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More intense rainfall may cause a range of negative impacts upon society and the environment. In this study we analyzed trends in extreme ETCCDI (Expert Team on Climate Change Detection and Indices) rainfall indices in Montenegro for the period 1951-2010. Montenegro has been poorly studied in terms of rainfall extremes, yet it contains the wettest Mediterranean region known as Krivo²ije. Several indices of precipitation extremes were assessed including the number of dry days and rainfall totals, and their trends to identify possible changes. The results generally suggest that the number of days with precipitation decreased while rainfall intensity increased particularly in south-western parts of the country. A slight tendency towards intense rainfall events is suggested. Calculated trends for each index are spatially presented and examined using a plotGoogleMaps software package. This study also examined spatial pattern of relationship between extreme rainfall indices and North Atlantic Oscillation. Results suggested negative, mainly statistically significant correlations at annual, winter and autumn scale. [ABSTRACT FROM AUTHOR]

As part of the High Definition Clouds and Precipitation for advancing Climate Prediction Observational Prototype Experiment (HOPE), a high spatial density network of 99 silicon photodiode pyranometers was set up around Jülich (10km×12km area) from April to July 2013, to capture the variability in the radiation field at the surface induced by small-scale cloud inhomogeneity. Each of these autonomously operated pyranometer stations was equipped with weather sensors for simultaneous measurements of ambient air temperature and relative humidity. In this paper, we provide the details of this unique setup of the pyranometer network and the data analysis with initial quality screening procedure we adopted. We also present some exemplary cases consisting of the days with clear, broken cloudy and overcast skies to assess our spatio-temporal observations from the network, and validate their consistency with other collocated radiation measurements available during the HOPE period. [ABSTRACT FROM AUTHOR]

Gridded precipitation (PRP) data have been largely used in diagnostic studies on the climate variability in several time scales, as well as to validate model results. The three most used gauge-based PRP datasets are from the Global Precipitation Climatology Centre (GPCC), University of Delaware (UDEL), and Climate Research Unit (CRU). This paper evaluates the performance of these datasets in reproducing spatiotemporal PRP climatological features over the entire South America (SA) for the 1901–2015 period, aiming to identify the differences and similarities among the datasets as well as time intervals and areas with potential uncertainties involved with these datasets. Comparisons of the PRP annual means and variances between the 1901–2015 period and the non-overlapping 30-year subperiods of 1901–1930, 1931–1960, 1961–1990, and the 25-year subperiod of 1991–2015 for each dataset show varying means of the annual PRP over SA depending on the subperiod and dataset. Consistent patterns among datasets are found in most of southeastern SA and southeastern Brazil, where they evolved gradually from less to more rainy conditions from 1901–1930 to the 1991–2015 subperiod. All three datasets present limitations and uncertainties in regions with poor coverage of gauge stations, where the differences among datasets are more pronounced. In particular, the GPCC presents reduced PRP variability in an extensive area west of 50° W and north of 20° S during the 1901–1930 subperiod. In monthly time scale, PRP time series in two areas show differences among the datasets for periods before 1941, which are likely due to spurious or missing data: central Bolivia (CBO), and central Brazil (CBR). The GPCC has less monthly variability before 1940 than the other two datasets in these two areas, and UDEL presents reduced monthly variability before 1940 and spurious monthly values from May to September of the years from 1929 to 1941 in CBO. Thus, studies with these three datasets might lead to different results depending on the study domain and period of analysis, in particular for those including years before 1941. The results here might be relevant for future diagnostic and modelling studies on climate variability from interannual to multidecadal time scales. [ABSTRACT FROM AUTHOR]

Recent studies have drawn attention to a significant weakening trend of the South Asian monsoon circulation and an associated decrease in regional rainfall during the last few decades. While surface temperatures over the region have steadily risen during this period, most of the CMIP (Coupled Model Intercomparison Project) global climate models have dificulties in capturing the observed decrease of monsoon precipitation, thus limiting our understanding of the regional land surface response to monsoonal changes. This problem is investigated by performing two long-term simulation experiments, with and without anthropogenic forcing, using a variable resolution global climate model having high-resolution zooming over the South Asian region. The present results indicate that anthropogenic effects have considerably influenced the recent weakening of the monsoon circulation and decline of precipitation. It is seen that the simulated increase of surface temperature over the Indian region during the post-1950s is accompanied by a significant decrease of monsoon precipitation and soil moisture. Our analysis further reveals that the land surface response to decrease of soil moisture is associated with significant reduction in evapotranspiration over the Indian land region. A future projection, based on the representative concentration pathway 4.5 (RCP4.5) scenario of the Intergovernmental panel on Climate Change (IPCC), using the same high-resolution model indicates the possibility for detecting the summer-time soil drying signal over the Indian region during the 21st century, in response to climate change. While these monsoon hydrological changes have profound socioeconomic implications, the robustness of the high-resolution simulations provides deeper insights and enhances our understanding of the regional land surface response to the changing South Asian monsoon. [ABSTRACT FROM AUTHOR]

Global climate change has numerous implications for members of mountain communities who feel the impacts in both physical and social dimensions. In the Western Himalayas of India, a majority of residents maintain a livelihood strategy that includes a combination of subsistence or small-scale agriculture, seasonal pastoral migration, male out-migration, and localized natural resource extraction. Particularly under conditions of heavy male outmigration, but throughout the region, mountain women play a key role in providing labor and knowledge related to the management of local natural resources, yet often lack authority in related political and economic decision-making processes. This gap has important implications for addressing the impacts of climate change: while warming temperatures, irregular patterns of precipitation and snowmelt, and changing biological systems present challenges to the viability of these traditional livelihood portfolios throughout the region, mountain women increasingly face new challenges in their roles as household managers that have not adequately been emphasized in larger scale planning for climate change adaptation and mitigation. These challenges are complex in nature, and are shaped not only by gender issues but also interacting factors such as class, caste, ethnicity, and age (among others). In this paper, we review the main arguments behind the discursive gender/climate change nexus, discuss the implications for gendered vulnerabilities and transformation of adaptive capacities in the region, and suggest ways that researchers and policymakers seeking to promote "climate justice" can benefit from the incorporation of gender-based perspectives and frameworks. [ABSTRACT FROM AUTHOR]

A model was developed to simulate spatial, seasonal and interannual variations in vegetation in response to temperature, precipitation and atmospheric CO2 concentrations; the model addresses shortcomings in current implementations. The model uses the minimum of 12 temperature and precipitation constraint functions to simulate NDVI. Functions vary based on the Köppen-Trewartha climate classification to take adaptations of vegetation to climate into account. The simulated NDVI, referred to as the climate constrained vegetation index (CCVI), captured the spatial variability (0.82 < r <0.87), seasonal variability (median r = 0.83) and interannual variability (median global r = 0.24) in NDVI. The CCVI simulated the effects of adverse climate on vegetation during the 1984 drought in the Sahel and during dust bowls of the 1930s and 1950s in the Great Plains in North America. A global CO2 fertilisation effect was found in NDVI data, similar in magnitude to that of earlier estimates (8% for the 20th century). This effect increased linearly with simple ratio, a transformation of the NDVI. Three CCVI scenarios, based on climate simulations using the representative concentration pathway RCP4.5, showed a greater sensitivity of vegetation towards precipitation in Northern Hemisphere mid latitudes than is currently implemented in climate models. This higher sensitivity is of importance to assess the impact of climate variability on vegetation, in particular on agricultural productivity. [ABSTRACT FROM AUTHOR]

The migratory locust, Locusta migratoria (L.), a significant grasshopper species known for its ability to form large swarms and cause extensive damage to crops and vegetation, is subject to the influence of climate change. This research paper employs geographic information system (GIS) and MaxEnt ecological modelling techniques to assess the impact of climate change on the distribution patterns of L. migratoria. Occurrence data and environmental variables are collected and analysed to create predictive models for the current and future distribution of the species. The study highlights the crucial role of climate factors, particularly temperature and precipitation, in determining the locust's distribution. The MaxEnt models exhibit high-performance indicators, accurately predicting the potential habitat suitability of L. migratoria. Additionally, specific bioclimatic variables, such as mean temperature and annual precipitation, are identified as significant factors influencing the species' presence. The generated future maps indicate how this species will invade new regions especially in Europe. Such results predict the risk of this destructive species for many agriculture communities as a direct result of a warming world. The research provides valuable insights into the complex relationship between locust distribution and environmental factors, enabling the development of effective strategies for locust management and early warning systems to mitigate the impact on agriculture and ecosystems. [ABSTRACT FROM AUTHOR]

Climate and land use change in the Mediterranean region is expected to affect natural and agricultural ecosystems by decreases in precipitation, increases in temperature as well as biodiversity loss and anthropogenic degradation of natural resources. Demographic growth in the Eastern and Southern shores will require increases in food production and put additional pressure on agro-ecosystems and water resources. Coping with these challenges requires informed decisions that, in turn, require assessments by means of a comprehensive agro-ecosystem and hydrological model. This study presents the inclusion of 10 Mediterranean agricultural plants, mainly perennial crops, in an agro-ecosystem model (LPJmL): nut trees, date palms, citrus trees, orchards, olive trees, grapes, cotton, potatoes, vegetables and fodder grasses. The model was successfully tested in three model outputs: agricultural yields, irrigation requirements and soil carbon density. With the development presented in this study, LPJmL is now able to simulate in good detail and mechanistically the functioning of Mediterranean agriculture with a comprehensive representation of ecophysiological processes for all vegetation types (natural and agricultural) and in a consistent framework that produces estimates of carbon, agricultural and hydrological variables for the entire Mediterranean basin. This development pave the way for further model extensions aiming at the representation of alternative agro-ecosystems (e.g. agroforestry), and opens the door for a large number of applications in the Mediterranean region, for example assessments on the consequences of land use transitions, the influence of management practices and climate change impacts. [ABSTRACT FROM AUTHOR]

JULES-crop is a parametrisation of crops in the Joint UK Land Environment Simulator (JULES). We investigate the sources of the interannual variability in the modelled maize yield, using global runs driven by reanalysis data, with a view to understanding the impact of various approximations in the driving data and initialisation. The standard forcing dataset for JULES consists of a combination of meteorological variables describing precipitation, radiation, temperature, pressure, specific humidity and wind, at subdaily time resolution. We find that the main characteristics of the modelled yield can be reproduced with a subset of these variables and using daily forcing, with inter nal disaggregation to the model timestep. This has implications in particular for the use of the model with seasonal forcing data, which may not have been provided at subdaily resolution for all required driving variables. We also investigate the effect on annual yield of initialising the model with climatology on the sowing date. This approximation has the potential to considerably simplify the use of the model with seasonal forecasts, since obtaining observations or reanalysis output for all the initialisation variables required by JULES for the start date of the seasonal forecast would present significant practical challenges. [ABSTRACT FROM AUTHOR]

The paper explores the occurrence of minimal precipitation extremes at specific meteorological stations in the southeastern region of Serbia. With climate change leading to increased instances of droughts, these natural phenomena have garnered heightened interest due to their negative impacts on society, environment, and the economy. Employing the SPI-12 index in the southeastern part of Serbia from 1946 to 2021, the study sheds light on the vulnerability of this natural phenomenon in the observed stations. Understanding historical manifestation of these events helps water resource managers, farmers and policymakers manage these risks in the southeastern region of Serbia. [ABSTRACT FROM AUTHOR]

The high variability of the sub-desert climate, especially in the south-eastern region of Morocco, has severe socioeconomic impacts on the inhabitant's way of life, as is the case in the Daoura watershed, where this variability is associated with droughts or exceptional rainfall. The data collected from the Guir-Ziz-Rheriss hydraulic agency were processed, corrected and analyzed using the Climatol package (version 4.0.0) developed in R software to homogenize rainfall data. Through this work, the significance and amplitudes of annual and monthly rainfall trends were defined using the Mann-Kendall test and Sens's slope estimator, while comparing the results of raw and homogenized data. The Daoura watershed has a sub-desert climate, and the homogenization process revealed a few rainfall stations with significant positive trends at confidence levels ranging from 90% to 95%. According to the raw and homogenized data, the majority of these stations are located in the High Atlas (CR1) and Anti-Atlasic (CR2) zones, where there is considerable spatiotemporal variability in rainfall from one year to the next. The essential objective of this scientific paper was to analyze the spatiotemporal variability of monthly and annual precipitation and to study their trends through rainfall data homogenized by the climatol package (version 4.0.0) from 13 stations over a period (1957-2018). The contribution of this study to science is the rainfall data it offers, which is useful for managing natural resources in sub-desert areas. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to examine the role of high intensity precipitation events in increasing the vulnerability to floods in Mediterranean Spain. Precipitation intensity in this area appears to have augmented in the last two decades in association with warming trends of the Mediterranean Sea. At the same time, intense urbanization processes, occupying and transforming flood prone land, have produced an important increase in exposure. The main objective is to assess whether higher intensity precipitation and changing patterns in exposure aggravate vulnerability to floods. Design/methodology/approach: In this paper, vulnerability is understood as the result of the interrelationships between exposure, sensitivity, impacts and adaptive capacity. Consequently, methods used involved the compilation and analysis of published and unpublished precipitation data, population and land use data, data on insurance claims, and media sources related to those variables. Findings: Changes toward episodes of more intense precipitation in the expanding urban areas of Mediterranean Spain increase exposure but not necessarily vulnerability, at least in terms of human deaths. However, adaptative capacity needs to be formulated. Actions that attempt to absorb and eventually reuse flood flows (as the flood park in Alicante) appear to be more effective than traditional hydraulic solutions (as in Majorca). Originality/value: The paper provides a systematic and coherent approach to vulnerability analysis taking into account the changing dynamics of its components. Especially, it signals the limits of current adaptive approaches to flooding and advocates for changes toward a more circular and less linear approach to urban drainage. [ABSTRACT FROM AUTHOR]

This study investigates how the climate is changing at individual weather stations around the world by measuring means and extremes. Extensive python code was written to read in the daily data from thousands of stations and compute average yearly temperature, precipitation, and extremes such as heat waves, cold spells, very wet and dry periods. A best-fit line and goodness-of-fit statistic were computed for each statistic at each station. All these linear trends were collected into histograms and geographic distribution plots. It was found that the earth is undergoing significant changes: 97% of all stations are increasing in temperature since 1950, averaging 4° F per century. All measures of extreme heat are increasing, and all measures of extreme cold are decreasing. Almost all stations are recording significant increases in the number of warm days (days above a reference 90th percentile) and heat waves (three consecutive warm days) and the warmest day of the year is getting hotter. There are fewer cold nights and cold spells. The number of frost nights is significantly decreasing, averaging 25 fewer frost nights per year over a century. Changes in precipitation vary by geography: some regions are drier while others are wetter. For example, precipitation changes are strongly varied in both the U.S. and Australia. This study confirms that the earth's climate is rapidly changing in both means and extremes. To help the public better understand climate change, this data is presented in an online map for interactive exploration at http://lillianpetersen.github.io. [ABSTRACT FROM AUTHOR]

This paper presents a precipitation reconstruction that is based on the continuous observations by Louis Morin in Paris from 1665–1713. Morin usually recorded precipitation intensity and duration, when it snowed/rained, three times each day (sometimes up to six times). The consistency of his observations can be calculated from his other measurements and observations (e.g. temperature, cloud cover), where at least one entry of his different measurements and observations for 98.7 % of all days is noted. To 5 convert these observations to common units, we calibrated them with a multiplicative interacting model using Philippe and Gabriele-Philippe de la Hire's instrumental measurements from Paris. The two series of measurements by de la Hire (father and son) and observations by Morin overlap from 1688–1713. To test the quality of the reconstruction, we analyzed it with the de la Hire's measurements, proxy data, an internal analysis of Morin's measurements of different climate variables, and modern data. Thus, we assess the reliability of the precipitation reconstructions based on Morin's data as follows. We have moderate confidence regarding the exact quantities of daily, seasonal, and annual precipitation totals. We have low confidence regarding exceptionally high precipitation amounts, but we have high confidence in the indices of an impact analysis (i.e., dry days, wet days, consecutive dry days, consecutive wet days), in monthly frequencies of rainfall, and in interannual, interseasonal, and interdecadal variability. Rainy seasons with precipitation totals greater than 250 mm occurred in MAM 1682, JJA 1682, SON 1687, JJA 1697 and JJA 1703. Furthermore, compared to other DJF seasons, the winter of 1666/67 stands out with a precipitation total of 248 mm. Dry seasons with precipitation totals less than 60 mm occurred in SON 1669, DJF 1690/91 and DJF 1693/94. An impact analysis shows no abnormalities regarding consecutive dry days or wet days in MAM. In JJA a longer dry period of 31 days appeared in 1686 and a dry period of 69 days appeared in DJF 1671/72. [ABSTRACT FROM AUTHOR]

This paper presents a research study of expected precipitation extremes across the Gandaki Province, Nepal. The study used five indices to assess extreme precipitation under climate change. Precipitation output of two Global Climate Models (GCMs) of Coupled Model Intercomparison Project Phase Six (CMIP6) were used to characterize the future precipitation extremes during the rainfall season from June to September (JJAS) and overall days of the year. To characterize extreme precipitation events, we used daily precipitation under the SSP2–4.5 and SSP5–8.5 scenarios from the Beijing Climate Center and China Meteorological Administration, China; and Meteorological Research Institute (MRI), Japan. Considering large uncertainties with GCM outputs and different downscaling (including bias correction) methods, direct use of GCM outputs were made to find change in precipitation pattern for future climate. For 5-, 10-, 20-, 50-, and 100-year return periods, observed and projected 24 h and 72 h annual maximum time series were used to calculate the return level. The result showed an increase in simple daily intensity index (SDII) in the near future (2021–2040) and far future (2081–2100), with respect to the base-year (1995–2014). Similarly, heavy precipitation days (R50 mm), very heavy precipitation days (R100 mm), annual daily maximum precipitation (RX1day), and annual three-day maximum precipitation (RX3day) indices demonstrated an increase in extreme precipitation toward the end of the 21st century. A comparison of R50 mm and R100 mm values showed an extensive (22.6% and 63.8%) increase in extreme precipitation days in the near future and far future. Excessive precipitation was forecasted over Kaski, Nawalparasi East, Syangja, and the western half of the Tanahun region. The expected increase in extreme precipitation may pose a severe threat to the long-term viability of social infrastructure, as well as environmental health. The findings of these studies will provide an opportunity to better understand the origins of severe events and the ability of CMIP6 model outputs to estimate anticipated changes. More research into the underlying physical factors that modulate the occurrence of extreme incidences expected for relevant policies is suggested. [ABSTRACT FROM AUTHOR]

Any hydro-meteorology variable includes different components, in general, such as periodicity, trend, possibly jump, and uncertain stochastic parts. Among these, the trend analysis gained importance in the last three decades due to global warming and climate change effects. The literature is full of monotonic trend applications by taking into consideration trend analysis methodologies such as Mann–Kendall trend identification, Sen trend slope calculation, and Şen innovative trend analysis (ITA). It is more important in practical studies to deal with less than one-year durations to assess the possible trend pieces for better practical uses such as agricultural productivity purposes. In this paper, a new concept is applied, known as the innovative polygon trend analysis (IPTA), to assess the trend component transitions between two successive months. The application of the methodology is presented for the coastal region of northeast Algerian precipitation records. The emanated results from this study provided information that El Taref station has the most unstable precipitation behavior among all the meteorology stations in the study area, moving from a month to another rather very unsystematically; whereas other meteorology stations have systematic movement from a month to the subsequent one. [ABSTRACT FROM AUTHOR]

The impact of climate change on forest ecosystems may manifest itself by a shift in forest vegetation zones in the landscape northward and into higher elevations. Studies of climate change-induced vegetation zone shifts in forest ecosystems have been relatively rare in the context of European temperate zone (apart from Alpine regions). The presented paper outlines the results of a biogeographic model of climatic conditions in forest vegetation zones applied in the Central European landscape. The objective of the study is a prediction of future silvicultural conditions for the Norway spruce (Picea abies L. Karst.), which is one of the principal tree species within European forests. The model is based on a general environmental dependence of forest vegetation zones on the long-term effect of altitudinal and exposure climates defined by the mean and extreme air temperatures and the amount and distribution of atmospheric precipitation. The climatological data for the model were provided by a validated regional climate database for 2010 – 2090 according to the SRES A1B scenario, bound to specific geo-referenced points in the landscape. The geobiocoenological data in the model were provided by the Biogeography Register database which contains ecological data on the landscape bound to individual cadastres of the entire Czech Republic. The biogeographic model applies special programs (the FORTRAN programming language) in the environment of geographic information systems. The model outputs can be clearly graphically visualized as scenarios of predicted future climatic conditions of landscape vegetation zones. Modelling of the regional scenario of changes in the climatic conditions of forest vegetation zones reveals that in the prediction period of 2070 and beyond, good and very good climatic conditions for the cultivation of forests with dominant Norway spruce will be found only in some parts of its today's native range in forest vegetation zones 5 – 8. Based on the results provided by the regional scenario, the authors of this paper recommend fundamental reassessment of the national strategy of sustainable forest management in the Czech Republic, stipulating that the current practice of spruce cultivation be reduced only to areas specifically defined by the biogeographic model. The paper shows that biogeographic models based on the concept of vegetation zoning can be applied not only in regional scenarios of climate change in the landscape but also as support tools for the creation of strategies of sustainable forest management. [ABSTRACT FROM AUTHOR]

The aim of this paper is to identify the trends of changes in atmospheric precipitation percolation under the changing climate conditions of Lithuania (the East Baltic region) based on long-term lysimeter studies. Data from 1987–2022 research (n = 1296) was used to determine trends in precipitation infiltration changes. Two 10-year periods, 1989–1998 and 2011–2020, were selected from the whole observation period (1987–2022) to assess changes in precipitation infiltration due to climate change. The air temperature has increased significantly in November (+3.4 °C) and December (+3.3 °C), with a +2.2 °C increase in the standard climate normal. The distribution of yearly precipitation has changed, with the annual amount decreasing from 686 to 652 mm. Precipitation increased the most in July and August (10.9 and 22.9 mm). In autumn, the amount of precipitation decreased by 7.9–31.1 mm. The number of rainy days did not change during the year, but the frequency of heavy precipitation increased significantly in August. The annual percolation increased by 14.2% over 2011–2020 compared to 1989–1998. Percolation increased by 19.0, 22.3, and 20.1% during the spring, autumn, and winter, respectively, and decreased by 35.0% in summer. The increase in annual percolation is mostly related to the increase in temperature during the cold season: November and December. During these months, the likelihood of early freeze formation, which interrupts gravitational water percolation in soil, is significantly reduced. In the spring, the increase in average air temperatures in March leads to faster melting of the winter snow in a shorter period, which significantly increases percolation processes. In Lithuania, higher percolation in autumn and winter, when part of the agricultural land is not covered by vegetation, may lead to higher leaching of chemical elements. [ABSTRACT FROM AUTHOR]

This paper presents the results of a trend analysis of three climate elements: precipitation, cloudiness and humidity. Almost the entire period of instrumental measurements (precipitation and humidity) and visual observations (cloudiness) are covered. In the observed 68-year period (1951-2018), the trend of annual and seasonal precipitation amounts is insignificant. Though, there is a significant decrease in the number of days with precipitation = 1 mm, which implies a movement towards more arid conditions. On the other hand, the number of days with extreme rainfall = 40 and 50 mm is increasing. In Podgorica, the annual statistics of days with snow cover decreases as well. There is also a decrease in the relative humidity and cloudiness, and with both elements the trend is insignificant only in the autumn season. The results of the trend calculation show that the number of gloomy days is more intensively reduced than the number of increasing bright days. In general, the results of the research show that the climate of Podgorica tends to be more arid with more extreme weather events. The climate variations happening in this city are, to small amount, caused by the urbanization process. Podgorica has the character of an urban heat island in a cooler environment, with an average annual intensity of about 0.7°C and the highest in winter (about 0.8°C). The most symptomatic indicator of urbanization is temperature, but anthropogenic heat production in the city (asphalt, constructions, increase of aerosols, etc.) also affects other climate elements. Compared to the non-urban environment, Podgorica has a higher annual rainfall of 100 mm and a lower humidity of 3%, while this difference is not noticeable in the overall cloudiness. [ABSTRACT FROM AUTHOR]

The main atmospheric climate parameters are important for the daily and seasonal variation of the parameters of the Comana Puddle aquariums. The anomalous variation of temperatures, precipitation and evaporation induces a fluctuation in the volume of water from the pond and the river Neajlov. Atmospheric temperature and precipitation directly affect winter phenomena and breakdown processes during the summer period, with significant effects on the agriculture, the most vulnerable domain on climate changes. In the hilly or hill area, the amount of rainfall decreases, thus influencing the water intake in these aquariums. The high warming time of the heat season leads to an increase in evaporation values, so that a water deficit is recorded in the hillside, hillside and plain areas, which also entails a loss in the volume of water in the lagoons. These seasonal fluctuations directly affect the limbic or aquatic fauna, but also the agriculture. In the cold season winter phenomena (ice bridge, ice on the shore, slopes, snowballs) and blocking water as snow, creates a deficiency in the water supply of lakes, ponds, puddles and swamps. This paper analysed the impact of climatic changes but also the possibilities of the recovery a part of the gloss of water, a gloss that existed years ago and which was greatly diminished after the work done downstream changed the hydrological balance of the area. This effect adds to the fact that climate change has made it possible for the volume of evaporation to be increased and sometimes to exceed the volume of precipitation. [ABSTRACT FROM AUTHOR]

In this paper, we have analyzed the time series of daily values for three meteorological elements, two continuous and a discontinuous one, i.e., the maximum and minimum air temperature and the precipitation. The analysis was done based on the observations from seven stations in Serbia from the period 1951-2010. The main aim of this paper was to quantify the complexity of the annual values for the mentioned time series and to calculate the rate of its change. For that purpose, we have used the sample entropy and the Kolmogorov complexity as the measures which can indicate the variability and irregularity of a given time series. Results obtained show that the maximum temperature has increasing trends in the given period which points out a warming, ranged in the interval 1-2 °C. The increasing temperature indicates the higher internal energy of the atmosphere, changing the weather patterns, manifested in the time series. The Kolmogorov complexity of the maximum temperature time series has statistically significant increasing trends, while the sample entropy has increasing but statistically insignificant trend. The trends of complexity measures for the minimum temperature depend on the location. Both complexity measures for the precipitation time series have decreasing trends. [ABSTRACT FROM AUTHOR]

Physical-natural, economic, social, and spatial factors constitute processes that, when associated, form and give meaning to the spatial complexity of the Metropolitan Region of Rio de Janeiro, configuring it as a susceptible and vulnerable space to the occurrence of climate exceptionalities. Thus, this paper aims to analyze the spatial and temporal variability of extreme precipitation events in the Metropolitan Region of Rio de Janeiro. Daily data regarding 48 rainfall stations were used: 40 stations in a series from 2008 to 2019 and 8 stations concerning the period between 1970 and 2019. The percentile technique was used to establish standard years (1, 10, 90, and 99 percentile) and to define the extremes (99th percentile). The R software was used to perform autocorrelation tests, to extract the RX1Day and RX5Day indices, and to perform the Mann-Kendall, Pettitt, and Sen's Slope tests. The influence of altitude, slope orientation, and sea level was verified on the spatial distribution of precipitation and extreme events. The years with the highest occurrence of extremes, as well as concentrated and persistent events of greater magnitude, are identified as rainy and extremely rainy, namely 1988 e 2009. 90% of extremes occur in the rainy season, especially during December, January, and March. However, April manifests extremes of a greater magnitude. Four stations with negative and two with positive trends were identified. [ABSTRACT FROM AUTHOR]

Crop yields are threatened by global climate change. Maize has high water requirements, and precipitation fluctuations can impact its yield. In this study, we used the Environmental Policy Integrated Climate (EPIC) model to simulate maize yields in eight northeastern U.S. states. We used precipitation fluctuations and the coefficient of variation (CV) of yield as indicators to construct a vulnerability curve for the CV of yield and precipitation fluctuations. We then evaluated the vulnerability of maize yields under precipitation fluctuations in the region. We obtained the following results: (1) the fitted vulnerability curves were classified into three categories (positive slope, negative slope, and insignificant fit), of which the first category accounted for about 92.7%, indicating that the CV of maize yield was positively correlated with precipitation fluctuations in most parts of the study area; and (2) the CV of maize yield under 11 precipitation fluctuation scenarios was mapped to express the CV at the spatial level, and the maize yield in Connecticut and Maryland proved to be the most sensitive to precipitation fluctuations. This study provided a theoretical and experimental basis for the prevention of maize yield risk under fluctuating precipitation conditions. [ABSTRACT FROM AUTHOR]

This paper presents the first study to identity, in historical records, regional changes in the mechanisms of extreme water available for runoff (W). We used a quality‐controlled Snowpack Telemetry data set (1979–2017) combined with the nonparametric regional Kendall test to examine changes in annual maximum W under four hydrometeorological conditions (melt only/rain‐on‐snow/all melt/all melt plus rainfall) over the mountainous regions of the western United States. Under a warming climate, our analyses indicated significant declining trends in annual maximum W at regional scale under all four conditions. The annual maximum of all melt plus rainfall decreased significantly by 15% in the southwestern United States, while the frequency of rain‐on‐snow events increased significantly by 32% in the northwestern United States. The annual maximum snowmelt only decreased significantly by 21% across the entire western United States. Our results confirmed that interaction between regional humidity and solar radiation with warming temperature helps drive these changes. Plain Language Summary: In the western United States, mountain snowmelt generates about 50% of the region's streamflow and plays a critical role in sustaining water resources. It is important to understand how snowpack are changing under warming, as risks related to these changes involve trillions of dollars. This paper presents the first study to identify, in historical records, large‐scale changes in the mechanisms of extreme water available for runoff (W). We used a regional trend analysis to examine spatiotemporal changes in rain‐on‐snow (ROS) frequency and the mechanisms of extreme W from 1979 to 2017, based on our newly developed quality‐controlled observed snow and precipitation data set. We found that, under a significant warming trend, annual maximum W from snowmelt only (not including ROS) has been decreasing by 21% across the western United States. The northwestern United States showed significant increasing trends in ROS frequency by 32%, but the rate of annual maximum ROS showed nonsignificant trends (i.e., more frequent but similar in magnitude). The annual maximum W from all conditions (melt plus rain) has been decreasing significantly by 15% in the southwestern United States. Decreasing trends in the mechanisms of extreme W may have significant ramifications for water management relative to flood risk and public safety. Key Points: Annual maximum snowmelt (not including rain‐on‐snow) decreased significantly by 21% averaged across the snowy regions of the western United StatesThe frequency of rain‐on‐snow events increased significantly by 32% averaged in the higher humidity snowy regions of the northwestern United StatesAnnual maximum water available for runoff (melt + rain) decreased significantly by 15% in the snowy regions of the southwestern United States [ABSTRACT FROM AUTHOR]

In recent years, numerous studies have investigated the relationship of extreme precipitation intensities with temperature derived from a binning method using present‐day weather data. The aim of this approach is that these dependencies, or so‐called apparent scaling rates, provide insights on how precipitation extremes could evolve in the future climate. In a recent paper, Bao et al. showed that there is a large discrepancy between the present‐day apparent scaling rates—showing a negative dependency of daily rainfall extremes on temperature for Darwin—and the climate change response showing a substantial increase in daily rainfall extremes. Their results provide compelling evidence that it may not be straightforward to predict the climate change response from the temperature scaling. We agree with this statement, but disagree with the physical explanation put forward in that study and think that moisture limitations are the most likely cause. Therefore, we advocate the use of dew point temperatures in scaling studies as a much more direct proxy of the absolute humidity of the air in which precipitation extremes develop, which we think is physically more consistent with the underlying mechanism causing the increase in precipitation extremes with global warming. [ABSTRACT FROM AUTHOR]

Drought (similarly as flooding) is considerably the gravest agrometeorological extreme connected with climate change and bringing the highest losses in an agricultural production. The objective of this paper is to study the spatial and temporal variability of the Aridity Index (AI) in the Czech Republic, per decade, during the 55-year period (1961 - 2015). AI is a climatic index, which is important for recording of the drought phenomenon evolution. The climatic data used, include monthly precipitation totals and air temperature from 120 meteorological stations operated by the Czech Hydrometeorological Institute. The potential evapotranspiration was calculated based on the modified algorithm Penman-Monteith. The data processing was done by the statistical tools of Microsoft Excel and the Geographical Information Systems (Clidata GIS, ArcGIS 10). The results of the analysis showed, that during the decade 1961 - 1970, almost the whole area of the Czech Republic is classified as "wet" with AI values ranging above 0.60, but over the next years (1971 - 2015), areas of the south Moravia (e.g. Dyjsko-svratecký ravine, Valticko-lednický area, surroundings of Brno city), and also Prague city and Poohří river basin shifted gradually to "sub-humid" climate zone with AI < = 0.60. Especially, during the pre-last decade of the study period 1991 - 2000. [ABSTRACT FROM AUTHOR]

This paper used data on land use, normalized difference vegetation index, digital elevation model, temperature and precipitation, and urban distribution to analyse the impacts of climate change, urban expansion and the Grain for Green project implementation on land use and land cover change in the Loess Plateau between 1980 and 2015 based on a single factor and comprehensive factor analysis. The aim of this paper is to explore the spatial expression of human activities under the influence of urban expansion, climate change, and the implementation of the Grain for Green project. The results indicated that climate change dominated among the influencing factors of land use and land cover change in the Loess Plateau, accounting for 93.65% of the total, with a surface-like distribution. It was followed by urban expansion, accounting for 5.46% of the total, with a point-like distribution. The impact of the Grain for Green project implementation accounted for 0.64%, with a patchy distribution. However, due to the low resolution, the quantitative assessment results regarding the role of the Grain for Green project implementation was lower, while for climate change and urban expansion, results were higher. [ABSTRACT FROM AUTHOR]

This paper shows that joint temperature-precipitation information over a global domain provides a more accurate estimate of aerosol forced responses in climate models than does any other combination of temperature, precipitation, or sea level pressure. This fact is demonstrated using a new quantity called potential detectability, which measures the extent to which a forced response can be detected in a model. In particular, this measure can be evaluated independently of observations and therefore permits efficient exploration of a large number of variable combinations before performing optimal fingerprinting on observations. This paper also shows that the response to anthropogenic aerosol forcing can be separated from that of other forcings using only spatial structure alone, leaving the time variation of the response to be inferred from data, thereby demonstrating that temporal information is not necessary for detection. The spatial structure of the forced response is derived by maximizing the signal-to-noise ratio. For single variables, the north-south hemispheric gradient and equator-to-pole latitudinal gradient are important spatial structures for detecting anthropogenic aerosols in some models but not all. Sea level pressure is not an independent detection variable because it is derived partly from surface temperature. In no case does sea level pressure significantly enhance potential detectability beyond that already possible using surface temperature. Including seasonal or land-sea contrast information does not significantly enhance detectability of anthropogenic aerosol responses relative to annual means over global domains. [ABSTRACT FROM AUTHOR]

The study of climate changes is most often based on the analysis of time series of temperature and precipitation in urban areas and the increase in the emission of gases having a greenhouse effect. On the other hand, the selection of representative and relevant stations and comprehensive analysis of climate indicators lead to better and more exact assessments on climate changes at the regional level. In order to connect climate changes with agricultural, biological, socio-economic, and tourism databases, the paper deals with the dynamic analysis of changes in thermal component expressed through the values of regional climate indices in four climatological stations with different geographical positions in Serbia. There are significant differences between the two time series data (1961-1990 and 1991-2013) on temperature and humidity, precipitation, insolation, and wind speed. However, after using the climatic indices as a tool for assessing climate changes, the results of the study suggest the relative influence of the thermal component on the change of climate indices, with a slight increase in the index of significance for human activities. Relying on the results of this alternative approach to the study of climate changes, the fact remains that the climate is not fixed but highly variable factor that should be taken into consideration in terms of monitoring, evaluation, and management of the area. [ABSTRACT FROM AUTHOR]

The present paper investigates fluvial flood hazards in urban areas in the Mekong Delta to inundation due to seasonal flooding, a phenomenon which is likely to be exacerbated by future sea-level rise. Unlike past researches which mainly focus on flooding due to river discharge from upstream or heavy precipitation, the present paper scrutinises the influence of ocean tides. The research reveals that ocean tides predominantly determine water elevation even in an upstream location such as Can Tho City, 80 km inland from the river mouth, and that the river flow causes tidal damping and effectively reduces the energy of the incoming tides. This tidal damping is especially pronounced during the rainy season. Analysis based on the water levels monitored by the Mekong River Commission revealed that the ground near the riverbank of Can Tho had experienced inundation for a total of 215 h between July 2009 and June 2010 (2.5% of the time over a 1-year period). Assuming three scenarios of sea-level rise of 20, 40, and 60 cm, all within the range of the Intergovernmental Panel on Climate Change (IPCC) AR4's projections, it was found that the duration of inundation will be prolonged from the present percentage of 2.5% to 6%, 13%, and 24% of the year, respectively. Furthermore, the field survey carried out by the authors shows that inundation reached up to a height of 47 cm above the roads of Can Tho downtown. [ABSTRACT FROM AUTHOR]

In this paper, climate change impact on flood frequency has been investigated in Bagmati River Basin of Nepal using biascorrected global climate model (GCM) precipitation output. The research reported in this paper employed a high- resolution (approximately 20-km) daily GCM precipitation and temperature output of Meteorological Research Institute (MRI), Japan. Comparison of observation and GCM data pointed out that the MRI-GCM precipitation consists of significant biases in frequency and intensity values. Quantile-quantile mapping method of GCM bias correction was applied for minimizing the biases in precipitation frequencies and intensities. Concept of homogeneous precipitation regions was introduced to link the uneven observation data stations and GCM grid cells. Analyses of return period curves, shape, and scale factors at different observation stations enabled delineation of three homogeneous precipitation regions. Accordingly, regional quantile-quantile bias-correction technique was developed for minimizing biases in MRI-GCM precipitation output. A distributed rainfall-runoff model enabled generation of streamflow series using bias-corrected GCM output for 1979-2003 and 2075-2099 periods, as current and future scenarios, respectively. Finally, comparative flood frequency analyses were carried out for the simulated annual daily maximum streamflow series of current and future climates. The analyses revealed that the climate change will result more extreme precipitation events in monsoon months and less precipitation in other months. The analyses also revealed that flood events will be significantly increased in future. The range of change in 2-100 year return period floods was from 24-40%. [ABSTRACT FROM AUTHOR]

The objective of this paper is to identify better performing Coupled Model Intercomparison Project phase 3 (CMIP3) global climate models (GCMs) that reproduce grid-scale climatological statistics of observed precipitation and temperature for input to hydrologic simulation over global land regions. Current assessments are aimed mainly at examining the performance of GCMs from a climatology perspective and not from a hydrology standpoint. The performance of each GCM in reproducing the precipitation and temperature statistics was ranked and better performing GCMs identified for later analyses. Observed global land surface precipitation and temperature data were drawn from the Climatic Research Unit (CRU) 3.10 gridded data set and re-sampled to the resolution of each GCM for comparison. Observed and GCM-based estimates of mean and standard deviation of annual precipitation, mean annual temperature, mean monthly precipitation and temperature and Köppen-Geiger climate type were compared. The main metrics for assessing GCM performance were the Nash-Sutcliffe efficiency (NSE) index and root mean square error (RMSE) between modelled and observed long-term statistics. This information combined with a literature review of the performance of the CMIP3 models identified the following better performing GCMs from a hydrologic perspective: HadCM3 (Hadley Centre for Climate Prediction and Research), MIROCm (Model for Interdisciplinary Research on Climate) (Center for Climate System Research (The University of Tokyo), National Institute for Environmental Studies, and Frontier Research Center for Global Change), MIUB (Meteorological Institute of the University of Bonn, Meteorological Research Institute of KMA, and Model and Data group), MPI (Max Planck Institute for Meteorology) and MRI (Japan Meteorological Research Institute). The future response of these GCMs was found to be representative of the 44 GCM ensemble members which confirms that the selected GCMs are reasonably representative of the range of future GCM projections. [ABSTRACT FROM AUTHOR]

Future projections of precipitation at regional scales are vital to inform climate change adaptation activities. Therefore, is it important to quantify projected changes and associated uncertainty, and understand model processes responsible. This paper addresses these challenges for southern Africa and the adjacent Indian Ocean focusing on the local wet season. Precipitation projections for the end of the twenty-first century indicate a pronounced dipole pattern in the CMIP5 multimodel mean. The dipole indicates future wetting (drying) to the north (south) of the climatological axis of maximum rainfall, implying a northward shift of the ITCZ and south Indian Ocean convergence zone that is not consistent with a simple "wet get wetter" pattern. This pattern is most pronounced in early austral summer, suggesting a later and shorter wet season over much of southern Africa. Using a decomposition method we determine physical mechanisms underlying this dipole pattern of projected change, and the associated intermodel uncertainty. The projected dipole pattern is largely associated with the dynamical component of change indicative of shifts in the location of convection. Over the Indian Ocean, this apparent northward shift in the ITCZ may reflect the response to changes in the north-south SST gradient over the Indian Ocean, consistent with a "warmest get wetter" mechanism. Over land subtropical drying is relatively robust, particularly in the early wet season. This has contributions from dynamical shifts in the location of convection, which may be related to regional SST structures in the southern Indian Ocean, and the thermodynamic decline in relative humidity. Implications for understanding and potentially constraining uncertainty in projections are discussed. [ABSTRACT FROM AUTHOR]

I investigate the intraday effects of rain on the demand for indoor leisure. To do so, I use sub-daily museum attendance and weather data to reveal a dynamic response to precipitation that would be obscured using day-level data. I find that the magnitudes and signs of the effects of rainfall vary significantly throughout the day. In some hours, the predicted increase in visitors is nearly three times larger than would be expected from estimates using daily measures. Many individuals appear to actively adjust their plans throughout the day in response to rain, while others’ attendance depends upon prior weather forecasts of rain. Further analysis reveals that visit duration also increases during rainy periods, and visitors are more likely to attend pay-to-enter special exhibits. International visitors make up a greater share of total visitors during periods of observed precipitation. More broadly, this paper establishes the viability and value of working with widely available sub-daily rainfall data to uncover these dynamics. [ABSTRACT FROM AUTHOR]

Reanalysis data show an increasing trend in Arctic precipitation over the 20th century, but changes are not homogenous across seasons or space. The observed hydroclimate changes are expected to continue and possibly accelerate in the coming century, not only affecting pan-Arctic natural ecosystems and human activities, but also lower latitudes through the atmospheric and ocean circulations. However, a lack of spatiotemporal observational data makes reliable quantification of Arctic hydroclimate change difficult, especially in a long-term context. To understand Arctic hydroclimate and its variability prior to the instrumental record, climate proxy records are needed. The purpose of this review is to summarise the current understanding of Arctic hydroclimate during the past 2000 years. First, the paper reviews the main natural archives and proxies used to infer past hydroclimate variations in this remote region and outlines the difficulty of disentangling the moisture from the temperature signal in these records. Second, a comparison of two sets of hydroclimate records covering the Common Era from two data-rich regions, North America and Fennoscan-dia, reveals inter- and intra-regional differences. Third, building on earlier work, this paper shows the potential for providing a high-resolution hydroclimate reconstruction for the Arctic and a comparison with last-millennium simulations from fully coupled climate models. In general, hydroclimate proxies and simulations indicate that the Medieval Climate Anomaly tends to have been wetter than the Little Ice Age (LIA), but there are large regional differences. However, the regional coverage of the proxy data is inadequate, with distinct data gaps in most of Eurasia and parts of North America, making robust assessments for the whole Arctic impossible at present. To fully assess pan-Arctic hydroclimate variability for the last 2 millennia, additional proxy records are required. [ABSTRACT FROM AUTHOR]

This paper studies the long-term variability of frequency of atmospheric blockings over Western Siberia in 1948-2015 based on the data of three reanalysis projects. We revealed a decreasing blocking frequency for eight of twelve months. However, since the estimated trends of blocking frequency are small comparing to the significant amplitude of interannual variations, we proposed to divide the entire studied period into several quasi-decadal intervals that differ both in the amplitude of interannual fluctuations of blocking frequency and in trends. The effect of Western Siberian blockings imposed on synoptic and climatic variability of meteorological parameters in Asia was studied. The study demonstrated that in summer teleconnection patterns in temperature and precipitation fields are of the close sign-alternating structure; this indirectly indicates that in Western Siberia the blocking is a part of a large-scale wave mechanism. Like the Ural blockings, the blockings occurring over Western Siberia affect meteorological characteristics within the East Asian monsoon area. In winter time they contribute to lower surface temperature and decreased precipitation in Southeast Asia. In summer during blocking events over Western Siberia, precipitation increases in the East Asian monsoon area. [ABSTRACT FROM AUTHOR]

Reliable knowledge of the near-future climate change signal of extremes is important for adaptation and mitigation strategies. Especially compound extremes, like heat and drought occurring simultaneously, may have a greater impact on society than their univariate counterparts and have recently become an active field of study. In this paper, we use a 12-member ensemble of high-resolution (7 km) regional climate simulations with the regional climate model COSMO-CLM over central Europe to analyze the climate change signal and its uncertainty for compound heat and drought extremes in summer by two different measures: one describing absolute (i.e., number of exceedances of absolute thresholds like hot days), the other relative (i.e., number of exceedances of time series intrinsic thresholds) compound extreme events. Changes are assessed between a reference period (1971–2000) and a projection period (2021–2050). Our findings show an increase in the number of absolute compound events for the whole investigation area. The change signal of relative extremes is more region-dependent, but there is a strong signal change in the southern and eastern parts of Germany and the neighboring countries. Especially the Czech Republic shows strong change in absolute and relative extreme events. [ABSTRACT FROM AUTHOR]

The Romanian Plain, covering a surface area of about 52 600 sq.km and stretching along the Danube, is one of the largest agricultural regions in the European Union. It presents diverse ecological conditions in four major zonal units, steppe, silvo-steppe, forest zone and its large Danube floodplain. In this context, the assessments of climate change, specifically of those climatic elements like temperature and precipitation which may have an important impact on various economic sectors, represent a necessary scientific support for end-users to envisage sustainable development strategies. This paper presents 1) the evaluation of the regional climatic model RCA4 driven by the ERA-Interim reanalysis and five general climatic models under historical forcing, 2) the adjustment of the bias identified in the simulations compared to the observation data using the Delta Change method, and 3) the projected changes of seasonal mean temperature and precipitation in the Romanian Plain for the mid-term period 2021-2050 under the RCP4.5 scenario compared with the reference period 1971-2000 of ROCADA observations. [ABSTRACT FROM AUTHOR]

Extreme precipitation plays a major role in flooding events and their occurrence and intensity are expected to increase. Because climate models are the only tools for providing quantitative projections of precipitation, flood risk management for the future climate may be based on the simulation of such events. The goal of the paper is to develop a spatiotemporal statistical model for extremes that is particularly suited to climate model outputs, which are transient and lie on a regular grid. Using the statistical model proposed, projected precipitation return levels for the coming climate over North America are estimated. [ABSTRACT FROM AUTHOR]

In other to improve the ability of decisionmakers to prepare for and deal with the unforeseen circumstances resulting from climate change as consequences of precipitation fluctuations, extreme and torrential rainfall. It is important to provide a more complete understanding of the range and likelihood of rainfall patterns a location could receive using a probabilistic model whose parameters might complement or even replace such common measures as the mean, median, variance, minimum, maximum and quartile values as major descriptors of rainfall at such location. Daily precipitation totals can be approximated by the gamma distribution as it is bounded on the left at zero and positively skewed indicating an extended tail to the right which suit the distribution of daily rainfall and accommodate the lower limit of zero which constrains rainfall values. This paper presents the comparison between Maximum Likelihood Estimation (MLE) of closed & open form solutions and Method of Moment Estimation (MME) of location and scaling parameters of the twoparameter gamma distribution, the parameters were estimated using MME and MLE with their performance adjudged and the result obtained showed that the closedform solution of the MLE outperformed the open form solution and MME by comparing their estimates for the scaling parameter. [ABSTRACT FROM AUTHOR]

According to the geographic latitude and proximity to the Aegean and Adriatic Sea, in a sense Macedonia belongs to the Mediterranean climate, but because of the stress relief it has a variable climate. These climatic features are presented with essentially the Pollog hollow where Sharr, Korab, and Rudoka mountains, on the border with Albania, measures to prevent infiltration of humid air coming from the Adriatic Sea. Therefore, due to this the Pollog hollow is characterized with not a lot of precipitation such as the Adriatic coast. The distribution of air pressure has significant influence on thermal conditions and climate in this hollow. Pressing air in January mainly declines moving toward the South, while in July is moving toward the southeast. In relation to this, air currents are directed to these directions. Air currents during the summer and winter move from larger geographical width toward smaller ones and thereby reduce the temperature influence: Although, the character of the climate over certain areas is influenced by many factors, in this paper particular attention will be given to changes of temperature, winds, air, humidity and rainfalls. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [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]