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This article deals with the spatio-statistical analysis of temperature trend using Mann-Kendall trend model (MKTM) and Sen's slope estimator (SSE) in the eastern Hindu Kush, north Pakistan. The climate change has a strong relationship with the trend in temperature and resultant changes in rainfall pattern and river discharge. In the present study, temperature is selected as a meteorological parameter for trend analysis and slope magnitude. In order to achieve objectives of the study, temperature data was collected from Pakistan Meteorological Department for all the seven meteorological stations that falls in the eastern Hindu Kush region. The temperature data were analysed and simulated using MKTM, whereas for the determination of temperature trend and slope magnitude SSE method have been applied to exhibit the type of fluctuations. The analysis reveals that a positive (increasing) trend in mean maximum temperature has been detected for Chitral, Dir and Saidu Sharif met stations, whereas, negative (decreasing) trend in mean minimum temperature has been recorded for met station Saidu Sharif and Timergara. The analysis further reveals that the concern variation in temperature trend and slope magnitude is attributed to climate change phenomenon in the region. [ABSTRACT FROM AUTHOR]

Based on data from 1966 to 2018, the present study analyses precipitation trends in the Zohreh–Jirahi basin in Iran. The homogeneity of data was estimated based on the Kolmogorov–Smirnov method. Missing data were reconstructed using inverse distance weighted (IDW) and ordinary-linear-kriging methods. The results were evaluated by the root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2). A multidimensional raster was generated containing precipitation values related to the statistical period years, and time-series data were produced in array format per unit area. Based on the period range, 34,267 points underwent the time-series analysis, and the trend change was assessed based on the Mann–Kendall method. The Sen’s slope was evaluated using yearly and monthly scales in these points, followed by producing raster maps. The IDW was selected with an R2 value of 0.95 as the optimal method of missing data reconstruction in this time period based on the model evaluation. The results showed no significant trends on a yearly scale, but on the monthly scale, December–April–November–August–September showed the highest ascending trends, respectively, February–December–March–May exhibited the highest descending trend, respectively, and June–July–September showed no trends. The maximum and minimum mean Sen’s Slope were estimated for December (0.213) and February (–0.68), respectively. Water resources management is inevitable, particularly in the agricultural sector as the main consumer with macro socioeconomic dimensions. Given the notable impact of water supply time to optimise and increase productivity, the current study can contribute to revising the cultivation patterns and time in the region. The recharge of aquifers, the storage process, and the consumption process should be compatible with forthcoming changes. [ABSTRACT FROM AUTHOR]

The current study focuses on the altering historical rainfall data analysis and its variability in Kolkata (Kolkata Municipal Corporation), a metropolitan city in India. The research area experiences detrimental urban floods (pluvial floods) at near-annual regularity during the monsoon, and during the pre-monsoon seasons it commonly experiences water shortage problems. Analysing trends and temporal variability of rainfall over 120 years from 1901 to 2020 is the main objective of this study. The original Mann-Kendall (M-K) test has been applied to the rainfall dataset in conjunction with Sen's Slope Estimator using Python 3.10, after the Durbin-Watson (DW) statistic initially suggested that there is no serial correlation effect. The M-K test, with a Kendall's tau of 0.17058 (significant at a 5% level), shows an upward trend in annual rainfall between 1901 and 2020. The Sen's slope, which measures the rate of change annually, has a value of 2.48152. Regression analysis and other dispersion measures are also used in this study to investigate the monthly rainfall trend and its variability. The phase-wise (30-year) analysis of annual rainfall variability reveals a considerable variation over 120 years. While fitting the linear regression line month by month over the entire period, mostly negative trends were found in the pre-monsoon and positive trends in the monsoon and post-monsoon seasons. The findings of this analysis could be useful to urban planners for water supply and management in the study area. The primary concern of planners for effectively managing rainwater and the accompanying issues should be the growing variability of annual precipitation. [ABSTRACT FROM AUTHOR]

Analysis of rainfall distribution and its changing pattern plays a vital role in managing water resources in a region. This work examined the spatio-temporal variability and trend of rainfall on yearly and season-wise scales during 1971–2013 in the Wainganga river basin situated in middle India. The Mann–Kendall (MK) test was implemented for identifying the temporal variation in rainfall trends. The magnitude of this changing trend was estimated by applying Sen's slope (SS) method. A paired sample t-test was also employed to appraise the statistical significance of changes in rainfall data. The results of MK and SS tests show both upward and downward trends. The results show positive and negative trends in the south-eastern and northwestern parts of the study area for annual rainfall. The monsoon rainfall also shows very close proximity with annual rainfall data trends. The t-test states that the observed changes in precipitation are statistically significant. After trend and pattern analysis, state-space models (SSMs) were used to predict rainfall for future scenarios. Four SSMs (single, double, and triple exponential, autoregressive integrated moving average (ARIMA)) were employed for rainfall prediction. The analysis shows that the ARIMA is best for rainfall prediction with architecture of (0,0,0) (2,1,0) and can be used in Wainganga River basin. [ABSTRACT FROM AUTHOR]

Understanding local-scale climate change is vital to developing adaptive strategies in the face of the century-old river of global warming posing a threat to humanity. This study focuses on assessing temperature and rainfall trends in Beni City, using monthly and yearly (1990–2020) weather station data. Climate variability was analysed using the standardised variable index, and rainfall concentration patterns were highlighted using the precipitation concentration index (PCI). The climate trends were analysed by using the Mann–Kendall test and Sen's slope estimator. The findings indicated that the Tmin is 18.82±0.62°C, and Tmax is 28.22±0.75°C, resulting in a mean temperature of 23.52±0.57°C. The annual and seasonal temperature trend analysis indicated that a significant warming trend was observed in both Tmin and Tmax. Beni City's precipitation trends also showed a mean annual rainfall of 1988.38±416.59 mm, with significant year-to-year variations. Annual rainfall analysis exhibited a slight upward trend; meanwhile, the seasonal trend analysis revealed an increase in rainfall during Mar–Apr–May (MAM) and Aug–Sep–Oct–Nov (ASON) seasons with roughly no discernible trend during Dec–Jan–Feb (DJF), and Jun–Jul (JJ) seasons. Overall, annual and seasonal analyses of specific temperature and rainfall patterns have shown pronounced warming and increased rainfall in the study area. Research highlights: The study reveals significant trends in temperature and rainfall in Beni city, Democratic Republic of Congo, over a 31-year period (1990–2020). Both minimum and maximum temperatures show significant warming trends, with the most recent decade witnessing substantial increases in maximum temperatures. Rainfall patterns exhibit variations, with a slight upward trend in annual rainfall, although the 1990s experienced a notable decrease in precipitation. Monthly analyses highlight specific temperature and rainfall patterns with some months experiencing pronounced warming and increased rainfall. [ABSTRACT FROM AUTHOR]

Rainfall seasonality in Serbia is examined trough the analysis of several indices: seasonality index (SI), individual seasonality index ( SI i) , and replicability index (RI). Based on data from 14 synoptic stations that are well distributed over Serbian territory, spatial distribution of general seasonality index SI ¯ , mean individual seasonality index SI ind ¯ , and RI are analyzed in two subperiods (1961–1990 and 1991–2020). The modified Mann–Kendall test (MMK) and Sen's slope methods are used to investigate the possible trends and its magnitudes in time series of SI i . The values of SI ¯ show that precipitation regime in Serbia is very equitable or equitable with definite wetter season. For the entire Serbian territory, the values of RI are low, indicating that the month of maximum rainfall occurs over large spread of months along the studied periods. The existence of significant negative correlation between RI and longitude is found. Results show a highest influence of the North Atlantic Oscillation and East Atlantic/West Russia pattern on rainfall seasonality in Serbia. [ABSTRACT FROM AUTHOR]

This study explores the spatiotemporal variability and determinants of rainfall patterns during the March to May (MAM) season in Rwanda, incorporating an analysis of teleconnections with oceanic–atmospheric indices over the period 1983–2021. Utilizing the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) dataset, the study employs a set of statistical tools including standardized anomalies, empirical orthogonal functions (EOF), Pearson correlation, the Mann–Kendall (MK) trend test, and Sen's slope estimator to dissect the intricacies of rainfall variability, trends, and their association with large-scale climatic drivers. The findings reveal a distinct southwest to northwest rainfall gradient across Rwanda, with the MK test signaling a decline in annual precipitation, particularly in the southwest. The analysis for the MAM season reveals a general downtrend in rainfall, attributed in part to teleconnections with the Indian Ocean Sea surface temperatures (SSTs). Notably, the leading EOF mode for MAM rainfall demonstrates a unimodal pattern, explaining a significant 51.19% of total variance, and underscoring the pivotal role of atmospheric dynamics and moisture conveyance in shaping seasonal rainfall. The spatial correlation analysis suggests a modest linkage between MAM rainfall and the Indian Ocean Dipole, indicating that negative (positive) phases are likely to result in anomalously wet (dry) conditions in Rwanda. This comprehensive assessment highlights the intricate interplay between local rainfall patterns and global climatic phenomena, offering valuable insights into the meteorological underpinnings of rainfall variability during Rwanda's critical MAM season. [ABSTRACT FROM AUTHOR]

In this study, we evaluated the spatiotemporal variability and trends of hydro-climatic time series over the Modjo watershed, central Ethiopia using long-term records of precipitation, temperature, and river flow. In the study, the modified Mann–Kendall trend test was used to identify temporal trends, and Sen's slope estimator was employed to determine trend magnitude at multiple scales. Results of the study show that the spatial variability of annual and seasonal rainfall has decreased from north to south and west to east, whereas this was increased for the evapotranspiration (ETo) over the study watershed. Based on the trend tests, the annual and main rainy season flow exhibit significantly decreasing trends, with magnitudes of −19.2 mm/yr and −18.82 mm/yr, respectively, at a 95% confidence level. Whereas, the rainfall and ETo experienced monotonic trends during most of the wet season months and the annual total. The study highlights that the drop in river flow may be better explained by human activities, as seen by the weak association with climatic indicators. Water resources and irrigated agricultural production systems may be at risk in the area due to the unpredictability and declining trend in the river flow. Therefore, the study suggests appropriate watershed management, enhanced alternative water management techniques, and efficient use of the available water resources in the future. [ABSTRACT FROM AUTHOR]

This study presents a statistical analysis of maximum precipitation amounts at different time intervals in Dobrudja - a historical region in Romania, with semi-arid mid-latitude climate, spanning over the entire historical period of measurements available for each weather station taken into consideration. The data provided by the National Meteorological Administration have different time spans for each weather station, starting with 1948 (at Constanţa weather station). Two methodologies were used for data recording: the pluviographs being used during the last century, and the automatic weather sensors, which have been introduced into general use starting with 2008. In this study, a sub-hourly temporal scale was used to estimate extreme rainfalls: 5, 10, 15, 20, 25, 30 minutes. Then, the corresponding evolution trends were calculated over the entire period of reference (1948-present day), with Mann-Kendall and Sen's slope tests being applied (cases with p-level < 0.05 have been considered statistically significant). The probability for extremely high rainfall amounts to occur in very short periods of time and consequently, the resulting rainfall intensities have also been computed by means of Gumbel distribution. Our findings show that, despite rather scarce rainfall amounts, mostly due to the prevalent mid-latitude semi-arid conditions (the annual rainfall amounts in Dobrudja hardly exceed 400 mm/year), when occurring, they turn into downpours, mounting up to 21 mm in 5 minutes (two events exceed 20 mm) and sometimes 10 mm in one minute (one event). [ABSTRACT FROM AUTHOR]

This study focuses on modeling and predicting extreme rainfall based on data from the Southern Highlands region, the critical for rain-fed agriculture in Tanzania. Analyzing 31 years of annual maximum rainfall data spanning from 1990 to 2020, the Generalized Extreme Value (GEV) model proved to be the best for modeling extreme rainfall in all stations. Three estimation methods–L-moments, maximum likelihood estimation (MLE), and Bayesian Markov chain Monte Carlo (MCMC)–were employed to estimate GEV parameters and future return levels. The Bayesian MCMC approach demonstrated superior performance by incorporating noninformative priors to ensure that the prior information had minimal influence on the analysis, allowing the observed data to play a dominant role in shaping the posterior distribution. Furthermore, return levels for various future periods were estimated, providing guidance for flood protection measures and infrastructure design. Trend analysis using p value, Kendall's tau, and Sen's slope indicated no statistically significant trends in rainfall patterns, although a weak positive trend in extreme rainfall events was observed, suggesting a gradual and modest increase over time. Overall, the study contributes valuable insights into extreme rainfall patterns and underscores the importance of L-moments in identifying the best fit distribution and Bayesian MCMC methodology for accurate parameter estimation and prediction, enabling effective measures and infrastructure planning in the region. [ABSTRACT FROM AUTHOR]

The problem of detecting hydrometeorological trends is still a concern. In this study, monthly, seasonal, and annual temperature and precipitation variations in the Van Province of Türkiye are assessed using both traditional such as Mann–Kendall (MK) and Spearman's Rho (SRHO) and graphical such as Innovative trend significance test (ITA-ST) and Innovative polygon trend analysis (IPTA) methods. In order to determine trend slope and change-point detection, Sen's Slope and Sequential Mann–Kendall tests are also used, respectively. The findings show that the MK, SRHO, and ITA-ST approaches detect a decreasing trend for annual total precipitation at the Erciş and Başkale stations. Additionally, the MAM and SON seasons at Erciş and the SON season at Gevaş stations also show a noticeably decreasing trend. All stations have an increasing trend at a 95% significant level for annual mean temperatures. Except Gevaş station, all four seasons have an increasing trend for temperature series. Results from the IPTA show that for precipitation data, the transition from May to June exhibits the highest trend length. In addition, for temperature data, the minimum trend length and slope are captured in the transition from July to August. In general, ITA-ST and IPTA are superior to MK and SRHO at identifying trends and that the outcomes of these methods are significantly more suitable to visual inspection and linguistic interpretation. Different hydro-climatological variables can be analyzed more flexibly and thoroughly utilizing innovative methodologies. [ABSTRACT FROM AUTHOR]

Farmers usually do not know the precise output that is affected by climatic factors such as temperature and rainfall and are characterized by inter-annual variability, part of which is caused by global climate change. No study covers the influences of climate factors on yield and yield risk in the context of chickpea farming in Andhra Pradesh, India. In this context, this study aimed to investigate the trends in climate change variables during Rabi season (October to January, 1996-2020) and evaluated their variability on chickpea yields across different agro-climatic zones in Andhra Pradesh by employing Just and Pope production function. Four non-parametric methods-Alexandersson's Standard Normal Homogeneity Test, Buishand's Range Test, Pettitt's Test and Von Neumann's Ratio Test are applied to detect homogeneity in the data. Mann--Kendall (MK) test and Sen's slope (SS) method were employed to analyze monthly rainfall trends and minimum and maximum temperature trends. Results of Just and Pope (panel data) quadratic and Cobb-Douglas methods revealed that monthly minimum temperature positively influenced the mean yield of chickpea (0.22% and 0.16%, respectively). However, rainfall (-0.41% and -0.31%) and maximum temperature (-0.08% and -0.04%) negatively influenced the mean yield of chickpea under quadratic and Cobb-Douglas models, respectively. Accordingly, rainfall (0.08% and 0.06%) and maximum temperature (0.83% and 0.72%) positively influenced the yield variability and minimum temperature (-0.77% and -0.67%) reduced yield variability of chickpea under quadratic and Cobb- Douglas models respectively. In view of these findings, it is imperative to advocate the farmers about the importance of cultivating drought-tolerant chickpea varieties, drought-proofing and mitigation strategies, micro-irrigation practices and improving their access to agro-meteorological information towards sustainable chickpea cultivation in Andhra Pradesh. [ABSTRACT FROM AUTHOR]

The study was conducted to analyze spatial and temporal variations of lightning activity over Sri Lanka and the surrounding coastal belt region bounded by 5.75–10.00 N and 79.50–89.00 E. Flash data collected by the Lightning Imaging Sensor (LIS) on NASA's Tropical Rainfall Measuring Mission (TRMM) satellite from 1998 to 2014 and the Lightning Imaging Sensor placed on the International Space Station (ISS) from 2018 to 2021 were used for the study. The Mann-Kendall test and Sen's slope estimator were applied to annual and seasonal lightning data from 1998 to 2014 to identify the trends in the TRMM dataset. A positive slope of 0.23 was obtained for annual flash densities, while a slope of 0.956 was obtained for First Inter-Monsoon (FIM) seasonal data. Considering the ISS data, the annual variation of lightning activity in 2020 displays the lowest flash density, whereas the highest is represented in 2019 with a value of 10.48 flashes km−2 year−1. The highest mean flash density is observed in Colombo in 2019 at a value of 34.85 flashes km−2 year−1. Overall, April displayed the highest annual flash distribution from 2018 to 2021, whereas the second peak was mostly viewed around September and November. All districts have displayed a significant amount of lightning during April for the period 2018 to 2021. FIM displayed the highest lightning distribution over the country. When considering the seasonal variation, districts belonging to the wet zone and intermediate zone displayed most flashes during the FIM. [ABSTRACT FROM AUTHOR]

The Dongting Lake basin, located in the middle Yangtze River region, has long been under the threat of climate change. However, there has been a lack of comprehensive analysis and research on the long-term trends and interactions among hydrometeorological factors within the region. To address this gap, this study collected data from 31 meteorological stations in the region and employed statistical analysis methods, including the non-parametric Mann–Kendall test, Sen's slope test, and cross-wavelet analysis. The results revealed significant increases in temperatures, especially in the spring season, while summer, winter, and annual rainfall also exhibited a significant increase. However, spring and autumn rainfall showed a non-significant decrease, and there was a clear decreasing trend in annual streamflow. Interestingly, evaporation demonstrated a significant increasing trend. The annual average temperature and annual runoff exhibited approximately negative correlations in the 6–10-year resonance period and positive correlations in the 4–6-year resonance period. There are significant positive resonance periods in the relationship between annual precipitation and annual runoff within the range of 0–12 years, indicating that precipitation has a substantial impact and serves as the primary source of runoff. Furthermore, there was a transition between "abundance" and "dry" periods in the annual runoff around 4 a, occurring before and after 1973 and 2005. The change points in annual precipitation and runoff were identified as 1993 and 1983. [ABSTRACT FROM AUTHOR]

This study explores variations and trends in dry/wet days and spells over Banas River basin during 1961–2020. For this, daily rainfall data acquired from Water Resources Department of Rajasthan, India have been utilised. The variations have been identified in relation to number (dry/wet days and spells), mean and maximum length of dry/wet spells. For identifying trends, Mann–Kendall (MK), innovative trend analysis (ITA) and Sen’s slope estimator tests have been executed, whereas change points have been detected with the help of Pettit, Buishand range, standard normal homogeneity and Neumann ratio tests. In Banas River basin, dry days have been found much higher (330 days) as compared to wet (35 days), while the number of dry/wet spells has been found almost identical (18). A decreasing trend in dry days has been detected, whereas wet days have increased. In addition, change point detection tests have detected 1993 as the year of noteworthy change in dry/wet days and spells, whereas most of the stations witnessed such change in 1995 and 2009. These results will be valuable for water resource and risk reduction managers in managing the risks of drought and flood over the Banas River basin. [ABSTRACT FROM AUTHOR]

The article provides a long-term trend analysis of the Kesinga catchment daily gridded rainfall at a (0.25° × 0.25°) high spatial resolution from 1901 to 2020 (120 years). The trend in seasonal and annual rainfall was detected using rank-based nonparametric statistical tests, namely Spearman's rho and Mann-Kendall test, which are used for detecting monotonic trends in time series data at the 5% significant level, smoothing curve, Sen's slope test, and a plot of innovative trend analysis. The results showed that statistically significant trends had a pattern with both positive (increasing) and negative (decreasing) trends, with positive and negative trends evident in the winter and negative trends shown in the monsoon, PREMON, and annual seasons. The middle of the study area revealed the highest negative trend, and the lower Kesinga catchment showed the lowest negative annual rainfall trend. In the entire Kesinga catchment, the seasonal data and annual rainfall both showed statistically significant and non-significant patterns. Consistently, the MK and SR tests were both conducted at the validated significance level. In various contexts, the statistically significant massive trend that has occurred was negative (70%). If the current pattern continues in the future, there will be a scarcity of water and more strain on the control of water resources at the given grids in corresponding temporal scales. [ABSTRACT FROM AUTHOR]

Afghanistan, as a landlocked country located within central and southwestern Asia, has an arid to semi-arid climate. Most of the people are involved in agricultural activities, and a major part of the country's gross domestic product depends on agriculture, but the country has the lowest water storage capacity. Consecutive periods of drought and rapid snowmelt due to climate change have made it more challenging for suitable water resource management practices. This study investigates the historical meteorological drought characteristics across the whole country by employing the Reconnaissance Drought Index for the period 1979–2019 using data from 55 meteorological stations. Trends in precipitation and temperature are also investigated using the Mann-Kendall's and the Sen's slope statistical tests. A four-decadal countrywide drought map is generated. Extreme and severe droughts were observed in 1999 and 2000 across the whole country. Moderate drought events have started to occur with a frequency of 3 to 5 years since 1999. The decadal annual rainfall values in each river basin indicate that rainfall has decreased in the last two decades with a significant decline in 1999-2008. The trends of increase in temperature and decrease in precipitation are indications of rapid climate change in the country, especially in the south, west, and southwest regions. Due to the intensity and frequency of the droughts, river flow rates have decreased; and therefore, there is a need for the upstream and downstream neighboring countries to come to terms with the phenomenon of a new normal in the hydrological cycle and accordingly revise new water sharing treaties. [ABSTRACT FROM AUTHOR]

This study presents an analysis of long-term rainfall variability and trends in the summer monsoon region of Southeast Asia, encompassing Lao People's Democratic Republic (Lao PDR), Thailand, Vietnam, Cambodia, and Myanmar, as well as their respective river basins. Utilizing Climate Hazards Group InfraRed Precipitation with Station Data (CHIRPS) having a spatial resolution of 5 km spanning from 1981 to 2021, rainfall variability and trends were examined. Data preprocessing and geospatial analysis were conducted using R-Studio and ArcGIS software. The Mann–Kendall (MK) test and Sen's slope estimator were employed for annual and seasonal rainfall trend analysis. Myanmar exhibited the highest average annual rainfall of 2137 mm during the study period, while Thailand had the lowest (1641 mm). Over the past four decades, the Peninsula Malaysian Basin experienced the highest average annual rainfall (2691 mm), whereas the Chao Praya Basin recorded the lowest (1311 mm). Increasing trends in rainfall were observed across all five countries and nine major river basins. Vietnam displayed the highest annual rainfall trend of 5.63 mm/year, while Lao PDR exhibited the lowest trend (3.16 mm/year). Among the river basins, the Chao Phraya Basin demonstrated the maximum annual rainfall trend (11.21 mm/year), while the Peninsula Malaysia Basin had the minimum trend (1.21 mm/year). These findings could significantly contribute to climate change monitoring in the region and can aid policymakers in sectors such as agriculture, urban planning, and disaster management. [ABSTRACT FROM AUTHOR]

Climate change is the most serious threat to agricultural productivity. Ethiopia's agricultural sector is affected by climate change. The northern part of Ethiopia is among the drought prone and topographically diversified areas. The purpose of this study was to examine the impact of climate change on crop yields, assess the pattern of rainfall maximum and lowest temperatures and assess the trajectory of selected crop yields. Historical weather station and National Aeronautics and Space Administration (NASA) power data were collected from 1981 to 2020. The Mann–Kendall (MK) trend test and Sen's slope (SS) method estimator were employed to estimate the trends and the direction of the trend. RClimDex package is used for climate extreme analysis. Nine rainfall and 11 temperature indices from a list of 27 extreme rainfall and temperature indices were used. The study found that the rainfall showed a significant decreasing and insignificant decreasing trend in Farta and Yilmana Densa districts, respectively. Maximum and minimum temperatures in both sites showed increasing trends. Rainfall happenings become more unanticipated, owing to the precipitation concentration index and anomaly trends. The majority of the indicators for extreme rainfall at both sites showed a downward trend. With the exception of the duration of cold spells, the annual lowest value of the daily minimum temperature, cold days and cold nights, the majority of the extreme temperature indices at both sites showed an increasing trend. The principal crop yields were connected with rainfall and temperature fluctuation, according to Pearson's product–moment correlation results, although the effects varied by crop and region. In summary, rising temperatures and decreasing precipitation may have a negative influence on agricultural activities, especially crop productivity. [ABSTRACT FROM AUTHOR]

Bangladesh has been ranked as one of the world's top countries affected by climate change, particularly in terms of agricultural crop sector. The purpose of this study is to identify spatial and temporal changes and trends in long-term climate at local and national scales, as well as their implications for rice yield. In this study, Modified Mann-Kendall and Sen's slope tests were used to detect significant trends and the magnitude of changes in temperature and rainfall. The temperature and rainfall data observed and recorded at 35 meteorological stations in Bangladesh over 65-years in the time span between the years 1949 and 2013 have been used to detect these changes and trends of variation. The results show that mean annual Tmean, Tmin, and Tmax have increased significantly by 0.13°C, 0.13°C, and 0.13°C/decade, respectively. The most significant increasing trend in seasonal temperatures for the respective Tmean, Tmin, and Tmax was 0.18°C per decade (post-monsoon), 0.18°C/decade (winter), and 0.23°C/decade (post-monsoon), respectively. Furthermore, the mean annual and pre-monsoon rainfall showed a significant increasing trend at a rate of 4.20 mm and 1.35 mm/year, respectively. This paper also evaluates climate variability impacts on three major rice crops, Aus, Aman, and Boro during 1970–2013. The results suggest that crop yield variability can be explained by climate variability during Aus, Aman, and Boro seasons by 33, 25, and 16%, respectively. Maximum temperature significantly affected the Aus and Aman crop yield, whereas rainfall significantly affected all rice crops' yield. This study sheds light on sustainable agriculture in the context of climate change, which all relevant authorities should investigate in order to examine climate-resilient, high-yield crop cultivation. [ABSTRACT FROM AUTHOR]

Temporal variability analysis of rainfall is important for planning agricultural crop production activities, designing water resource systems, and conducting climatological research, particularly climate change analysis. This study aimed to analyze the temporal trends of annual (total and 1-d maximum) and seasonal (total) rainfall observed in Region IV-A. Historical rainfall data were collected from seven weather stations scattered all over the region. Each dataset was initially subjected to a series of homogeneity tests (standard normal homogeneity, Pettitt's, Buishand's range, and von Neumann ratio), followed by trend analysis using both linear regression analysis and non-parametric methods [Mann-Kendall (MK), modified MK (MMK), and Sen's slope (SS) estimator]. All data series proved to be homogeneous except for the annual and seasonal (DJF) total rainfall in Sangley Point station. The results of the homogeneity test in Sangley Point in annual and DJF timescale suggest the consideration of the breakpoint on the years of 1984 and 1999, respectively, for trend analysis. Temporal trend based on linear regression showed a weak correlation between rainfall of various time scales and time in years, with only three stations showing a significant trend at a 5% significance level - namely, Los Baños (DJF, 2.86 mm/yr), Tayabas (DJF, 7.99mm/yr), and Sangley Point (JJA, 9.32 mm/yr). On the other hand, both MK and SS indicates a significant increase in the seasonal (DJF) total rainfall in both stations of Ambulong (1.04 mm/yr) and Los Baños (2.68 mm/yr). Overall, the results of trend analysis revealed an increasing trend in the cumulative rainfall across timescales in most stations in the region which has an implication on the timing of the optimum cropping patterns in agricultural areas and on the hydrology of the watersheds in the region. This study has generated new knowledge and information that could prove useful for agricultural production management and for proper planning, design, and management of water resource systems. [ABSTRACT FROM AUTHOR]

Location-specific information on annual and seasonal rainfall trends has immense utility in devising crop planning as well as water resource management in West Bengal. We assessed long-period (1901–2020) trends and magnitudes of seasonal and annual rainfall across districts of West Bengal. The non-parametric Mann-Kendall (MK) test, sequential Mann-Kendall (SQMK) test, and Sen's slope estimator were applied to the gridded (0.25° × 0.25°) rainfall dataset. Results revealed that both the annual and seasonal rainfall of West Bengal increased non-significantly (p>0.05), except for the winter season, which experienced a non-significant decrease. Annual rainfall across a majority of the districts in sub-Himalayan West Bengal (SHWB) declined non-significantly. On the contrary, a significant (p<0.05) increase in annual rainfall was observed across most of the districts of Gangetic West Bengal (GWB) at the rate of 1.8 mm year−1 to 2.9 mm year−1. Monsoon rainfall increased significantly over Gangetic West Bengal (GWB) at 1.4 mm year−1 to 2.1 mm year−1, while it declined significantly in Dakshin Dinajpur district at 3.2 mm year−1 of SHWB. Post-monsoon rainfall increased significantly over GWB at the rate of 0.5 mm year−1 to 0.9 mm year−1. The winter rainfall decreased non-significantly across all the districts. Normalized rainfall anomaly (NRA) revealed that 17% of the study period experienced surplus (NRA>1) rainfall, while another 17% received deficit (NRA>−1) rainfall. Nearly 70% year received normal monsoon rainfall (NRA = ±1) and 16% year deficit and 14% year surplus rainfall. The SQMK test for seasonal rainfall showed a general trend change point around 1960 and 1970 in both the district and state-level annual rainfall. [ABSTRACT FROM AUTHOR]

This study investigates possible rainfall and drought trends using data from 38 rainfall stations in the Medjerda basin (northeast of Algeria) over 54 years (1965–2018). Drought-related data were calculated with the Standardized precipitation index (SPI). The Mann–Kendall test was used to find positive or negative precipitation trends. The magnitude of these trends was calculated using Sen's slope method. According to the analysis, a decrease during the spring precipitation season was observed. Furthermore, the authors found the maximum increasing (decreasing) precipitation magnitude to be 2.14 mm/season (− 4.41 mm/season) in winter (spring). In addition, the magnitude of the precipitation trend per year ranged from − 6.26 to 2.54 mm/year, with an average reduction of 39% for the entire basin. From the outcomes of drought trend analysis, it can be inferred that for a short-time scale, the innovative trend analysis method exhibited a negative trend for the minimum and maximum SPI values. Drought severity was found to have increased during severe and extreme wet episodes, directly affecting Algeria's frequently drought-affected agricultural regions, such as the Merdja plain and the irrigated perimeters of Sedrata and Zouabi. Considering the long-time scales, an increase was detected in drought severity and a decline during severe and extreme wet episodes. These findings show that the southeastern and central parts of the Medjerda basin's long-term water resources have been severely affected, which negatively impacts the newly-constructed Ouldjet Mellegue dam in Tébessa province. [ABSTRACT FROM AUTHOR]

The study explores the seasonal rainfall and rainy days trend in the Himalayan Kingdom of Bhutan. Mann-Kendall and Sen's slope test was applied to detect the trend and magnitude of the trend for both the rainfall and rainy days. The trends are also analyzed with respect to the elevation of the climatic stations. Further, an attempt has been made to recognize the El-Ni ño- Southern Oscillation (ENSO)-rainfall interaction using station-based rainfall with the ENSO cycle considering the period of 33 years. Cross-correlation of ENSO and rainfall with respect to elevation has also been presented. The trend analysis showed that in the localized regions, both the rainfall and rainy days trend was significantly declining, however, the trend in most of the stations is hardly conspicuous which may be attributed to the influence of the orographic phenomena. From the ENSO-rainfall assessment, it was observed that rainfall in the southern foothills correlates negatively with the ENSO phenomena indicating intense rainfall after 1–2 months of the cooling phase of the Pacific Ocean. However, such an ENSO effect is not observed in the majority of the meteorological stations which may be attributed to the location of the station in the mountainous region where the topography affects the rainfall variation. [ABSTRACT FROM AUTHOR]

Regional weather variability depends on various meteorological variables such as temperature and rainfall. The current research focuses on the variability and trends in annual aerosol optical depth (AOD), temperature (T), and rainfall (RF) in 11 Vidarbha districts. The annual trend analysis of AOD, T, and R is determined using the non-parametric Sen slope and Mann–Kendall (MK) test at a 5% significant level from 1980 to 2019. Annual T and AOD indicate a substantial increase in this study, whereas rainfall shows a non-significant trend (MK, test) over the study period. According to Sen's slope trends, the relatively high rainfall area (Chandrapur = 1.273 and Garchiroli = 4.06) got positive trends, but Gondia and Bhandara districts have negative (Sen's slope = − 2.79 and − 2.56) trends. The moderate rainfall areas are showing a less negative Sen slope (Wardha = − 0.21, Washim = − 1.13 and Yavatmal = − 2.75), whereas Nagpur districts' Sen's slope shows a positive value (Sens's slope = 0.72). The assured rainfall area districts show Sen's slope trends are positive (Akola = 0.45, Amravati = 1.17 and Buldana = 0.42). Sen's slope trend indicates rising rainfall, whereas negative trends indicate decreasing rainfall in the time series. This study has also looked at the effect of RF, AOD, and T on the last two decades' cash crop production (2000–2019) for Vidarbha districts. The relationship between rainfall departure (DRF) and cash crop yield has also been highlighted. Five cash crops, such as cotton (Ct), total cereals (TCrl), total oilseeds (TOsd), total pulses (TPS), and sugarcane (Sc), are selected for the present study. [ABSTRACT FROM AUTHOR]

The western Himalayan region is susceptible to minor climate changes because of its fragile ecology, which might threaten the valley's prestigious ecosystems and socio-economic components. The Himalayas's local climate and weather are vulnerable to and interlinked with world-scale climatic changes since the region's hydrology is predominantly dominated by snow and glaciers. The Himalayas, notably the Jammu and Kashmir region in the western Himalayas, has clearly shown distinct and robust evidence of climate change. This study used observed data to examine the climatic variability and trends of change in precipitation and temperature for the Kashmir valley between 1980 and 2020. Gulmarg, Pahalgam, Kokernag, Qazigund, Kupwara, and Srinagar (Shalimar) meteorological stations in the Kashmir valley were studied in detail for long- and short-term as well as localized fluctuations in temperature and precipitation. The annual temperature and precipitation fluctuations were calculated using Sen's slope approach, and the sloping trend was determined using linear regression. The research showed statistically insignificant growing trends in maximum and minimum temperatures throughout the Kashmir valley. The average annual temperature in the Kashmir valley increased by 1.55 °C during the last 41 years (from 1980 to 2020), with a higher rise in maximum and minimum temperature by 2.00 and 1.10 °C, respectively. However, precipitation showed a non-significant decreasing trend concerning time series analysis over 1980 to 2020 in Kashmir valley. Results of annual average maximum temperature at all the stations revealed that Pahalgam (2.2 °C), Kokernag (1.8 °C), and Kupwara (1.8 °C) displayed a steep upsurge and statistically significant trends; however, annual average minimum temperature followed an increasing trend from 1980 to 2020 at all the stations except Shalimar. However, non-significant declining trends in precipitation were recorded at all the locations in Kashmir valley. This changing pattern of temperature and precipitation could have significant environmental consequences, affecting the western Himalayan region's food security and ecological sustainability. [ABSTRACT FROM AUTHOR]

The climate trend is one of the most dominant factors likely to affect the structure and function of the wetlands of Keoladeo and Bhitarkanika. This study compares the climate conditions and trends of two Ramsar sites in India, the Bhitarkanika and Keoladeo wetlands. Forty-year climate data (1980-2020) were used to identify and measure the strength of possible climate change in these habitats. Mann-Kendall's test, Sen's slope estimates and Sequential Mann-Kendall's (SQMK) test were used to study the long-term and short-term trends of rainfall and climate of Bhitarkanika and Keoladeo. The results of this study matched those of earlier studies conducted at a larger geographical scale. The study indicated significant changes in the parameters of rainfall and temperature trends. A significant increase in annual rainfall (Sen's slope = 5.24E+00, New p value = 2.75E-02) was observed at Bhitarkanika, while the trend at Keoladeo was positive but insignificant. Both ecosystems are getting warmer. Seasonal changes were also identified in the rainfall and temperature. The summer temperature rise was comparatively stronger at Keoladeo (Tmax: Sen's slope=2.33E-02, New p value=2.45E-02; Tmin: Sen's slope=2.68E-02, New p value=1.39E-02). An increase in monsoon temperature was also recorded in both ecosystems. Both wetland ecosystems are vulnerable to climate change, but the Keoladeo wetland is at higher risk because stronger temperature changes have occurred in the past four decades. The SQMK test also suggests a more erratic climate in the Keoladeo wetlands. The study highlights the comparative changes occurring in both ecosystems. This is the first study identifying both long-term and short-term changes in these wetlands at a smaller geographical scale. [ABSTRACT FROM AUTHOR]

Climate change is an environmental challenge for rural communities that rely heavily on rainwater-based agriculture. The main goal of this study is to investigate spatiotemporal variability and trends in rainfall and temperature in southern Ethiopia. Extreme temperature and rainfall indices were computed using the ClimPACT2 software. The detection and quantification of trends in rainfall and temperature extremes were analyzed using a nonparametric modified Mann–Kendall (MMK) test and Sen's slope estimator. Results indicated that the mean annual rainfall has a declining trend at Boditi School and Mayokote stations with a statistically significant amount at magnitudes of 0.02 mm and 0.04 mm, respectively. The highest average monthly rainfall in the catchment was observed in the months of April, May, June, July, and August up to maximum rainfall of 117.50 mm, 177.43 mm, and 228.84 mm in Bilate Tena, Boditi, and Mayakote stations, respectively. On a seasonal scale, rainfall in Bilate Tena station was highly variable in all months, ranging from 49.54% to 126.92%, and three seasons except spring which showed moderate variation at 40.65%. In addition, the three locations over the catchment exhibited varied drought signs such as severe (1.28 < SRA < 1.65) and extreme drought (SRA > 1.65). The temperature indices, on the other hand, exhibited a warming trend over the catchment which was observed through an increased annual number of warm days (TX90p) and warm nights (TN90p) ranges from 0.274 to 6.03 and 0.274 to 3.16, respectively. The annual maximum value of the daily maximum temperature (TXx) ranges from 30.10 to 33.76°C in the three agroecological zones and showed low, medium, and high values in Dega, Woyna Dega, and Kola agroecologies, while the annual maximum value of the daily minimum temperature (TNx) ranged between 17 and 17.44°C at Dega and Kola, respectively. Therefore, based on trends in rainfall variability and persistent temperature rise, appropriate adaptation strategies should be adopted. [ABSTRACT FROM AUTHOR]

The variability, intensity, and distribution of rainfall have drawn a lot of interest globally and especially in nations where rainfed agriculture is the norm. This article uses rainfall data from the Rwanda Meteorology Agency for the years 1981 to 2021 to delineate and analyze rainfall variability and trends in the Kayonza District. The time series were grouped using the K-means clustering technique based on computed Euclidean distance, the total within-cluster sum of squares, and the elbow plot technique to determine the optimal number of clusters. The coefficient of variation measures was employed to analyze rainfall variability, while Sen's slope and the Mann–Kendall (MK) test were used, respectively, to find trends and changes in magnitude. The results indicated four near homogeneous zones named region one to four. The dry seasons indicated higher variability compared to rainy seasons and annual rainfall total with a variability of 128–142% over the southeastern part during June to August (JJA) season, while a variability of 16–48% was observed over most of the district during both annual and rainy seasons. It was further noted that the areas in the central part of the Kayonza District indicated a significant increasing trend at a significance level of 95% and above during January to February (JF), September to December (SOND), and on annual basis, while March to May (MAM) and JJA season exhibited no significant trend. The findings of this study are essential for creating adequate mitigation strategies to lessen climate change's effects on agriculture as well as other socioeconomic sectors. [ABSTRACT FROM AUTHOR]

Variability in rainfall and temperature results in different impacts on agricultural practices. Assessesment of variability and trend of rainfall and temperature for the district of Musanze in Rwanda was conducted using six meteorological stations for a period of 37 years, ranging from 1981 to 2018, and data were obtained from Rwanda Meteorology Agency. Musanze district is located in highland areas of Rwanda, understanding the variability and trend in rainfall and temperature is paramount to increase the uptake of climate information and support strategic orientation. The Mann–Kendall nonparametric test and modified Mann–Kendall were used to assess the trend in rainfall and temperature, whereas Sen's slope estimator was used to assess the magnitude of change. The results from both methods showed much similarity and consistency. The assessment of variability and trend in rainfall and temperature in Musanza district indicated that increasing temperature and decreasing rainfall trends gave an indication of changes in variability and trend in rainfall and temperature. The annual pattern revealed a substantial downward tendency of −25.7% for Nyange, the only station with constant decreasing trend over all seasons, DJF, −61.4%, SON, −12.2%, JJA, −40.3%, and MAM, −4.35. Temperature analysis for both maximum and minimum indicated increasing trend which was signal for constant warming up in the area. The results from coefficient of variation indicated a high disparity in rainfall variation from June to August which ranged between 51 and 74%, and other seasons changes were moderate. [ABSTRACT FROM AUTHOR]

Streamflow alteration is one of the most noticeable effects of changes in rainfall patterns (both intensity and amount) in the Himalayan region. Additionally, the impact of climate change on the localized rainfall patterns is particularly significant, which is more crucial in the Himalayas. This study carries out a comprehensive analysis on temporal variability of the rainfall and its relation to streamflow in a typical mountain river basin, located in the southern aspect of central Himalayas. The primary objective of this study is to analyze seasonal and annual rainfall trends across rain gauge stations within the selected Kali Gandaki (KG) River Basin. Monthly rainfall data were used to examine the rainfall and streamflow trends. Mann-Kendall (MK) trend test, Sen's slope, and sequential MK (SQMK) analysis were employed to evaluate monotonic trends on homogenized time series data. Our findings revealed the formation of an anticlockwise hysteresis loop between streamflow and rainfall within the catchment. Understanding the relationship between streamflow and rainfall would provide a foundation for effective water resources management. [ABSTRACT FROM AUTHOR]

In the present study, long-term rainfall trend was analyzed using the traditional Mann–Kendall (MK) test and innovative trend analysis (ITA) method for annual and seasonal rainfall series for 20 districts of Punjab state for the period of 1951–2021. The autocorrelation test was performed to detect the presence or absence of serial correlation in the rainfall series. Based on the autocorrelation test, MK or modified Mann–Kendall (MMK) test and Sen's slope test were applied to determine the direction and magnitude of the rainfall trend, respectively. The ITA which revealed the presence of a trend graphically was compared with the traditional MK/MMK test. The autocorrelation test showed that all the annual rainfall series are serially independent, except for the Hoshiarpur. The MK/MMK test revealed the presence of a decreasing trend in annual rainfall series of all districts, except for Fatehgarh Sahib, Kapurthala, Patiala, and Tarn Taran of the central zone and Muktsar of the south west zone. The computed probable change point year was 1998. The innovative trend slope revealed the presence of a significant decreasing trend for the districts of Punjab missed by the traditional MK/MMK test. The highest decrease (− 4.5 mm/year) in annual rainfall was observed at Gurdaspur of the north zone and Faridkot of the south west zone. The ITA showed the statistically significant decreasing trend in annual rainfall for all the districts of the south west zone at 1% significance level. The analysis using ITA determined the presence of hidden trends missed by the traditional MK/MMK test. The decreasing pattern in rainfall over most of the districts and high irrigation requirement for largely growing paddy crop of Punjab indicated the urgent need of efficient planning of water resources. The study may guide planners and policy makers for effective implementation of the rainwater harvesting and groundwater recharge strategies to improve the status of water resources in the entire Punjab. [ABSTRACT FROM AUTHOR]

This study aims to investigate spatiotemporal variability, trends, and anomaly in rainfall and temperature in the Sidama region, Ethiopia. The TerraClimate gridded dataset on a monthly time scale for 30 years (1991–2020) with a horizontal resolution of approximately 4 km was used for the study. Trends in annual and seasonal rainfall and temperature were assessed using a nonparametric test (Mann-Kendal test) and Sen's slope to test the statistical significance and magnitude of trends (increase/decrease), respectively. Our findings revealed that annual rainfall, summer (Hawado), and spring (Badhessa) rainfall have shown an increasing trend in most parts of the region, except for its northwest parts. We found a low annual rainfall variability (CV < 13%) over the southeastern and northwestern parts of the region. Rainfall variability revealed the difference in both time and space across the region. Six drought years (1999, 2001, 2002, 2003, 2012, and 2019) with different magnitudes were identified across the region. Annual average maximum (up to 0.4 °C decade−1) and minimum (up to 0.25 °C decade−1) temperatures revealed significantly increasing trends across the region. The standardized anomaly in the mean annual temperature indicated that the years in the recent decade (2011–2020) are getting warmer compared to the past two decades (1991–2010) due to natural and anthropogenic activities causing weather extremes in the region. The results of this study for rainfall contradict the other studies in the rift valley part of the region. Therefore, we suggest appropriate climate change adaptation strategies so that there is high rainfall and temperature variability across the region and between seasons. [ABSTRACT FROM AUTHOR]

This study aims to examine the spatiotemporal variability and trends of rainfall over Somalia using the Mann-Kendall (MK) test and Sen’s slope estimator to investigate the trend and magnitude of the rainfall changes and the arithmetic mean and coefficient of variation (CV) to examine the rainfall variability. To achieve this aim, the gridded monthly satellite rainfall datasets from Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) for the period between 1991 and 2020 were used. Results show that annual rainfall generally exhibits bimodal rainfall distribution, March to May (Gu) and September to November (Deyr), though southern coastal regions receive extended Gu rains into July and northwestern regions experience early onset of Deyr rains. The study further showed that a low and moderate degree of inter-annual variability (CV<30%) is observed in most parts of the country, while on a seasonal basis, the short rainy season (Deyr) has a higher rainfall variability (CV>30%) compared to the primary rainy season (Gu) and most regions in the south receiving highest amounts of rainfall experience highest variability (CV>50%) during Deyr season. Furthermore, the trend analysis of the annual rainfall showed a non-significant increasing trend. On a seasonal basis, the trends of Gu rainfall decreased in some regions while trends for the Deyr season increased in most regions. However, rainfall trends observed were not statistically significant throughout the country at a significance level of 0.05. [ABSTRACT FROM AUTHOR]

Study on rainfall pattern of a region over a number of years is very useful for crop planning and irrigations scheduling. The present study deals with the probability and trend analysis of monthly rainfall in selected rain gauge stations scattered over the entire state of Haryana. Probabilities for drought, normal and abnormal events for monthly rainfall have been worked out using monthly rainfall data for 42 years (1970- 2011), covering 27 rain gauge stations in the state of Haryana. Analysis indicated that drought months are more probable than normal months while normal months are more probable than abnormal months. The monotonic trend direction and magnitude of change in rainfall over time have been examined using the Mann-Kendall test and Sen's slope estimator tests. Using the Mann-Kendall test and Sen's slope estimator, the significant decrease in annual rainfall was noticed at Ballabgarh and Thanesar, While in monsoon rainfall, a significant decrease was noticed at Thanesar and Narnaul. But Sirsa is the only district which shows a significant increase in annual and monsoon rainfall. In probability analysis the highest per cent of normal, draughts and abnormal months was observed for Ambala, Hassanpur and Dujana respectively. [ABSTRACT FROM AUTHOR]

Maize is one of the most important cereal food crops, and it can be grown all year in various agroecological zones. However, its vegetative growth and yield are susceptible to rainfall and temperature variability. As a result, the analysis of rainfall and temperature variability and trend was urgently needed in maize-growing agroecology zones to restructure the production system. The aim of the study was to examine rainfall and temperature variability and trends for developing a climate-resilient maize farming system in major agroecology zones in northwest Ethiopia. The study was implemented in low productive agroecology zones (LPZ), medium productive agroecology zones (MPZ), and high productive agroecology zones (HPZ) of northwest Ethiopia using daily time series climate data during the period 1987–2018. The coefficient of variation (CV), precipitation concentration index (PCI), rainfall anomaly index (RAI), and standardized precipitation (SPI) were applied to examine rainfall variability. Mann–Kendall's and Sen's slope estimator trend tests were used to detecting the statistical significance of changes in rainfall and temperature. Statistically significant increasing trends for annual maximum and minimum temperatures were recorded for all maize-producing agroecology zones. The mean annual temperature has exhibited a significant warming trend of 0.12 to 0.54°C per decade. The average annual rainfall has decreased by 38 to 67 mm per decade in all maize agroecology zones. Our research also showed that droughts now happen every one to three years; even consecutive droughts were seen in 2009, 2010, and 2011. For this reason, it could be required to develop a system of climate-resilient maize farming to address the issues of both global warming and the sub-Saharan countries that make up our study area. Climate-resilient maize agronomic activities have been determined by analyzing the onset, length of the growth period (LGP), and cessation date. Accordingly, the lower and upper quartiles of the date of onset of rainfall were in a range of May 9 to June 2, respectively; the length of the growth period (LGP) during the rainy season ranges from 97 to 232 days, and the cessation date of rainfall was November 1. Therefore, the short- to long-maturing maize varieties can be planted from May 9 to June 2 and can begin to be harvested in the first week of November under the current climatic circumstances. [ABSTRACT FROM AUTHOR]

Mann–Kendall trend test and Sen's slope estimator method were used to find out significant changes in extreme climate indices for daily temperature and precipitation in Cherrapunji over the period from 1979 to 2020. In this study, 21 precipitation and temperature-based extreme climate indices were calculated using RClimDex v 1.9-3, among which six were derived from the number of days above nn mm rainfall (Rnn) according to India Meteorological Department (IMD) convention and the rest 15, in accordance with the Expert Team on Climate Change Detection and Indices (ETCCDI). It was observed that, among all the indices, consecutive dry days (CDD), summer days (SU25) and very light rainfall (VLR) days increased significantly with 0.54, 1.58 and 0.14 days/yr, respectively, while only consecutive wet days (CWD) decreased significantly with 0.36 days/yr. A slight negative trend was observed in the case of tropical nights (TR20) and among the other precipitation indices as well. Again, the indices associated with daily maximum temperature increased significantly with 0.06–0.07°C/yr. For the indices associated with daily minimum temperature, almost no change or a slight negative change was observed, except a significant positive trend in February and significant negative trend in November for monthly minimum of daily minimum temperature (TNN) only. The analysis revealed that some of the extreme climate indices which explain the climatic conditions of Cherrapunji have shown statistically significant change over the period of 42 years and if this trend continues, then Cherrapunji will be under threat when it comes to climate change. [ABSTRACT FROM AUTHOR]

In this study, auto-correlated Mann–Kendall (MK) and Sen's slope estimator tests were utilized to determine trends of rainfall, temperatures, and characteristics of crop-growing season during 1980–2009. Moreover, the Van Belle and Hughes' for homogeneity of general trend and Pettitt's test for the occurrence of abrupt changes were applied. On monthly, Kiremt (June–September) and annual time scale, the MK-trend test for rainfall exhibited non-significant increasing trend, while in Belg (February–May) rainfall season exhibited non-significant decreasing trend at the most of the stations. On the contrary, temperatures showed significant increasing trends in annual and Belg at the 5% significant level. In Kiremt season, however, the maximum temperature showed non-significant increasing, while the minimum temperature showed non-significant decreasing trend. Results of homogeneity for general trend obtained by the Van Belle and Hughes' test seem fairly consistent with those of the MK-trend test. Moreover, results of Pettitt's test indicated a homogeneous trend in monthly, annual, and seasonal rainfall series and no break point was distinguished, except few stations. On the contrary, the abrupt changes were found to be quite variable in temperatures. The study also found that trends of growing season characteristics (June–September) have not changed significantly at the 5% significant level. Nevertheless, the high coefficient of variation in Kiremt rainfall (21–31%) as well as dry spell length (25–43%) in conjunction with the short nature of the length of growing period (68–90 days) had negative implications to crop production in the eastern zone of Tigray region. [ABSTRACT FROM AUTHOR]

The aim of this study is the detection of trends of precipitation from (1986-2020) over Târgu Mureș city. Precipitation data for 35 years were processed with MS Excel spreadsheets to find monthly, seasonal and annual variability of rainfall. The Mann-Kendall test was used for trend analysis of precipitation and the Sen's slope estimator was used for the magnitude of variation. The calculations of the two methods were performed using the MAKESENS program. The standard deviation and the coefficient of variation were used to highlight the dispersion. Results show that all three scales (annual, seasonal and monthly) show a tendency to increase rainfall. The highest monthly average of precipitation is 227.70 mm (August, 2005), and the lowest monthly average of precipitation is 0.80 mm (November, 2011). The maximum value of annual precipitation is 852.60 mm and was registered in 2005, and the minimum value was 408.70 mm registered in 2000. [ABSTRACT FROM AUTHOR]

Rainfall is the dynamic weather parameter having a significant role in the agriculture livelihood. Growth in agriculture and other related sectors depends mainly on the adequate amount and timely availability of rainfall. Variability in precipitation exerts a huge impact on human beings and agriculture. This variation gives the necessity to study the regular pattern of rainfall. The present study aims at analysing the trends in rainfall intensity across various blocks of Tiruchirappalli district using daily rainfall data for the period 1990 to 2017. Non-parametric tests such as Mann- Kendall test and Sen's slope estimator were employed for this purpose. Results revealed that two blocks showed statistically significant increasing trends (95% confidence level) and one block showed significant decreasing trend (95% confidence level) and the remaining eleven blocks showed no significant trends. [ABSTRACT FROM AUTHOR]

The global climate has changed, and there are concerns about the effects on both humans and the environment, necessitating more research for improved adaptation. In this study, we analyzed extreme temperature and rainfall events and projected future climate change scenarios for the coastal Savannah agroecological zone (CSAZ) of Ghana. We utilized the ETCCDI, the RClimDex software (version 1.0), the Mann–Kendall test, Sen's slope estimator, and standardized anomalies to analyze homogeneity, trends, magnitude, and seasonal variations in temperature (Tmax and Tmin) and rainfall datasets for the zone. The SDSM was also used to downscale future climate change scenarios based on the CanESM2 (RCP 2.6, 4.5, and 8.5 scenarios) and HadCM3 (A2 and B2 scenarios) models for the zone. Model performance was evaluated using statistical methods such as R2, RMSE, and PBIAS. Results revealed more changepoints in Tmin than in Tmax and rainfall. Results again showed that the CSAZ has warmed over the last four decades. The SU25, TXn, and TN90p have increased significantly in the zone, and the opposite is the case for the TN10p and DTR. Spatially varied trends were observed for the TXx, TNx, TNn, TX10p, TX90p, and the CSDI across the zone. The decrease in RX1day, RX5day, SDII, R10, R95p, and R99p was significant in most parts of the central region compared to the Greater Accra and Volta regions, while the CDD significantly decreased in the latter two regions than in the former. The trends in CWD and PRCPTOT were insignificant throughout the zone. The overall performance of both models during calibration and validation was good and ranged from 58–99%, 0.01–1.02 °C, and 0.42–11.79 °C for R2, RMSE, and PBIAS, respectively. Tmax is expected to be the highest (1.6 °C) and lowest (−1.6 °C) across the three regions, as well as the highest (1.5 °C) and lowest (−1.6 °C) for the entire zone, according to both models. Tmin is projected to be the highest (1.4 °C) and lowest (−2.1 °C) across the three regions, as well as the highest (1.4 °C) and lowest (−2.3 °C) for the entire zone. The greatest (1.6 °C) change in mean annual Tmax is expected to occur in the 2080s under RCP8.5, while that of the Tmin (3.2 °C) is expected to occur in the 2050s under the same scenario. Monthly rainfall is expected to change between −98.4 and 247.7% across the three regions and −29.0 and 148.0% for the entire zone under all scenarios. The lowest (0.8%) and highest (79%) changes in mean annual rainfall are expected to occur in the 2030s and 2080s. The findings of this study could be helpful for the development of appropriate adaptation plans to safeguard the livelihoods of people in the zone. [ABSTRACT FROM AUTHOR]

Climate extremes are predicted to become more frequent and severe in the future, owing to rising greenhouse gas emissions in the atmosphere. Using appropriate trend indices, this study intends to analyze the effects of climate change on rainfall variability and extreme rainfall events in the millennium city of Mumbai. The analysis was carried out for the period 1985–2020 for 2 stations and 23 stations were selected (2006–2020) later from the dense rain gauge network of Municipal Corporation of Greater Mumbai (MCGM). To comprehend the trend and behaviour of rainfall and extreme events, three statistical models were used: Mann–Kendall test, Sen's slope estimator, and simple linear regression; for abrupt change point detection, Pettitt's test, standard normal homogeneity test, Buishand's range test, and von Neumann ratio test were used. The results indicated that average annual rainfall in the study area is 2208.82 mm which is increasing at the rate of 5.18 mm/year (at 99% confidence level). The frequency of heavy (> 120 mm/day) and extreme heavy rainfall events (250 mm/day) increased over Santacruz after 1994 and in the case of Colaba, it increased after 2005. The examination of rainfall and temperature data series for abrupt change point identification suggests that several change points exist, with the highest change points occurring between 2001 and 2005. Extreme climate event scenarios shown here could have large-scale negative consequences for the ecosystem and ecological resources of the study area. [ABSTRACT FROM AUTHOR]

This study explores the spatio-temporal distribution and trends on monthly, seasonal, and annual scales of rainfall in the central Punjab districts of Punjab province in Pakistan by using observation and satellite data products. The daily observed data was acquired from the Pakistan Metrological Department (PMD) between 1983 and 2020, along with one reanalysis, namely the Climate Hazard Infrared Group Precipitation Station (CHIRPS) and one satellite-based daily Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks climate data record (PERSIANN-CDR) using the Google Earth Engine (GEE) web-based API platform to investigate the spatio-temporal fluctuations and inter-annual variability of rainfall in the study domain. Several statistical indices were employed to check the data similarity between observed and remotely sensed data products and applied to each district. Moreover, non-parametric techniques, i.e., Mann–Kendall (MK) and Sen's slope estimator were applied to measure the long-term spatio-temporal trends. Remotely sensed data products reveal 422.50 mm (CHIRPS) and 571.08 mm (PERSIANN-CDR) mean annual rainfall in central Punjab. Maximum mean rainfall was witnessed during the monsoon season (70.5%), followed by pre-monsoon (15.2%) and winter (10.2%). Monthly exploration divulges that maximum mean rainfall was noticed in July (26.5%), and the minimum was in November (0.84%). The district-wise rainfall estimation shows maximum rainfall in Sialkot (931.4 mm) and minimum in Pakpattan (289.2 mm). Phase-wise analysis of annual, seasonal, and monthly trends demonstrated a sharp decreasing trend in Phase-1, averaging 3.4 mm/decade and an increasing tendency in Phase-2, averaging 9.1 mm/decade. Maximum seasonal rainfall decreased in phase-1 and increased Phase-2 during monsoon season, averaging 2.1 and 4.7 mm/decade, whereas monthly investigation showed similar phase-wise tendencies in July (1.1 mm/decade) and August (2.3 mm/decade). In addition, as district-wise analyses of annual, seasonal, and monthly trends in the last four decades reveal, the maximum declined trend was in Sialkot (18.5 mm/decade), whereas other districts witnessed an overall increasing trend throughout the years. Out of them, Gujrat district experienced the maximum increasing trend in annual terns (50.81 mm/decade), and Faisalabad (25.45 mm/decade) witnessed this during the monsoon season. The uneven variability and trends have had a crucial imprint on the local environment, mainly in the primary activities. [ABSTRACT FROM AUTHOR]

Coastal areas are among the densely populated regions in the world with growing population and subsequent increasing demands for water. Understanding the long-term variations in available water resources aids in efficient water conservation, management and allocation strategies. The present study investigated the long-term trends in groundwater depths (GWDs) for pre-monsoon and post-monsoon seasons in the coastal district of Kollam during the period 1996∼2017, where groundwater is the primary source for domestic and agricultural uses during summer season. The trends examined using the modified Mann Kendall (mMK), innovative trend analysis (ITA) and Sen's slope estimator indicated a decreasing pre-monsoon GWD trends at an average of −0.5m/decade in 63% of the wells, while increasing post-monsoon GWD trends at an average rate of +0.43m/decade in 72% of the wells at 5% significance level. The singular spectrum analysis (SSA) captured monotonic as well as non-monotonic trend trajectories for the GWDs. About 41% wells exhibited a correlation below — 0.5 (p<0.05) between post-monsoon GWDs and JJASO (June, July, August, September and October) rainfall totals. The increasing post-monsoon GWDs could be related to recent changes in the southwest monsoon patterns over the peninsular India. Adequate planning and management of existing water resources could impart better control on water conservation strategies under the scenario of climate change. [ABSTRACT FROM AUTHOR]

This paper examined seasonal and annual rainfall trends of the Mae Klong River Basin in Thailand. Monthly rainfall data of eight stations were used for the period 1971--2015. The non-parametric Mann-Kendall test was used to detect trends whereas the slope of the trends was determined by Sen's slope method. Datasets with significant serial correlation were corrected by the pre-whitening approach. For the dry season, 5 out of 8 stations showed increasing rainfall trends while for the wet season, 50% of the stations showed increasing trends. On an annual scale, 75% of the stations exhibited increasing rainfall trends. The upper region of the basin which contributes inflows to the Srinagarind and Vajiralongkorn Dams had increasing annual rainfall trends. For the entire basin, the trend analysis found increasing rainfall on both seasonal and annual scales. The results of this study can help water resource managers prepare better assessments and planning of water resources in the basin. [ABSTRACT FROM AUTHOR]

The rise of global surface temperature due to warming climate is expected to increase the intensity and occurrence of extreme precipitation events. Previous studies in Southeast Asia revealed complex variations in changes of precipitation extremes. This study presents a spatial–temporal analysis on changes of precipitation extremes in Peninsular Malaysia by utilizing long‐term daily rainfall records at 64 observed stations during 1989–2018. The modified Mann–Kendall and Sen's slope tests were performed to detect the significance and magnitude of trends in eight extreme precipitation indices recommended by the Expert Team on Climate Change Detection and Indices. Statistically significant increasing trends are observed for four of these extreme indices in the annual assessment. Spatial analysis demonstrates an obvious contrast between wet and dry regions in patterns of precipitation extremes. Seasonal analysis reveals the intensity and frequency of wet extremes are enhanced significantly during the northeast monsoon season. Significant correlations are found between precipitation extremes and El Niño–Southern Oscillation, particularly in the northern, eastern and southwest regions. Collectively, the evidence presented suggests that the occurrence of precipitation extremes in Peninsular Malaysia tends to be more frequent and intense over the year and is closely associated with the combined effects of tropical monsoon cycles and El Niño–Southern Oscillation. [ABSTRACT FROM AUTHOR]

This paper summarises an updated climate change trends analysis—developed for the period from 1 October 1864 to 30 September 2021 within the scope of a Horizon 2020-funded project to increase climate resilience in European coastal cities—for a representative site of the Lisbon Metropolitan Area (Portugal). By using long ground-based daily records of rainfall and surface temperature at the Lisboa-Geofísico climatological station, the analysis aimed to identify (i) long-term and recent climate trends in rainfall and temperature, (ii) changes in extreme rainfalls, heatwaves, and droughts, and (iii) possible effects of the coupled changes of minimum and maximum daily temperatures (Tmin and Tmax, respectively) on drought development based on the diurnal temperature range (DTR) indicator. To detect these trends and quantify their magnitude, the Mann−Kendall and Sen's slope estimator tests were implemented. The analysis of the mean annual temperatures indicated that the study area has warmed ∼1.91 °C through the 157 analysed years. Results evidenced statistically significant upward trends in both Tmin and Tmax, and in the number of Tmax heatwave days. In what concerns the extreme hydrological events, the analysis of annual maximum rainfall series and peaks-over-threshold (POT) techniques showed more frequent and intense events in recent years, reaching up to ∼120.0 mm in a single day. With regard to drought, the study proved that the characterisation based on the commonly used standardised precipitation index (SPI) might differ from that based on the standardised precipitation evapotranspiration index (SPEI), as the latter can take into account not only rainfall but also temperature, an important trigger for the development of drought. According to the SPEI index, severe and extreme drought conditions have been more frequent in the last 60 years than in any other recorded period. Finally, a decreasing DTR trend towards the present was found to influence evapotranspiration rates and thus drought characteristics. [ABSTRACT FROM AUTHOR]

New dammed reservoirs are expected to have a significant effect on the regional hydrocycle, but the detailed patterns may not be well understood. Regional climate change is likely to cause soil erosion uncertainty by affecting rainfall erosivity. In the present study, local precipitation and rainfall erosivity were investigated to determine the impounding influence of the Three Gorges Reservoir. Daily erosive precipitation, from 1980 to 2020, was categorized into four intensity levels (light, moderate, heavy, and very heavy), as well as extreme rainfall, to understand their contribution to erosivity. It was found that the impoundment significantly affected local precipitation, with both heavy precipitation and the relative erosivity showing a substantial declining trend (Sen’s slope ¼ 2.141, p, 0.05). The Mann–Kendall test indicated an abrupt change point around the year 2002, evidencing the effect of the reservoir impoundment (since 2003). Reservoir impoundment redistributed the intensity levels of erosive precipitation, leading to a 24.3% decrease in the erosivity of heavy precipitation and an 8.2% increase in the moderate category. The unimodal distribution of monthly precipitation was altered to a bimodal distribution with peaks in July and September, resulting in a longer but lower-risky erosion period of high concern. The fluctuations of Rx1day and Rx5day were obviously flattened after impoundment, with a 54.2% peak reduction in relative erosivity on average. Results indicated that heavy rainfall (including extreme rainfall) was reduced, and annual precipitation and erosivity both had a more even seasonal distribution following reservoir impoundment. [ABSTRACT FROM AUTHOR]

The Amazon region is of interest to the scientific community because it has the largest tropical rainforest in the world and has plentiful water and solar energy which are essential for climate regulation. In this context we analyzed the annual and seasonal rainfall of the Brazilian Legal Amazon Region over a period of 30 years (1986 to 2015) using data from 268 pluviometric stations from the ANA HIDROWEB database to provide information for the management and planning of the water resources. The spatial and temporal dynamics of the rainfall were analyzed using these data along with isohyet maps of the estimates of rainfall and rainfall volume; the trends and magnitudes of rainfall were analyzed by nonparametric Mann–Kendall and Sen's slope tests respectively. The results indicated a mean precipitation of 2070 mm/year. The Legal Amazon is a region with wide rainfall variability both spatially (the precipitation trend increases from the south to the north of the region) and temporally (both seasonally and interannual). The statistical tests indicated both positive and negative trends in and magnitudes of precipitation. In general an average decrease in precipitation of 5 mm per year was estimated in the Legal Amazon. In addition the rainfall behavior is not homogeneous and is influenced by atmospheric systems and phenomena especially the most intense ENSO events. Important changes are occurring in pluviometry and have the potential to cause hydrological and climatic risks. [ABSTRACT FROM AUTHOR]