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.     

Rainfall and rainy days trend in Iran

In this study, long-term annual and monthly trends in rainfall amount, number of rainy days and maximum precipitation in 24?h are investigated based on the data collected at 33 synoptic stations in Iran. The statistical significance of trend and climate variability is assessed by the Mann-Kendall test. The Linear trend analysis and the Mann-Kendall test indicate that there are no significant linear trends in monthly rainfall at most of the synoptic stations in Iran. However, the maximum number of stations with negative trends have been observed in April (29 station), and then in May (21 stations) and February (21 stations) and with positive trends in December (26 stations) and July (24 stations). The significant linear trends, with a significant level of 0.05, in annual rainfall have been noticed only at five stations. The monthly number of rainy days does not show any significant linear trend for most areas in Iran. The maximum number of stations with monthly negative trends in rainy days has also been observed in April with the minimum in December. In April, out of 24 stations with negative trends, 12 stations have a significant negative trend. Contrary to that, in October there is no significant linear trend. Most stations have positive trends in annual number of rainy days. Also, the monthly maximum precipitation in 24?h does not show any significant linear trend for most areas in Iran. The maximum number of stations with monthly negative trends in maximum precipitation has also been observed in February with the minimum in December. In spite of that, there are almost no significant precipitation variations in Iran during the last 50-odd years, the tendency of decreasing rainfall amount in April and increasing rainfall amount in December and July could indicate an eventual climate change in this area in the future.     

Evaluation of spatial and temporal characteristics of rainfall in Malawi: a case of data scarce region

This paper presents the methods, procedure and results in studying spatial and temporal characteristics of rainfall in Malawi, a data scarce region, between 1960 and 2006. Rainfall variables and indicators from rainfall readings at 42 stations in Malawi, excluding Lake Malawi, were analysed at monthly, seasonal and annual scales. In the study, the data were firstly subjected to quality checks through the cumulative deviations test and the standard normal homogeneity test. Spatial rainfall variability was investigated using the spatial correlation function. Temporal trends were analysed using Mann?CKendall and linear regression methods. Heterogeneity of monthly rainfall was investigated using the precipitation concentration index (PCI). Finally, inter-annual and intra-annual rainfall variability were tested using normalized precipitation anomaly series of annual rainfall series (|AR|) and the PCI (|APCI|), respectively. The results showed that (1) most stations revealed statistically non-significant decreasing rainfall trends for annual, seasonal, monthly and the individual months from March to December at the 5% significance level. The months of January and February (the highest rainfall months), however, had overall positive but statistically non-significant trends countrywide, suggesting more concentration of the seasonal rainfall around these months. (2) Spatial analysis results showed a complex rainfall pattern countrywide with annual mean of 1,095?mm centred to the south of the country and mean inter-annual variability of 26%. (3) Spatial correlation amongst stations was highest only within the first 20?km, typical of areas with strong small-scale climatic influence. (4) The country was further characterised by unstable monthly rainfall regimes, with all PCIs more than 10. (5) An increase in inter-annual rainfall variability was found.     

成都地区降水时空分布变化

分析成都地区12个气象观测站50年（1960—2009年）逐日降水资料的时空分布变化规律得出：成都地区年降水量、汛期有雨日降雨强度、最大日降水量均呈现出逐渐下降的趋势。降水量主要集中在夏季,盛夏7、8两个月降水量占全年降水总量的47%;降水空间分布的主要类型为东—西走向,即降水量的地区分布趋势是西部多于东部;对降水量的M-K突变检验表明,大部分地方存在年降水总量的突变。     

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.     

Rainfall trends in the Brazilian Amazon Basin in the past eight decades

Rainfall series at 18 stations along the major rivers of the Brazilian Amazon Basin, having data since 1920s or 1930s, are analyzed to verify if there are appreciable long-term trends. Annual, rainy-season, and dry-season rainfalls are individually analyzed for each station and for the region as a whole. Some stations showed positive trends and some negative trends. The trends in the annual rainfall are significant at only six stations, five of which reporting increasing trends (Barcelos, Belem, Manaus, Rio Branco, and Soure stations) and just one (Itaituba station) reporting decreasing trend. The climatological values of rainfall before and after 1970 show significant differences at six stations (Barcelos, Belem, Benjamin Constant, Iaurete, Itaituba, and Soure). The region as a whole shows an insignificant and weak downward trend; therefore, we cannot affirm that the rainfall in the Brazilian Amazon basin is experiencing a significant change, except at a few individual stations. Subregions with upward and downward trends are interspersed in space from the far eastern Amazon to western Amazon. Most of the seasonal trends follow the annual trends, thus, indicating a certain consistency in the datasets and analysis.     

Analysis of mid-twentieth century rainfall trends and variability over southwestern Uganda

A methodology has been applied to investigate the spatial variability and trends existent in a mid-twentieth century climatic time series (for the period 1943–1977) recorded by 58 climatic stations in the Albert–Victoria water management area in Uganda. Data were subjected to quality checks before further processing. In the present work, temporal trends were analyzed using Mann–Kendall and linear regression methods. Heterogeneity of monthly rainfall was investigated using the precipitation concentration index (PCI). Results revealed that 53 % of stations have positive trends where 25 % are statistically significant and 45 % of stations have negative trends with 23 % being statistically significant. Very strong trends at 99 % significance level were revealed at 12 stations. Positive trends in January, February, and November at 40 stations were observed. The highest rainfall was recorded in April, while January, June, and July had the lowest rainfall. Spatial analysis results showed that stations close to Lake Victoria recorded high amounts of rainfall. Average annual coefficient of variability was 19 %, signifying low variability. Rainfall distribution is bimodal with maximums experienced in March–April–May and September–October–November seasons of the year. Analysis also revealed that PCI values showed a moderate to seasonal rainfall distribution. Spectral analysis of the time components reveals the existence of a major period around 3, 6, and 10 years. The 6- and 10-year period is a characteristic of September–October–November, March–April–May, and annual time series.     

A stochastic model for the analysis of maximum daily temperature

Accurately predicting precipitation trends is vital in the economic development of a country. Ground observed data from the Nigeria Meteorological Agency (NIMET) was analyzed to study the long-term spatio-temporal trends of rainfall on annual and seasonal scales for 23 stations in Nigeria during a 40-year period spanning from 1974 to 2013. After testing the presence of autocorrelation, Mann–Kendall (modified Mann–Kendall) test was applied to non-autocorrelated (autocorrelated) series to detect the trends in rainfall data. Theil and Sen’s slope estimator test was used to find the magnitude of change over a time period. Pettitt’s test, Standard Normal Homogeneity Test, and Buishand’s test were further used to test the homogeneity of the rainfall series. The results show an increasing trend in annual rainfall; however, only nine stations have a significant increase during the period of study. On the seasonal time scale, a significant increasing trend was observed in the pre- and post-monsoon seasons, while only nine stations show a significant increasing trend in monsoon rainfall and a significant decreasing trend in the winter rainfall over the last 40 years. During the study period, 15.4 and 13.90 % increase were estimated for annual and monsoonal rainfall, respectively. Furthermore, seven stations exhibit changes in mean rainfall while majority of the stations considered (Eighteen stations) exhibit homogeneous trends in annual and seasonal rainfall over the country. The performance of the different tests used in this study was consistent at the verified significance level.     

Recent disruptions in the timing and intensity of precipitation in Calakmul,Mexico

This study addresses changes in the timing and intensity of precipitation from 1982 to 2016 from three meteorological stations around Calakmul, Mexico, a landscape balancing biodiversity conservation and smallholder agricultural production. Five methods were used to assess changes in precipitation: the Mann-Kendall test of annual and wet season trends; a fuzzy-logic approach to determine the onset of the rainy season; the Gini Index and Precipitation Concentration Index (PCI) to evaluate the temporal distribution of precipitation; Simple Precipitation Intensity Index (SDII) to evaluate precipitation intensity; and the Rainfall Anomaly Index (RAI) to identify the deficit or surplus of rainfall compared with the long-term mean. Overall, rainfall trends in Calakmul over this period indicate a slight increase, though results of the indices (Gini, SDII, PCI) all indicate that rainfall has become more intense and more unevenly distributed throughout the year. There was no significant trend in the onset date of rainfall or the RAI overall, though there were more pronounced crests and troughs from 2004 to 2016. Higher interannual variability and more pronounced rainfall anomalies, both positive and negative, suggest that rainfall in the Calakmul region has become more extreme. This research informs for management and livelihood strategies in the local region and offers insights for analyses of regional patterns of seasonal precipitation events in tropical landscapes worldwide.     

甘肃雨养农业区降雨概率特征研究

利用甘肃雨养农业区 19个代表站点的 4 0a降雨量资料 ,结合weibull、gringorfen等概率统计分析的方法 ,对这一地区的降雨概率特征进行了研究 ,结果表明 ,甘肃雨养农业区各站年降雨量与其概率对数相关显著 ,可以利用所得关系式计算任一概率下的降雨量 ;各站年降雨量服从正态分布 ,也可用正态法求算任一概率下的降雨量 ;甘肃雨养农业区年平均有效降雨量理论上可以满足小麦生育期的作物需水量。     

Searching for evidence of changes in extreme rainfall indices in the Central Rift Valley of Ethiopia

Extreme rainfall events have serious implications for economic sectors with a close link to climate such as agriculture and food security. This holds true in the Central Rift Valley (CRV) of Ethiopia where communities rely on highly climate-sensitive rainfed subsistence farming for livelihoods. This study investigates changes in ten extreme rainfall indices over a period of 40 years (1970–2009) using 14 meteorological stations located in the CRV. The CRV consists of three landscape units: the valley floor, the escarpments, and the highlands all of which are considered in our data analysis. The Belg (March–May) and Kiremt (June–September) seasons are also considered in the analysis. The Mann-Kendall test was used to detect trends of the rainfall indices. The results indicated that at the annual time scale, more than half (57 %) of the stations showed significant trends in total wet-day precipitation (PRCPTOT) and heavy precipitation days (R10mm). Only 7–35 % of stations showed significant trends, for the other rainfall indices. Spatially, the valley floor received increasing annual rainfall while the escarpments and the highlands received decreasing annual rainfall over the last 40 years. During Belg, 50 % of the stations showed significant increases in the maximum number of consecutive dry days (CDD) in all parts of the CRV. However, most other rainfall indices during Belg showed no significant changes. During Kiremt, considering both significant and non-significant trends, almost all rainfall indices showed an increasing trend in the valley floor and a decreasing trend in the escarpment and highlands. During Belg and Kiremt, the CDD generally showed increasing tendency in the CRV.

     

Trends in the annual extreme rainfall events of 1 to 3 days duration over India

Summary In this paper, the annual extreme rainfall series in the time scale of 1 to 3 days duration at 316 stations, well distributed over the Indian region, covering 80-years of rainfall data from 1901 to 1980 were analysed for trend and persistence using standard statistical tests. It has been found that the annual extreme rainfall records of most stations are free from trend and persistence. However, the extreme rainfall series at stations over the west coast north of 12°N and at some stations to the east of the Western Ghats over the central parts of the Peninsula showed a significant increasing trend at 95% level of confidence. Stations over the southern Peninsula and over the lower Ganga valley have been found to exhibit a decreasing trend at the same level of significance. The data series of the stations which showed trends were subjected to a 10-year moving average and the resulting smoothed series have been discussed. It may be said that this increasing or decreasing trend in the annual extreme rainfall events at a few places will have tremendous implications in the hydrologic studies and dam design projects.With 9 Figures     

Assessment of climate extremes in the Eastern Mediterranean

Summary Several seasonal and annual climate extreme indices have been calculated and their trends (over 1958 to 2000) analysed to identify possible changes in temperature- and precipitation-related climate extremes over the eastern Mediterranean region. The most significant temperature trends were revealed for summer, where both minimum and maximum temperature extremes show statistically significant warming trends. Increasing trends were also identified for an index of heatwave duration. Negative trends were found for the frequency of cold nights in winter and especially in summer. Precipitation indices highlighted more regional contrasts. The western part of the study region, which comprises the central Mediterranean and is represented by Italian stations, shows significant positive trends towards intense rainfall events and greater amounts of precipitation. In contrast, the eastern half showed negative trends in all precipitation indices indicating drier conditions in recent times. Significant positive trends were revealed for the index of maximum number of consecutive dry days, especially for stations in southern regions, particularly on the islands.Current affiliation: National Observatory of Athens, Athens, Greece.     

Monthly and daily precipitation trends in the Mediterranean (1950–2000)

Summary The aim of the paper lies in the identification of possible significant linear trends at monthly, seasonal and annual timescales in the Mediterranean during the second half of the 20th century. Monthly and daily records of 63 stations have been used to elaborate several precipitation indices: sum of daily precipitation (SDP) for rainfall >0.1 mm, >10 mm and >95^th percentile, of number of rainy days (RD) >0.1 mm and >10 mm and of mean daily precipitation (MDP) >0.1 mm and >10 mm. For each index the stations have been gathered together by Rotated Principal Component Analyses to determine 8 sub-areas which can be considered as identical for all the timescales at the spatial scale of the research. Trends have been estimated from the scores of each eigenvector retained in all RPCAs. They are mainly non existant or non significant decreasing, even if a few monthly trends appear to be significantly diminishing, primarily during winter months, March in the Atlantic region, October in the Mediterranean Spain, December in the Lions and Genoa Gulfs, January, winter and the year in Greece, winter and the year in Italy and winter in the Near East and increasing in April in the two gulfs. Correlation coefficients between SDP>0.1 mm and other indices have been computed: the significant trends seem mainly related to RD>10 mm, which represents a high percentage of the total rainfall amount. Greece is remarkable: SDP>0.1 mm and >10 mm decrease significantly during January, winter, the rainy season and the entire year whereas SDP>95^th percentile increases significantly, in accordance with the climatic change scenarios for the end of this century as does the decreasing of the total monthly and seasonal rainfall.     

江苏降水长期趋势及年代际变化空间差异分析

根据江苏省60个气象站1961~2001年的逐月降水量资料，计算了逐月、季和年降水量距平百分率（RAP），以此研究了江苏降水的长期趋势和年代际变化特征及其空间差异。结果表明:全省平均降水量1、3、6月有显著的增多趋势，而4、9两月有显著的减少趋势；年降水量，南部增多，而北部减少；春季降水量大部分地区减少，夏季降水量主要是南部增多，北部减少，秋季大部分地区降水量减少，冬季全省降水量增多。4个年代年RAP符号变化，在江苏南部呈“--++”型，北部为“++--”型，中部则呈“+--+”、“+-+-”等过渡型。春季则在北方呈“-+-+”型，中部呈“+--+”型，南部呈“+---”型，徐州和盐城地区主要为“++-+”型。夏季RAP符号，主要分布型由北到南依次为“++--”、“+-+-”、“+--+”、“-+-+”和“--++”。秋季RAP符号全省绝大多数台站为“+-+-”型。冬季RAP符号在东部和南部大片地区为“-+-+”型，而西部则主要为“-+++”、“--++”、“-+-+”和“---+”型混杂。     

Spatiotemporal variations in rainfall erosivity during the period of 1960–2011 in Guangdong Province,southern China

Rainfall erosivity, which shows a potential risk of soil loss caused by water erosion, is an important factor in soil erosion process. In consideration of the critical condition of soil erosion induced by rainfall in Guangdong Province of southern China, this study analyzed the spatial and temporal variations in rainfall erosivity based on daily rainfall data observed at 25 meteorological stations during the period of 1960–2011. The methods of global spatial autocorrelation, kriging interpolation, Mann–Kendall test, and continuous wavelet transform were used. Results revealed that the annual rainfall erosivity in Guangdong Province, which spatially varied with the maximum level observed in June, was classified as high erosivity with two peaks that occur in spring and summer. In the direction of south–north, mean annual rainfall erosivity, which showed significant relationships with mean annual rainfall and latitude, gradually decreased with the high values mainly distributed in the coastal area and the low values mainly occurring in the lowlands of northwestern Guangdong. Meanwhile, a significant positive spatial autocorrelation which implied a clustered pattern was observed for annual rainfall erosivity. The spatial distribution of seasonal rainfall erosivity exhibited clustering tendencies, except spring erosivity with Moran’s I and Z values of 0.1 and 1.04, respectively. The spatial distribution of monthly rainfall erosivity presented clustered patterns in January–March and July–October as well as random patterns in the remaining months. The temporal trend of mean rainfall erosivity in Guangdong Province showed no statistically significant trend at the annual, seasonal, and monthly scales. However, at each station, 1 out of 25 stations exhibited a statistically significant trend at the annual scale; 4 stations located around the Pearl River Delta presented significant trends in summer at the seasonal scale; significant trends were observed in March (increasing trends at 3 stations), June (increasing trends at 4 stations located in the Beijiang River Basin), and October (decreasing trends at 4 stations) at the monthly scale. In accordance with the mean annual rainfall over Guangdong Province, the mean annual rainfall erosivity showed two significant periodicities of 3–6 and 10–12 years at a confidence level of 95 %. In conclusion, the results of this study provide insights into the spatiotemporal variation in rainfall erosivity in Guangdong Province and support for agrolandscape planning and water and soil conservation efforts in this region.     

Rainfall uncertainty in the Mediterranean: time series, uncertainty, and extreme events

Temporal precipitation irregularities, extreme rainfall, or droughts represent great climate concerns and have major impacts on the natural environment. The present study focuses on 41 stations spread over the entire Mediterranean region. The datasets contain daily rainfall totals, with a median length of 56?years within the period of 1931?C2006. The study aims at detecting significant trends in the time series and the uncertainties of four parameters: annual rainfall total, number of rain spells, the rain-spells yields, and rainy season length. In addition, it aims to detect significant temporal changes in the occurrence of extreme events of these parameters. Several methodologies have been used in this study, and the main conclusion is that despite the general assumption of tremendous changes in the rainfall regime, no significant temporal trends or uncertainty trends were found in most of the stations, neither in their annual totals, their number of rain spells, and their rain-spell yields, nor in their rainy season length. However, in the few cases that a significant trend was detected, former years tended to be wetter, longer, and with more abundant rain spells, while the opposite is seen in the later years; and uncertainty, tends to increase more than to decrease.     

Iranian rainfall series analysis by means of nonparametric tests

The study of the trends and fluctuations in rainfall has received a great deal of attention, since changes in rainfall patterns may lead to floods or droughts. The objective of this study was to analyze the annual, seasonal, and monthly rainfall time series at seven rain gauge stations in the west of Iran for a 40-year period (from October 1969 to September 2009). The homogeneity of the rainfall data sets at the rain gauge stations was checked by using the cumulative deviations test. Three nonparametric tests, namely Kendall, Spearman, and Mann–Kendall, at the 95 % confidence level were used for the trend analysis and the Theil–Sen estimator was applied for determining the magnitudes of the trends. According to the homogeneity analysis, all of the rainfall series except the September series at Vasaj station were found to be homogeneous. The obtained results showed an insignificant trend in the annual and seasonal rainfall series at the majority of the considered stations. Moreover, only three significant trends were observed at the February rainfall of Aghajanbolaghi station, the November series of Vasaj station, and the March rainfall series of Khomigan station. The findings of this study on the temporal trends of rainfall can be implemented to improve the water resources strategies in the study region.     

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.

     

1961—2012年重庆市的降水特征分析

利用重庆市1961—2012年34个气象观测站的逐日降水资料,采用EOF分析、线性回归及相关分析的方法对重庆市的降水量时空特征、降水频数特征及降水强度特征进行诊断分析研究,并进行了相关讨论.结果表明:重庆市的年总降水量呈逐年减少的变化特征,并且年总降水量存在空间一致性与重庆市东北地区和其他地区反相变化的空间分布形式;各类持续性降水过程频数的空间分布差异较大,持续性降水过程频数的变化趋势表明短期降水过程(持续2 d)逐年增加而持续较长时间(持续5 d及以上)的连阴雨天气过程减少趋势明显;降水强度分析中发现一般降水(小雨、中雨、大雨)的年总降水量呈下降趋势,是引起重庆市年总降水量减少的主要原因,小雨、中雨降水强度逐年减弱而大雨的强度有弱的增强,较强降水等级(暴雨与大暴雨)的年总降水量呈较弱的上升趋势,降水强度也表现为弱的增强趋势;持续5 d及以上降水过程频数的减少可能与当地500 hPa位势高度场的上升及赤道太平洋海表温度的升高相关,大雨及以上等级降水的强度变化可能与El Niño Modoki现象有关.