Geographic Variation in Growing Season Rainfall during three Decades in Nigeria Using Principal Component and Cluster Analyses

Summary  Reports of changes in the seasonal and annual rainfall in Nigeria suggests that a more detailed analyses of the geographic extent of these changes and of their impact on agriculture could be of value. Variation in the growing season (April to September) rainfall from stations across Nigeria was analysed over the 30-yr period, 1960–90. Regression analyses were used to examine long-term trends. Principal component and cluster analyses were used to group stations with similar trends in standardised seasonal rainfall. Mean accumulated standardised seasonal rainfall were used to examine short- and medium-term trends for each of the groups identified. Significant (P ≤ 0.05) decreases in rainy season rainfall were found at 8 stations mostly in the Guinea and arid/semi-arid savannas of northern Nigeria, whereas no station showed significant increases. Examination of the monthly (April through September) rainfall showed that only three – Kano, Sokoto and Potiskum in the arid/semi-arid savanna – of the twenty-three stations used in the analysis had declining rainfall trends for each of the months April to September and subsequently declining seasonal rainfall trends. However, 12 to 15 stations had consistently declining rainfall trends in atleast some but not all the growing season months. However, a similar pattern was not the case in terms of increasing rainfall trends, where only one to three stations had consistently increasing rainfall trends in some but not all of the months from April to September. Stations that showed increasing rainfall trends were in the southern parts of Nigeria. Six groups with similar patterns in standardised seasonal rainfall were identified by Principal Component and Cluster analyses. For most of the groups, the period from 1967 to 1973 was that of consistently below average seasonal rainfall. However, the timing and extent of the decline varied with location. Common to stations in four of the six groups was a negative trend in seasonal rainfall for the period considered. The geographic variation in seasonal rainfall trends has tremendous agricultural significance since there are indications that the reliability of the season is decreasing from the humid forest zone with positive seasonal trends to the arid/semi-arid savanna with significant negative seasonal trends. Received June 24, 1998 Revised December 18, 1998     

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.     

Monthly air temperature trends in Switzerland 1901–2000 and 1975–2004

Summary We analysed long-term temperature trends based on 12 homogenised series of monthly temperature data in Switzerland at elevations between 316 m.a.s.l. and 2490 m.a.s.l for the 20^th century (1901–2000) and for the last thirty years (1975–2004). Comparisons were made between these two periods, with changes standardised to decadal trends. Our results show mean decadal trends of +0.135 °C during the 20^th century and +0.57 °C based on the last three decades only. These trends are more than twice as high as the averaged temperature trends in the Northern Hemisphere. Most stations behave quite similarly, indicating that the increasing trends are linked to large-scale rather than local processes. Seasonal analyses show that the greatest temperature increase in the 1975–2004 period occurred during spring and summer whereas they were particularly weak in spring during the 20^th century. Recent temperature increases are as much related to increases in maximum temperatures as to increases in minimum temperature, a trend that was not apparent in the 1901–2000 period. The different seasonal warming rates may have important consequences for vegetation, natural disasters, human health, and energy consumption, amongst others. The strong increase in summer temperatures helps to explain the accelerated glacier retreat in the Alps since 1980. Authors’ addresses: Martine Rebetez, WSL Swiss Federal Research Institute, 1015 Lausanne, Switzerland; Michael Reinhard, Laboratory of Ecological Systems (ECOS), EPFL Swiss Federal Institute of Technology, 1015 Lausanne, Switzerland.     

Homogeneity tests and non-parametric analyses of tendencies in precipitation time series in Keszthely,Western Hungary

This study aims to investigate the precipitation trends in Keszthely (Western Hungary, Central Europe) through an examination of historical climate data covering the past almost one and a half centuries. Pettitt’s test for homogeneity was employed to detect change points in the time series of monthly, seasonal and annual precipitation records. Change points and monotonic trends were analysed separately in annual, seasonal and monthly time series of precipitation. While no break points could be detected in the annual precipitation series, a significant decreasing trend of 0.2–0.7 mm/year was highlighted statistically using the autocorrelated Mann-Kendall trend test. Significant change points were found in those time series in which significant tendencies had been detected in previous studies. These points fell in spring and winter for the seasonal series, and October for the monthly series. The question therefore arises of whether these trends are the result of a shift in the mean. The downward and upward shift in the mean in the case of spring and winter seasonal amounts, respectively, leads to a suspicion that changes in precipitation are also in progress in these seasons. The study concludes that homogeneity tests are of great importance in such analyses, because they may help to avoid false trend detections.     

北京市房山区大气污染物时空分布特征及气象影响因素分析

利用北京市房山区良乡镇和琉璃河镇内的区域自动气象站和环境监测站观测数据,对2013年至2015年PM_(2. 5)、PM_(10)、NO_2、SO_2、CO 5种大气污染物浓度变化特征进行了统计分析。结果显示,近3年来,两个镇综合污染物指数呈现逐年下降趋势,各污染物对房山区整体大气污染的贡献率从大至小依次为PM_(2. 5)、PM_(10)、SO_2、NO_2、CO,PM_(2. 5)已取代传统大气污染物SO_2成为房山区的主要大气污染贡献体。两个站点各污染物浓度均表现出明显的季节、月、日变化特征。在不同季节条件下,局地气象要素与污染天气发生概率之间有着很好的相关关系。因此,可根据气象要素分级方法找出各季节污染天气发生时最敏感的气象因素,为局地污染天气预报提供参考指标,也为防范空气污染、制定科学的综合管理措施提供科学参考。     

Long-term trend analysis for temperature in the Jinsha River Basin in China

On the basis of the mean annual and seasonal temperatures from 30 meteorological stations in the Jinsha River Basin (JRB) from 1961 to 2008, the temperature trends are analyzed by using Mann–Kendall test and linear trend analysis. There is an increasing trend in mean annual and seasonal temperatures during this period, and the increasing trends in winter seem more significant than those in the other three seasons. The mean annual temperature has increased by 0.0158°C/year during the last 48 years. There are more than 70% of stations exhibiting increasing trends for annual and seasonal temperatures. The increasing trends in the headwater and upper reaches are more dominant than those in the middle and lower reaches. The largest increase magnitude occurred in the low temperature area, while the largest decrease magnitude occurred in the high temperature area. The decreasing trends are mainly characterized for the maximum temperature time series, and summer is the only season showing a slight and insignificant increasing trend. All the time series showed a statistically significant increasing trend at the level of α?=?0.05 for the minimum temperature time series. As a whole, the increasing magnitude of the minimum temperature is significantly greater than the decreasing magnitude of the maximum temperature.     

Long-term rainfall characteristics in the Mzingwane catchment of south-western Zimbabwe

Rainfall characteristics during the annual rainy season are explored for the Mzingwane catchment of south-western Zimbabwe, for both historic period (1886–1906) and more recent times (1950–2015), based on available daily and monthly precipitation series. Annual and seasonal rainfall trends are determined using the modified Mann-Kendall test, magnitude of trends test and Sen’s slope estimator. Rainfall variability is quantified using the coefficient of variation (CV), precipitation concentration index (PCI) and standard precipitation index (SPI). Results suggest that contemporary mean annual rainfall may not have changed from that measured during the historic period of 1886–1906. However, the number of rainy days (≥ 1 mm) has decreased by 34%, thus suggesting much more concentrated and increased rainfall intensity. A notable shift in both the onset and cessation dates of the rainy season is recorded, particularly during the twenty-first century, which has resulted in a significantly reduced (p < 0.05) length of the rainy season. The combination of a reduced number of rainy days (≥ 1 mm) and a shortened rainy season suggests that long intra-season dry spells have become more common through time and have considerable negative consequences for agriculture and wetland ecosystem in the region. In addition, high spatio-temporal rainfall variability and seasonal PCI values indicate strong seasonality in the rainy season. Based on the SPI results, the El Niño Southern Oscillation (ENSO) strongly influences rainfall variability. The results further suggest high uncertainty in rain season characteristics, which requires effective planning for water needs.     

Analysis of recent trends in mean maximum and minimum temperatures in a region of the NW of Spain (Castilla y León)

Summary The present paper is an analysis of mean maximum and minimum temperatures carried out on monthly, seasonal and annual time-scales examining the data collected at 171 meteorological stations over a region in the North West of Spain (Castilla y León) for the period 1961–1997. Various statistical tools were used to detect and describe significant trends in these data. The magnitude of the trends was derived from the slopes of the regression lines using the least squares method, and the statistical significance was determined by means of the non-parametric Mann-Kendall test. The pattern obtained is quite similar for mean maximum and minimum temperatures with increases in all months of the year, and in the annual series. The seasonal series corresponding to winter and summer also followed this same pattern. Spring and autumn were found to be more irregular. Because maximum temperature increased at a higher rate than minimum temperature in this period, an increase in the annual diurnal temperature range (DTR) was observed. The correlation between the North Atlantic Oscillation (NAO) and the regional maximum and minimum temperatures and DTR series for the period 1961–1997 have also be studied in this paper.     

南海海洋观测台站海表温度资料的均一性检验与订正

采用最大惩罚T检验（Penalized Maximum T Test,PMT）方法,结合海洋台站元数据信息,选取临近气象站做为参考站,对中国南海9个海洋观测台站月平均SST资料序列进行均一性检验,在充分考虑区域性气候变化因素的影响下,对检验结果进行气候合理性分析并对不连续点进行订正。结果表明:（1）通过多种数据的相关性比较和分析发现,临近气象站的气温资料序列是南海台站SST资料订正最优的参考序列;（2）平均每个海洋台站SST资料序列存在1~2个不连续点,其中站址变迁、仪器变更和环境变化对均一性的影响较大;（3）订正后的南海SST序列质量有大幅提高,表明南海SST具有更明显的增暖趋势。      

基于SPI的1961－2020年昌吉地区作物生长季气象干旱时空特征研究

基于昌吉地区7个气象站1961－2020年降水量资料，计算昌吉地区作物生长季标准化降水指数（SPI-7）。运用趋势分析法、M-K突变检验法和小波分析法探究了昌吉地区作物生长季SPI-7指数的年际和年代变化特征；在此基础上分析了作物生长季干旱的站次比和干旱强度的年际变化,并结合该区实际发生的旱灾对SPI进行了验证。结果表明：1961—2020年昌吉地区作物生长季标准化降水指数以0.08/10 a的速率呈微弱的正趋势（变湿），在年代变化趋势中呈现出变干-变湿-变干的变化波动, 1981年标准化降水指数由低到高突变；干旱强度呈增加趋势，干旱发生的区域面积有轻微减少的趋势；干旱强度在全区范围内主要为轻旱和中旱等级，并表现为全域性干旱和区域性干旱；空间分布上看干旱率最高区域在东部地区，轻旱主要集中在东部，中旱、重旱和特旱集中在西部地区，干旱强度大的区域大致分布在西部地区；在周期性变化方面，SPI指数存在着6年、9年、16年周期震荡；历史旱灾与SPI指数干旱评价结果吻合率较高，SPI指数在昌吉地区作物生长季的干旱监测与分析中具有较好的实用性。     

Recent Climate Change at the Upper Danube—A temporal and spatial analysis of temperature and precipitation time series

The following study investigates temperature and precipitation trends in instrumental time series between 1960 and 2006 at 88 meteorological stations located in the Upper Danube Basin. Time series were tested for inhomogeneities with several common homogeneity tests, trend magnitudes of annual and seasonal time series were calculated by least square fitting and the significance of trend values was checked and quantified by the Mann-Kendall test. The results confirm a particularly strong recent Climate Change in the investigation area. Increasing temperature trends show remarkably high trend values up to 0.8°C/decade in the summer season. The trends are highly significant for all investigated summer, spring and annual time series. Winter and spring temperature trends show consistently positive trend values as well even though some time series show no significance at all and the calculated trend values are smaller. Autumn temperature trends are mostly non-significant with low values (up to 0.3°C/decade) and several negative trends. Most of the highest trend values can be found in lower altitudes whereas stations situated in alpine regions tend to show low trend magnitudes and often exhibit non-significant results. Precipitation time series show positive as well as negative trends in the annual and seasonal analysis. At most stations a precipitation decrease in summer and autumn and an increase in winter was observed during the last 47?years whereas the spring and mean annual precipitation exhibits no change at all. But most time series are not conclusive since they show predominantly no significance and they often exhibit only low trend values.     

Detection Time for Plausible Changes in Annual Precipitation, Evapotranspiration, and Streamflow in Three Mississippi River Sub-Basins

We use diagnostic studies of off-line variable infiltration capacity (VIC) model simulations of terrestrial water budgets and 21st-century climate change simulations using the parallel climate model (PCM) to estimate the time required to detect predicted changes in annual precipitation (P), evapotranspiration (E), and discharge (Q) in three sub-basins of the Mississippi River Basin. Time series lengths on the order of 50–350 years are required to detect plausible P, E, and Q trends in the Missouri, Ohio, and Upper Mississippi River basins. Approximately 80–160, 50, and 140–350 years, respectively, are needed to detect the predicted P, E, and Q trends with a high degree of statistical confidence. These detection time estimates are based on conservative statistical criteria (α = 0.05 and β = 0.10) associated with low probability of both detecting a trend when it is not occurring (Type I error) and not detecting a trend when it is occurring (Type II error). The long detection times suggest that global-warming-induced changes in annual basin-wide hydro-climatic variables that may already be occurring in the three basins probably cannot yet be detected at this level of confidence. Furthermore, changes for some variables that may occur within the 21st century might not be detectable for many decades or until the following century – this may or may not be the case for individual recording station data. The long detection times for streamflow result from comparatively low signal-to-noise ratios in the annual time series. Finally, initial estimates suggest that faster detection of acceleration in the hydrological cycle may be possible using seasonal time series of appropriate hydro-climatic variables, rather than annual time series.     

Comparison of rainfall structures between NCEP/NCAR reanalyses and observed data over tropical Africa

 A comparison is made between modelled (NCEP/NCAR reanalysis) and observed (CRC and CRU dataset) annual and monthly precipitation over tropical Africa during the period 1958–1997. The split moving-windows dissimilarity analysis (SMWDA) is used to locate abrupt changes in rainfall time series. In the NCEP reanalysis data, we identify a main abrupt shift, which occurs in 1967 and concerns more than 50% of grid points. In the observation, this shift is only found over parts of tropical North Africa. Three other NCEP abrupt shifts (1975, 1983 and 1987) in the reanalysis shown by the SMWDA, each concerning about 20% of tropical Africa, are not identified in the observation. One hypothesis concerning the 1967 marked abrupt shift is a problem of data assimilation in the NCEP/NCAR model which generated artificial shifts in the time series. In view of this result, further comparisons have been restricted to the period 1968–1997. On a continental scale, while the CRC and NCEP mean seasonal rainfall patterns are almost the same, however, some regional features are not well reproduced. Using five regional rainfall indexes, the mean seasonal rainfall cycle is correctly reproduced, but the NCEP reanalysis generally underestimates the amounts during the rainy season. The NCEP reanalysis rainfall is closer to the observation when the region shows a single rainy season. The correlation values between NCEP and CRC interannual rainfall variations over the period 1968–1997 are very low and seldom significant. The NCEP four main structures of rainfall variability as deducted from rotated principal component analysis are not realistic at all and the associated time series are systematically dominated by a marked low-frequency variability not present in the observation. However, the main teleconnections between ENSO and African rainfall variations are fairly well reproduced, with a correct location of the main structures, but with lower correlation values than those found in the observation. Received: 22 September 1999 / Accepted: 10 May 2000     

塔克拉玛干沙漠腹地1961-1998年逐月平均气温序列的重建

 利用塔里木盆地周边27个气象站1961-2006年逐月平均气温和塔中气象站1999-2006年逐月平均气温资料,同时选取1961-2006年NCEP/NCAR 2.5°×2.5°经纬度距地表2 m的月平均气温再分析格点资料,分别用逐步回归分析、EOF分解和NCEP资料3种方法对塔中气象站1961-1998年历年逐月平均气温序列进行了恢复与重建,分析了误差,并与周边气象站的变化特征进行对比。结果表明,逐步回归和EOF法都能够作为重建塔中逐月平均气温的方法,但相对而言,逐步回归法重建的序列误差更小,平均拟合绝对误差为0.3℃,最大绝对误差为1.9℃。而NCEP/NCAR资料由于冬季存在明显的系统性误差,数值显著偏高,不能用于塔中气温序列的重建。     

Surface Air Temperature Variations in Italy: Recent Trends and an Update to 1993

Summary Historical series of monthly mean temperatures from 27 Italian stations, updated to 1993, are analysed. Building on previous analysis the following new results were obtained: there is an upward trend in seasonal and annual temperatures during the last 20 years; a positive trend, stronger at southern stations compared to northern stations, is apparent from 1920 to 1950, after when temperature shows no significant trend until 1985 when it starts to increase again. Data from Northern Italy show similar characteristics to a subset of data from a global climatic database, for the period 1881–1988. This comparison, however, suggests that good station coverage is important for the construction of a more detailed picture of seasonal climate variability. Received February 19, 1998 Revised July 13, 1998     

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.     

Trends of Minimum and Maximum Daily Temperatures in Italy from 1865 to 1996

Summary Annual and seasonal changes in maximum and minimum temperatures (Tmax and Tmin) and in daily temperature range (DTR) in Italy are investigated. Monthly average series for northern and southern Italy are analysed for evidence of trend. Tmax and Tmin show a positive trend over the period 1865–1996 which is greater in southern Italy than in northern Italy. DTR shows a positive trend, but greater in the North than in the South. There is a positive correlation between DTR and mean monthly temperature especially in spring and in summer, while there is a high significant negative correlation between DTR and monthly precipitation. Analysis of temperature, precipitation and DTR during the period 1865–1996 suggests that a general relationship between the very warm last 15–20 years and an increase in the frequency of sub-tropical anticyclones over the Central-Western Mediterranean. This relationship is based on the hypothesis that in Italy more frequent sub-tropical anticyclones could have been the most characteristic feature of the warm periods during the last 130 years. Received June 4, 1999 Revised November 2, 1999     

Changes of Accumulated Temperature, Growing Season and Precipitation in the North China Plain from 1961 to 2009

Using the high-quality observed meteorological data, changes of the thermal conditions and precipitation over the North China Plain from 1961 to 2009 were examined. Trends of accumulated temperature and negative temperature, growing season duration, as well as seasonal and annual rainfalls at 48 stations were analyzed. The results show that the accumulated temperature increased significantly by 348.5℃ day due to global warming during 1961-2009 while the absolute accumulated negative temperature decreased apparently by 175.3℃ day. The start of growing season displayed a significant negative trend of -14.3 days during 1961- 2009, but the end of growing season delayed insignificantly by 6.7 days. As a result, the length of growing season increased by 21.0 days. The annual and autumn rainfalls decreased slightly while summer rainfall and summer rainy days decreased significantly. In contrast, spring rainfall increased slightly without significant trends. All the results indicate that the thermal conditions were improved to benefit the crop growth over the North China Plain during 1961-2009, and the decreasing annual and summer rainfalls had no direct negative impact on the crop growth. But the decreasing summer rainfall was likely to influence the water resources in North China, especially the underground water, reservoir water, as well as river runoff, which would have influenced the irrigation of agriculture.     

Long-range forecasting of seasonal air temperature using the time analog method

A method is proposed to forecast monthly mean anomalies of air temperature for three months of the moving season, on the basis of statistical analysis of a selected set of processes with temperature changes analogous to that in the initial season. The set of the analogous processes is used to reveal the most frequent values of temperature anomalies in their grouping by three equiprobable categories. The set of analyses for each station gives a field of predicted anomalies at the CIS area for every month of the season. The anomaly sign forecast verification is presented for 1981–2004.     

Testing for Trends in Data Unevenly Distributed in Time

Summary  The question discussed in this study is how to calculate linear trends in data that are not distributed evenly in time. This is examined with time series of ten climate elements at a single station, stratified according to a classification based on daily circulation patterns. Trends are calculated in three different ways: (i) from seasonal means, which is a common approach, (ii) from means of individual events, the event being defined as a sequence of days classified as one particular type, preceded and succeeded by another type, and (iii) from individual daily values. The most common method of estimating trend significance, i.e. the t-test of the Pearson correlation coefficient, has been shown to be applicable to seasonal and event-mean trends for all variables. For daily trends, the Monte Carlo test should be used instead. The daily, event-mean and seasonal trends differ from each other considerably for many combinations of climate variable and circulation type. The reason for this difference is identified. Received December 3, 1998 Revised June 21, 1999