A Trend Analysis of Temperature in Selected Stations in Nigeria Using Three Different Approaches

Rainfall and temperature are the two major climatic variables affecting humans and the environment. Hence, it is essential to study rainfall and temperature variability over urban areas. This study focused on analyzing the spatiotemporal trends and variability of rainfall and temperature over Benin metropolitan region, Nigeria. Time series analysis was used to determine temporal trends in rainfall as well as minimum and maximum atmospheric temperatures over a study period of 30 years (1990 to 2019). Analysis of variance was used to understand spatiotemporal variations of climatic elements among the spatial units (urban core, intermediate and peripheral areas). Land surface temperature (LST) and land use/land cover (LULC) classes of the study area were analyzed from Landsat TM Imagery of 2020. Results revealed a decreasing trend for rainfall and increasing trend for minimum and maximum atmospheric temperatures in all the spatial units. Rainfall distribution and temperature among the spatial units were statistically insignificant; however, significant temporal decadal variations were noticed for minimum and maximum air temperatures. This investigation provided valuable information for assessing changes in rainfall and temperature and concluded that the study area is becoming warmer; an indication of global warming and climate change.

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“…Similarly, other studies (Ragatoa et al 2018;Eresanya et al 2018;Amadi et al 2014) have shown a rising trend in air temperature across Nigeria.…”

Section: Trend Analysis Of Atmospheric Temperaturesupporting

confidence: 51%

Spatiotemporal Trends And Variability Analysis Of Rainfall And Temperature Over Benin Metropolitan Region, Edo State, Nigeria

Balogun

Ekpenkhio

Ebena

2023

GES

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“…Mann-Kendall (MK) and four modified Mann-Kendall methods (MMK) were applied to examine the trends. Previous studies showed better performance of the MMK method with the monthly data [169]. The results of the MK and MKK tests applied to the NDVI data series at a confidence interval of 90% are shown in Table 9.…”

Section: Spatiotemporal Analyses Of Trend Using Landsat Ndvi Time Seriesmentioning

confidence: 90%

Multidecadal Trend Analysis of Armenian Mountainous Grassland and Its Relationship to Climate Change Using Multisensor NDVI Time-Series

Muradyan¹,

Asmaryan²,

Ayvazyan³

et al. 2022

Preprint

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This paper presents a comprehensive analysis of links between satellite-measured vegetation vigor and climate variables in Armenian mountain grassland ecosystems in years 1984–2018. NDVI is derived from MODIS and Landsat data, temperature and precipitation data are from meteorological stations. Two study sites were selected, representing arid and semi-arid grassland vegetation types, respectively. Various trend estimators including Mann-Kendall (MK) and derivatives were combined for vegetation change analysis at different time scales. Results suggest that temperature and precipitation had negative and positive impacts on vegetation growth, respectively, in both areas. NDVI-to-precipitation correlation was significant but with an apparent time-lag effect that was further investigated. No significant general changes were observed in vegetation along the observed period. Further comparisons between results from corrected and uncorrected data led us to conclude that MODIS and Landsat data with BRDF, topographic and atmospheric corrections applied are best suited for analyzing relationships between NDVI and climatic factors for the 2000-2018 period in grassland at a very local scale, but in the absence of correction tools and information, uncorrected data can still provide meaningful results. Future refinements will include removal of anthropogenic impact, and deeper investigation of time-lag effects of climatic factors on vegetation dynamics.

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“…Wavelet analysis (Abdullayev et al, 2017;Joseph et al, 2015;Banović et al, 2013), as the name suggests, is a small waveform. The so-called "small" or "let" means that it has attenuation; the so-called "wave" refers to its volatility, and its X. T. Tian et al Mann-Kendall is also often used for the detection of precipitation and drought frequency trends under the influence of climate change (Bera, 2017;Ragatoa et al, 2018;Koudahe et al, 2017).…”

Section: Methodsmentioning

confidence: 99%

Characteristics Analysis on Short-Time Heavy Rainfall during the Flood Season in Shanxi Province, China

Tian¹,

Li²,

Zhou³

et al. 2019

GEP

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In order to provide a reference for the correct forecasting of short-term heavy rainfall and better disaster prevention and mitigation services in Shanxi Province, China, it is very important to carry out systematic research on short-term heavy precipitation events in Shanxi Province. Based on hourly precipitation data during the flood season (May to September) from 109 meteorological stations in Shanxi, China in 1980-2015, the temporal and spatial variation characteristics of short-time heavy rainfall during the flood season are analyzed by using wavelet analysis and Mann-Kendall test. The results show that the short-time heavy rainfall in the flood season in Shanxi Province is mainly at the grade of 20-30 mm/h, with an average of 97 stations having short-time heavy rainfall each year, accounting for 89% of the total stations. The short-time heavy rainfall mainly concentrated in July and August, and the maximal rain intensity in history appeared at 23-24 on June 17, 1991 in Yongji, Shanxi is 91.7 mm/h. During the flood season, the short-time heavy rainfalls always occur at 16-18 pm, and have slightly different concentrated time in different months. The main peaks of June, July and August are at 16, 17 and 18 respectively, postponed for one hour. Short-time heavy rainfall overall has the distribution that the south is more than the north and the east less than the west in Shanxi area. In the last 36 years, short-time heavy rainfall has a slight increasing trend in Shanxi, but not significant. There is a clear 4-year period of oscillation and inter-decadal variation. It has a good correlation between the total precipitation and times of short-time heavy rainfall during the flood season.

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A Trend Analysis of Temperature in Selected Stations in Nigeria Using Three Different Approaches

Cited by 17 publications

References 40 publications

Spatiotemporal Trends And Variability Analysis Of Rainfall And Temperature Over Benin Metropolitan Region, Edo State, Nigeria

Spatiotemporal Trends And Variability Analysis Of Rainfall And Temperature Over Benin Metropolitan Region, Edo State, Nigeria

Multidecadal Trend Analysis of Armenian Mountainous Grassland and Its Relationship to Climate Change Using Multisensor NDVI Time-Series

Characteristics Analysis on Short-Time Heavy Rainfall during the Flood Season in Shanxi Province, China

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