Trend In Annual Rainfall Research Articles

Analyzing Temporal Patterns of Temperature, Precipitation, and Drought Incidents: A Comprehensive Study of Environmental Trends in the Upper Draa Basin, Morocco

Quantifying variation in precipitation and drought in the context of a changing climate is important to assess climate-induced changes and propose feasible mitigation strategies, particularly in agrarian economies. This study investigates the main characteristics and historical drought trend for the period 1980–2016 using the Standard Precipitation Index (SPI), Standard Precipitation Evaporation Index (SPEI), Run Theory and Mann–Kendall Trend Test at seven stations across the Upper Draa Basin. The results indicate that rainfall has the largest magnitude over the M’semrir and Agouim (>218 mm/pa) and the lowest in the Agouilal, Mansour Eddahbi Dam, and Assaka subregions (104 mm–134 mm/pa). The annual rainfall exhibited high variability with a coefficient of variation between 35−57% and was positively related to altitude with a correlation coefficient of 0.86. However, no significant annual rainfall trend was detected for all stations. The drought analysis results showed severe drought in 1981–1984, 2000–2001, and 2013–2014, with 2001 being the driest year during the study period and over 75% of both SPEI and SPI values returned drought. Conversely, wet years were experienced in 1988–1990 and 2007–2010, with 1989 being the wettest year. The drought frequency was low (<19%) across all the timescales considered for both SPI and SPEI, with Mansour Eddahbi Dam and Assaka recording the highest frequencies for SPI-3 and SPEI-3, respectively.

Recent changes in the climatological characteristics of daily contiguous rain areas over India

This study documents the climatological feature (1951–1980) and recent changes (1981–2020) in rainfall characteristics considering the observed nearly full spectrum of rain event sizes (daily contiguous rain area (CRA) events) in all seasons over India. It is found that the low frequency very large CRA (~synoptic scale) from monsoon season contributes ~50% of annual rainfall. However, the small-sized CRA (isolated thunderstorms) are the most frequent daily rain events (~70% of annual frequency) and hence are important for rain-fed agricultural practices. The well-documented widespread drying trend in the monsoon season has manifested in the annual rainfall trend but with reduced magnitude illustrating the compensatory effect from other seasons. Spatial aggregated annual statistics show that there is no significant change in rainfall amount and frequency of occurrence of rain events in the recent past compared to the base period. However, seasonally the pre-monsoon rainfall amount has increased significantly. Annually, the number of extremely heavy CRA (EHR) events have significantly increased by ~55% owing to a significant increase in pre-monsoon and monsoon rainfall. In all seasons, small-sized extremely heavy CRA has intensified substantially by 50–200% as compared to the base period. Additionally, the rain events from areal category large (~Mesoscale Convective Complexes (MCC)) have intensified in all seasons except winter. Thus, to decrease the uncertainty in rain-fed agricultural practices and better prediction of EHR to develop effective climate change mitigation strategies; process studies beyond monsoon season and processes other than synoptic scales are also required.

Temporal Trend Analysis of Annual, Maximum, and Seasonal Rainfall in Selected Weather Stations in Region IV-A, Philippines

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.

Ecological assessment of a subtropical floodplain wetland of the Ganga basin in the context of changing climate using GIS tools

Abstract Climate change associated with anthropogenic stressors are considered the main threat to the tropical wetlands, resulting in reduced water connection followed by a decline in ecological functions. This article presents a systemic approach to assess the present ecological status of a tropical floodplain wetland concerning the fisheries and associated ecosystem services. The analysis of historic climatic data indicated significant change (increasing average annual air temperature, R2 = 0.098; decreasing total annual rainfall, R2 = 0.042). In addition, a significant reduction in the wetland area was also observed. Altogether, 45 fish species were reported in the studied wetland, of which 2 are listed as endangered and 7 are near threatened. The present study demonstrated the variation of the important fisheries-related environment and nutrient parameters of the wetland through the geographic information system (GIS)-based spatial distribution map for the reader's digest. It has been found that the provisioning ecosystem services are higher in number (n=9) followed by supporting (n=6), regulating (n=4), and cultural (n=2) ecosystem services. Finally, we have discussed some important case-specific sustainable climate-smart adaptation and mitigation approaches to strengthen the resilience and adaptive capacity of fishers.

Long‐term trend analysis in annual, seasonal and monthly rainfall in East Northeast of Brazil and the influence of modes of climate variability

AbstractThe study of rainfall trends is crucial for food security and water availability in Alagoas state, Northeast of Brazil. In this work, monthly, seasonal and annual rainfall trends have been studied (1960–2016) for homogeneous rainfall regions over the eastern part of the Northeast Brazil (ENEB) and later related to climate variability. Cluster analysis was applied to identify homogeneous rainfall regions while the Mann–Kendall (MK), modified Mann–Kendall (MMK) and Pettitt tests were used in the analysis and identification of trends on a spatial and temporal scale. To relate rainfall and climate variability modes, Spearman's correlation was used in each homogeneous region. The rainfall series provided evidence of a general decrease in rainfall in the rainy period and an increase in the dry period, mainly over the driest region. The break points of time series occurred mostly in periods of great variations in values of modes of climate variability, especially the Monthly Niño3.4 Index and the Southern Oscillation Index (SOI), both having a robust influence across the region. Moreover, the probable rainfall in the time series with trends was different in most months before and after the breakpoint. After the breakpoint, probable rainfall was lower, influenced by the breakpoint year (size of the series before and after the breakpoint), which mainly occurred in the 1980s and 1990s and presented a warm phase and a greater number of El Niño events. The MK and MMK trend tests showed the ability to detect trends, although there is no established standard on which test or version to use due to self‐correlated, nonhomogeneous series with nonrandom or nonindependent data. Rainfall is an important variable for water and food security and in the monitoring of natural disasters. The changes detected in this study can be used as reference information for public policies on water resources and future studies for Alagoas and similar regions.

The Impact of Extreme Rainstorms on Escarpment Morphology in Arid Areas: Insights From the Central Negev Desert

AbstractThe impact of climate on topography, which is a theme in landscape evolution studies, has been demonstrated, mostly, at mountain range scales and across climate zones. However, in drylands, spatiotemporal discontinuities of rainfall and the crucial role of extreme rainstorms raise questions and challenges in identifying climate properties that govern surface processes. Here, we combine methods to examine hyperarid escarpment sensitivity to storm‐scale forcing. Using a high‐resolution DEM and field measurements, we analyzed the topography of a 40‐km‐long escarpment in the Negev desert (Israel). We also used rainfall intensity data from a convection‐permitting numerical weather model for storm‐scale statistical analysis. We conducted hydrological simulations of synthetic rainstorms, revealing the frequency of sediment mobilization along the sub‐cliff slopes. Results show that cliff gradients along the hyperarid escarpment increase systematically from the wetter (90 mm yr−1) southwestern to the drier (45 mm yr−1) northeastern sides. Also, sub‐cliff slopes at the southwestern study site are longer and associated with milder gradients and coarser sediments. Storm‐scale statistical analysis reveals a trend of increasing extreme (>10 years return‐period) intensities toward the northeast site, opposite to the trend in mean annual rainfall. Hydrological simulations based on these statistics indicate a higher frequency of sediment mobilization in the northeast, which can explain the pronounced topographic differences between the sites. The variations in landscape and rainstorm properties across a relatively short distance highlight the sensitivity of arid landforms to extreme events.

Comparative Analysis of the General Attitude of Rainfall Changes in the Regions of Hail and Assir, Kingdom of Saudi Arabia

This comparative study analyzes the general rainfall in Ha'il and Assir based on the maximum daily and annual rainfall over 42 years (1976-2017). The data were collected at seven stations in Ha'il and ten stations in Assir to detect climate change phenomena there. The Shapiro-Wilk Test examined the rainfall data distribution. The Levene and ANOVA Tests examined variances of homogeneity. To analyze the general rainfall trend and its statistical significance, the study adopts the Semi-Averages Ratio, Binomial, and the Student's T-Tests. In Ha'il, the Semi-averages method results, and the Binomial Test showed a maximum annual and daily rainfall decrease. The Student's T-Test confirmed this trend for the daily and annual rainfall in Simira, Al Ha'it, Ha'il, and Al Ghazalah stations, and for the maximum daily rainfall in the stations of Simira, Al Ha'it, Uqlat Bin Jibrin, and Al Ghazala. The results revealed increasing annual rainfall in Sabah Billahmar, Al Tajir, Bani Thawr, and As Sudah. Similar trends were detected for the maximum daily rainfall in Khaybar Al Janoub, Bani Thawr, and An Namas. A rainfall decrease was detected in all other stations in Assir. The results of the Binomial and the Student's T-Tests varied. The rest of the annual rainfall trends have no statistical significance and are just phenomenal. This study concluded that the decreasing and increasing trends of annual and maximum daily rains do not definitively indicate there is climate change in Assir and Ha'il. Despite some decreasing rainfall trends of statistical significance, this did not deny some increasing rainfall trends.

Analysis of Trend in Meteorological and Hydrological Time-series using Mann-Kendall and Sen’s Slope Estimator Statistical Test in Akwa Ibom State, Nigeria

The monthly, seasonal, annual, and decadal trends of seven hydro-meteorological variables were analysed for stations in Akwa Ibom State, Nigeria, controlled by the Nigerian Meteorological Agency (NiMet) and the Cross River Basin Development Authority (CRBDA) from 1972 to 2021. At the 5% statistical significance level, the non-parametric Mann-Kendall and Sen's slope estimator techniques were used to detect if there was a positive or negative trend and the magnitude of the trend in hydro-meteorological data. In the present study, there was a significant statistically increasing (positive) trend in mean seasonal and annual rainfall, maximum temperature, minimum temperature, and runoff. However, there was a significant statistically decreasing (negative) trend in average annual relative humidity, solar radiation, and potential evapotranspiration. The magnitudes of the trends were 19.39mm/year, 0.0314oC/year, 0.013oC/year, -0.104%/year, -8.78MJ/m2/year, -1.440mm/year, and 0.028m3/s/year for annual rainfall, maximum temperature, minimum temperature, relative humidity, solar radiation, PET, and runoff, respectively. The rising trends in precipitation, temperature, and runoff in this research area show that this region is subject to climatic variability. The results of the Mann-Kendall and Sen's slope estimator statistical tests revealed the consistency of performance in the detection of the trend for the hydro-meteorological variables.

Trend Analysis of Rainfall Patterns in Rajnandgaon District, Chhattisgarh, India

Climate is a crucial determinant of an area's vegetation, wildlife, and livability, influenced by long-term atmospheric characteristics and fluctuations. Precipitation, particularly rainfall, plays a vital role in the Earth's hydrological cycle, connecting weather, climate, and water resources. This study focuses on Rajnandgaon district in Chhattisgarh, India, with an average annual precipitation of 1274mm. Analyzing trends, we identify changes in certain properties over time. The findings indicate that rainfall variability, measured by the coefficient of variation, is lowest during June to September (CV < 76%). Monsoon rainfall displays the least variability (CV of 30.88%), while pre-monsoon rainfall and winter rainfall exhibit higher variability (CV of 33.83% and 208.48%, respectively). The analysis also reveals a significant decreasing trend in annual, monsoon, and September rainfall. However, May rainfall shows a significant increase at a 5% level of significance. The study utilizes the non-parametric Mann-Kendall and Sen's Slope Estimator tests, employing monthly rainfall data from 1988 to 2018 for Rajnandgaon district, Chhattisgarh.

Spatiotemporal Rainfall Variability and Trends over the Mahi Basin, India

Climate change can have an influence on rainfall that significantly affects the magnitude frequency of floods and droughts. Therefore, the analysis of the spatiotemporal distribution, variability, and trends of rainfall over the Mahi Basin in India is an important objective of the present work. Accordingly, a serial autocorrelation, coefficient of variation, Mann–Kendall (MK) and Sen’s slope test, innovative trend analysis (ITA), and Pettitt’s test were used in the rainfall analysis. The outcomes were derived from the monthly precipitation data (1901–2012) of 14 meteorology stations in the Mahi Basin. The serial autocorrelation results showed that there is no autocorrelation in the data series. The rainfall statistics denoted that the Mahi Basin receives 94.8% of its rainfall (821 mm) in the monsoon period (June–September). The normalized accumulated departure from the mean reveals that the annual and monsoon rainfall of the Mahi Basin were below average from 1901 to 1930 and above average from 1930 to 1990, followed by a period of fluctuating conditions. Annual and monsoon rainfall variations increase in the lower catchment of the basin. The annual and monsoon rainfall trend analysis specified a significant declining tendency for four stations and an increasing tendency for 3 stations, respectively. A significant declining trend in winter rainfall was observed for 9 stations under review. Likewise, out of 14 stations, 9 stations denote a significant decrease in pre-monsoon rainfall. Nevertheless, there is no significant increasing or decreasing tendency in annual, monsoon, and post-monsoon rainfall in the Mahi Basin. The Mann–Kendall test and innovative trend analysis indicate identical tendencies of annual and seasonal rainfall on the basin scale. The annual and monsoon rainfall of the basin showed a positive shift in rainfall after 1926. The rainfall analysis confirms that despite spatiotemporal variations in rainfall, there are no significant positive or negative trends of annual and monsoon rainfall on the basin scale. It suggests that the Mahi Basin received average rainfall (867 mm) annually and in the monsoon season (821 mm) from 1901 to 2012, except for a few years of high and low rainfall. Therefore, this study is important for flood and drought management, agriculture, and water management in the Mahi Basin.

Hydroclimatic Trends and Drought Risk Assessment in the Ceyhan River Basin: Insights from SPI and STI Indices

This study examined the spatiotemporal climate variability over the Ceyhan River basin in Southern Anatolia, Türkiye using historical rainfall and temperature observations recorded at 15 meteorology stations. Various statistical and geostatistical techniques were employed to determine the significance of trends for each climatic variable in the whole basin and its three sub-regions (northern, central, and southern regions). The results revealed that the recent years in the basin were generally warmer compared with previous years, with a temperature increase of approximately 4 °C. The standardized temperature index analysis indicated a shift towards hotter periods after 2005, while the coldest periods were observed in the early 1990s. The spatial distribution of temperature showed non-uniform patterns throughout the basin. The first decade of the study period (1975–1984) was characterized by relatively cold temperatures, followed by a transition period from cold to hot between 1985 and 2004, and a hotter period in the last decade (2005–2014). The rainfall analysis indicated a decreasing trend in annual rainfall, particularly in the northern and central regions of the basin. However, the southern region showed an increasing trend in annual rainfall during the study period. The spatial distribution of rainfall exhibited considerable variability across the basin, with different regions experiencing distinct patterns. The standardized precipitation index analysis revealed the occurrence of multiple drought events throughout the study period. The most severe and prolonged droughts were observed in the years 1992–1996 and 2007–2010. These drought events had significant impacts on water availability and agricultural productivity in the basin.

Modelling the Impacts of the Changing Climate on Streamflow in Didesa Catchment, Abay Basin, Ethiopia

The Didesa catchment, which is the second largest subbasin of the Abay basin, significantly contributes to the Blue Nile’s outflow. Understanding the dynamics of water availability under the changing climate in such a basin assists in the proper planning of land use and other development activities. This study presents changes in climatic elements such as rainfall, temperature, and evapotranspiration using observation data and regional climate models (RCMs) under two representative concentration pathways (RCPs) for three future periods. We use a calibrated hydrological model to further assess climate change’s effects on streamflow. We select three RCMs and their ensemble’s mean by evaluating their performance with respect to observations. We apply the modified Mann–Kendall test to detect trends in each dataset. The result shows that annual mean maximum and minimum temperatures increase in the catchment for the 2021–2040, 2041–2070, and 2071–2100 periods as compared to baseline (1989–2018) under both RCP4.5 and RCP8.5 scenarios. Annual mean maximum temperature and potential evapotranspiration experienced a significant decreasing trend during the year from 1989 to 2018. Furthermore, there was an increasing trend in annual rainfall from 1989 to 2018, which could be related to the cooling of sea surface temperature over the equatorial Pacific. We detect an increasing trend in temperature in both scenarios and all periods; however, no clear trend pattern is found in rainfall. The result from hydrological model simulations reveals that the mean monthly streamflow slightly increases in the winter season while it decreases during the main rainy season. Further study of detailed weather systems, which affect the subbasin’s climate, is recommended.

Nature of climate change-induced risks in semi-arid northwestern Ghana: Gauged observations, perceptions of smallholder farmers, and perspectives for livelihood adaptation

Climate variability and impact have been an endemic challenge to smallholder farmers who largely depend on rainy weather for livelihoods in semi-arid north-western Ghana. Many households in semi-arid regions exhibit low levels of adaptive capacity due to ineffective adaptation strategies and poor coping strategies. This study examined (1) trends in gauged rainfall and temperature data spanning the period from 1984 to 2014 and (2) smallholder farmers’ perceptions about yearly cyclical weather, and difficulties associated with climate change adaptations. The study adopted the participatory rural appraisal design using questionnaire, interviews and focus group discussions for collection of data for analysis. Estimated parameters partially supported that yearly temperatures are increasing, whereas annual rainfall is declining, although the latter is not significantly related to the former. Smallholder farmers’ perceptions about changing weather conditions did not corroborate the observed declining annual rainfall trend. These farmers are faced with livelihood-affecting risks during either ‘prolonged dry periods from October to May’ or ‘short annual rainy season from mid-May to September. Therefore, access to climate information and available climate adaptation strategies could improve farming activities and livelihoods of farmers in response to climate change.

Generation of climate change scenarios for rainfall and temperature using SDSM in a Mediterranean environment: a case study of Boufakrane river watershed, Morocco

Climate change is the global phenomenon of climate transformation characterized by changes in the planet’s habitual climate. The main objective of this work is to assess and predict climate change for the 2015–2100 period, in the Boufakrane river watershed, Morocco. In this study, the Statistical DownScaling Model (SDSM) method has been used to generate the climate scenarios for rainfall and temperature related to Representative Concentration Pathway (RCP) scenarios such as RCP 2.6, RCP 4.5, and RCP 8.5. For this purpose, the region’s annual, monthly, and daily rainfall records were analyzed. A rainfall index was calculated to differentiate and distinguish between dry and humid years of the climate series, and a non-parametric Pettitt’s test has been applied to determine the trend of precipitation series for the projection period. The application of Pettitt’s test with a confidence interval of 99% and a significance level of 0.05 shows a break in the 1979/80 rainfall series, with an average of 675.78 mm and 511.94 mm respectively before and after the break. The combined application of the two approaches of SDSM, and the non-parametric Pettitt test for the period 2015–2100, showed a downward trend of annual rainfall with 17.29% for RCP 2.6. While no trend was recorded for the two scenarios RCP 4.5, and RCP 8.5. Therefore, this study highlighted the importance and urgent need for developing strategies and decision-making plans for climate change adaptation for sustainable water resources management.Graphical

Rainfall Trends Analysis in context of Climate Change in Imam Turki Bin Abdullah Royal Nature Reserve (ITBA) – Saudi Arabia

Rainfall trend analysis, on different spatial and temporal scales, has been used during the past century as the indicate of global climate change by the scientific community. According to some recent studies, the Nature Reserve (ITBA) has been suffering a rainfall decrease, especially in the second half of the studied period (1993-2018). The aim of the present study is to analyze the rainfall trends using the time series of 52 years in five rain stations (Linah, Rafha, Ha’il, Dawmat Al Jandal and Hafr Al Batin) surrounding the Nature Reserve of (ITBA) that extended on area of about 91500 km2 in the Northeast of Saudi Arabia. The trends analysis of annual rainfall, rainy days, shows that the fluctuations or variations in climatic parameters is a recurring phenomena in the studied stations. Inter-annual variability of the rainfall and the actual mean of daily rainfall are characterized by the high coefficients of variation, varying from 0.73 (Linah) to 0.83 (Ha’il) and from 0.53 (Linah) to 1.09 (Rafha), respectively. The variance test of Fmax-ratio method indicates the homogeneous annual rainfall distribution at Linah, Rafha and Ha’il, the homogenous rainy days distribution at only Ha’il and the homogeneous distribution of the actual mean of the daily rainfall at only Linah. The trends of annual rainfall, rainy days and actual mean of the daily rainfall obtained by using T-student test are significant in Ha’il and Dawmat Al Jandal, in all stations and in only Hafr Al Batin, respectively.

Relation Between the Madden Julian Oscillation with Wet and Dry Spells During Belg Season Over Ethiopia

The main objective of this study is to explore seasonal impacts of the Madden–Julian oscillation (MJO) on tropospheric circulations affecting Ethiopia during Belg (March–May) rains and associated variability in precipitation. The data used daily rainfall, daily Madden-Julian (MJO) indices, daily Outgoing Longwave Radiation (OLR) and zonal and meridional wind data. The methods used for this study is Correlation and composite analyses are used to establish the association and the relationship between the MJO and rainfall over Ethiopia. A non-significant declining trend in annual rainfall across Ethiopia has been observed over the past three decades trend change per year over by -0.602 mm and P-Value 0.338. The mean length of wet spells 90 days over SNNPR and Southern Oromia Region, and with a least mean length of wet spell is 10 days over Afar, Tigray and western Amhara Region. The results reveals that there is a strong correlation between Ethiopian rainfall and MJO to the west of the region especially around Central and Southeastern parts of the Country. Out of phase (opposite) relationship between the west and the east is also indicating different rain causing mechanisms for the two regions. The rainfall amount also shown to depend on the configuration of the winds at lower and upper levels. Based on composite analysis extreme rainfall events shown to occur during preferential phases of the MJO. Phase 2 coincides with enhanced rainfall, high negative anomaly OLR values as well as westerly and easterly winds configuration at 200hpa and 850hpa while phase 5, 6 and 7 are associated with deficit of rainfall. The inclusion of other modes of variability such as Sea surface Temperatures (SSTs) and the Indian Ocean Dipole (IOD), as predictors recommended in predicting interaseasonal rainfall.

Spatiotemporal variability and trend of rainfall and temperature in Sidama Regional State, Ethiopia

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.

Time Series Analysis of Temperature and Rainfall in the Savannah Region in Togo, West Africa

This study investigates the trend in monthly and annual rainfall, and minimum and maximum temperature (Tmin and Tmax) in the Savannah region of Togo. The historical data of Mango and Dapaong weather stations from 1981 to 2019 were used. A serial correlation test was applied to all time series to identify serially independent series. A Non-parametric Mann–Kendall (MK) test was applied to serially independent series. The magnitude of the trend was calculated using the Sen’s slope (SS) method. For the data influenced by serial correlation, a modified version of the Mann–Kendall test was applied. An open-source library package was developed in the R language, namely, “mkmodified”. For annual rainfall, results showed a significant increasing trend at Dapaong (p &lt; 0.05) and a non-significant decreasing trend at Mango (p &gt; 0.05) at 95%. There was an increasing trend in the Tmin both at Mango and Dapaong. No statistically significant trend was found at Mango (p &gt; 0.05), while at Dapaong (p &lt; 0.05), a significant trend was found at 95%. Simlarly, there was a statistically increasing trend in the Tmax both at Mango and Dapaong. Rainfall in Dapaong has increased (5.50 mm/year) whereas in Mango, it has decreased (−0.93 mm/year). Tmn increased by 0.04 and 0.008 °C per year in Mango and Dapaong, respectively. Tmax increased by 0.03 and 0.02 °C per year in Mango and Dapaong, respectively. A Rainfall Anomaly Index (RAI) was also used to present a temporal variation in rainfall; the historical series presented drier years. Many studies have analysed the trend of climate parameters in northern Togo, but none of them has specifically targeted the Savannah region that is considered the poorest region of the country.

Case study of rainfall and temperature assessment through trend and homogeneity analyses in Vadodara and Chhotaudepur district of Gujarat State, India

This study aims to assess the climate change impact on the rainfall and temperature data of the Vadodara-Chhotaudepur district of India and to focus on the environmental challenges related to the rainfall and temperature in the present state of development, land use, industrialization, and urbanization. The study utilized nine trend analysis methods, namely linear regression (LR), Sen's robust slope estimator (SS), Mann-Kendall test (MK), Spearman's rank correlation (SRC), the trend-free pre-whitening (TFPW), variance correction approach by Hamed and Rao (1998) with MK test (MK-CF1), variance correction approach by Yue and Wang (2004) with MK test (MK-CF2), block bootstrap with MK test (BBS-MK), and graphical method as innovative trend analysis (ITA), applied on monthly, annual, and seasonal scales. Additionally, the study also employed four homogeneity analysis methods, including Pettitt's test, standard normal homogeneity test (SNHT), Buishand's test, and Von Neumann Ratio test (VNRTs). The IMD (Indian meteorological department) gridded long-term rainfall data from 1901 to 2019 and temperature data from 1951 to 2019 are used in the present study to assess the homogeneity and trends of the data series. Results showed a warming trend of maximum temperature (MaxT) and minimum temperature (MinT) at the monthly, annual, and seasonal time scale and significant (at 5%) warming trend in annual MinT in the entire study area. Annual rainfall showed negative trend in the study area with significant (at 5%) negative trend in eastern deforested area western industrial and area adjacent to thermal power station. The change point is detected in annual rainfall time series in eastern forest area in 1959 and western area in 1983, i.e., after development of the industries and commissioning of thermal power station in the western study area. The trend rate of MaxT and MinT has been recognized as 0.004°C/year and 0.019°C/year, respectively, for the data period of 1951 to 2019. The annual rainfall trend rate has been observed as -0.743mm/year for the data range 1901 to 2019. All trend analysis methods revealed consistent results except MK-CF2 method, which portraits greater number of significant trends in trend analysis methods.

Effect of Temperature and Rainfall Variability on Selected Crop Yields in Wenchi Municipality of Ghana

The paper examines how rainfall and temperature variability affect the yields of selected food crops in the Wenchi municipality of Ghana. The study employed the quantitative research method to achieve its objective. The datasets consisted of historical records of monthly observational data of temperature and rainfall collected over 22 years (2000-2021), and yearly records of cassava, yam, and maize yield data collected over 22 years (2000 to 2021). Trend analysis was conducted to examine the trend in the climate variables (temperature and rainfall) and the yield of the selected food crops (cassava, yam, and maize) over the study period. A marginal variation in annual rainfall and temperature was observed over the study period. The municipality experienced slightly decreasing trends in annual rainfall and increasing trends in annual temperatures. Significant variations and increasing trends in the yields of the respective food crops were observed. Using standard regression methods, the result shows that maximum and minimum temperatures are associated with increased yields for yam, maize and cassava, but annual rainfall is not significantly associated with the variations in the yields of the selected food crops. The study, therefore, suggests that further research be undertaken to investigate how other environmental and non-climatic factors influence crop production in the Wenchi municipality.