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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]

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]

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]

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 Langat River Basin provides fresh water for about 1.2 million people in the Langat and Klang valleys. Any change in the pattern of rainfall could affect the quantity of water in the basin. Studying the pattern of change in rainfall is crucial for managing the available water resources in the basin. Thus, in this study, for the first time, both parametric and non-parametric methods were employed to detect rainfall trend in the basin for the period 1982-2011. The trends were determined at 30 rainfall stations using the Mann-Kendall (MK) test, the Sen's slope estimator and the linear regression analysis. Lag-1 approach was utilized to test the serial correlation of the series. On the annual scale, it was found that most of the stations in the basin were characterized with insignificant trends. The significant trends were found only at the four stations, namely 44301, 44305, 44320 and 2719001. The results of the seasonal trend analysis showed that most of the stations during the northeast monsoon (NEM) and the inter monsoon 1 (INT1) seasons and half of the stations during the southwest monsoon (SWM) season experienced insignificant positive trends. To the contrary, for the inter monsoon 2 (INT2) season, majority of the stations showed negative trends. It was found that during the NEM season the station 44301, for the INT1 season stations 44301, 2719001 and 3118069 were established as having significant changes, while in the SWM season station 2917001 and during the INT2 season, the stations 2615131 and 44301 showed significant trends. It is worth mentioning that the maximum rainfall occurs in inter-monsoon seasons. [ABSTRACT FROM AUTHOR]

Studying rainfall patterns is very important because agricultural production and flood conditions depend on proper water management. Therefore, accurately identifying trends in climate scenarios is essential to achieve this goal. This study, therefore, analyses rainfall trends using the Mann–Kendall test (MKT), modified Mann–Kendall test (MMKT), Spearman rank correlation (SRC), Şen slope estimator (SSE), and innovative trend analysis method (ITAM). This investigation analyses annual, monsoon, autumn, summer, and winter rainfall trends using the most extensive hydrometeorological time series from 1901 to 2020. Five such methods of trend analysis use 120 years of gridded meteorological data from the India Meteorological Department for the neighbouring four river basins Kangsabati, Keliaghai, Silabati, and Dwarkeswer in east India. For the winter period, no significant trend is detected using the MKT, MMKT, SRC, and SSE. While the ITAM detects a significant trend at 88% of grid points of the study area. During other seasons, the MKT, MMKT, SRC and SSE notice trends for 76% of grid points with less significance than the ITAM method. Overall results obtained using the ITAM and MMKT methods are proved to be more effective in detecting sensitive trends. This study can serve as scientific support for the identification and strategic mitigation of climatic change impacts on water management to reduce the risk of climate change. [ABSTRACT FROM AUTHOR]

The coastlines have been identified as the most vulnerable regions with respect to hydrological hazards as a result of climate change and variability. The east of peninsular Malaysia is not an exception for this, considering the evidence of heavy rainfall resulting in floods as an annual phenomenon and also water scarcity due to long dry spells in the region. This study examines recent trends in rainfall and rainfall- related extremes such as, maximum daily rainfall, number of rainy days, average rainfall intensity, heavy rainfall days, extreme rainfall days, and precipitation concentration index in the east coast of peninsular Malaysia. Recent 40 years (1971-2010) rainfall records from 54 stations along the east coast of peninsular Malaysia have been analyzed using the non-parametric Mann-Kendall test and the Sen's slope method. The Monte Carlo simulation technique has been used to determine the field significance of the regional trends. The results showed that there was a substantial increase in the annual rainfall as well as the rainfall during the monsoon period. Also, there was an increase in the number of heavy rainfall days during the past four decades. [ABSTRACT FROM AUTHOR]

This study has been undertaken to find out the spatiotemporal variations of rainfall and droughts over India in two future periods (2020–2059 and 2060–2099) under two SSP (SSP2-4.5 and SSP5-8.5) scenarios. Here we have selected the four most suitable Coupled Model Inter-comparison Project Phase 6 (CMIP6) Global Climate Models (GCMs) to project rainfall and drought over India. We have found that rainfall over India is on the rise under considered periods and emission scenarios with few spatial departures. The rainfall is higher under higher warming. Central India, particularly Maharashtra and Madhya Pradesh, shows an increase in rainfall in all emission scenarios. This region also shows a higher increase in rainfall variability. The rainfall variability is found to be the maximum in the northeast Himalayan region. In the future, drought frequency does not show any appreciable change but drought duration changes and shows spatial variations. An increase in drought duration is observed over northwestern parts of India, particularly over Gujarat, Rajasthan, parts of MP, UP and Haryana. [ABSTRACT FROM AUTHOR]

The present study has been carried out to investigate the past and future rainfall and temperature change scenarios over three locations (Patna, Gaya, and Bhagalpur) falling in two agro-climatic zones (IIIa and IIIb) of South Bihar, using rainfall and temperature records from the India Meteorological Department (IMD) and Global Climate Model (GCM) data from the Coupled Model Intercomparison Project Phase 5 (CMIP5). It was observed that CMIP5 models exhibit either dry or wet bias in rainfall and warm or cool bias in temperature. Multi-model ensemble (MME) using large numbers of GCMs can produce more realistic climate information, at least at the local scale where a wide range of uncertainty is exhibited. Both model and observational records indicated moderate warming in the last century, although some models revealed higher warming. Rainfall in Patna and Gaya showed a declining trend during 1901–2015, whereas Bhagalpur has shown an increasing trend. Future projection of rainfall in CMIP5 GCMs indicated an increase of 0–25% annual rainfall in all three locations, whereas the pre-monsoon rainfall may increase at a higher rate, i.e., 0–40%, than the total annual rainfall towards the end of the 21st century. It is found that the rate of increase of annual and pre-monsoon rainfall during the 2090s could be ~2 times more than the 2030s in the study locations. [ABSTRACT FROM AUTHOR]

The present study is mainly concerned with detecting the trend of run-off over the mainland of India, during a time period of 35 years, from 1971-2005 (May-October). Rainfall, soil texture, land cover types, slope, etc., were processed and run-off modelling was done using the Natural Resources Conservation Service (NRCS) model with modifications and cell size of 5×5 km. The slope and antecedent moisture corrections were incorporated in the existing model. Trend analysis of estimated run-off was done by taking into account different analysis windows such as cell, medium and major river basins, meteorological sub-divisions and elevation zones across India. It was estimated that out of the average 1012.5 mm of rainfall over India (considering the study period of 35 years), 33.8% got converted to surface run-off. An exponential model was developed between the rainfall and the run-off that predicted the run-off with an R of 0.97 and RMSE of 8.31 mm. The run-off trend analysed using the Mann-Kendall test revealed that a significant pattern exists in 22 medium, two major river basins and three meteorological sub-divisions, while there was no evidence of a statistically significant trend in the elevation zones. Among the medium river basins, the highest positive rate of change in the run-off was observed in the Kameng basin (13.6 mm/yr), while the highest negative trend was observed in the Tista upstream basin (−21.4 mm/yr). Changes in run-off provide valuable information for understanding the region's sensitivity to climatic variability. [ABSTRACT FROM AUTHOR]

Climate change is receiving more attention from researchers as the frequency of occurrence of severe natural disasters is getting higher. Tropical countries like Malaysia have no distinct four seasons; rainfall has become the popular parameter to assess climate change. Conventional ways that determine rainfall trends can only provide a general result in single direction for the whole study period. In this study, rainfall series were modelled using additive Holt-Winters method to examine the rainfall pattern in Langat River Basin, Malaysia. Nine homogeneous series of more than 25 years data and less than 10% missing data were selected. Goodness of fit of the forecasted models was measured. It was found that seasonal rainfall model forecasts are generally better than the monthly rainfall model forecasts. Three stations in the western region exhibited increasing trend. Rainfall in southern region showed fluctuation. Increasing trends were discovered at stations in the south-eastern region except the seasonal analysis at station 45253. Decreasing trend was found at station 2818110 in the east, while increasing trend was shown at station 44320 that represents the north-eastern region. The accuracies of both rainfall model forecasts were tested using the recorded data of years 2010-2012. Most of the forecasts are acceptable. [ABSTRACT FROM AUTHOR]

The summer monsoon rainfall affects most of the population of the Indian subcontinent. A slight variation of strength and spatial distribution in monsoon rains has huge societal impacts. So understanding the significance of its variability and the factors that control this variability is an imperative task. The Indian monsoon (also regarded as a global phenomenon) varies with the global climatic components like geopotential height, sea surface temperature, outgoing long-wave radiation and mean sea level pressure. The paper presents a statistical analysis of rainfall (over India) and climatic components (over the Arabian Peninsula) and the relationship between them. The period (1979–2013) shows a decrease in monsoon rainfall over the country. During this period, there was an increase in the tropospheric temperature over the Arabian Peninsula. Rainfall showed a direct relationship with the tropospheric temperature and thickness that gets stronger during the period (1979–2013). Except for the northeastern region of India, the rest showed a strong positive correlation with the middle and upper tropospheric temperature over the Arabian Peninsula while the lower tropospheric temperature showed a weak relationship. However, this correlation gets weakened during the El Nino and La Nina years. The findings will be helpful to enhance the Indian rainfall variation and the climatic factors responsible for this variation. [ABSTRACT FROM AUTHOR]

Globally, climate change has caused changes in frequency and intensity of climate extremes such as heat waves, droughts, floods and tropical cyclones. There is a need to understand the pattern of regional climate extremes to develop crucial adaptation strategies for the farming community. This paper focuses on developing the Expert Team on Climate Risk and Sector-specific Indices for rainfall, relevant for the agriculture and food security sector. The indices have been developed for Lower Vellar River sub-basin, a coastal basin in Tamil Nadu, India. Trend analysis has been done for the climatic and cropping seasons in the sub-basin. Overall, there has not been any trend in the annual rainfall index values. The monthly trend values for the different indices have mostly exhibited insignificant trends throughout the study period (1978–2015) except for a few indices. Overall, the southwest monsoon season has shown a significantly decreasing trend in the indices. The northeast monsoon season has shown insignificant trends with positive slopes for most indices. There were insignificant or no trends in the indices for the summer season. The findings from the study can be used as a guiding tool for developing adaptation strategies, for the farming community. [ABSTRACT FROM AUTHOR]