Nonlinear dynamics of meteorological variables: multifractality and chaotic invariants in daily records from Pastaza, Ecuador

Weather represents the daily state of the atmosphere. It is usually considered as a chaotic nonlinear dynamical system. The objectives of the present study were (1) to investigate multifractal meteorological trends and rhythms at the Amazonian area of Ecuador and (2) to estimate some nonlinear invariants for describing the meteorological dynamics. Six meteorological variables were considered in the study. Datasets were collected on a daily basis from January 1st 2001 to January 1st 2005 (1,460 observations). Based on a new multifractal method, we found interesting fractal rhythms and trends of antipersistence patterns (Fractal Dimension >1.5). Nonlinear time series analyses rendered Lyapunov exponent spectra containing more than one positive Lyapunov exponent in some cases. This sort of hyperchaotic structures could explain, to some extent, larger fractal dimension values as the Kaplan–Yorke dimension was also in most cases larger than two. The maximum prediction time ranged from ξ?=?1.69 days (approximately 41 h) for E/P ratio to ξ?=?14.71 days for evaporation. Nonlinear dynamics analyses could be combined with multifractal studies for describing the time evolution of meteorological variables.     

Universal inverse power-law distribution for temperature and rainfall in the UK region

Meteorological parameters, such as temperature, rainfall, pressure, etc., exhibit selfsimilar space–time fractal fluctuations generic to dynamical systems in nature such as fluid flows, spread of forest fires, earthquakes, etc. The power spectra of fractal fluctuations display inverse power-law form signifying long-range correlations. A general systems theory model predicts universal inverse power-law form incorporating the golden mean for the fractal fluctuations. The model predicted distribution was compared with observed distribution of fractal fluctuations of all size scales (small, large and extreme values) in the historic month-wise temperature (maximum and minimum) and total rainfall for the four stations Oxford, Armagh, Durham and Stornoway in the UK region, for data periods ranging from 92 years to 160 years. For each parameter, the two cumulative probability distributions, namely c_max and c_min starting from respectively maximum and minimum data value were used. The results of the study show that (i) temperature distributions (maximum and minimum) follow model predicted distribution except for Stornowy, minimum temperature c_min. (ii) Rainfall distribution for c_min follow model predicted distribution for all the four stations. (iii) Rainfall distribution for c_max follows model predicted distribution for the two stations Armagh and Stornoway. The present study suggests that fractal fluctuations result from the superimposition of eddy continuum fluctuations.     

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.     

Climatic trends in the Amazonian area of Ecuador: Classical and multifractal analyses

The climate evolution and change in the Amazonian area is very important at least at a continental scale involving Latin America where more than 550 million people live. The objective of the present study was to investigate, from an environmental perspective, the climatic trends in the Amazonian area of continental Ecuador. We performed both classical and multifractal analyses of these trends on four climatic variables (maximum and minimum temperature, evaporation and evaporation/precipitation ratio). Data were collected from Puyo meteorological station, Pastaza Province, Ecuador. Data sets covered 31 years (from January 1974 to September 2005). Each time series consisted of 380 months.Piecewise regression analyses with breaking point showed two regimes with a cutoff ranging from t = 80 months (maximum and minimum temperature) to t = 133 months for the evaporation pattern (determination coefficient ≥ 0.979) while the multifractal analyses showed an increasing complexity within each climatic variable. All the considered climatic variables showed an increase since 1974 to approximately 1985. After that some type of smoother increase was observed.     

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.

     

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.     

Climate change and crop yields in the Indian Cardamom Hills, 1978–2007 CE

In this study we analyzed climate and crop yields data from Indian cardamom hills for the period 1978–2007 to investigate whether there were significant changes in weather elements, and if such changes have had significant impact on the production of spices and plantation crops. Spatial and temporal variations in air temperatures (maximum and minimum), rainfall and relative humidity are evident across stations. The mean air temperature increased significantly during the last 30?years; the greatest increase and the largest significant upward trend was observed in the daily temperature. The highest increase in minimum temperature was registered for June (0.37°C/18?years) at the Myladumpara station. December and January showed greater warming across the stations. Rainfall during the main monsoon months (June–September) showed a downward trend. Relative humidity showed increasing and decreasing trends, respectively, at the cardamom and tea growing tracts. The warming trend coupled with frequent wet and dry spells during the summer is likely to have a favorable effect on insect pests and disease causing organisms thereby pesticide consumption can go up both during excess rainfall and drought years. The incidence of many minor pest insects and disease pathogens has increased in the recent years of our study along with warming. Significant and slight increases in the yield of small cardamom (Elettaria cardamomum M.) and coffee (Coffea arabica), respectively, were noticed in the recent years.; however the improvement of yield in tea (Thea sinensis) and black pepper (Piper nigrum L.) has not been seen in our analysis.     

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.     

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.     

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.     

从时间序列中提取维数信息

作者介绍了分形和分维的概念、性质和意义，重点讨论了从一维序列中提取维数信息的，并给出了一些在天气了气候中的应用。     

Watershed-wide trend analysis of temperature characteristics in Karun-Dez watershed, southwestern Iran

Trend estimation of climatic characteristics for a watershed is required to determine developing compatible strategies related to design, development, and management of water resources. In this study, the trends of the annual maximum (T _max), minimum (T _min), and mean (T _mean) air temperature; temperature anomaly (T _anomaly); and diurnal temperature range (DTR) time series at 13 meteorological stations located in the Karun-Dez watershed were analyzed using the Mann–Kendall and linear regression trend tests. The pre-whitening method was used to eliminate the influence of serial correlation on the Mann–Kendall test. The result showed increasing trends in the T _min, T _mean, and T _anomaly series at the majority of stations and decreasing trend in the T _max and DTR series. A geographical analysis of the trends revealed a broad warming trend in most of the watershed, and the cooling trends were observed only in the southern parts. Furthermore, the geographical pattern of the trends in the T _mean and T _anomaly series was similar, and the T _max data did not show any dominant trend for the whole watershed. This study provides temperature change scenarios that may be used for the design of future water resource projects in the watershed.     

Falling Lake Victoria water levels: Is climate a contributing factor?

Recently, and perhaps most threatening, Lake Victoria water level has been receding at an alarming rate. A recent study suggested the possibility of the expanded hydroelectric power station in Uganda. However, since the lake receives 80% of its refill through direct rainfall and only 20% from the basin discharge, climatic contributions cannot be ignored, since the 80% water is directly dependant on it. It is therefore necessary to investigate climatic contribution to the declining Lake Victoria water level observed over a long period, i.e., 30 years. This contribution uses 30 years period anomalies for rainfall, river discharge and lake level changes of stations within Lake Victoria basin to analyse linear and cyclic trends of climate indicators in relation to Lake levels. Linear trend analysis using the Student’s t test indicate a decreasing pattern in rainfall anomalies, with the slope being statistically similar to those of water levels at both Kisumu, Maziba and Jinja stations for the same period of time (1976–1999), thus showing a strong correlation. On the other hand, cyclic trend analysis using Discrete Fourier Transform (DFT) shows cyclic period of water level to coincide with those of droughts and rainfall. The strong relationship between climatic indicators of drought and rainfall on one-hand and lake levels on the other hand signifies the need to incorporate climate information in predicting, monitoring and managing lake level changes.     

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.     

Trends, stability and stress in the Colombian Central Andes

Mountain ecosystems have been projected to experience faster rates of warming than surrounding lowlands. These changes in climatic conditions could have significant impacts on high-altitude Andean environments, affecting the quality and magnitude of their economic and environmental services. Even though long-term data in these regions are limited, it is important to identify any discernible long-term trends in local climatic conditions. Time series of several variables were analyzed to detect statistically significant long-term linear trends that occurred over recent years in a páramo ecosystem of the Colombian Central Andes. Records included cloud characteristics, sunshine, rainfall, minimum and maximum temperatures, diurnal temperature range, and relative humidity. Conditions of atmospheric stability were also explored. Total sunshine exhibited decreasing trends ranging from ?3.7 to ?8.5% per decade at altitudes around the pluviometric optimum. The strongest changes in sunshine occurred during the December-January-February season. Mean relative humidity observed at altitudes around and below this threshold showed increasing trends of +0.6 to +0.7% per decade. Annual rainfall and mean relative humidity above the optimum showed decreasing trends ranging from ?7 to ?11% per decade and from ?1.5 to ?3.6% per decade, respectively. Minimum temperatures on the coldest days and maximum temperatures on the warmest days exhibited increasing trends at all altitudes ranging from +0.1 to +0.6, and from +0.2 to +1.1°C per decade, respectively. Increases in minimum and maximum temperatures at higher altitudes were significantly greater than those observed in average at lower altitudes. The strongest changes in minimum temperatures, particularly, occurred during the December–January–February and June–July–August dry seasons. All these changes suggest that atmospheric conditions in the area are shifting from statically unstable conditions to conditionally unstable or statically stable conditions. Observed historical trends indicate that climate impacts and other human activities have stressed these unique and fragile environments.     

Variability of rainfall and effective onset and length of the monsoon season over a sub-humid climatic environment

The study has analyzed the variability and trends in monthly, seasonal and annual rainfall and rainy days of four locations over different agro-ecological zones of Bihar, namely Samastipur (zone-I), Madhepura (zone-II), Sabour (zone-IIIA) and Patna (zone-IIIB). The Mann–Kendall nonparametric test was employed for detection of statistical significance and slopes of the trend lines were determined using the method of least square linear fitting. The variability and trends of onset of effective monsoon and length of monsoon period were also analyzed using the same method. The mean annual rainfall varies from 1137 mm at Patna to 1219 mm at Sabour. July is the rainiest month in all the zones followed by August. Maximum increase in annual rainfall was found at Sabour (40.1% of mean/30 years at 95% confidence level) and minimum for Patna (10.1% of mean/30 years). Significant increasing trend of rainfall during July, August and September at rates of 41.9, 83.2, and 112.7% of the mean/30 years, respectively has been noticed at Madhepura. Analysis of rainy days indicates that rainy days increased during winter and annually for all the sites. The mean effective onset of monsoon varies from 18th June at Sabour to 28th June at Patna. The trends in the date of effective onset of monsoon indicate that the date tends to be early in all the sites except Madhepura. But a significant delayed trend in the onset at a rate of 2.8% of the mean/30 years has been observed for Madhepura. The early trend of the effective onset of monsoon and increasing trends of length of monsoon season have been observed for Samastipur, Sabour and Patna.     

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.     

Rainfall over Friuli-Venezia Giulia: High amounts and strong geographical gradients

Summary The precipitation distribution over Friuli-Venezia Giulia — the easternmost region of Northern Italy extending from the Adriatic Sea to the Alps — has been studied. Monthly rainfall data over the region and the bordering areas of Veneto and Slovenia during the period from 1951 to 1986 have been analyzed by standard statistical methods, including cluster analysis. The overall results emphasize a distribution with rainfall increasing from the sea to the prealpine areas. The highest precipitations were recorded over the Musi-Canin range, with average values exceeding 3 200 mm per year. Noteworthy is the unforeseen subdivision of the region by the clustering procedure by means of the Angot index.With 12 Figures     

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.     

Detection of long-term trends in monthly hydro-climatic series of Colombia through Empirical Mode Decomposition

We test for the existence of long-term trends in 25- to 50-year long series of monthly rainfall, average river discharges, and minimum air temperatures in Colombia. The Empirical Mode Decomposition method is used as a mathematical filter to decompose a given time series into a finite number of intrinsic mode functions, assuming the coexistence of different frequency oscillatory modes in the series, and that the residual captures the likely existing long-term trends. The Mann-Kendall test for autocorrelated data is used to assess the statistical significance of the identified trends, and the Sen test is used to quantify their magnitudes. Results show that 62 % of river discharge series exhibit significant decreasing trends between 0.01-1.92 m ³ s ^?1 per year, which are highly consistent downstream albeit with different ratios between the trend magnitudes and mean discharges. Most minimum temperature series (87 %) exhibit increasing trends (0.01-0.08 °Cyr ^?1). Results for precipitation series are inconclusive owing to the mixing between increasing trends (41 %, between 0.1-7.0 mm yr ^?1) and decreasing trends (44 %, between 0.1-7.4 mm yr ^?1), with no clear-cut geographical pattern, except for the increasing trend identified along the Pacific region, consistent with the increasing trend identified in the strength of the Chocó low-level wind jet off the Pacific coast of Colombia, an important moisture source of continental precipitation. Our results contribute to discerning between signals of climate change and climate variability in tropical South America.