1° resolution (~10 km), available online within the framework of the project CarpatClim (climate of the Carpathian region) for the period 1961–2010. The results show decreasing trends in cold-related indices, especially in the number of frost days, and increasing trends in warm-related ones. The trend patterns are consistent over the region, i.e., there are no mixed trends for a given index. Regional differences in climate extreme trends within the Carpathian region are related to altitude, rather than latitude. The number of summer days is increasing over the entire area, while the number of tropical nights presents upward trends mainly at lower elevations. The Warm Spell Duration Index presents upward trends over 60 % of the region. The (annual) East Atlantic pattern shows strong correlations with the warm-related indices. Our results are in agreement with previous temperature-related studies in the region.