Spatiotemporal variability of land surface temperature in north-western Ethiopia

Abstract

The aggravating deforestation, industrialization and urbanization are increasingly becoming the principal causes for environmental challenges worldwide. As a result, satellite-based remote sensing helps to explore the environmental challenges spatially and temporally. This investigation analyzed the spatiotemporal discrepancies in Land Surface Temperature (LST) and the link with elevation in Amhara region, Ethiopia. The Moderate Resolution Imaging Spectroradiometer (MODIS) LST data (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018)(2019)(2020) was used. The pixel-based linear regression model was employed to explore the spatiotemporal discrepancies of LST changes pixel-wise.Furthermore, Sen's slope and Mann-Kendall were used for determining the extent of temporal shifts of the areal average LST and evaluating trends in areal average LST values, respectively.Coefficient of Variation (CV) was calculated to examine spatial and temporal discrepancies in seasonal and annual LST for each pixel. The distribution of average seasonal LST spatially ranged from 43.45-16.62℃, 39.89-14.59℃, 50.39-21.102℃ and 43.164-20.39℃ for autumn (September-November), summer (June-August), spring (March-May) and winter (December-February) seasons, respectively. The seasonal LST CV varied from1.096-10.72%, 0.7-11.06%, 1.29-14.76% and 2.19-10.35% for average autumn, summer, spring and winter seasons, respectively. The seasonal spatial LST trend varied from -0.7-0.16, -0.4-0.224, 0.6-0.19 and -0.6-0.32 for average autumn, summer, spring and winter seasons, respectively. Besides, the annual spatial LST slope varied from -0.58-0.17. An insignificantly declining trend in LST shown at 0.036℃ yr -1 , 0.041℃ yr -1 , 0.074℃ yr -1 , 0.005℃ yr -1 in autumn, summer, spring and winter seasons (P<0.05), respectively. Moreover, the annual variations of mean LST decreased insignificantly at 0.046℃ yr -1 . Generally, the LST is tremendously variable in space and time and negatively correlated with an elevation.

Climate trend analysis for a semi-arid Borana zone in southern Ethiopia during 1981–2018

“…It is observed in the study area that, seasonal variability of temperature is observed even though it is not at the scale of precipitation. Similar pattern of temperature was observed in the studies conducted by (Mengistu et al 2014;Wedajo et al 2019;Bayable and Alemu 2021;Belay et al 2021). On the contrary to this result, Alemayehu et al (2020) found a significant decreasing trend of maximum temperature particularly during Bega season and an overall decreasing trend of annual and seasonal temperature in Alwero watershed in western part of Ethiopia.…”

“…in eastern and southeastern Ethiopia andHarka et al (2021) in the upper Wabishebelle River Basin. Mean monthly rainfall shows a statistically significant increasing trend (P-value < 0.05) during August, October and November whereas during the remaining months, it is true to not to reject the null hypothesis for the existence of trend in the time series Bayable et al (2021). also found not significant decreasing trend of rainfall during all the months except in July, October and November between 1983 and 2019 in Western Harerghe zone, eastern Ethiopia.Concerning temperature, the mean Tmax and Tmin observed in the study area were 29.66 °C and 16.33 °C respectively.…”

Variability and time series trend analysis of temperature over 1981-2018 in semi-arid Borana zone, southern Ethiopia

“…Therefore, there found to be inter-annual variability of temperature in the Borana lowland. Similar pattern of temperature was observed in the studies conducted by (Mengistu et al 2014;Wedajo et al 2019;Bayable and Alemu 2021;. On the contrary to this result, Alemayehu et al (2020) From this it can be concluded that, temperature is not uniformly distributed across the Borana lowland.…”

“…Climate variability study gained careful attention and the most important parameters either temperature and/or rainfall were studied at national/sub-national scale to watershed level. A range of studies has been carried out in this aspect (Gebrehiwot and van der Veen 2013;Jury and Funk 2013;Mengistu et al 2014;Fazzini et al 2015;Wassie and Fekadu 2015;Biraraet al 2018;Asfaw et al 2018;Wedajo et al 2019;Tesfamariam et al 2019;Esayas et al 2019;Gedefaw et al 2019;Mekonnen and Berlie 2020;Berhane et al 2020;Alemayehu et al 2020;Bayable and Alemu 2021;Belay and Demissie et al 2021). Some of these studies used satellite-based data sources which provides long-term data over a century but coarse resolution; while others studied large-scale spatial variability such as country level or beyond.…”

Spatial and Temporal Variation of Land Surface Temperature and Its Spatially Heterogeneous Response in the Urban Agglomeration on the Northern Slopes of the Tianshan Mountains, Northwest China

“…The Mann–Kendall (M–K) test is a nonparametric trend test, which is often used to determine the significance of changes in temperature, precipitation, and other factors over a long time series, mainly through the standard statistic Z and confidence level α to determine the significance of the data [ 50 , 51 ]. Suppose the LST time series are , and they are independently identically distributed, for any and , the statistic S is calculated: where is the symbolic function whose function equation is: …”