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Adequate water resources management includes understanding patterns and spatiotemporal variability of precipitation, as this variable is determinant for ecosystems' stability, food security, and most human activities. Based on satellite estimations validated through ground measurements from 59 meteorological stations, the objective of this study is to evaluate the long-term spatiotemporal variability and trends of the average monthly precipitation in the Magdalena Department, Colombia, for the 1981-2018 period. This heterogeneous region comprises many different ecoregions in its 23,188 km² area. The analysis of spatial variability allowed for the determination of four different subregions based on the differences in the average values of precipitation and the degree of rainfall variability. The trend analysis indicates that the current rainfall patterns contradict previous estimates of a progressive decrease in annual averages due to climate change in the study region, as most of the department does not exhibit statistically significant trends, except for the Sierra Nevada de Santa Marta area, where this study found reductions between 10 mm yr-1 and 30 mm yr-1. The findings of this study also suggest the existence of some links between precipitation patterns with regional phenomena of climate variability and solar activity. [ABSTRACT FROM AUTHOR]

Hydropower accounts for 16.4% of world's electricity demand. The key element in hydropower generation is the runoff and this runoff totally depends on the precipitation. However, the future climate is predicted to be debatable and can severely affect the water resources around the world. Therefore, a critical question to answer by the research community is, what would be the impact of climate change/variability on hydropower development? Hence, this paper aims to study the impingement of climate change on hydropower generation for Denawaka Ganga mini-hydropower located in Ratnapura district, Sri Lanka. Multi-year rainfall trend analysis for 30 years along with power generation trend study for 6 years have been carried out to evaluate the performance of the hydropower station under possible shifting precipitation pattern. Mann–Kendall test and Sen's slope estimator tests were used to culminate the trend analysis. Seasonal and monthly trend analysis did not render negative trends (except one rain gauge) in rainfall. However, positive rainfall trends were found in several rain gauging stations for several months. Power generation trend study showcased a decreasing trend in electricity generation for January and November. Nevertheless, the results elucidate that the catchment area is not under an intense threat due to the climate variability. ROR: Run-of-river; SW: Southwestern; NE: Northeastern; SNHT: Standard Normal Homogeneity Test [ABSTRACT FROM AUTHOR]

ABSTRACT: Understanding the spatio‐temporal variability of rainfall over mountainous regions such as the Andes is crucial for the maintenance of water resources and ecosystems. This study provided a comprehensive analysis of the signal, statistical significance and spatial pattern of rainfall trends in central and southern Peruvian Andes (CSPA) from 1965 to 2010. Rainfall from 47 quality‐controlled rain gauge stations was examined using the hydrologic calendar year. Total and extreme rainfall indices proposed by the Expert Team on Climate Change Detection and Indices (ETCCDI) were calculated and trends were examined with Mann–Kendall test and Sen's slope estimator. Significant regional patterns of changes in rainfall extremes were investigated and compared with previous studies. Four major regions of stations were identified based on principal component analysis and clustering techniques: Amazon, central Pacific, southern Pacific and Titicaca basins. Statistically significant trend patterns showed that the annual total rainfall has decreased in the Amazon basin, despite the increase in the number of rainy days and some extreme rainfall indices. Decrease in 1‐day and 5‐day yearly maximum rainfall was observed in central Pacific, along with an increase in the number of wet days. Positive trends in indices related to the intensity of very strong daily rainfall were detected in southern Pacific. Titicaca basin showed an increase in the intensity of rainfall extremes. Rainfall variability and trends were evaluated during contrasting El Niño‐Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). Most stations in the CSPA exhibited positive (negative) anomaly of total and extreme rainfall indices (consecutive dry days) during La Niña (El Niño) years. Positive (negative) anomalies of annual total rainfall and consecutive dry days during positive (negative) PDO occurred in the Amazon, southern Pacific and Titicaca basins, respectively. The ENSO–PDO conditions may have influenced the complex and mostly non‐statistically significant long‐term trends in CSPA. [ABSTRACT FROM AUTHOR]

The aim of this study is to update the analysis of historical rainfall trends with reference to the work from previous studies, through optimizing the highest spatial resolution with the longest possible period of analysis, i.e., 1921-2015. Two interlinked datasets, namely the district rainfall and individual rainfall stations datasets were used for the trend analyses, namely, daily time series of 60 individual rainfall stations and the daily district rainfall of 88 of 94 rainfall districts in South Africa. The extreme precipitation indices defined by the World Meteorological Organization Expert Team on Climate Change Detection and Indices were applied. In general, the results show an increase in rainfall for most rainfall stations in the southern interior of South Africa, and indications of decreases in rainfall in the far northern and north-eastern parts. The increase in the annual rainfall in the south is reflected in the seasonal trends, where summer rainfall shows a similar increase, but also extends into the central interior. For other seasons, most of the country shows no significant historical trends in annual total rainfall. From the extreme rainfall analyses, an increase in daily rainfall extremes in the southern to western interior is apparent. Also, most of the country experienced increases in the intensity of daily rainfall, which confirms global results in general. Decreases in rainfall from wet spells were noted in most places over the east and north-east, while the southern and eastern parts along the escarpment experienced shorter annual dry spells. This study improves on previous studies in the region by more than doubling the analysis period, largely eliminating the influence that decadal-scale cycles might have on analyses over shorter periods. However, some differences in the trend results compared to previous studies are apparent, e.g., less pronounced drying in the east and the previously observed increase in rainfall in the western and southern interior not extending as far as the south-western Cape. The observed trends broadly confirm those of projected changes in summer rainfall, i.e., an increase in the west and decrease in the east. [ABSTRACT FROM AUTHOR]

Changes in the spatiotemporal patterns of precipitation have great impacts on drought/flood risk and utilization of water resources. In this study, we presented the results of a comparative analysis of spatial-temporal variability of precipitation in the Southwest China. The analysis investigated the trends of annual precipitation and explored the changes of two indices: the precipitation concentration index (PCI) and the concentration index (CI) which are designed for measuring seasonality and daily heterogeneity, respectively. The trends of annual precipitation and CI were tested by the Mann-Kendall method. The results show a significant seasonality of the rainfall distribution and very inhomogeneous temporal distribution of the daily rainfall in the study area. Positive trends in the CI were found at most stations, although most of them were not statistically significant. To detect the futures trends of precipitation in the study area, Hurst's rescaled range (R/S) analysis was introduced and the corresponding Hurst Exponent was estimated. The results suggested that some drought hazards will happen in the intersection of Sichuan, Guizhou and Yunnan, and the west part of Sichuan, the north part of Chongqing and the middle part of Yunnan are under the risk of flood in the future. [ABSTRACT FROM AUTHOR]

Understanding precipitation variations on various timescales and their correlations is important for assessment of flood risk and utilization of water resources. In this study, the spatial and temporal patterns of precipitation concentration in the upper reaches of the Huai River, China, were investigated using two indices: the precipitation concentration index (PCI) and the concentration index (CI) for measuring seasonality and daily heterogeneity using monthly and daily precipitation series, respectively. In particular, the trends of PCI and CI were tested by the Mann-Kendall method, and relationship among PCI, CI and percentage of precipitation contributed by the rainiest days was analyzed by the linear correlation analysis. The results show a significant seasonality of the rainfall distribution and very in homogeneous temporal distribution of the daily rainfall in the south part of the study area, especially in the three reservoirs. Positive trends in the PCI and CI were found at most stations, although none of the PCI trends were statistically significant. Daily heterogeneity of the rainfall in a year is highly correlated with the heavy rainfall amount of the 15 % rainiest days, and seasonality in rainfall distribution over a year can be partly explained by the daily rainfall heterogeneity. [ABSTRACT FROM AUTHOR]

The objective of this work is to study rainfall variability in different timescales in central Argentina. Rainfall trends were maximum in summer in the west of the study region, showing rainfall decrease in the west and recent period. 15, 23 and 30 years significant cycles were detected. The interannual summer rainfall variability was study in 3 sub-regions, based on the comparison of the atmospheric and oceanic variables behavior in years with deficit and excess of rainfall. The geopotential height was the best discriminator variable. Rainfall greater than normal was associated with the weakness of the Pacific heights and lows and the intensification of the Atlantic heights in the region next to the continent. The central Pacific Ocean water warming (positive phase of ENSO-El Niño Southern Oscillation) was another factor related to rainfall all over the area. A multiple linear regression model was developed and explained the 43,3% of the summer rainfall variance. [ABSTRACT FROM AUTHOR]

A new monthly precipitation database has been developed for conterminous provinces in Spain by exploiting the total amount of data available at Spanish Meteorological Agency (AEMET, formerly INM). The new MOPREDAS (monthly precipitation database of Spain) database has been constructed by using all 6821 original data series that have been recorded for at least 10 years. These provide a total of 2670 complete, homogeneous series for the period 1946-2005, and are the most complete and extensive monthly precipitation dataset available in Spain at present. MOPREDAS has been created with the aim of analysing the behaviour of precipitation in the conterminous provinces of Spain, and to help validate the downscaling of climate models on a detailed spatial level. To this end, the station data were also interpolated on a regular grid, at 1/10 of degree of resolution, over the whole Spain. Trend analysis confirms great spatial and temporal variability in the behaviour of precipitation across Spain. The monthly precipitation trends vary from month to month, from coherent spatial trend patterns in March, June (both with a general and significant negative trend) and October (general positive trends), to highly regionalized trend patterns in July (with positive trends in north-west and mainly negative in the remainder), February and April (positive and negative trends in the south-east, respectively). These results suggest that both global and local factors affect the spatial distribution of trends in the Iberian Peninsula. Mountain ranges seem to be the most significant geographical factor in determining the spatial distribution of monthly trends on a detailed, sub-regional spatial scale. These results show that it is possible to accurately delineate the areas affected by different precipitation trends if a dense spatial database is available. Copyright © 2010 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

The article presents a study which assesses the trends of seasonal rainfall and, the wet and dry season months in Bangladesh. The study uses Mann-Kendall trend test and Sen's slope method to observe the changes in precipitation in the country. Results show that the average rainfall in Bangladesh increase and the wet months of the country also increase. Result also show that annual rainfall in the country in the Sen's slope method indicates an increase at a rate of +5.525 millimeter (mm) a year.

The article presents an analysis of monthly precipitation trends in Iberian Peninsula's eastern Mediterranean fringe. The analysis show high temporal and spatial variability. Trends for winter months are prevailed by an East-West gradient with a latitudinal temporal change. Positive trends are primarily situated in coastland areas and negative ones in overriding inland.

The article reports on the study that examines the trends in Australian precipitation from 1970 to 2006 using daily rainfall dataset. The findings of the study suggested a linkage between changes in the monsoon trough and rainfall trends over northwestern Australia. It revealed a dominant change in total rainfall by trends in heavy rainfall events across the nation. It also found a decline in frequency of extreme rainfall events along the Queensland coast during summer and autumn, showing changes in the position of the precipitation distribution.

Abstract: Winter rainfall on the Iberian Peninsula presents a significant decrease in its western and central areas throughout the second half of the 20th century, whereas over the eastern fringe it shows hardly any variation. This spatial distribution of precipitation trends are related to teleconnection indices trends and changes in the frequency of surface circulation patterns over Western Europe. We determined these circulation patterns by carrying out a daily objective synoptic classification by means of a principal components analysis (PCA) using sea-level pressure (SLP) data. In order to better understand Iberian winter precipitation trends, circulation patterns are associated with those teleconnection patterns that have an important influence on Iberian rainfall: Arctic Oscillation (AO), North Atlantic Oscillation (NAO) and Western Mediterranean Oscillation (WeMO). The circulation pattern showing the biggest increases involves high pressure over Central Europe. This pattern is showing a positive AO and NAO phase, and simultaneously, a negative WeMO phase. [Copyright &y& Elsevier]

Since several datasets are available with marked differences, the assessment of precipitation data is a key aspect to support the choice of the most adequate precipitation product for a certain research or operational application. In the present study, we evaluated the use of the daily rainfall dataset from CHIRPS with spatial resolution of 0.05° for different purposes in the states of the Brazilian Legal Amazon. We compared monthly rainfall, annual rainfall indices and their trends calculated using CHIRPS data and rain gauge observations with a point-to-pixel analysis. The use of daily CHIRPS data provided mean monthly rainfall similar to that obtained using data from the rain gauge stations, but CHIRPS data tend to underestimate the values for the rainiest months. The correlation was usually lower in the western Amazon, especially during its rainy season. The same underestimation was observed for extreme rainfall indices. CHIRPS product produces more similar results to rain gauge data for the indices PRCPTOT, nP, and R95pad, while strong underestimate the most extreme rainfall indices (R50mm, Rx1day, Rx5days). For the 45 stations and 15 rainfall indices analysed, 63 significant trends were detected using rain gauge data, of which only 13 were detected using CHIRPS product. Therefore, the use of CHIRPS data does not well represent the trends in rainfall indices. • Use of the rainfall dataset from CHIRPS for different purposes in Brazilian Amazon. • CHIRPS data tend to underestimate the rainfall for the rainiest months. • The correlation was greater for the rainy season in eastern Amazonia. • CHIRPS data underestimate the extreme rainfall indices. [ABSTRACT FROM AUTHOR]