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     

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.     

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.     

Change trends of air temperature and precipitation over Shanxi Province, China

A dataset of air temperature and precipitation time series (1959?C2008) from 61 stations across Shanxi, China is used to analyze the climate change. The monotonic trends and step (abrupt) trends for annual and seasonal series data of mean air temperature and total precipitation are tested by using Mann?CKendall test and Mann?CWhitney test, respectively. The results show that annual mean air temperature has increased by 1.20°C during the past 50?years. Winter, spring, and autumn have experienced a significant increase in air temperature. The step trend for annual mean air temperature is different from, but closely related with, those for seasonal mean air temperature. Spatially, there is an enhanced warming trend from south to north in Shanxi, and the most remarkable warming occurs in northern Shanxi. Annual precipitation has decreased by 99.20?mm during the past half century. The decrease is mainly caused by precipitation decline in rainy season (June?CSeptember), though precipitation in post-rainy season (October?CNovember) also tended to decrease. An abrupt decrease in precipitation has occurred since late 1970s. Decrease in precipitation is highest in central Shanxi and in the area along the west fringe between Sanchuan River and Fenhe River in western Shanxi.     

Trend analysis of winter rainfall over southern Québec and new Brunswick (Canada)

Abstract

Winter rainfall is a non‐negligible issue for urban drainage in Canada as it can generate significant flooding, especially when it occurs at the same time as high air temperature and in the presence of an appreciable snow cover. According to climate change scenarios, it is expected that the occurrence of these events will increase in a future climate. The purpose of this paper is to perform a trend analysis on six indices related to winter rainfall (January–February) at 60 weather stations located in southern Québec and New Brunswick (Canada) in order to detect possible trends in the frequency or intensity of winter rainfall events during the twentieth century. Datasets were provided by Environment Canada and come from the Canadian Daily Rehabilitated Precipitation Database. The bootstrap‐based Mann‐Kendall test is used to detect possible non‐stationarities in the dataset, while Sen's slope estimator is used to quantify the magnitude of the slope. Results show that 19 stations out of 60 present a significant trend (18 of them being positive) at a 5% level for winter (January–February) total rainfall. In most cases where a trend was detected for winter rainfall there was also an increase in the number of days with rainfall (42% of the stations). These results suggest that globally, for the region under study, rainfall during January and February was more likely to occur, often resulting in a significant increase in the total rainfall during these months. Increasing trends in maximum daily rainfall during January and February were also observed for 9 stations (15% of the stations). The spatial distribution of stations where significant trends were detected is consistent with the hypothesis that trends in winter rainfall are more likely to be observed for stations located in the southern part of the region under study.     

Long-term changes in heat and moisture related to corn production on the Canadian Prairies

Long-term (approximately 80?years) daily climate records at 12 weather stations across the agricultural production region of the Canadian Prairies were assessed to evaluate trends in seasonal heat units and moisture characteristics for corn (Zea mays). Crop water demand (CWD) and crop water deficit were modelled at each station. Growing season accumulation of these as well as corn heat units (CHU) and rainfall were tested for long-term trends using linear regression. Significant positive trends in CHU were present in the southernmost stations while the northern stations displayed no trend or significant negative trends. Growing season precipitation showed a significant increase on average and most stations showed a positive trend but only one station showed a significant positive trend. CWD declined at most stations with significant negative trends at seven stations. Crop water deficient also declined with significant negative trends at six stations. The spatial variation in these results and those reported in other studies in the region underscores the difficulty involved in forecasting future trends in agroclimatic conditions.     

西藏高原汛期降水类型的研究

利用西藏高原２６个测站２６年（１９７３￣１９９８年）汛期（５￣９月）降水量资料,采用主成分分析和旋转主成分分析方法,对高原汛期降水空间分布型进行了分析。结果表明,主成分分解得到的降水空间分布形式较为集中,前３个特征向量场的分布型具有十分明确的物理意义,可表示降水场部方差的６３．１４％。旋转主成分分解生前６个载荷向量的累积方差贡献达７６．６７％,可较好反映西藏高原汛期降水６个异常敏感区：东南部、东北     

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.     

Climate change in the Tahoe basin: regional trends, impacts and drivers

The purpose of this study was to quantify the decadal-scale time trends in air temperature, precipitation phase and intensity, spring snowmelt timing, and lake temperature in the Tahoe basin, and to relate the trends to large-scale regional climatic trends in the western USA. Temperature data for six long-term weather stations in the Tahoe region were analyzed for trends in annual and monthly means of maximum and minimum daily temperature. Precipitation data at Tahoe City were analyzed for trends in phase (rain versus snow), decadal standard deviation, and intensity of rainfall. Daily streamflow data for nine gaging stations in and around the Tahoe basin were examined for trends in snowmelt timing, by two methods, and an existing record for the temperature of Lake Tahoe was updated. The results for the Tahoe basin, which contrast somewhat with the surrounding region, indicate strong upward trends in air temperature, a shift from snow to rain, a shift in snowmelt timing to earlier dates, increased rainfall intensity, increased interannual variability, and continued increase in the temperature of Lake Tahoe. Two hypotheses are suggested that may explain why the basin could be warming faster than surrounding regions. Continued warming in the Tahoe basin has important implications for efforts to manage biodiversity and maintain clarity of the lake.     

影响华北汛期降水的水汽输送过程

利用1951～2005年NCEP再分析资料和中国160站月降水资料,分析了华北汛期水汽输送的时空特征及其与降水的关系,发现不同水汽通道对华北降水的影响区域不同。华北的水汽输送也具有明显的年际变化,华北多雨年和少雨年的水汽通量分布有明显差异。EOF分析表明,在华北汛期多雨年,上述水汽通道有向华北地区的正异常水汽输送。华北汛期水汽主要来自亚洲季风水汽输送,其次是西风带的水汽输送,它们与降水具有相似的年代际变化。1970年代中期以后,季风的水汽输送显著减弱,西风带水汽输送的重要性相对增大,华北降水在1980年代初的突变与季风水汽输送1970年代中期的突变密切相关。     

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.     

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.     

Evaluating persistence and identifying trends and abrupt changes in monthly and annual rainfalls of a semi-arid region in Western India

In this study, 43-year (1965–2007) monthly and annual rainfall time series of ten rainfall stations in a semi-arid region of western India are analyzed by adopting three tests for testing normality and by applying autoregressive technique for exploring persistence. Gradual trends are identified by three tests, and their magnitudes are assessed by the Sen’s slope estimator. Also, abrupt changes are detected by using four tests and they are further confirmed by two tests. Box-whisker plots revealed that the rainfalls of June and September are right skewed for all the stations. The annual rainfalls of Bhinder, Dhariawad, and Gogunda stations are found considerably right skewed. The normality tests indicated that the rainfall of July does not deviate from the normal distribution at all the stations. However, the annual rainfall is found non-normal at five stations. The monthly rainfalls of June, July, and August have persistence respectively at three (Mavli, Salumber, and Sarada), two (Kherwara and Sarada), and one (Mavli) stations, whereas the annual rainfall has persistence at Girwa and Mavli stations. Significantly increasing trend is detected at Mavli in the rainfall of July and in the annual rainfall (p value?>?0.05), while the negative trend in August rainfall at Dhariawad is found significant (p value?>?0.10). This study revealed that the presence of serial correlation does not affect the performance of the Mann-Kendall test. Mean values of trend magnitudes for the rainfalls of June, July, August, and September are 0.3, 0.8, ?0.4, and 0.4 mm year^?1, respectively, and the overall mean value for the annual rainfall is 0.9 mm year^?1. It is found that the standard normal homogeneity test and the Pettitt test are biased towards the end of the series to locate a change point. Conversely, the Bayesian test has a tendency to look for a change point in the beginning of time series. Confirmed abrupt changes in the rainfall time series are found in the year 2003 (Bhinder) in June; years 1974 (Mavli) and 1989 (Dhariawad and Salumber) in July; years 1972 (Sarada), 1990 (Dhariawad), and 2003 (Mavli) in August; years 1977 (Dhariawad), 1991 (Sarada), and 2004 (Kotra) in September; and in the year 1972 (Mavli and Sarada stations) in the annual series. It is emphasized that the significantly increasing trend of rainfall may have linkages with climate change and/or variability. Finally, this study recommends use of multiple statistical tests for analyzing hydrologic time series in order to ensure reliable decisions.     

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     

赤峰地区近50a气候变化诊断分析

利用线性回归、累积距平和多项式回归法,对赤峰地区1951—1990年12个气象台站的月、季、年平均气温、最高气温、最低气温序列进行连续性变化趋势分析,确定该区域的气候变化趋势。应用Mann-Kendall法和滑动t检验法检验气温序列变化的不连续性,确定突变时间。结果表明:赤峰地区12个月的平均气温均有升温趋势,增温幅度从0.56℃/10a到0.15℃/10a,其中2月份最强。季节增温最显著的是冬季,其次是秋季和春季,夏季最弱。年平均气温增温率是0.28℃/10a,1988年是变暖的第一年,突变时间在1993年;年平均最低气温增温率是0.29℃/10a,1988年是变暖的第一年,突变时间在1988年;年平均最高气温增温率是0.26℃/10a,1993年是变暖的第一年,突变时间在1993—1996年附近;平均最低气温和最高气温的变暖时间具有不对称性。     

国华北地区汛期降水变化趋势的初步预测

根据华北地区18个代表站1951－1999年月降水资料，利用回归分析研究了华北地区汛期降水的长期变化特征，并从海洋对气候的影响出发，运用基于均生函数的生主成分建模方案对华北地区汛期降水的长期变化趋势进行了初步预测。结果表明：华北地区汛期降水的长期变化具有明显的地域性；在1951－1999年的49a间，华北I区汛期降水量减少了近64mm，而华北Ⅱ区则减少了119mm，华北I区汛期降水从偏多（少）到偏少（多）的转换期约为17a，而华北Ⅱ区约为20a。预测结果指出：1999－2008年的10a间，华北地区汛期降水的长期变化具有明显的地域性；在1951－1999年的49a间，华北I区汛期降水量减少了64mm，而华北Ⅱ区则减少了119mm；华北Ⅰ区汛期降水从偏多（少）到偏少（多）的转换期约为17a，而华北Ⅱ区约20a。预测结果指出：1999－2008年的10a间，华北地区汛期降水基本处于其多年平均状态，即不会出现明显的干旱现象。     

Calibration of TRMM rainfall climatology over Saudi Arabia during 1998–2009

The short-term rainfall climatology regime over Saudi Arabia is obtained from the Tropical Rainfall Measuring Mission (TRMM) data for the period 1998–2009. The TRMM rainfall amounts are calibrated with respect to the rain-gauge data recorded at 29 stations across the country. Day-to-day rainfall comparisons show that the TRMM rainfall trends are very similar to the observed data trends, even if a general overestimation in the satellite products must be highlighted. Besides, especially during the wet season, some of the TRMM algorithm runs tend to underestimate the retrieved rainfalls. The TRMM rainfall data also closely follow the observed annual cycle on a monthly scale. The correlation coefficient for rainfall between the TRMM and the rain-gauge data is about 0.90, with a 99% level of significance on the monthly scale.The spatio-temporal distributions of rainfall over Saudi Arabia are analyzed. Besides the four conventional seasons, this analysis consider the wet (November–April) and dry (June–September) seasons, based on the rainfall amounts recorded. Spring is the highest and winter is the second highest rainfall-occurring season, resulting in large amounts of rainfall during the wet season over most of the country. Regional variations in the rainfall climatology over Saudi Arabia are studied through defining four regions. The false alarm ratio, probability of detection, threat score, and skill score are calculated to evaluate the TRMM performance. The country's average annual rainfall measured by the TRMM is 89.42 mm, whereas the observed data is 82.29 mm. Thus, the rainfall in Saudi Arabia is suggested as being the TRMM value multiplied by 0.93 plus 0.04. After this calibration, the TRMM-measured rainfall is almost 100% of the observed data, thereby confirming that TRMM data may be used in a variety of water-related applications in Saudi Arabia.     

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.     

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.     

Shift changes and monotonic trends in autocorrelated temperature series over Iran

Temperature data from 29 synoptic stations in Iran for a period of 40?years (1966–2005) were analyzed to test for the existence of monotonic trends and shift changes in the annual, seasonal, and monthly mean air temperature series using the Mann–Kendall and Mann–Whitney tests. The influences of significant lag-1 serial correlation were eliminated from data by the trend-free pre-whitening method prior to the trend analysis. The magnitude of the temperature trends was derived from the Theil–Sen’s slope estimator. It was found that annual mean air temperature increased at 25 out of the 29 stations, of which 17 stations showed significant monotonic trends. The magnitude of the annual mean air temperature trends averagely was (+)0.224°C per decade. Most of the stations with the significant positive monotonic trends had a significant upward shift change. The analysis indicated that the change point year of the significant upward shift changes was 1972 for the whole stations except the coastal ones. Moreover, the strongest monotonic increasing trends and upward shift changes were observed in summer especially in August and September. The spatial analysis of the mean air temperature trends revealed the highest numbers of significant monotonic trends in the big cities of Iran. These findings provide more insights for better understanding of regional temperature behavior in the study area.