Analysis of the trends of climate variability over two different eco-regions of Ethiopia

Abstract This study analyzed the trends of precipitation and temperature in two eco-regions, which represent the whole part of Ethiopia based on climate variations. Mann–Kendall, Sen’s slope estimator test and innovative trend analysis method were used to detect precipitation and temperature trends. The observed historical meteorological data from 1980 to 2016 were used to analyze the trends in this study. MATLAB software was used to analyze the trends of climate variability. The findings of this study showed that the trends of precipitation were statistically significant with a positive trend in Gondar (β = 1.84) and Bahir Dar (β = 1.80) of highland eco-regions, whereas a significant increasing trend was observed in Negele (β = 23.40) and Gewane (β = 0.10) of lowland eco-regions. However, Sekoru (β = 0.01) and Degahabur (β = 4.13) stations showed a significant decreasing trend. As far as trends of temperature are concerned, a statistically significant increasing trend of temperature was observed in Gondar (β = 0.04) and Bahir Dar (β = 0.08), and a sharp significant decreasing trend was observed in Sekoru (β = 0.01) stations of highland eco-regions. The lowland eco-regions (Gewane (β = 0. 10), Degahabur (β = 0.03) and Negele (β = 0.07)) showed a statistically significant increasing trend. The consistency in precipitation and temperature trends over the two eco-regions of Ethiopia confirms the robustness of the change in trends. Further study should be done by taking more stations and datasets to reach a conclusion whether climate change has occurred or not. However, the findings of this study could provide insights for policy- and decision-makers to take proactive measures for climate change mitigation.

The global seasonal temperature has been showing an increasing trend across the globe.Global land and ocean surface temperature has increased by 0.85°C during 1880-2012.Climate change is expected to exacerbate variability in rainfall and temperature in Ethiopia, potentially increasing farmers' exposure to climate-related risks.Ethiopia is classified into two eco-regions, i.e, highland and lowland.Strong topographic contrasts lead to high spatial variability of climatic conditions in these eco-regions.Thus, this study analyzed the trends of precipitation and temperature in two eco-regions using Mann-Kendall (MK), innovative trend analysis method (ITAM) and Sen's slope estimator tests.It was confirmed that precipitation is mainly caused by cold summer, and thus correlates to a large extent with temperature in the study area.The findings of this study could provide insights for policy-and decision-makers to take proactive measures for climate change mitigation.

Introduction
The global seasonal temperature has been showing an increasing trend across the globe (Jemal et al., 2022).The historical changes in global mean rainfall have been more uncertain, varying by season and region (Asfaw et al., 2017;Jemal et al., 2022).Global land and ocean surface temperature has increased by 0.85°C during 1880-2012(IPCC, 2013)).The average global temperature for the years 2015-2019 is the warmest period recorded in history (Gemeda et al., 2021).It is estimated to be 1.1°C (±0.1°C) above the pre-industrial times.
Extreme changes in rainfall and temperature were observed at different parts of the world (Worku et al., 2018).Climate change is expected to exacerbate variability in rainfall and temperature in Ethiopia, potentially increasing farmers' exposure to climate-related risks (Dereje et al., 2020).Such changes in precipitation and rising temperature are undeniably clear with the impacts affecting ecosystems and biodiversity (Gong et al., 2018;Wen et al., 2017).Ethiopia is characterized by erratic and unreliable rainfall (Seleshi & Zanke, 2004;Wen et al., 2017).The variation is very high when comparing the highland parts of the country with its lowland regions (Gedefaw et al., 2018).This study investigated the trends of climate variations in these two eco-regions.Strong topographic contrasts lead to high spatial variability of climatic conditions in highland eco-regions (Dereje et al., 2020).The lowland eco-regions are particularly affected by drought and extreme heats.Most deserts are found in the lowland parts of the country.Thus, it is essential to examine climate variability and trends in these eco-regions.Climate change and variability have negative impacts on water resources, agriculture and livelihoods, which leads to food insecurity (Gemeda et al., 2021).Scientific evidence indicates that rainfed agriculture is severely affected by the change in climate (Alemayehu & Bewket, 2016;Seaman et al., 2014).Climate change that leads to extreme events, such as flooding, drought and excessive heat, contributes to the increment of global food prices (Tabari et al., 2015;Ureta et al., 2020;Wu et al., 2016).The magnitude of the climate change effect relies on the level at which the community relies on rainfed agriculture, level of technology and institutional capacity to adapt such situations (Naab et al., 2019).
Concrete information is needed to clearly understand the climate variability and trend analysis at a spatiotemporal scale.These analyses have been used to inform adaptation options for agriculture and water resources sectors (Bewket, 2014).The trends of rainfall and temperature were analyzed using MK, Sen's slope estimator and ITAM.These methods are very common to detect the trends of climate datasets.Numerous studies have been conducted so far in Ethiopia to examine climate variability and trends using the above methods (Asfaw et al., 2017;Behailu et al., 2014;Bewket, 2007;Gedefaw et al., 2018;Girma et al., 2016;Mekasha et al., 2014;Seleshi & Zanke, 2004;Tekleab et al., 2013;Yenehun et al., 2017).
However, no study has examined the trends and variability of climate in the given two ecoregions of Ethiopia yet.Thus, this study aimed to investigate the spatiotemporal characteristics of climate variability and trends over these two eco-regions.The findings of this study will provide insights for water resource managers for future sustainable water resources management.

Description of the study area
Ethiopia is lying between 3°−15° north latitude and 33°-48° east longitude (Figure 1).It covers a total area of about 1.12 million km 2 and consists of 12 river basins (Seleshi & Zanke, 2004).It is estimated that the total number of population is 120 million.It is divided into two eco-regions, namely highlands and lowlands (Wondie et al., 2011).The country is characterized by seasonal and annual variability of rainfall (Seleshi & Zanke, 2004).The mean annual precipitation is 834.97 mm, with 509.93 and 1015.90 mm as the minimum and maximum precipitation, respectively.However, the mean annual temperature is 29.16°C.The minimum and maximum temperatures are 27.92°C and 30.35°C, respectively.

Data sources
Daily precipitation and temperature data were collected from 1980 to 2016 from the National Meteorological Services Agency of Ethiopia (Table 1).

Methods
Long-term trends in the observed and adjusted time series data were detected using trend detection methods (Figure 2).Significance levels at 10%, 5% and 1% were taken to assess the precipitation and temperature trends.

Mann-Kendall trend detection
The MK test statistics (Kendall, 1975;Mann, 1945) used a non-parametric test to detect the trends of precipitation and temperature time series data using the following equations.MK is insensitive to outliers and does not require data to be normally distributed.The trend test is applied to X i data values (i = 1, 2, . . .,n-1) and X j (j=i + 1,2, . . .n).The data values of each X i are used as a reference point to compare with the data values of X j which is given as: where X i and X j are the values in period i and j.When the number of data series is greater than or equal to 10 (n ≥ 10), MK test is then characterized by normal distribution with the mean E(S) = 0 and variance (Var(S)) is equated as follows (Ma et al., 2014): where m is the number of the tied groups in the time series, and t k is the number of data points in the kth tied group.The test statistic Z is as follows: In time sequence, the statistics are defined independently: Given the confidence level α, if UF k > UFα/2, it indicates that the sequence has a significant trend.Then, the time sequence is arranged in reverse order.According to the equation calculation, while making

Methods Analysis
Annual precipitation UB k and UF k are drawn as UB and UF curve.If there is an intersection between the two curves, the intersection is the beginning of the mutation (Zhang et al., 2012).

Sen's slope estimator test
The slope (Q i ) between two data points is equated as follows (Sen, 1968): where X j and X k are the data points at time j and k (j > k), respectively.

Innovative Trend Analysis Method (ITAM)
The trend indicator of ITAM is multiplied by 10 to make the scale similar with the other two tests.
The trend indicator is calculated as follows (Sen, 2014): where ϕ = trend indicator, n = number of observations in the subseries, X i = data series in the first half subseries class, X j = data series in the second half subseries class and μ = mean of the data series in the first half subseries class.

Precipitation concentration index (PCI)
The PCI was adopted to quantify the distribution of rainfall and its heterogeneity pattern across the stations (Ademe et al., 2020;Guo et al., 2020).PCI values were categorized as uniform (<10), moderate (11-15), irregular (16-20) and strongly irregular (>20) in monthly rainfall distributions (De Luis et al., 2011).The PCI of the six stations is depicted in Table 2.
The annual PCI was computed as follows: where P i is the amount of rainfall of the ith month.

Data preparation and quality control
Daily data were averaged to monthly and annual data for each station to simplify the calculations.Missing data were also checked.The data were arranged in Excel data sheet as required for each analysis.The data were also checked for significant difference in each datasets as well as stations.

Analysis of mean annual precipitation and temperature
The results revealed that the annual rainfall was found to be 834.97mm and coefficient of variation was 15% (CV = 15%).The maximum rainfall was 1015.90 mm and the minimum rainfall was 509.93 mm.The findings showed that the highland eco-regions received high amount of rainfall (>650 mm) (Gondar, Bahir Dar and Sekoru), whereas the lowland eco-regions received less rainfall, which accounts about 20.30% (Gewane, Degahabur and Negele).The mean annual temperature was found to be 29.16°C.The maximum and minimum temperatures were 30.35°C and 27.92°C, respectively.Figure 3 shows some selected stations with seasonal variability of precipitation in Ethiopia.However, this study only focused on two eco-regions, i.e highland ecoregions (Gondar, Bahir Dar and Sekoru) and lowland eco-regions (Gewane, Degahabur and Negele).
Results indicate that all stations in the study area showed a positive trend in mean maximum temperature over the study period, which is in line with the increasing global mean temperature and increasing number of warm days and warm nights in Ethiopia.More concentrated spatial storm events could be expected with higher temperatures as global temperature increases (Wasko et al., 2016).The mean annual maximum temperature change over the country is about 0.01°C/ year over the last 50 years (NMSA, 2001).Land use, land cover change and over exploitation of natural resources are the main driving forces for the variations of current trends of maximum temperature over the study area.The present study indicated that the mean maximum temperature across the study area showed statistically significant positive trends at five out of six stations.This is exactly consistent with the results of Suryabhagavan ( 2017), who has reported that most of the weather stations in Ethiopia experienced a significant increasing trend in temperature.This needs policy interventions and public awareness to decrease the adverse impacts of climate change.

Analysis of mean annual precipitation trends
The findings of this study showed that the trends of precipitation were statistically significant with an increasing trend in Gondar (β = 1.84) and Bahir Dar (β = 1.80) of highland eco-regions (Table 3).A significant increasing trend was observed in Negele (β = 23.40) and Gewane (β = 0.10) of lowland eco-regions.However, Sekoru (β = 0.01) and Degahabur (β = 4.13) stations showed a significant decreasing trend (Figure 3).Four out of six stations showed a positive trend of precipitation, whereas Sekoru and Degahabur showed negative trends.Table 3 shows the statistical trend results of precipitation using MK, ITAM and Sen's slope estimator tests.Similar results were reported by Gemeda et al. (2021) where a statistically significant decreasing trend of rainfall was observed at Sekoru station.The inter-annual variability of rainfall is a common phenomenon across the different parts of the country including the above eco-regions (Suryabhagavan, 2017).Mekasha et al found contrasting results on Negele station that reported a negative trend of precipitation in Negele, which represent site specific and region wide differences in climate.Overall, the findings of the present study are consistent with other studies (Asfaw et al., 2017;Gedefaw et al., 2018;Gemeda et al., 2021;Suryabhagavan, 2017).The changes in these climatic elements across the stations during the study period ) could be associated with human activities and climate changes.

Analysis of mean annual maximum temperature trends
The trend detection result showed that a statistically significant increasing trend of temperature was observed in Gondar (β = 0.04) and Bahir Dar (β = 0.08) and a sharp significant decreasing trend in Sekoru (β = 0.01) stations of highland eco-regions (Table 4).Lowland eco-regions (Gewane (β = 0. 10), Degahabur (β = 0.03) and Negele (β = 0.07)) showed a statistically significant  increasing trend (Figure 4 and 5).Table 4 shows the statistical trend results of maximum temperature using MK, ITAM and Sen's slope estimator test.Five out of six stations showed increasing trends of temperature during the study period.Only Sekoru station showed a sharp decreasing trend.Gemeda et al. (2021) also found statistically significant decreasing trend at Sekoru station (−2.22).The results of the present study are generally consistent with previous studies on climate change trends in the same study area, which reported significant increasing trends in the mean annual maximum temperature (Asfaw et al., 2018;Gedefaw et al., 2018;Jemal et al., 2020).Inter-annual variability of temperature is also more persistent in the study area than rainfall variability (Fig 4).The observed increasing temperature in the area has a significant impact on agricultural activities, and more evapotranspiration lead to lose more water from the catchment.These changes may be due to land use, land cover changes and human activities.

Correlation analysis
The correlations analysis between precipitation and temperature showed a coherent pattern of relationship (Figure 6).It was confirmed that precipitation is mainly caused by cold summer, and thus correlates to a large extent with temperature in the lowland eco-regions.There is a fluctuation of the two climatic variables over the different stations across the eco-regions.The findings of this study are consistent with Behailu et al. (2014), Gedefaw et al. (2018), Girma et al. (2016), Tekleab et al. (2013) and Yenehun et al. (2017).The cause of these changes could be associated with anthropogenic actions.
Some stations, such as Sekoru and Degahabur, showed decreasing trends of precipitation (Figure 6(c,e)).These could impact the sustainability of water resources recharge (Karmeshu, 2015).Increasing transpiration due to increasing of temperature could increase the chance of rainfall and may interfere groundwater recharge triggered by summer season reduction.

Conclusions
The present study investigated the trends of mean annual precipitation and maximum temperature at two eco-regions of Ethiopia.The findings showed that the highland eco-regions received high amount of rainfall (≥650 mm), but the lowland regions received less rainfall.The mean annual rainfall was found to be 834.97mm.The maximum rainfall was 1015.90 mm and the minimum rainfall was 509.93 mm.The mean annual temperature was found to be 29.16°C.The maximum and minimum temperatures were 30.35°C and 27.92°C, respectively.Precipitation showed statistically significant increasing trend in Gondar, Bahir Dar, Negele and Gewane stations.The declining trend in mean annual precipitation in the latest decade has changed the overall scenario of rainfall in the study area, and this variability may impact future climatic conditions and agricultural practices.
As far as trends of temperature are concerned, statistically significant increasing trend of temperature was observed in Gondar and Bahir Dar highland eco-regions as well as in all lowland eco-regions.This could imply that there is an occurrence of climate change.The major contributor to the decline in annual precipitation is the occurrence of frequent drought.Lowland eco-regions are very sensitive to seasonal rainfall changes.Further study should be conducted to confirm the change in climate in the study eco-regions by taking latest datasets and including more stations.However, the findings of this study could help to understand the trends in precipitation and temperature in the two eco-regions of Ethiopia.Thus, policy-makers should plan to minimize the adverse effects of climate change through improving the accessibility of weather forecasting and improving climate resilient green economy.Policy intervention should be taken towards climate change adaptation and mitigation strategies in these two eco-regions.

Figure 1 .
Figure 1.Location map of the study area.

Figure 4 .
Figure 4. Seasonal variability of rainfall across the country.

Figure
Figure 5. Trend analysis of precipitation.