In-depth investigation of precipitation-based climate change and cyclic variation in different climatic zones

Climate change and cyclic variation are investigated based on station data of 61 years (1951–2011), representing twelve climatic zones in Iran. Climate change is investigated by applying the non-parametric Mann–Kendall test and the three-dimensional loglinear model to the12-month SPI time series, and by applying the likelihood ratio test to precipitation time series. Cyclic variation is studied by applying the three-dimensional loglinear model to the 12-month SPI time series. Analysis included entire data period, two sub-periods [(1951–1981), (1982–2011)] and three sub-periods [(1951–1971), (1972–1991), (1992–2011)]. The Mann–Kendall test results indicated combinations of different trend behaviors, whereby climate change could not be evaluated. The likelihood ratio test did not confirm climate change (at 95 % confidence level), in most of the studied stations. However, the more in-depth analysis by the three-dimensional loglinear model, i.e., detection of significant differences among drought frequencies, did not confirm climate change (at 95 % confidence level), in any of the studied stations. Cyclic variation was not confirmed by the three-dimensional loglinear model (at 95 % confidence level), in any of the studied stations. The findings of this research illustrate the need for meticulous techniques like the three-dimensional loglinear model, as a necessary tool for climate change and cyclic variation studies.     

Long-term trend and variability of precipitation in Chhattisgarh State,India

Spatial and temporal precipitation variability in Chhattisgarh State in India was examined by using monthly precipitation data for 102 years (1901–2002) from 16 stations. The homogeneity of precipitation data was evaluated by the double-mass curve approach and the presence of serial correlation by lag-1 autocorrelation coefficient. Linear regression analysis, the conventional Mann–Kendall (MK) test, and Spearman’s rho were employed to identify trends and Sen’s slope to estimate the slope of trend line. The coefficient of variation (CV) was used to analyze precipitation variability. Spatial interpolation was done by a Kriging process using ArcGIS 9.3. Results of both parametric and non-parametric tests and trend tests showed that at 5 % significance level, annual precipitation exhibited a decreasing trend at all stations except Bilaspur and Dantewada. For both annual and monsoon precipitation, Sen’s test showed a decreasing trend for all stations, except Bilaspur and Dantewada. The highest percentage of variability was observed in winter precipitation (88.75 %) and minimum percentage variability in annual series (14.01 %) over the 102-year periods.     

Detecting climate change signals in Saudi Arabia using mean annual surface air temperatures

Climate change signals in Saudi Arabia are investigated using the surface air temperature (SAT) data of 19 meteorological stations, well distributed across the country. Analyses are performed using cumulative sum, cumulative annual mean, and the Mann–Kendall rank statistical test for the period of 1978–2010. A notable change in SAT for the majority of stations is found around 1997. The results show a negative temperature trend (cooling) for all stations during the first period (1978–1997), followed by a positive trend (warming) in the second period (1998–2010) with reference to the entire period of analysis. The Mann–Kendall test confirms that there is no abrupt cooling at any station during the analysis period, reflecting the warming trend across the country. The warming trend is found to be 0.06 °C/year, while the cooling trend is 0.03 °C/year, which are statistically significant.     

Recent trends in regional air temperature and precipitation and links to global climate change in the Maharlo watershed,Southwestern Iran

Trends in air temperature and precipitation data are investigated for linkages to global warming and climate change. After checking for serial correlation with trend-free pre-whitening procedure, the Mann–Kendall test is used to detect monotonic trends and the Mann–Whitney test is used for trend step change. The case study is Maharlo watershed, Southwestern Iran, representing a semi-arid environment. Data are for the 1951–2011 period, from four temperature sites and seven precipitation sites. A homogeneity test investigates regional similarity of the time series data. The results include mean annual, mean annual maximum and minimum and seasonal analysis of air temperature and precipitation data. Mean annual temperature results indicate an increasing trend, while a non-significant trend in precipitation is observed in all the stations. Furthermore, significant phase change was detected in mean annual air temperature trend of Shiraz station in 1977, indicating decreasing trend during 1951–1976 and increasing trend during 1977–2011. The annual precipitation analysis for Shiraz shows a non-significant decrease during 1951–1976 and 1977–2011. The result of homogeneity test reveals that the studied stations form one homogeneous region. While air temperature trends appear as regional linkage to global warming/global climate change, more definite outcome requires analysis of longer time series data on precipitation and air temperature.     

Streamflow trend analysis by considering autocorrelation structure,long-term persistence,and Hurst coefficient in a semi-arid region of Iran

Due to the substantial decrease of water resources as well as the increase in demand and climate change phenomenon, analyzing the trend of hydrological parameters is of paramount importance. In the present study, investigations were carried out to identify the trends in streamflow at 20 hydrometric stations and 11 rainfall gauging stations located in Karkheh River Basin (KRB), Iran, in monthly, seasonal, and annual time scales during the last 38 years from 1974 to 2011. This study has been conducted using two versions of Mann–Kendall tests, including (i) Mann–Kendall test by considering all the significant autocorrelation structure (MK3) and (ii) Mann–Kendall test by considering LTP and Hurst coefficient (MK4). The results indicate that the KRB streamflow trend (using both test versions) has decreased in all three time scales. There is a significant decreasing trend in 78 and 73 % of the monthly cases using the MK3 and MK4 tests, respectively, while these percentages changed to 80 and 70 % on seasonal and annual time scales, respectively. Investigation of the trend line slope using Theil–Sen’s estimator showed a negative trend in all three time scales. The use of MK4 test instead of the MK3 test has caused a decrease in the significance level of Mann–Kendall Z-statistic values. The results of the precipitation trends indicate both increasing and decreasing trends. Also, the correlation between the area average streamflow and precipitation shows a strong correlation in annual time scale in the KRB.     

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.     

Quantifying the effects of climate variability and human activities on runoff for Kaidu River Basin in arid region of northwest China

Much attention has recently been focused on the effects that climate variability and human activities have had on runoff. In this study, data from the Kaidu River Basin in the arid region of northwest China were analyzed to investigate changes in annual runoff during the period of 1960–2009. The nonparametric Mann–Kendall test and the Mann–Kendall–Sneyers test were used to identify trend and step change point in the annual runoff. It was found that the basin had a significant increasing trend in annual runoff. Step change point in annual runoff was identified in the basin, which occurred in the year around 1993 dividing the long-term runoff series into a natural period (1960–1993) and a human-induced period (1994–2009). Then, the hydrologic sensitivity analysis method was employed to evaluate the effects of climate variability and human activities on mean annual runoff for the human-induced period based on precipitation and potential evapotranspiration. In 1994–2009, climate variability was the main factor that increased runoff with contribution of 90.5 %, while the increasing percentage due to human activities only accounted for 9.5 %, showing that runoff in the Kaidu River Basin is more sensitive to climate variability than human activities. This study quantitatively distinguishes the effects between climate variability and human activities on runoff, which can do duty for a reference for regional water resources assessment and management.     

Annual and seasonal variability of precipitation in Vojvodina,Serbia

Annual and seasonal variability of precipitation observed at 92 stations in Vojvodina (Serbia) were analyzed during the period 1946–2006. The rainfall series were examined by means of the empirical orthogonal functions (EOF). The first set of singular vectors explains from 68.8 % (in summer) to 81.8 % (in winter) of the total variance. The temporal variability of the time series associated with the main EOF configurations (the principal components, PCs) was examined using the Mann–Kendall test and the spectral analysis. The time series of PC1 revealed decreasing trend in the winter and spring precipitation and increasing trend in the autumn, summer, and annual precipitation. The relationships between the first PC and circulation patterns, such as the North Atlantic Oscillation (NAO), the East Atlantic (EA) pattern, and East Atlantic/West Russia pattern, were also investigated. The PC1, displaying temporal behavior of the first mode, demonstrated evident correspondence with the NAO index in analysis of the annual, winter, and autumn precipitation. Power spectra of the PC1 show statistically significant oscillations of about 3.3 years for the spring precipitation and about 8 and 15 years for the winter precipitation. Comparisons with spectral analysis of authors for some regions in Europe, most of them in the Mediterranean domain, show that similar periodicities are detected.     

Trends of precipitation extremes during 1960–2008 in Xinjiang, the Northwest China

The spatial–temporal variability of the precipitation extremes defined by eight precipitation indices based on daily precipitation dataset was analyzed using the linear regression method and the Mann–Kendall test. The results indicate that increasing trends in the precipitation amount, rainy days, and the intensity of the extreme precipitation were identified at above 70 % of the total rain stations considered in this study, with more than 30 % of them were significant, while most stations show notable decreasing trend in the annual maximum consecutive no-rain days. Significantly increasing trends of the precipitation extremes are observed mainly in the northern Xinjiang and the north of the southern Xinjiang. Most extreme precipitation indices show a potential regime shift starting from the middle of 1980s. The magnitude of the trends is compatible with their pattern of spatial stability. The generally increasing trends in precipitation extremes are found in this study.     

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.     

Temperature and precipitation long-term trends and variations in the Ili-Balkhash Basin

This study analyzed the long-term trends and variations of temperature and precipitation on annual timescale in the Ili-Balkhash Basin (IBB), Kazakhstan. Some statistical tools were employed to detect any climate variations at four stations in the IBB during the period between 1936 and 2005. These methods included the Mann–Kendall trend test, the Theil–Sen approach, and the sequential Mann–Kendall test. The results showed that in temporal scale, the climate in the IBB has been becoming warmer and wetter in the past several decades as a whole. The annual mean temperature and the annual precipitation in the IBB showed an increasing trend since the 1970s and the 1940s, respectively. The significance of the annual mean temperature and annual precipitation trends in the IBB was tested at >95 % confidence level. The slope of the increasing trend of annual mean temperature ranges from 0.019 to 0.029 °C/year, and that of the annual precipitation ranges from 0.654 to 2.179 mm/year. In spatial scale, the multiyear mean values of temperature and precipitation are greater in the southern mountain region than those in the northern plain and hilly land area of the basin. The multiyear mean temperature decreases with the increasing latitudes, while increases with the increasing altitudes except for Karaganda; the multiyear mean precipitation increase with the increasing altitudes, while decreases centered with the Lake Balkhash from the surrounding area. The results may provide climatic backgrounds for solving the problems related to water sources of the IBB.     

Regional precipitation trend analysis at the Langat River Basin,Selangor, Malaysia

Various hydrological and meteorological variables such as rainfall and temperature have been affected by global climate change. Any change in the pattern of precipitation can have a significant impact on the availability of water resources, agriculture, and the ecosystem. Therefore, knowledge on rainfall trend is an important aspect of water resources management. In this study, the regional annual and seasonal precipitation trends at the Langat River Basin, Malaysia, for the period of 1982–2011 were examined at the 95 % level of significance using the regional average Mann–Kendall (RAMK) test and the regional average Mann–Kendall coupled with bootstrap (RAMK–bootstrap) method. In order to identify the homogeneous regions respectively for the annual and seasonal scales, firstly, at-site mean total annual and separately at-site mean total seasonal precipitation were spatialized into 5 km?×?5 km grids using the inverse distance weighting (IDW) algorithm. Next, the optimum number of homogeneous regions (clusters) is computed using the silhouette coefficient approach. Next, the homogeneous regions were formed using the K-mean clustering method. From the annual scale perspective, all three regions showed positive trends. However, the application of two methods at this scale showed a significant trend only in the region AC1. The region AC2 experienced a significant positive trend using only the RAMK test. On a seasonal scale, all regions showed insignificant trends, except the regions I1C1 and I1C2 in the Inter-Monsoon 1 (INT1) season which experienced significant upward trends. In addition, it was proven that the significance of trends has been affected by the existence of serial and spatial correlations.     

Interrelationship of rainfall,temperature and reference evapotranspiration trends and their net response to the climate change in Central India

The monthly rainfall data from 1901 to 2011 and maximum and minimum temperature data from 1901 to 2005 are used along with the reference evapotranspiration (ET₀) to analyze the climate trend of 45 stations of Madhya Pradesh. ET₀ is calculated by the Hargreaves method from 1901 to 2005 and the computed data is then used for trend analysis. The temporal variation and the spatial distribution of trend are studied for seasonal and annual series with the Mann-Kendall (MK) test and Sen’s estimator of slope. The percentage of change is used to find the rate of change in 111 years (rainfall) and 105 years (temperatures and ET₀). Interrelationships among these variables are analyzed to see the dependency of one variable on the other. The results indicate a decreasing rainfall and increasing temperatures and ET₀ trend. A similar pattern is noticeable in all seasons except for monsoon season in temperature and ET₀ trend analysis. The highest increase of temperature is noticed during post-monsoon and winter. Rainfall shows a notable decrease in the monsoon season. The entire state of Madhya Pradesh is considered as a single unit, and the calculation of overall net change in the amount of the rainfall, temperatures (maximum and minimum) and ET₀ is done to estimate the total loss or gain in monthly, seasonal and annual series. The results show net loss or deficit in the amount of rainfall and the net gain or excess in the temperature and ET₀ amount.     

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.     

Precipitation trends using in-situ and gridded datasets

Six in situ precipitation time series of varying time periods in the northwestern region and the Global Precipitation Climatology Centre (GPCC) v6 0.5° monthly dataset (1901–2010) were statistically examined for monotonic trends in Trinidad. The Pettit test was used to investigate the abrupt changes in the mean while the Mann–Kendall test was employed to assess the monotonic trends. It was found that three in situ stations and the six grids experienced abrupt changes in the rainfall patterns and that there was an apparent shift in the seasons. In addition, for five out of the six in situ stations no monotonic change was detected in the monthly, seasonal, and annual rainfall patterns. Gradual decreases were detected in the calculated weighted area average for five stations, the GPCCv6 dataset and St. Ann’s time series. The GPCCv6 data indicated that the dry season in the southern Trinidad is becoming drier. Results also suggested that the range between the greatest and lowest recorded rainfall values for some months have increased while others decreased. The gridded dataset appears to give a good representation of the dry season (January to May) rainfall compared with the wet season (June to December) and was found to be negatively biased for the north-western region but may not necessarily be so for the entire island. The results suggested that in the north-western region mirco-climates may exist. It is recommended that further investigations are needed using in situ data.     

Observed spatiotemporal characteristics of drought on various time scales over the Czech Republic

This paper analyses the observed spatiotemporal characteristics of drought in the Czech Republic during the growing season (April to September) as quantified using the Standardised Precipitation Evapotranspiration Index (SPEI) on various time scales. The SPEI was calculated for various lags (1, 3, 6, 12, and 24 months) from monthly records of mean temperature and precipitation totals using a dense network of 184 climatological stations for the period 1961–2010. The characteristics of drought were analysed in terms of the temporal evolution of the SPEI, the frequency distribution and duration of drought at the country level, and for three regions delimited by station altitude. The driest and the wettest years during the growing season were identified. The frequency distribution of the SPEI values for seven drought category classes (in per cent) indicates that normal moisture conditions represent approximately 65 % of the total SPEI values for all time scales in all three regions, whereas moderate drought and moderate wet conditions are almost equally distributed around 10.5 %. Differences in extremely dry conditions (5 %) compared with extremely wet conditions (1.5 %) were observed with increasing SPEI time scales. The results of the non-parametric Mann–Kendall trend test applied to the SPEI series indicate prevailing negative trends (drought) at the majority of the stations. The percentage of stations displaying a significant negative trend for the 90, 95, 99, and 99.9 % confidence levels is approximately 40 %. An Empirical Orthogonal Functions (EOF) analysis was used to identify the principal patterns of variability of the SPEI during the growing season that accounted for the highest amount of statistical variance. The variance explained by the leading EOF range 66 to 56 %, whereas for EOF2 and EOF3, the value is between 7 and 11 % and between 4 and 7 %, respectively, for the SPEI is calculated for 1- to 24-month lags.     

Streamflow drought severity analysis by percent of normal index (PNI) in northwest Iran

The streamflow drought is the most important type of drought due to the high dependence of many activities on surface water resources. The streamflow drought severity was identified by the percent of normal index (PNI) in the western basins of the Lake Urmia located in northwest Iran. The streamflow records were obtained from 14 hydrometric stations for the period October 1975–September 2009. The temporal trends of the streamflow drought severity were detected by the parametric Student’s t test and the nonparametric Mann–Kendall and Sen’s tests. The worst streamflow droughts at almost all the stations occurred in 1999–2000 and 2000–2001. The streamflow drought severity based on the PNI increased during the last 34 years. The results also indicated that the temporal dependency of time series had a dominant role in detecting trend by the parametric Student’s t test.     

Climate change in Turkey for the last half century

Climate change and its urban-induced bias in selected Turkish cities is studied with a quality controlled temperature and precipitation data of Turkish stations in the period of 1950–2004. These stations are classified into two groups according to their populations; S1, including rural and suburban stations and S2, including large urban stations. Moving average signals, 365-day, and their digital low pass filtered versions are produced to eliminate the short term fluctuations and examine the possible trends or anomalies in climate data. Furthermore, ‘relative difference’ signals are introduced and applied to temperature and precipitation series to observe the actual local changes in the climate data independent from large-scale effects. Mann–Kendall test statistics are calculated for maximum, minimum, mean temperature and precipitation series and plotted on maps to determine any spatial trend patterns. Signal analysis show a cool period extending from early 1960s till 1993, generally with the lowest temperature values on 1992–1993 owing to the eruption of Mount Pinatubo. A last decade significant warming trend is observed in both of the series, S1 and S2, leading to 2000–2002 temperatures to be recorded as maximums in record history. The variability of urban precipitation series is generally larger than the rural ones, suggesting that urban stations can experience more frequent and severe droughts and floods. Though not significant, an increase in the urban precipitation compared to the rural one is also found. Spatial analysis resulted in significant warming in southern and southeastern parts of the country. Particularly, minimum temperature series show significant warming in almost all of the regions indicating the effect of urbanization. Significant decreases of precipitation amounts in the western parts of Turkey, such as Aegean and Trachea regions, are found. On the other hand, some Turkish northern stations show increases in precipitation of which some are significant.     

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.     

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.