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Given the importance of climate for society at different scales, such as local, regional, and global scales, the analysis of trends of climatic elements improves the assessment of projections and variations, aiding in the design of policies focused on processes of adaptation to and mitigation of the effects of climate change. The aim of this study was to detect mean air temperature trends in the Sertão Paraibano mesoregion in Brazil by constructing temperature series with observed data provided by the Brazilian National Institute of Meteorology (INMET) collected in the localities of Patos and São Gonçalo and with data estimated using Estima_T software to study the spatial and temporal distribution of the mean air temperature of seven localities in the Sertão Paraibano mesoregion: Água Branca, Aguiar, Coremas, Patos, Princesa Isabel, São Gonçalo, and Teixeira. The temperature series with observed and estimated data were compared, showing the variability of using temperature estimates to overcome the lack of meteorological stations in the study area. Descriptive analysis shows low data dispersion in relation to the annual mean values and, therefore, low variability. The monthly mean temperature pattern was similar in all localities and December was always the warmest month, whereas July was the coldest, both in the estimated and observed data series. The non-parametric Mann-Kendall test indicated that estimated series show trends of significant increases in mean air temperature, in annual, biannual, quarterly, and monthly periods, in all localities. Sen's slope results indicate significant increases in temperature from 0.008 to 0.011 °C/year.

Trend analysis of meteorological variables is important in the determination of climate change. Precision is an important component of the hydraulic cycle and changes in temperature and precipitation affect agriculture, living ecosystems and water resources management. This study analyses Innovative Trend Analysis (ITA), Mann-Kendall, Sen slope and Innovative Polygon Trend Analysis (IPTA) to determine the trends of temperature and precipitation variables between 1980 and 2023 in Siirt province and climate change indicators were determined. Meteorological variables were evaluated separately on monthly, seasonal and annual scales. The results obtained from Mann-Kendall, ITA, IPTA and Sen trend analyses for precipitation and temperature variables were compared against each other. The results of all trend analyses for precipitation show a decreasing slope, while an increasing trend is detected in temperature values. The trend values are larger at monthly and seasonal scales. The trend results obtained in the present study indicate that more attention should be paid to drought risk management and water resources management in Siirt province. [ABSTRACT FROM AUTHOR]

This study examines trends in minimum and maximum temperatures at various climate stations located in different regions of Morocco for a period of five decades (1970 to 2019). Mann–Kendall, Sen's estimator, Innovative Trend Analysis (ITA) and Innovative Polygon Trend Analysis (IPTA) were used in the analysis. The results show significant fluctuations, at different time scales, between minimum and maximum temperatures at all stations. In coastal areas, such as Rabat Sale, minimum temperatures fell during January and February while other months saw increases. Average minimum temperatures in Rabat Sale tend to fall by 0.5 °C. On the other hand, maximum temperatures in Rabat Sale rose by 0.2 °C. A decrease of 0.4 °C for Tmin and 1.6 °C for Tmax were observed in higher continental regions, such as Meknes. Other stations, such as Fez Sais (0.6 °C Tmin and 2.6 °C Tmax) and Taza (1.1 °C Tmin and 2.6 °C Tmax) showed an upward trend. Trends also vary, with notable increases in minimum and maximum temperatures, indicating different climatic dynamics according to altitude and locality. In particular, the ITA highlights a significant increase in annual maximum temperatures, with a P-value < 0.05 and trend slopes ranging from 0.0015 °C per year in Rabat Sale to 0.0076 °C per year in Taza. In addition, the IPTA results confirm diversity of upward and downward trends on monthly and seasonal scales, highlighting impact of geographical factors such as proximity to sea, topography, and continentality that contribute to formation of regional microclimates. The results highlight significant impact of climate change in Morocco. [ABSTRACT FROM AUTHOR]

Central Punjab includes over 40% of the state of Punjab. In Central Punjab, groundwater levels are dropping by more than 1 m every year. The primary cause of groundwater depletion in Central Punjab between 1998 and 2019 is presented in this paper. In order to detect any sudden changes in the area under paddy and the depth of groundwater, Pettitt's test was used. Based on change points and trends, the entire duration was split into two time periods: 1998–2008 (T1) and 2009–2019 (T2); rainfall, potential evapotranspiration, and paddy area were assessed in both periods with 1998–2019 (T3). The slope methodology developed by Mann–Kendall and Sen demonstrated the trend analysis. The findings showed that changes in climate were caused by humans during the 1998–2008 era, changes in meteorological variables were caused by humans during the 2008–2019 period, and changes in climate were caused by humans during the T3 period. The major growing trend of groundwater depth loss is thought to be caused by the combined effects of rainfall variations, an increase in the maximum temperature, cropping intensity, and the number of pumping units. HIGHLIGHTS Paddy area has been increasing in Punjab for the last 20 years, and this increase is causing a huge decrease in groundwater levels.; Pettitt's test was applied to see in which year an abrupt change happened.; Mann–Kendall and Sen's slope were applied to analyze the trend.; Rainfall was not enough for groundwater recharge as compared to declination due to the paddy area.; Central Punjab must evolve decision-making tools for arresting groundwater (GW) decline.;

Copyright of Journal of Central China Normal University is the property of Huazhong Normal University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Water resource management is highly impacted by variations in rainfall, maximum and minimum temperature, and potential evapotranspiration. The rice area is also a key aspect for groundwater declination due to high-water consuming crop. Groundwater in Central Punjab has declined at an alarming rate over the last two decades. The decisions regarding water resource management need accurate information for the groundwater level. Therefore, to explore the main reason for the depletion of groundwater, it is essential that the most influential factors responsible for groundwater depletion should be addressed. A study was conducted in Central Punjab by using artificial neural network (ANN) and multiple linear regression (MLR) models during 1998–2018 to forecast the groundwater depth. ANN performed better than MLR. The sensitivity analysis showed that tubewell density, rice area, and rainfall are highly responsible for groundwater fluctuation. HIGHLIGHTS In the present study, both climatic and human-induced factors were taken for groundwater modeling.; Artificial neural network, a complex phenomenon was used to forecast groundwater depth.; Python was used for groundwater modeling.; ANN was found to be more accurate than MLR.;

Analysis of the trends and variability of climate variables and extreme climate events is important for climate change detection in space and time. In this study, the trends and variabilities of minimum, maximum, and mean temperatures, as well as five extreme temperature indices, are analyzed over Rwanda for the period of 1983 to 2022. The Modified Mann–Kendall test and the Theil–Sen estimator are used for the analysis of, respectively, the trend and the slope. The standard deviation is used for the analysis of the temporal variability. It is found, on average, over the country, a statistically significant (α = 0.05) positive trend of 0.17 °C/decade and 0.20 °C/decade in minimum temperature, respectively, for the long dry season and short rain season. Statistically significant (α = 0.05) positive trends are observed for spatially averaged cold days (0.84 days/decade), warm nights (0.62 days/decade), and warm days (1.28 days/decade). In general, maximum temperature represents higher variability compared to the minimum temperature. In all seasons except the long dry season, statistically significant (α = 0.05) high standard deviations (1.4–1.6 °C) are observed over the eastern and north-western highlands for the maximum temperature. Cold nights show more variability, with a standard deviation ranging between 5 and 7 days, than the cold days, warm nights, and warm days, having, respectively, standard deviations ranging between 2 and 3, 4 and 5 days, and 3 and 4, and, especially in the area covering the central, south-western, south-central, and northwestern parts of Rwanda. Temperature increase and its variability have an impact on agriculture, health, water resources, infrastructure, and energy. The results obtained from this study are important since they can serve as the baseline for future projections. These can help policy decision making take objective measures for mitigation and adaptation to climate change impacts. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Introduction: Climate identification and classification have long been of interest to meteorologists. Researchers have classified the earth into homogeneous climatic zones using different methods and climatic variables such as rainfall and temperature. They have used the results of climate zoning to assess water scarcity and water resources on a small and large scale to anticipate practical measures to control drought in vulnerable areas. The purpose of this study is to update and analyze the Spatio-temporal analysis of Iran's climatic classification based on the Domarten index and the Mann-Kendall test. Because in studies based on climate classification maps, up-to-date maps can better help understand the study area.Material and methods: For this study, data related to temperature and precipitation variables were extracted monthly from 153 synoptic stations from 1995-2019 from the Meteorological Organization of Iran. First, the data of average annual temperature and total annual precipitation were obtained from monthly data and then, using isothermal maps, they were obtained using the kriging model. The final climate zoning map was prepared using the De-Martonne index based on rainfall and temperature. The non-parametric Mann-Kendall test was also used to evaluate the significance or non-significance of the De-Martonne climate index and determine the trend.Results and discussion: The results showed that based on the Kriging model, R2 and RMSE for precipitation data were 0.58 and 167.51 mm, respectively, and for the temperature data were 0.83 and 2.23 °C, respectively. This indicates better performance of the model for temperature data. This is related to the high variance of precipitation data in the country. Iran's climatic zoning based on the De-Martonne index showed six main climatic types in Iran. Most of Iran's area has an arid climate and then a semi-arid climate. The study results showed that arid climate is 76.40%, the semi-arid climate is 19.65%, and other climates make up less than 4% of the area of ​​Iran. Also, the area of ​​arid and semi-arid climates with an area of ​​96.05% of the area of ​​Iran has increased compared to previous research, which may be due to reduced rainfall and increased temperature. Also, the results of the Mann-Kendall test showed that Khorramdareh, Miyaneh, Ramsar, Boroujerd, Piranshahr, Tabriz, and Bijar stations have a significant upward trend (wetting trend), and Dezful, Malayer, Sabzevar, Bandar Anzali, Tehran (Mehrabad), Tehran (Shemiran), Qazvin and Dushan Tappeh stations have a significant downward trend (drying trend) at the significance level of 5%.Conclusion: This study showed that Iran has six climatic regions, including arid, semi-arid, Mediterranean, semi-humid, humid, and very humid. Also, comparing the results with the results of research done by other researchers in the past showed that the area of arid and semi-arid climates in the study period has increased compared to previous periods. Also, 14% of stations with a downtrend (8 stations) have a significant downtrend, and 7% of stations with an uptrend (7 stations) have a significant uptrend at the significance level of 5%.

Agathis macrophylla (Araucariaceae) is a native tree in Fiji, found in Vanuatu and Solomon Islands, that is of great socio-economic value, ecological significance and cultural importance. Due to the impact of climate change on biodiversity, this bio-geographical study was initiated to analyse a 30-year (1989-2019) data set from the Monasasvu Meteorological station, using descriptive statistics coupled with Mann-Kendall and Sen's Slope test methods. The study detected the trend and impact of precipitation and rainfall on the fruiting phenology, mean fruit weight, total number of seed produced, volume seed count and germinants propagated for A. macrophylla from the Nausori Highlands, Ba Province, Western Division of Fiji for the period 2010-2019. The results showed significant deviation in the flowering and fruiting seasons and emergence of fruit cones which were observed between April to May, a five-month delay from the seed phenology calendar. There has also been a significant shift in fruiting and maturity richness and intensity as it occurred in the months when both the precipitation (456-652 mm) and temperature (26.8-28.6 °C) were higher. The phenological response to these climate variables was astounding as the coefficient of variation for the average fruit weight, seed numbers and germination rate ranged between 65-73%. This calls for more concerted conservation action in the identification and mapping of mature seed trees, a moratorium on timber harvesting during its fruiting and maturity seasons, establishing at least two seed stands, and germinating larger numbers of seedlings following mast seed years and holding them in the nursery under specific conditions until required for field planting. [ABSTRACT FROM AUTHOR]

In recent years, the urban area has continued to develop, and the demand for water resources is increasing. Rainfall, as an important source of water resources, is gaining more and more attention. Under this background, it is very necessary to analyse the changes in rainfall in Beijing, the capital of China. This study analysed the daily average temperature, rainfall data from 20 stations in the Beijing area in the past 50 years (1960–2012). Linear regression, mean variance, M-K method and ArcGIS spatial analysis are used to analyse Beijing's temperature and rainfall characteristics. These methods are applied to analyse the mutual relations between Beijing's rainfall, temperature changes and the Southern Oscillation Index (SOI). The results show that in the past 50 years in Beijing, the precipitation has shown a downward trend, the temperature has generally shown an upward trend, and the evaporation has generally shown a downward trend. The interrelation between regional climate change and the SOI is not significant. In the past 50 years, urban development has been closely related to the reduction of rainfall and increase in temperature. This study responds to the urgent need for research on the rainfall and temperature. HIGHLIGHTS Different methods are used to analyse temperature and rainfall characteristics.; The variation of rainfall and temperature in Beijing over the past 50 years was analysed.; Different regions are affected differently by SOI, and the difference between North and South China is obvious.;

Climate change is a global scientific problem, and its impact on the spatiotemporal variations of precipitation has been a crucial research topic. Although previous studies have used different methods to evaluate the precipitation characteristics of the Huaihe River Basin, the time series were short and the few stations could not fully and accurately represent the precipitation characteristics. In this study, daily temperature and precipitation data were collected from 233 meteorological stations in the Huaihe River Basin from 1960–2020. The Mann–Kendall test was used to analyze the trend and significance of interannual and interseasonal scale changes in temperature and precipitation in the Basin, respectively. The correlation between temperature and precipitation was analyzed using the Pearson correlation coefficient method. The spatial distribution of the significance of temperature and precipitation changes and the spatial distribution of the correlation between temperature and precipitation in the basin were plotted. The temperature in the basin tended to increase on interannual and interseasonal scales, with more noticeable changes in spring and winter. Precipitation showed an overall decreasing trend but an increasing trend in localized areas in the south. A decreasing trend in the interseasonal variation scale was observed in spring, an increasing trend in winter, a decreasing trend in the northeastern region in summer, an increasing trend in the southwestern region, and an increasing trend in the northern and southern parts in autumn were observed. The correlation between average temperature and precipitation on interannual and interseasonal scales was analyzed using Pearson's correlation coefficient method, and the annual average temperature and annual average precipitation in the Huaihe River basin were found to be negatively correlated, except for sporadic areas that showed extremely weakly positive correlations or no correlations. [ABSTRACT FROM AUTHOR]

Agriculture is affected by climate change, such as extreme increases or decreases rainfall and temperature patterns. It is possible to research that effect by using trend analysis methodologies. This paper investigates trends of monthly total rainfall and mean temperature data of nine selected stations from agricultural regions of Turkey between 1969 and 2020. To the end, the classical Mann–Kendall, Innovative Trend Significance Test (ITST), and Innovative Polygon Trend Analysis (IPTA) with Star Graph methods providing the opportunity to examine seasonal behavior were used for trend analysis. The analysis reveals that about 96% of all monthly rainfall in the Mann-Kendall test has no trend. However, nearly all stations tend to decrease (increase) in November (September) in both innovative approaches. For temperature, it is seen that increasing trend or no trend dominated in general. There were increasing trends in the innovative approaches throughout the year except for April. Temperatures have increased significantly throughout the year in all regions over the last decades. With the help of IPTA, it was also concluded that the seasonal internal variability of rainfall over the entire time and in the last 30 years is quite complex and persists in all agricultural regions. The results show that irregular changes in rainfall and rising temperatures in all stations negatively affected crop yield and/or required more irrigation. In addition, according to the results obtained by comparing trend methods, innovative approaches are very insistent on determining of trend and provide additional information through a visual review of trend behaviors. [ABSTRACT FROM AUTHOR]

In the present day, the acceleration of urban surface heat impacts resulting from urbanization and industrialization is critical for citizens and municipal governments in developing-country cities. The previous key findings have indicated the association between urban surface heat and the following areas: forests, mixed agricultural land, built-up area, and water bodies. This study was motivated by a lack of knowledge regarding the variation of temperature, evaporation, and humidity in Central Vietnam's major region. The non-parametric Mann–Kendall test, Sen's slope estimator, and Landsat image analysis were employed to determine the trend and statistical significance of the variables across the 42-year study period for Da Nang city and Quang Nam province. Our results show that Da Nang city has a consistent trend with a high correlation between temperature, evaporation, and relative humidity, whereas Quang Nam province showed an inverse relationship between temperature and relative humidity since the beginning of the regional urbanization. The maximum, minimum, and mean temperatures have increased by at least 0.29 °C in Quang Nam province and 0.71 °C in Da Nang city since 2000. Between 1979 and 2021, the frequency of days with temperatures exceeding 35 °C has increased by two and seven days during the past decade at the meteorological stations in Da Nang and Tam Ky, respectively. The temperature in Da Nang city varied from 31.80 °C to 32.82 °C with high temperatures concentrated in urbanized regions with less coverage of small trees, plants, and water bodies. Thus, the results of this study will serve as a scientific basis for decision-makers and regional officials for land-use management and to increase community awareness of sustainable planning, particularly in Da Nang city and Quang Nam province in Central Vietnam. [ABSTRACT FROM AUTHOR]

Introduction: Climate identification and classification have long been of interest to meteorologists. Researchers have classified the earth into homogeneous climatic zones using different methods and climatic variables such as rainfall and temperature. They have used the results of climate zoning to assess water scarcity and water resources on a small and large scale to anticipate practical measures to control drought in vulnerable areas. The purpose of this study is to update and analyze the Spatio-temporal analysis of Iran's climatic classification based on the Domarten index and the Mann-Kendall test. Because in studies based on climate classification maps, up-to-date maps can better help understand the study area. Material and methods: For this study, data related to temperature and precipitation variables were extracted monthly from 153 synoptic stations from 1995-2019 from the Meteorological Organization of Iran. First, the data of average annual temperature and total annual precipitation were obtained from monthly data and then, using isothermal maps, they were obtained using the kriging model. The final climate zoning map was prepared using the De-Martonne index based on rainfall and temperature. The non-parametric Mann-Kendall test was also used to evaluate the significance or non-significance of the De-Martonne climate index and determine the trend. Results and discussion: The results showed that based on the Kriging model, R2 and RMSE for precipitation data were 0.58 and 167.51 mm, respectively, and for the temperature data were 0.83 and 2.23 °C, respectively. This indicates better performance of the model for temperature data. This is related to the high variance of precipitation data in the country. Iran's climatic zoning based on the De-Martonne index showed six main climatic types in Iran. Most of the area of Iran has an arid climate and then a semi-arid climate. The study results showed that arid climate is 76.40%, the semi-arid climate is 19.65%, and other climates make up less than 4% of the area of Iran. Also, the area of arid and semi-arid climates with an area of 96.05% of the area of Iran has increased compared to previous research, which may be due to reduced rainfall and increased temperature. Also, the results of the Mann-Kendall test showed that Khorramdareh, Miyaneh, Ramsar, Boroujerd, Piranshahr, Tabriz, and Bijar stations have a significant upward trend (wetting trend), and Dezful, Malayer, Sabzevar, Bandar Anzali, Tehran (Mehrabad), Tehran (Shemiran), Qazvin and Dushan Tappeh stations have a significant downward trend (drying trend) at the significance level of 5%. Conclusion: This study showed that Iran has six climatic regions, including arid, semi-arid, Mediterranean, semi-humid, humid, and very humid. Also, comparing the results with the results of research done by other researchers in the past showed that the area of arid and semi-arid climates in the study period has increased compared to previous periods. Also, 14% of stations with a downtrend (8 stations) have a significant downtrend, and 7% of stations with an uptrend (7 stations) have a significant uptrend at the significance level of 5%. [ABSTRACT FROM AUTHOR]

In recent decades, the increase in temperature has caused widespread climate change all over the world, especially in arid and semi-arid regions of Iran and Yazd province. The purpose of this study is to project climate change in Yazd province using the CanESM2 model and new emission scenarios (RCP) during 2021-2050 (near future) and 2051-2080 (distant future) and to study the trend of changes in the baseline period using the Mann-Kendall test. The statistical indices of R2, RMSE, and NSE were used to evaluate the performance of the CanESM2 model. According to the results, the model had an appropriate performance for projecting precipitation and temperature in the future period and was classified into good and very good classes in terms of capability. Investigating the trend of the annual change of temperature and precipitation in the baseline period showed that the temperature had an increasing trend under most scenarios and stations, while the trend of the change of precipitation was no significant. The results of temperature changes in Yazd province indicated an increase of 2.2, 1.2, and 2.5 °C during 2021-2050 and 2.28, 3.19, and 4.77°C during 2051-2080 under RCP2, RCP4.5, and RCP8.5 scenarios, respectively. Changes in precipitation in Yazad province during the winter season showed a decrease in precipitation by 32, 26, and 34% during 2021-2050 and by 32, 32, and 5% during 2051-2080 under RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively.

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.

Copyright of Turkish Studies - Social Sciences is the property of Electronic Turkish Studies and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Understanding the variability in extreme meteorological events due to climate change and anthropogenic activities is crucial to ensure sustainable development. In this paper, the variation in precipitation and temperature in the Upper Narmada Basin (UNB), a humid subtropical region of central India, during 1901–2002, was analyzed using the Mann-Kendall (MK) test with the Sen's slope (SS) estimator and innovative trend analysis (ITA). As a result, a significant negative trend in the annual precipitation occurred at two stations (12.5%) in the UNB, whereas no well-defined significant seasonal trends were detected. Moreover, in the annual mean temperature, a significant increasing trend occurred in the basin, with the highest and lowest rates of 0.470 °C/10 year and 0.287 °C/10 year, respectively. The seasonal temperature exhibited a significant increasing trend in the spring and autumn seasons. The trends in the extreme values were investigated using the ITA method. Furthermore, a quantitative study was carried out to measure the suitability of the ITA by comparing it with nonparametric methods (the MK test and SS estimator). The results endorse the reliability of the ITA method and show strong agreement between the trends and statistics of the parametric (ITA) and nonparametric approaches. To visualize the extreme events in meteorological series, a discrete wavelet transform (DWT) was employed with the Daubechies (db3) mother wavelet. In addition, change points were detected using the sequential Mann-Kendall (SQMK) and cumulative sum (CUSUM) tests. Significant change points in the annual precipitation were detected at nine stations (56.25%) during 1955–1958, while only three stations (18.75%) exhibited the annual mean temperature during 1960. The findings of this study could provide support to understand the variability in the meteorological trend over the basin and can help with water resource planning in future development. [ABSTRACT FROM AUTHOR]

Several studies indicate that the hot season is lengthening at the expense of the intermediate seasons, and extreme events are becoming more intense and spread out over time. What is the situation in a climate described as very hot? This work aims to examine the evolution of minimum and maximum temperatures in the hot period from June to September during 1951--2010 in the Bechar region, which is classified among the hottest in the world and located in the south-west of Algeria. This study will also focus on the extending of the warm period (the period between the first and the last recording of an extremely hot day). The results showed an evolution of maximum and minimum temperatures, leading to an upward trend in the mid- 1990s. There was an average increase of 1°C at the maximum and 0.9°C at the minimum. The warm period experienced a significant expansion attributed to both the earliest and the latest extremely hot day events. [ABSTRACT FROM AUTHOR]

Deltas are geographically and socio-ecologically distinct systems, with a unique climate and contextually high vulnerabilities to climate dynamics. Hence, they require specific climate change adaptation and policy responses, informed by delta-scale analysis. However, available climate knowledge on deltas is based mainly on broad-scale analysis that masks information unique to deltas. This applies to the Volta Delta system of Ghana. This study presents annual and intra-annual climate variability and trend analysis carried out across the Volta Delta, using the coefficient of variation (CV), anomaly, Mann-Kendall and Pettit statistics. There were time and space differences in climate change and variability. Statistically significant (P < 0.05) positive trends were observed for the major wet season and the mean annual rainfall for Ada and highly significant (P < 0.01) positive trends for Akatsi. These contrasted with the observations in Adidome, which experienced a statistically highly significant (P < 0.01) decreasing trend in rainfall. There were significant (P< 0.05) increases in annual minimum, maximum, and mean temperatures over time in both coastal and inland delta stations. The annual rate of change of mean temperature ranged from 0.03 to 0.05. Ada, the more coastal location, has experienced a narrow range of temperature change, most probably due to the buffering capacity of the ocean. Point changes were observed in the climate data series in four (4) localities. We recommend that adaption and policy actions should include, the provision of small-scale irrigation, encouraging adoption of drought-resistant crop varieties and crop diversification, and also be made responsive to the existing spatiotemporal climate variability and change within the Volta Delta. [ABSTRACT FROM AUTHOR]

Statistical surveys to detect trends in time series are fundamental tools to evaluate farming dynamics of sugarcane and of adaptation plans for possible impacts caused by climate change. This work analyzed the influence of climate change in the cultivation of sugarcane in the state of Paraíba (Northeast Brazil), in order to investigate what are the consequences of temperature increase, air humidity level, and changes in the precipitation regime forecasted for the region in sugarcane farming. Data of temperature, total precipitation, and relative humidity of six meteorological stations kept by the Brazilian National Institute of Meteorology (INMET) spread across the state of Paraíba and data from the area of sugarcane harvesting from the Brazilian Institute of Geography and Statistics (IBGE). Mann-Kendall trend test was employed in order to analyze the existence of trends in each station, separately. The results pointed trends of significant increase in temperature for the stations of Campina Grande, João Pessoa, Monteiro, Patos, and Sousa. The stations of Areia, Campina Grande, and João Pessoa obtained significant precipitation trends. Regarding relative humidity, the stations of João Pessoa, Monteiro, and Patos presented significant decreasing trends, while Sousa showed significant increase trends. The results suggest that these trends may be increasing sugarcane production close to the coast of the region and decreasing production inland. [ABSTRACT FROM AUTHOR]

Climate variability, particularly, that of the annual air temperature and precipitation, has received a great deal of attention worldwide. The magnitude of the variability of the factors changes according to the locations. The present study focuses on detecting the trends and variability in the annual temperature and rainfall for the district of Mandi in Himachal Pradesh, India. This study used annual and monsoon time series data for the time period 1981-2010 and modified the Mann-Kendall test and Sen's slope estimator in analyzing the problem. The results of the analysis indicate that the annual maximum temperature (TMX) and annual minimum temperature (TMN) for the period of 30 years have shown an increasing trend, whereas the monsoon’s maximum and minimum temperatures have shown a decreasing trend, although it is statistically not significant. The amount of annual rainfall does not show any significant trend, but the monsoonal rainfall has shown an increasing trend that is also statistically not significant. The resulting Mann-Kendall test statistic (Z) and Sen’s slope estimate (Q) of all the parameters studied indicate that changes are occurring in the magnitude and timing of the precipitation and temperature events at the Mandi station.

Air temperature records provide strong evidence of change and variability in the climate system. The sensitivity of temperature to changes throughout the year renders it an ideal object of study when seeking to identify trends and changes in the frequency of extreme events. This study analyses temperature records from 18 stations in mainland Chile. By applying Mann–Kendall's non-parametric test to the data series and calculating specific extreme temperature indices, it is possible to identify significant trends in the series recorded from 1966 to 2015. The results show positive trends for both the minimum and maximum temperature series, although they are more marked for the former, especially during the warm months. The trend analysis of the extreme indices proposed by the Expert Team on Climate Change Detection and Indices, when applied to the data from the stations studied, suggests that there has been an increase in the frequency and intensity of warm extremes, whereas cold events manifest a negative trend, revealing differences between meteorological stations located in the north of mainland Chile and those in the centre and south. [ABSTRACT FROM AUTHOR]

Aims: In this study, it is aimed to determine the average monthly temperature data of Antalya and Alanya temperature observation stations (1975-2018). Methods and Results: In this study, the long-term climate values of the provinces in TR63 region have been determined and the temperature values reached during different periods of the air conditioning and production period, the required heating, ventilation, cooling times and the required fuel and cooling water amount have been determined. Heat requirement was calculated by using ISIGER-SERA expert system model using hourly temperature, solar radiation and wind speed values considering the temperature rise in the greenhouse. The heat energy required for keeping the greenhouse temperature at 16/18 °C day and night is 132.1 kWh m-2 a-1 in Kahramanmaraş province in the second region according to TS825 standards. The provinces in the first region were calculated as 85.5 and 71.8 kWh m-2 a-1 for Hatay and Osmaniye respectively. Conclusions: In general, temperatures tend to increase in Antalya and Alanya stations. Significance and Impact of the Study: The tendency to increase and decrease in temperature can be related to climate change. The increase in temperature shows very important agricultural results. In this context sowing high temperatures. may cause changes in planting and harvesting times. [ABSTRACT FROM AUTHOR]

Abstract The pattern of rainfall and temperature behaviour in the Hadejia River Basin (HRB) has been assessed. The behaviour of rainfall and temperature have been used as proxies in detecting the presence of climate variability. Historical rainfall and temperature monthly data spanning thirty-six years (1980–2015) obtained from the Nigerian Meteorological Agency (NIMET) was used in this study. ANOVA and Mann-Kendall trend test was used for the data analysis. The ANOVA results showed significant variation in rainfall, maximum and minimum temperature between the stations. The Mann-Kendall trend test result shows an increasing trend in both rainfall and temperature in annual statistics, though statistically insignificant. However, the monthly trends result showed mixed results of both significant and insignificant as well as increasing and decreasing trends. The mean, standard deviation and the coefficient of variation were spatially interpolated using inverse distance weightage technique for easy comprehension. Even though the annual increasing trends result was statistically insignificant except for two out of the ten stations, it is still crucial for planning water-related activities and programs considering the sensitivity and fragility of the region to minor climatic variations. Highlights • Detecting trends and variations in rainfall and temperature series is crucial in the determination of the presence of climate variability • Climate variability is manifested in rainfall and temperature irregularities and in the occurrence of extreme weather events. • The noticeable increase in the rainfall in the area create hope for the socio-economic activities e.g. agriculture and water supply. • Increased in the rainfall and temperature series with the occasional extreme observations are corroborative evidences of increased climate variability. [ABSTRACT FROM AUTHOR]

Temperature trends for KwaZulu-Natal (KZN), South Africa, are investigated for the period 1930–2015, with the intention to test whether interior regions (within ~ 100 km of the coast) are warming faster than coastal regions, given oceanic moderating effects along the coast. This is achieved through analyzing instrumental temperature records from the coastal station of Mount Edgecombe, and adjacent interior stations of Cedara and Emerald Dale. The modified Mann-Kendall test is used to determine annual and seasonal mean temperature ( T ¯ ), maximum temperature (Tmax), and minimum temperature (Tmin) trends for the period 1930–2015, and for the most recent few decades. For annual Tmax, a significant increasing trend (0.07 °C/decade) is recorded at the coast, whereas adjacent interior stations record no trend. Annual Tmin record significant warming at all stations, with warming rates over the interior being double that recorded at the coast for the period 1930–2015. For seasonal Tmin over the interior, significant warming rates are recorded: 0.21 °C/decade (summer), 0.22 °C/decade (autumn), 0.20 °C/decade (winter), and 0.15 °C/decade (spring). Seasonal Tmin warming over the coast were also significant: 0.16 °C/decade (summer), 0.08 °C/decade (autumn), 0.06 °C/decade (winter), and 0.12 °C/decade (spring). Thus, higher lying interior regions are warming at considerably greater magnitudes compared to adjacent coastal areas, mainly due to Tmin warming trends. For the period 1930–2015, record positive annual Tmax anomalies are reported for 2015 at Mount Edgecombe (mean anomaly = 1.6 °C), Cedara (mean anomaly = 1.7 °C), and Emerald Dale (mean anomaly = 2.0 °C). [ABSTRACT FROM AUTHOR]

One of the atmospheric cycle properties is climatic changes which can cause the fluctuations in meteorological parameters. These fluctuations in many world regions are considerable and water and soil resources are affected by them. To prepare against undesirable effect of climate change and adopt suitable development programs and water resources management, it is necessary to investigate the meteorological variable changes. The objective of this research was to investigate the climate change in Urmia region. In this research, the changes trend of temperature, precipitation, relative humidity, sunshine and potential evapotranspiration were studied. To achieve this goal, Urmia synoptic station daily data with 40 years period (1971-2010) were used. The Mann-kendall statistical test at confidence level of 95% was used to investigate the significance of trend in the mentioned parameters. The results showed that the trend slope of maximum, minimum and average of temperature was positive and this trend in 95% confidence level was significant. Urmia precipitation was decreased with slope of -2.26 so that this decrease was significant. The sunshine had positive slope and significant trend, but the negative trend of relative humidity and the positive trend of potential evapotranspiration (0.0068) were not significant. The monthly investigations showed that the average temperature in all months had positive slope, but this slope was not significant in all months. The other parameters in some months had positive or negative slopes.

Assessing of trends of temperature is imperative and fundamental to the success of many sectors of the economy in which water resources is principal ones. The effects of temperature trends on water resources were assessed. Temperature data for 57 years (1960–2016) were collected from Nigerian Meteorological Agency Oshodi. Data were and analyzed using Mann– Kendall non parametric test and Auto Correlation analyses respectively. The results indicated that annual temperature increased in trends in 15 out of 20 stations with return period ranged between 1–2 years to 13–15 years. Stations like Abeokuta, Akure, Enugu, and Maiduguri decreased in trends of annual temperature at rate of 0.080°C/mo/yr, 0.040°C/mo/yr, 0.030°C/mo/yr, and 0.120°C/mo/yr with return period between 1–2 years and 7–19 years. Benin station recorded the highest peak in trends of temperature in the month of September at the rate of 3.390°C/mo/yr with return period of 1–2 years. Some of the effects of these trends on water resources vary from one station to another, depending on the trends and magnitude of return period of temperature. Bauchi and Minna cities were observed to experience high rate of evaporation due to the continuous monotonic increase in trend of annual temperature. [ABSTRACT FROM AUTHOR]

Copyright of SDU Journal of Engineering Sciences & Design / Mühendislik Bilimleri ve Tasarım Dergisi is the property of Journal of Engineering Sciences & Design and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Al-Mustansiriyah Journal of Science is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Dryland ecosystems are highly vulnerable to environmental changes. Monitoring is vital in order to evaluate their response to fluctuating rainfall and temperature patterns for long-term ecosystem safeguarding. Monitoring of long term changes of normalized difference vegetation index (NDVI) and climate variables are fundamental for better understanding of change trajectories in dryland ecosystem, and to ascertain their potential interaction with anthropogenic drivers. In this study, we identify determinant factors of dryland changes by using MODIS NDVI, precipitation and temperature data for Breaks for Additive Seasonal and Trend (BFAST) and Mann Kendall test statistic. BFAST predicts iteratively time and number of changes within a time series data to depict the size and direction of changes. Analysis of NDVI, precipitation and temperature time series data showed substantial changes during the study period of 2000–2014. There is a reduction trend in vegetation showed by the decline in NDVI, with significant breakpoints till 2009 and recovery afterwards, without a significant change in annual trends of precipitation (α < 0.05) for the same study period. Furthermore 2 positive climate trends were founded: a) a significant positive trend on long term annual rainfall during the main rainy seasons and; 2) a significant (α < 0.05) annual increment of the long term mean minimum and mean maximum temperature of 0.03 °C/year and 0.04 °C/year, respectively. This assessment showed that climate variables cannot be considered as the main factors in explaining the observed patterns of vegetation dynamics. Seasonal and interannual precipitation changes have a lower weight as driving factors for the reduction in vegetation trends. Hence, the decline in vegetation productivity of the region can be attributed to the increasing pressure of human activities. [ABSTRACT FROM AUTHOR]

ABSTRACT Using station data from the United States Historical Climatology Network, we preformed a running trend analysis of temperature, precipitation and drought in the Alabama-Coosa-Tallapoosa and Apalachicola-Chattahoochee-Flint river basins for the time period 1895-2012 on annual and monthly timescales. Our study found that long-term precipitation and temperature trends were statistically detectible but relatively slight in the order of an increase at 3 mm per decade for precipitation and a decline of 0.02 °C per decade for temperature. Running trend analyses for the time period 1895-2012 found field-significant and relatively large annual precipitation increases and temperature decreases between the 1950s and early 1980s associated with the 'warming hole'. The magnitude of precipitation trends for the aforementioned period was in the range of 7 mm per year for precipitation and 0.6 °C per decade for temperature. For temperature, we observed generally decreasing maximum, minimum and mean temperatures in the 1960s and 1970s and increasing temperatures from the 1970s to present. Minimum temperatures particularly showed a strong increase in recent summer months in the range of 0.3 °C per decade. Trends in the diurnal temperature range showed a recent narrowing during summer and fall months. Differences in the standardized precipitation index ( SPI) and standardized precipitation evapotranspiration index ( SPEI) did not show a strong effect of temperature on drought for this region. [ABSTRACT FROM AUTHOR]

Temporal streamflow variability in an inland hydrologic station and temporal trends and frequency changes at three weather stations in a semiarid river basin located in Loess Plateau, China, were detected by using linear regression, Mann-Kendall analysis, and wavelet transform methods. Double cumulative curve and ordered clustering were used to identify the hydrological periods of upper Sang-kan (USK) basin between 1957 and 2012. The results indicate that (1) precipitation in the USK basin over the study period did not show any trend, while the temperature showed a significant increase; (2) streamflow flowing out of the USK basin indicated a significant decrease; (3) two distinct hydrological periods - the 'natural period' from 1957 to 1984 and the 'human impact period' from 1985 to 2012 - were present; and (4) the contributions of climate change and human activities to reduce the streamflow were 36.9% and 63.1% respectively. The results indicate that human activities may be contributing to a decrease in streamflow in the USK basin. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

There is a consensus that global warming leads to the frequent occurrence of extreme temperature events that significantly impact human life, water resources, agricultural production, and ecosystems. However, the magnitudes of projected temperatures and the probabilities of extreme event occurrences are still deficient for robust planning and early warning efforts at major river basins. This study aimed to analyze extreme temperature trends and mapping return periods in a changing climate for the case of the upper Tekeze river basin, Northern Ethiopia. The future temperature is projected based on global climate models (GCMs) under RCP 4.5 and RCP 8.5 scenarios. The annual extreme temperatures were obtained from the daily temperature data series for the 12 stations by applying the block maxima series method. The non-parametric Mann-Kendall (M-K) statistical test was used for trend detection. The inverse distance weighted (IDW) method has been used to interpolate the point data and reveal the spatial patterns of the extreme temperature of the 50-year return period. The result shows the future extreme temperature will rise by 0.6–2.2 °C. Moreover, the future extreme temperature revealed a significant increasing trend in most of the stations (around 66.3%). The spatial extent of the 50-year return period of the extreme temperature map showed that in the future (2022–2051), the extreme temperature will be increased by 0.2–3.4 °C compared to the baseline period (1980–2009). The extreme temperature trend and return period mapping under climate change will help better local plans and fine-tune mitigation and adaptation measures. • The future extreme temperatures have been projected using an ensemble of 20 GCMs. • The spatial extent of the extreme temperature return period has been mapped under a changing climate. • The future extreme temperature is expected to rise by 0.2–5 °C once every 50-year. • The finding helps to manage extreme temperature impacts on health, agriculture, and water resources. [ABSTRACT FROM AUTHOR]

The values of a precipitation and air temperature parameters are very important issues in climatological, meteorological and hydrological events. In this study we examined precipitation and air temperature trends in Aegean Region in Turkey for minimum 50 yearly time scale in 95% of confidence intervals. This study aims to determine trends in the long-term annual mean precipitation and air temperature series using the Linear regression analysis, Mann-Kendall and Sen's tests. Results of the temperature data trend show a general increasing trend. But result of the precipitation data trend show a general decreasing trend. [ABSTRACT FROM AUTHOR]

In this paper, the discrete wavelet transform (DWT), the Mann–Kendall (MK) trend test, and the sequential Mann–Kendall test are applied to temperature series at different time scales in order to detect the long-term trends (1956–2010) in synoptic-scale surface temperatures in Iran, as well as the dominant time scales affecting these temperature time series. The relevant data was extracted from a gridded data file of the region (44°E to 63.5°E, 25°N to 40°N) and divided into 12 regular zones (of dimensions 5 × 5°), each of which was analyzed as an individual unit. The results of this research show that at the monthly, seasonal and annual time scales, the trends in temperature were significant and positive in all of the study zones. In addition, the 2-month and 4-month components were dominant at the monthly time scale, the 48-month component dominant at the seasonal time scale, and the 8-year and 16-year components dominant at the annual time scale. Also, the temperature trends in the northern, and especially central, regions of the study zones increased from west to east, and these increasing trends in temperature were most prominent for the spring and summer seasons. The methodology applied here is generally applicable and quite useful for studying both trends and the dominant time scales affecting climatic data series and could find significant applications in related fields. [ABSTRACT FROM AUTHOR]

Monthly, seasonal and annual trends in mean temperatures have been analysed in this study using data from 37 weather stations from the Pakistan Meteorological Department with records from 1952 to 2009. Statistical tests including Sen's slope and Mann-Kendall were applied to each of the 37 stations in order to determine the sign and slopes of trends and their statistical significance. The study reveals that the temperature has generally increased in Pakistan at all time scales analysed over the past few decades. March and the pre-monsoon season were the periods with the highest number of weather stations showing statistical significance, and also with the highest magnitudes of trends. Mean annual temperature increased around 0.36 °C/decade. This rise in temperature is slightly higher than other results found for Pakistan. The association between temperatures and certain teleconnection patterns, as well as the influence of the urban effect, might be among the causes of the trends found in this study. The largest number of correlations between mean temperatures and teleconnection patterns was found in March, April and May with NAO, ENSO and NCP, respectively. The North Atlantic Oscillation (NAO) may also have an influence on the temperatures of certain months in the monsoon season and particularly in August. At a seasonal resolution, NAO and NCP may control temperatures in the pre-monsoon season. The lowest number of sites exhibiting correlations was found in winter and in the post-monsoon seasons. Copyright © 2012 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Abstract: Based on monthly mean temperature and precipitation data for 53 years, from 1957 to 2009, recorded at the Zhangweinan River Basin and five main meteorological stations around it, the non-parametric Mann-Kendall trend test method and cumulative anomaly methods were adopted to analyze the long-term trends here of such key meteorological elements as annual mean temperature, maximum temperature, minimum temperature and precipitation; the corresponding Hurst index was calculated; and future change trends for various meteorological elements were predicted. The results of the analyses indicate that: there is an inconspicuous downward trend in annual precipitation for the Zhangweinan River Basin, with large decreases appearing in summer, with an M-K slope of -11.82mm/10a; the annual mean temperature rises more significantly, and the M-K slope of the whole Basin''s annual mean temperature reaches 0.17°C/10a, the temperature increase being significant in spring and winter. According to the Hurst Index calculations, the annual mean temperature and precipitation series show strong continuity in the Zhangweinan River Basin, which indicates that the future trend will be consistent with that of the past. These research results will not only help provide evidence for the climate change in the Zhangweinan River Basin but can also lay the foundation for further studies on water resources security evaluation in conditions of climate change. [Copyright &y& Elsevier]

Climate variability and change constitute major challenges for Africa, especially West Africa (WA), where an important increase in extreme climate events has been noticed. Therefore, it appears essential to analyze characteristics and trends of some key climatological parameters. Thus, this study addressed spatiotemporal variabilities and trends in regard to temperature and precipitation extremes by using 21 models of the Coupled Model Intercomparison Project version 6 (CMIP6) and 24 extreme indices from the Expert Team on Climate Change Detection and Indices (ETCCDI). First, the CMIP6 variables were evaluated with observations (CHIRPS, CHIRTS, and CRU) of the period 1983–2014; then, the extreme indices from 1950 to 2014 were computed. The innovative trend analysis (ITA), Sen's slope, and Mann–Kendall tests were utilized to track down trends in the computed extreme climate indices. Increasing trends were observed for the maxima of daily maximum temperature (TXX) and daily minimum temperature (TXN) as well as the maximum and minimum of the minimum temperature (TNX and TNN). This upward trend of daily maximum temperature (Tmax) and daily minimum temperature (Tmin) was enhanced with a significant increase in warm days/nights (TX90p/TN90p) and a significantly decreasing trend in cool days/nights (TX10p/TN10p). The precipitation was widely variable over WA, with more than 85% of the total annual water in the study domain collected during the monsoon period. An upward trend in consecutive dry days (CDD) and a downward trend in consecutive wet days (CWD) influenced the annual total precipitation on wet days (PRCPTOT). The results also depicted an upward trend in SDII and R30mm, which, additionally to the trends of CDD and CWD, could be responsible for localized flood-like situations along the coastal areas. The study identified the 1970s dryness as well as the slight recovery of the 1990s, which it indicated occurred in 1992 over West Africa. [ABSTRACT FROM AUTHOR]