Spatial and temporal variability of precipitation indices during 1961–2010 in Hunan Province,central south China

Based on daily precipitation records at 75 meteorological stations in Hunan Province, central south China, the spatial and temporal variability of precipitation indices is analyzed during 1961–2010. For precipitation extremes, most of precipitation indices suggest that both the amount and the intensity of extreme precipitation are increasing, especially the mean precipitation amount on a wet day, showing a significant positive trend. Meanwhile, both of the monthly rainfall heterogeneity and the contribution of the days with the greatest rainfall show an upward trend. When it comes to rainfall erosivity, most of this province is characterized by high values of annual rainfall erosivity. Although the directions of trends in annual rainfall erosivity at most stations are upward, only 6 of the 75 stations have significant trends. Furthermore, the spatial and temporal variation of dryness/wetness has been assessed by the standardized precipitation index (SPI). The principal component analysis (PCA) was applied to the SPI series computed on 24-month time scales. The results demonstrated a noticeable spatial variability with three subregions characterized by different trends: a remarkable wet tendency prevails in the central and southern areas, while the northern areas are dominated by a remarkable dry tendency.     

The best fitting distribution of annual maximum rainfall in Peninsular Malaysia based on methods of L-moment and LQ-moment

This paper discusses patterns of annual and monthly precipitation variability at seven weather stations in east central Europe (1851–2007). Precipitation patterns were compared to three simple regional indices of atmospheric circulation, i.e., western circulation, southern circulation and the cyclonicity (C) index and a relationship between precipitation and the North Atlantic Oscillation index was identified. Correlations of the monthly records and multiple regression, using a principal components’ analysis, helped determine the statistical significance of the dependence of precipitation on the circulation indices. The Mann–Kendall test revealed no trend to change in any of the precipitation series, but a certain spatial regularity could be discerned in the phase of the annual periodic component. A common feature of the variability in central European annual precipitation is the dry period identified in the 1980s and the first half of the 1990s. In the northern part of the region, above-average precipitation was noted from the 1960s through to the mid-1970s as a result of the frequent prevalence of depressions. South of the divide, the wettest period was recorded at the turn of 1930s/1940s. After a number of very wet years in the last decade of the twentieth century and the beginning of the twenty-first century, precipitation began to fall at all of the region’s weather stations. The C index is the strongest circulation-linked factor influencing precipitation in central Europe and it accounts for more than 40% of the variance in spatially averaged wintertime precipitation.     

Spatial and temporal variability of precipitation in Serbia for the period 1961–2010

Monthly, seasonal and annual sums of precipitation in Serbia were analysed in this paper for the period 1961–2010. Latitude, longitude and altitude of 421 precipitation stations and terrain features in their close environment (slope and aspect of terrain within a radius of 10 km around the station) were used to develop a regression model on which spatial distribution of precipitation was calculated. The spatial distribution of annual, June (maximum values for almost all of the stations) and February (minimum values for almost all of the stations) precipitation is presented. Annual precipitation amounts ranged from 500 to 600 mm to over 1100 mm. June precipitation ranged from 60 to 140 mm and February precipitation from 30 to 100 mm. The validation results expressed as root mean square error (RMSE) for monthly sums ranged from 3.9 mm in October (7.5% of the average precipitation for this month) to 6.2 mm in April (10.4%). For seasonal sums, RMSE ranged from 10.4 mm during autumn (6.1% of the average precipitation for this season) to 20.5 mm during winter (13.4%). On the annual scale, RMSE was 68 mm (9.5% of the average amount of precipitation). We further analysed precipitation trends using Sen’s estimation, while the Mann-Kendall test was used for testing the statistical significance of the trends. For most parts of Serbia, the mean annual precipitation trends fell between −5 and +5 and +5 and +15 mm/decade. June precipitation trends were mainly between −8 and +8 mm/decade. February precipitation trends generally ranged from −3 to +3 mm/decade.

     

模糊C均值聚类法在新疆年降水气候分区中的应用

利用新疆98个气象站1960-2011年的年降水量资料,采用模糊C均值聚类法,对新疆年降水量进行分区研究;同时利用线性趋势、累积距平、M-K检验、t检验相结合的方法,对新疆年降水量在不同区域上的变化趋势以及突变时间等进行了对比诊断分析,得到了新疆地区年降水量分布的空间特征。结果表明：（1）新疆年降水的分布大致可分为7个区域;（2）根据模糊C均值方法所分区域能够体现出由于地形差异导致的降水分布不均匀的特点,这一结果与其他研究干旱区降水分布差异产生的原因相同。分区结果合理,说明该聚类方法适用于区域气候区划;（3）新疆大部分区域的降水量在20世纪80年代中后期以前偏少,低于多年平均值,自80年代中后期以后才开始偏多;不同区域的降水量依次从70年代初、80年代中后期、90年代初开始增加;整个南疆盆地、阿勒泰地区、准噶尔盆地降水的突变时间较为接近;（4）新疆降水量整体异常表现为降水一致多（或少）、北多南少、西多东少。     

A statistical analysis of the daily precipitation over Serbia: trends and indices

A statistical analysis of the daily maximum and mean monthly precipitation measured at ten meteorological stations in Serbia during the period 1949?C2007 is presented. Although the means of the daily maximum and monthly precipitation varied throughout the year, their ratio was almost uniform, with an average value of 32.6% for Serbia. The precipitation events within each year were ranked and then the trends on the ten wettest days of the year were assessed. Averaged across Serbia, the wettest day of the year produces 41.3?mm of precipitation and accounted for 6.3% of the total annual precipitation. Taken together, 35.5% (232.0?mm) of the total annual precipitation fell during the ten wettest days of the year. Over the course of the twentieth century, the average annual precipitation on the wettest day across Serbia increased by nearly 9%. Also, averaged across Serbia, statistically insignificant increasing trends were found on each of the ten wettest days of the year. Furthermore, four climate indices were analysed. Heavy precipitation indices (i.e., RR20 and R95T) increased in Serbia at the end of the twentieth century and thereafter.     

Non-parametric trend analysis of the aridity index for three large arid and semi-arid basins in Iran

Currently, an important scientific challenge that researchers are facing is to gain a better understanding of climate change at the regional scale, which can be especially challenging in an area with low and highly variable precipitation amounts such as Iran. Trend analysis of the medium-term change using ground station observations of meteorological variables can enhance our knowledge of the dominant processes in an area and contribute to the analysis of future climate projections. Generally, studies focus on the long-term variability of temperature and precipitation and to a lesser extent on other important parameters such as moisture indices. In this study the recent 50-year trends (1955–2005) of precipitation (P), potential evapotranspiration (PET), and aridity index (AI) in monthly time scale were studied over 14 synoptic stations in three large Iran basins using the Mann–Kendall non-parametric test. Additionally, an analysis of the monthly, seasonal and annual trend of each parameter was performed. Results showed no significant trends in the monthly time series. However, PET showed significant, mostly decreasing trends, for the seasonal values, which resulted in a significant negative trend in annual PET at five stations. Significant negative trends in seasonal P values were only found at a number of stations in spring and summer and no station showed significant negative trends in annual P. Due to the varied positive and negative trends in annual P and to a lesser extent PET, almost as many stations with negative as positive trends in annual AI were found, indicating that both drying and wetting trends occurred in Iran. Overall, the northern part of the study area showed an increasing trend in annual AI which meant that the region became wetter, while the south showed decreasing trends in AI.     

Analysis of drought in the region of Abruzzo (Central Italy) by the Standardized Precipitation Index

The paper presents a comprehensive analysis of drought phenomena in the Region of Abruzzo (Central Italy) using the Standardized Precipitation Index (SPI) computed at different time scales (3, 6, 12, 24 months). The study is based on monthly precipitation data collected from 1951 to 2009 at 69 climatic stations uniformly distributed over the region. According to the trend analysis, most stations are characterized by increments in both drought severity and variability, particularly at the longer time scales. A principal component analysis applied to SPI time series enabled to identify two main patterns: the first more correlated to the coastal areas, the second more correlated to the inland, mountainous areas. However, the spatial patterns become less defined as the time scale increases, making more uncertain the definition of homogenous areas to be used in drought management plans. In most cases, the identified drought patterns have similar negative overall tendencies, but different trend directions in some sub-periods. In particular, the first drought pattern is clearly characterized by a trend reversal (from decreasing to increasing) during the last decade. This temporal evolution, consistent with that observed by large-scale analyses in the corresponding (or near) grid points, was not detected for the second pattern, which is probably influenced by local topographic and/or orographic factors. The results confirm the complexity of drought phenomenon in a typical Mediterranean region and the necessity of high-resolution datasets to capture its temporal and spatial variability.     

动力延伸预报产品在辽宁短期气候预测中的释用

基于1961～2000年辽宁53个测站40 a逐年的月气温距平和月降水距平百分率资料,根据EOF(经验正交函数)展开的空间特征向量分布特征,将前3个主要特征向量时间系数作为预报量,将500 hPa高度场的高度距平、地转涡度作为预报因子,利用多元统计回归分析,建立了一套定点、定量预测辽宁各月气温与降水量的数学模型。利用该模型对2001~2005年辽宁53个测站的月气温距平和月降水距平百分率进行逐月预报试验。结果表明:对气温和降水量的趋势预报的评分均比较好,有87%以上的月气温距平预测结果的评分超过66.0分,各月的平均Ps评分均高于66.0分,年平均为75.5分或以上,总平均为83.1分;有70%的月降水距平百分率预测结果的Ps评分超过60.0分,各月的平均Ps评分都高于53.0分,年平均为58.0分以上,总平均为66.5分。但对异常气候的预测效果不明显。     

Trend of climate variability in China during the past decades

Trends in precipitation and mean air temperature in China are estimated, and trend analysis on statistical moments of residuals is further used to investigate climate variability at different timescales. Trends of statistical moments for residuals (i.e. detrended series of climate records) are estimated by using least-square method and Mann?CKendall test. Results show that upward trend is detected in annual mean air temperature but no linear trend for annual precipitation in China. Weak trend is found for variability of precipitation while no trend is found for that of air temperature for China as a whole. But some regional features of climate variability are observed. It is found that the northwest of China shows a significant increasing for precipitation variability, which is consistent with previous work, especially for monthly precipitation. No change is detected in monthly mean air temperature for all stations, while small decreasing and increasing trends are detected for variability of annual mean air temperature in northeast of China and southwest of China, respectively.     

基于西南地区台站降雨资料空间插值方法的比较

以西南地区1996～2000年93个气象台站观测的月均降雨量为基础,对各月降雨量进行空间自相关性,变异特征等空间分析后,采用反距离加权法(IDW)和以不同变异函数模型(指数模型、球面模型、高斯模型)为基础的普通克里金(O-Kriging)两种方法进行空间插值,通过交叉验证结果对两种方法进行分析比对。结果表明:(1)西南地区月均降雨量存在明显的空间集聚现象,并具有显著的空间自相关性和变异特征,可对该研究区域降雨量进行空间插值研究。(2)在O-Kriging插值时,变异函数选用指数模型的效果最好,球面模型次之,高斯模型最差。(3)两种方法对月均降雨量及其极大值和极小值插值时,O-Kriging的插值误差均小于IDW,插值误差整体上与降雨量呈正相关关系。在剔除各月降雨量极大值较为集中的两个站点后进行插值,插值结果的误差均明显降低。(4)对研究区域整体来说,O-Kriging的插值效果优于IDW,但就单个站点来看,结果并非如此。在降雨量的空间插值中,由于研究区域和时间尺度的不同,并不存在绝对的最优方法,应根据实际应用效果选择最适方法。     

The analysis of aridity in Central Serbia from 1949 to 2015

In this study, we apply De Martonne and Pinna combinative indices to analyze the aridity in Central Serbia. Our dataset consists of mean monthly surface air temperature (MMT) and mean monthly precipitation (MMP) for 26 meteorological stations during the period 1949–2015. MMT and MMP are used for calculating monthly, seasonal, and annual aridity indices for period of 66 years. According to the De Martonne climate classification, we determine five, three, and four types of climate on the monthly, seasonal, and annual basis, respectively. During the observed period, winter was extremely humid, spring and autumn were humid, and summer was semi-humid. Humid and semi-humid climate with Mediterranean vegetation are identified by the annual Pinna combinative index. We find that there is no change in aridity trend in Central Serbia for the period 1949–2015. Aridity indices are additionally compared with the North Atlantic Oscillation and El-Niño South Oscillation in order to establish a possible connection with the large-scale processes. Results are further compared with several earlier studies of aridity in Serbia. With this study, the analysis of aridity in whole Serbia has become complete.     

An analysis of daily and monthly precipitation seasonality and regimes in Iran and the associated changes in 1951–2014

Daily and monthly total precipitation of 155 synoptic stations with relatively regular distribution over Iran, covering the 1990–2014 period, were used to investigate the spatial pattern of precipitation seasonality and regimes over Iran, using a set of precipitation seasonality indices. The results suggest a strong agreement between the indices computed at monthly time scale. The result also shows a latitudinal decreasing gradient from the lower index values in the north to the highest values in the south of Iran, suggesting a strong negative relationship between the latitude and the indices. A weak but statistically significant association was also found between the indices and the longitude, showing a gradual west-east contrast between the mountainous western Iran and the central-eastern lowlands and deserts of the country. The spatial patterns of the indices well agree in revealing different precipitation regimes in Iran, in spite of the observed discrepancies in their areal extent of the regions identified. All the indices characterized northern Iran by a precipitation regime having a moderate seasonality, while the mountainous areas of the western and northern Iran are featured by a marked precipitation regime possessing a longer dry season. However, the most seasonal precipitation regime with the longest dry period describes the southern country and some spot areas of the central-eastern Iran. The spatial distribution of the seasonal precipitation regimes and the month and season of maximum precipitation amounts across Iran was also identified, suggesting that from the 24 possible precipitation regimes over the globe, eight were found in Iran, from which a precipitation regime with the highest precipitation amount in winter, followed by autumn, spring, and summer characterized most parts of the country. January and JFM were also found as the month and season of maximum precipitation in a majority of stations distributed over Iran, respectively. The precipitation concentration index (DPCI) computed using daily precipitation data ranges between 0.56 and 0.76 across the country; nonetheless, the values between 0.64 and 0.70 characterized a majority of stations distributed over most parts of Iran. Contrarily to the indices computed at monthly time scale, the DPCI does not show a clear latitudinal pattern over the country. The Mann–Kendal trend test and the Sen slope estimator were applied to the computed indices relative to 16 stations with the longest and complete precipitation records during 1951–2014 time period. The indices time series showed no significant trend in the majority of the stations, indicating that the precipitation regimes of the studied stations did not change over 1951–2014 period.     

Spatial and temporal variability of winter and summer precipitation over Serbia and Montenegro

Summary The main characteristics of the spatial and temporal variability of winter and summer precipitation observed at 30 stations in Serbia and Montenegro were analysed for the period 1951–2000. The rainfall series were examined spatially by means of Empirical Orthogonal Functions (EOF) and temporally by means of the Mann-Kendall test and spectral analysis. The Alexandersson test was used to detect the inhomogeneity of the data set.The EOF analysis gave three winter and summer dominant modes of variations, which explained 89.7% and 70.4% of the variance, respectively. The time series associated with the first pattern showed a decreasing trend in winter precipitation. The spectral analysis showed a 16-year oscillation for the dominant winter pattern, around a 3-year oscillation for the dominant summer pattern, and a quasi-cycle of 2.5 years for the winter third pattern.     

Analysis of bulk precipitation chemistry in Serbia for the period from 1982 to 2010

Bulk precipitation samples collected daily through bulk collectors at eight meteorological stations in Serbia were analyzed for their chemical composition. The data covers time series, from 20 to 28 years, in the period between 1982 and 2010. The most abundant ion in the samples was sulfate. Only 0.17 % of all samples were from strong acid rains (pH < 3.5). The relatively high average pH values (5.94–6.26) of the collected precipitation indicate the neutral or alkaline nature of local rainwater. Trends in both the annual amount and the composition of precipitation were tested by the nonparametric Mann–Kendall test and Sen’s slope estimator. Significant increasing trend of precipitation was identified for almost all stations. Rebuilding activities after the bombing of Serbia in 1999 were identified as a possible anthropogenic cause of the sharp increase of some ions (Ca²⁺) in the first year following the bombing. The origin of air masses arriving at one particular station was examined using two-dimensional backward trajectories. Western sectors (W, SW and NW) accounted for almost half (44.3 %) of all rainy days, while eastern sectors (SE, E and NE) brought only 10.4 % of all rainy days. The distribution, per sector, of volume-weighted concentrations of sulfate, nitrate, ammonium, calcium, potassium, magnesium, chloride and sodium ions, as well as the amount of precipitation and its pH values for one station, was also analyzed. Rainwater from the SE and S sectors was the most polluted.     

中国近50年降水量变化区划(1961-2010年)

基于中国537个气象站点1961-2010年的年降水量数据,运用滑动概率分布模型、小波分析和Mann-Kendall检验法,结合中国地形特点,从降水量均值的变化、变率的变化、频率分布形式的变化、突变特征以及周期变化5个方面来分析中国降水量的变化特征和区域差异,构建具体的指标体系,对中国降水量变化进行区划。结果表明,中国降水量变化存在明显的区域差异,根据这些差异可以将中国划分为3个变率变化带、10个平均降水量变化区、35个周期变化亚区。      

近41年中国不同季节降水气候分区及趋势

利用中国486个测站1960—2000年逐日降水观测资料,采用分层聚类和相似分析方法,兼顾降水的年内季节变化和年际变化,对中国降水进行了气候区划。利用动态分析分层聚类过程中组内和组间平均相关系数的差异指标法,为不同季节降水研究找到了适合的分区方案。在年降水分区方案中,得到中国降水的三级气候分区:11区、28区和54区。用同样的方法得到各月、季降水的分区方案。在分析过程中发现:在同样相似条件下,夏季(及夏季各月)分区数明显多于其它季(月);11个Ⅰ级分区年降水具有明显的区域性特征。分析结果在一定程度上说明了所用分区方法的客观性。     

Changes in daily and monthly rainfall in the Middle Yellow River,China

Highly concentrated precipitation, where a large percentage of annual precipitation occurs over a few days, may include a high risk of flooding and severe soil erosion. Thus, areas with severe erosion such as the Loess Plateau in China are particularly vulnerable to highly concentrated precipitation events due to climate change. In this study, we investigated spatial and temporal patterns in the concentration of rainfall in the Middle Yellow River (MYR) from the last 56 years (1958–2013). We used daily and monthly precipitation data from 26 meteorological stations in the study area to calculate the precipitation concentration index (PCI) and the concentration index (CI). The southern and northern parts of the MYR were characterized by a lower CI with a decreasing trend, while the middle parts had a higher CI with an increasing trend. High PCI values occurred in the southern MYR, while lower PCIs with a more homogenous rainfall distribution were found mainly in the northern parts of the MYR. The annual PCI and CI exhibited positive trends at most stations, although only a minority of stations had significant trends (P < 0.05). At seasonal scales, CI exhibited significantly increasing trends in winter at most stations, while a few stations had significant trends in the other three seasons. These findings provide important reference information to facilitate ecological restoration and farming operations in the study region.     

Comparison of surface variables from ERA and NCEP reanalysis with station data over eastern China

This study compared precipitation, mean air temperature (MAT) and mean sea level pressure (MSLP) from two widely used reanalysis datasets (ERA-40 and NCEP) with those from observed stations across eastern China. The evaluation was based on a comparison of both temporal and spatial variability and included several assessment criteria such as the mean values, normalized root mean square error, Mann–Kendall test, empirical orthogonal functions (EOFs) and probability density functions. The results showed that both the ERA-40 and NCEP datasets could capture temporal and spatial variability of the observed precipitation, MAT and MSLP over eastern China. The results showed that the two reanalysis datasets performed better for MAT and MSLP than for precipitation. Overall, the two reanalysis datasets revealed reasonable agreement with observations according to the evaluation. ERA-40 was better at capturing the temporal and spatial distributions for these three variables than NCEP, especially for MAT and MSLP. NCEP tended to overestimate the annual precipitation for both mean and extreme values, while ERA-40 tended to underestimate it, particularly for extreme values. The two reanalysis datasets performed better in the east and northeast regions of the study area than in other regions for capturing the temporal variability of MAT and MSLP. ERA-40 was poor at capturing the temporal variability of precipitation in northeastern China. According to the trend analysis, the two reanalysis datasets showed lower trends for MAT and precipitation and higher trends for MSLP. Both ERA-40 and NCEP had larger explained variances for the first two EOFs than the observed precipitation. This implies that both reanalysis datasets tend to simulate a more uniform spatial distribution for precipitation in the study area.     

Spatio-temporal variability of seasonal rainfall in western equatorial Africa

This study reveals homogeneous sub-regions over the poorly studied area of western equatorial Africa (10S?C7N and 7E?C30E). Monthly totals of 141 stations covering the period 1955?C1984 are used. The stations are grouped based on the similarity of their interannual rainfall variability. In addition to annual totals, four different seasons are examined separately for regionalization, an approach that has lacked in previous studies. The four 3-month seasons are defined as follows: January?CFebruary?CMarch (JFM), April?CMay?CJune (AMJ), July?CAugust?CSeptember (JAS), and October?CNovember?CDecember (OND). Two different algorithms are applied and compared: the rotated principal component analysis (RPCA) in conjunction with Ward's method, and the RPCA in conjunction with k-means method. The principal components that explain about 65% of total variance are retained and then varimax rotated. The corresponding scores are utilized as input for cluster analysis. Using Ward's method, five sub-regions are recognized for AMJ, JAS and OND and 4 sub-regions for JFM and annual data. The regions are geographically well distributed over the area and consist of roughly the same number of stations. The F-test is used to evaluate the homogeneity of each sub-region. The results show that all sub-regions are strongly homogeneous. Assuming the same number of clusters, the k-means method provides comparable spatial patterns with those of Ward's method. However, there are some differences, which are more evident in JAS and OND. Like Ward's method, the values of F-ratio for the k-means algorithm also confirm the homogeneity of all seasons/sub-regions. The interannual variability of rainfall for each season/sub-region is also provided and compared.     

Detection of changes in the summer precipitation time series of the region Emilia-Romagna, Italy

Summary  The main characteristics of the spatial and temporal variability of summer precipitation observed in 40 rainfall stations of the Emilia-Romagna region in northern Italy, are analysed for the period 1922 to 1995. Non-parametric tests and Empirical Orthogonal Function (EOF) analysis were used as tools in order to achieve the paper’s objective. The Pettitt and Mann-Kendall tests detect shift points and trends in the precipitation time series, respectively, while the EOF analysis reveals the main characteristics of spatial variability. The Standard Normal Homogeneity Test (SNHT) was used to detect the inhomogeneity of the data set. Almost all stations exhibit an increasing trend with a systematic significant upward shift around 1962. The climate signal is more significant in the north-western, central and north-eastern part of the region, and the spatial extension strongly depends on the network density and the time period analysed. The change in summer precipitation is mainly due to a change during August and is confirmed by the SNHT test which does not reveal an inhomogeneity in the series. The first EOF pattern indicates that a common large-scale process could be responsible for summer precipitation variability in the Emilia-Romagna region. The second EOF pattern shows an opposite sign of climate variability between north-western and south-eastern areas. The Apennine mountains show the largest climate variability in the summer precipitation field. Received March 8, 2000 Revised July 17, 2000