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More than 85% of the Ethiopian population's livelihood depends on rain-fed agriculture. Therefore, accurate climate estimation is quite useful to improve food security. However, the poor spatial resolution of satellite open access Outgoing Long-wave Radiation (OLR) data and the complicated relationship with the temperature and precipitation over variable topography features, the climate estimation is below the satisfactory level. Hence, to address this problem, this paper aimed to model OLR based on moisture parameters related to the air temperature in Ethiopia. European Center for Medium-Range Weather Forecast (ECMWF) and satellite data from 1981 to 2020 has been used to develop a new OLR model. The atmospheric moisture budget equation was applied for the new OLR mode development. The results indicated that the seasonal variation moisture coefficient (α) for winter, spring, summer, and autumn is found 0.99, − 0.29, 0.91, and 0.98 m3w−1 which is satisfied the model requirement. During winter, spring, summer, and autumn, the average value of OLR are found 269.60, 246.10, 247.90, and 255.60 Wm−2 from satellite direct observation respectively; while from the developed model is found at 268.79, 244.01, 248.97 and 254.93 Wm−2 respectively. Based on error matrices the developed mode is well agreed with satellite direct observation at a specific point and it is helpful to estimate OLR in the required spatial resolution. Generally the increment of the local moisture which is decreased OLR and increases the air temperature. Hence, stakeholders must pay high attention to the new OLR model adaptations for flood prevention and drought monitoring in Ethiopia. [ABSTRACT FROM AUTHOR]

Rapid urbanisation is affecting people in different ways, with some becoming more vulnerable to the impacts of climate change. Africa's cities are projected to be home to nearly 60% of the continent's population by 2050. In conjunction with climate change, these cities are experiencing critical environmental challenges, including changes in the urban thermal environment. Urban areas generally exhibit significantly higher air and surface temperatures than their surrounding rural areas, resulting in urban heat islands. However, little has been done to synthesise existing knowledge and identify the key research gaps in this area, particularly in Africa. This paper focuses on the combined effects of urbanisation and climate change on the urban thermal environment in Africa, and provides a comprehensive review of results, major advances and the dominant direction of research. Our review of 40 publications from peer-reviewed journals from 2000 to 2021 revealed that South Africa, Ethiopia and Nigeria were most frequently studied, and satellite imagery-based data and analysis were used predominantly. Results from a few studies have shown the practical implications for urban land-use planning, informal settlement management, human wellbeing and productivity, energy use, air pollution and disease spread. Integrated approaches, strengthening planning institutions, and early warning systems are proposed to address climate change. Low-income groups are emphasised in efforts to help people cope with heat stress. Solutions based on land use and land cover dynamics and blue–green infrastructure are mentioned but are in need of further research. Cities with similar patterns of urbanisation, geographies and climate conditions could benefit from multi-disciplinary research collaboration to address the combined impacts of rapid urbanisation and climate change. [ABSTRACT FROM AUTHOR]

This paper examines soil temperature (Ts) in two different plantation forests relative to an adjacent open land area in a tropical highland environment. To achieve the objectives, Ts in a Juniperus procera (JP) plantation, a Grevillea robusta (GR) plantation, and in the adjacent open land (OL) area were measured. One-way ANOVA and Pearson's correlation were used for the data analysis. The result indicated that the mean daily Ts in the OL area at 10-cm depth of the soil was greater than the mean daily Ts recorded in the JP and GR plantations by 5 °C and 6 °C, respectively. The OL area Ts recorded at different soil depths (10 cm and 20 cm) was significantly different (p < 0.05). Rainfall (RF) and air temperature (Ta) of the study area have a direct relationship with the Ts in the plantation forests. The RF and Ta do not have a significant relationship with the Ts in the OL area at 10-cm soil depth. Overall, the study indicated that the Ts in the open land area was highly fluctuating monotonically, while it is relatively constant in the plantation forests. [ABSTRACT FROM AUTHOR]

The impact of climatic change can be on specific locations. However, the broader the affected area coverage, in mind, the higher would be the chance in missing critical details. In this light, this paper attempts to assess the possible climatic changes and their corresponding implications on agricultural production in northern Ethiopia. The analysis is based on the future (2030 and 2050) temperature and rainfall data, downscaled as ensemble of four general circulation models (GCMs) using the A2 and B1 emission scenarios for ten meteorological stations located in different agroecological zones of the study region. The result indicates that, based on emission scenarios, the mean maximum and minimum temperature would increase by 2-2.3 and 0.8-0.9 °C in 2030 and by 2.2-2.7 and 1.4-1.7 °C in 2050, respectively. This will be accompanied by an increase in the frequency of hot days and nights and a decrease in cool days and nights. While annual rainfall totals will remain unchanged, main rainy season ( kiremt) rainfall total would increase on average in 12.9 and 14.2 % under A2 and 9.5 and 11.2 % under B1 by 2030 and 2050, respectively. Owing to an increase in kiremt rainfall, the yield of maize and sorghum may increase at some sites under future climatic conditions, and the increase would be higher under CO fertilization. The results suggest the need for site-specific adaptation strategies to reduce the impact and/or exploit the opportunities of climate change. [ABSTRACT FROM AUTHOR]

The ability to produce high-resolution climate maps is crucial for assessing climate change impacts and mitigating climate disasters and risks in developing countries. Mainstream geostatistical downscaling techniques use spatial interpolation or multi-linear regression models to produce high-resolution climate maps in data-scarce regions. Since global climate evolution is a nonlinear process governed by complex physical principles, these linear downscaling techniques cannot achieve the desired accuracy. Moreover, these techniques cannot utilize different resolution data as model inputs. In this study, we developed a hybrid of multilayer perceptrons that could couple high-resolution topographic data with sparse climate observation data well and then generate high-resolution climate maps. To test the performance of our tool, we generated high-resolution precipitation and air temperature maps using sparse observation data from 21 meteorological stations in Ethiopia. The accuracy of the high-resolution climate maps generated using our hybrid of MLPs clearly outperformed those using a multi-linear regression model or a pure MLP. [ABSTRACT FROM AUTHOR]

Eastern Africa has experienced strong climatic changes since the last deglaciation (15 000 years ago). The driving mechanisms and teleconnections of these spatially complex climate variations are yet not fully understood. Although previous studies on lake systems have enhanced our knowledge of Holocene precipitation variation in eastern Africa, relatively few studies have reconstructed the terrestrial temperature history of eastern Africa from lake archives. Here, we present (i) a new branched glycerol dialkyl glycerol tetraether (brGDGT) temperature calibration that includes Bale Mountains surface sediments and (ii) a quantitative record of mean annual air temperature (MAT) over the past 12 ka cal BP using brGDGTs in a sediment core collected from Garba Guracha (3950 m a.s.l.) in the Bale Mountains. After adding Bale Mountains surface sediment (n=11) data (Baxter et al., 2019) to the existing East African lake dataset, additional variation in 6-methyl brGDGTs was observed, which necessitated modifying the MBT 5ME′ calibration (MBT denotes methylation of branched tetraethers) by adding 6-methyl brGDGT IIIa ′ (resulting in the MBT Bale Mountains index, r2=0.93 , p<0.05). Comparing the MBT 5ME′ and the new MBT Bale Mountains index, our high-altitude Garba Guracha temperature record shows that warming occurred shortly after the Holocene onset when the temperature increased by more than 3.0 ∘C in less than 600 years. The highest temperatures prevailed between 9 and 6 kacalBP , followed by a temperature decrease until 1.4 kacalBP. The reconstructed temperature history is linked to supraregional climatic changes associated with insolation forcing and the African Humid Period (AHP), as well as with local anomalies associated with catchment deglaciation and hydrology. [ABSTRACT FROM AUTHOR]

Identifying general circulation models (GCMs) that represent the climate of a specific area is crucial for climate change studies. However, the uncertainties in GCMs caused by computational constraints, such as coarser resolution, physical parameterizations, initializations, and model structures, make it imperative to identify a representative individual or group of GCM for a climate impact study. An advanced envelope-based multi-criteria selection approach was used to identify a subset of the most appropriate future GCMs in the Upper Awash Basin (UAB). The skill accounting is based on (1) the range of projected mean changes of climate variables, (2) range of variability in climate extremes, and (3) model run performance to represent historical climate data. Statistical Downscaling and bias correction were made for the selected model runs. The downscaled and bias-corrected monthly values for precipitation are expected to increase from 0.42 to 2.82% in mid-century and 0.15 to 3.79% by the end century, considering the SSP4.5 scenario. For SSP8.5, it increases from 1.45 to 5.51% and 2.57 to 9.78% in the respective periods. Likewise, under the SSP4.5 forcing scenario, the monthly average air temperature projected to be warmer, which increased from 0.68 to 1.5 °C during mid-century and 0.09 to 1.92 °C end-of-century. Meanwhile, for SSP8.5, the projection indicates an increment of 0.19 to 1.98 °C under mid-century and 2.37 to 7.00 °C end-century. The projected change of future precipitation and temperature in the study basin increases the precipitation intensities, wet days and dry spells due to high-temperature increment. [ABSTRACT FROM AUTHOR]

The objective of the study was to evaluate effects of liming on phosphorus (P) adsorption and desorption capacity of acid soils in Assosa and Bambasi Districts. The soil samples were collected from six rural Kebeles; three from each Kebele and totally 18 samples were collected. The study was conducted in accordance with batch equilibrium method and adsorption values were fitted to Langmuir, Freundlich, and Temkin models to evaluate the goodness of curve fit. Differences between the models' indices and soil property parameters were analyzed by analysis of variance (ANOVA). The study revealed that unlimed soils of Amba-7, Sonka, and Amba-1 sites had higher range of P-sorption maxima (416.7–500.0 mg/kg) than the limed ones. In addition, the limed soils had shown lower adsorption maxima than the unlimed soils based on the Langmuir model. According to Freundlich model, limed soils had a lower Kf value than the unlimed soils. Similarly, Temkin model also verified that unlimed soils had higher b value (sorption energy) than limed soils. Total P desorbed (TPD) value of limed soils had shown a significant difference (p =.022) between the soils of different sites; then soils of Amba-16, Amba-7 and Sonka had relatively higher TPD value than the soils of the left sites. On lime treated soils the total P desorbed had shown increment relative to the untreated soils. The P-sorption isotherm was fitted best to Temkin model than the Langmuir and Freundlich models. Soils of the study area require liming to improve the P-adsorption problem; especially soils of Amba-7, Sonka, and Amba-1. [ABSTRACT FROM AUTHOR]

Moringa stenopetala is a native plant in Ethiopia, which has a potential health effects due to its high bioactive contents. The aim of this study was to optimize spray drying microencapsulation conditions to maximize the encapsulation efficiency and total phenolic contents from M. stenopetala leaf extract. A Box-Behnken design was used to evaluate the influence of a spray drying process conditions such as maltodextrin: high methoxyl pectin (MD:HP) ratios (10:0, 9.5:0.5, and 9:1), core: coating ratios (1:10, 1:8, and 1:6), and inlet air temperature (120, 140 and 160 °C) on the encapsulation efficiency and total phenolic content (TPC) of microencapsulated bioactive products. The result showed that these parameters had significant effects on the responses. The encapsulation efficiency and the total phenolic contents of the microencapsulated bioactive product were in the range of 82.07-89.22% and 73.87-106.13 mg GAE/g micro, respectively. The spray drying process conditions considerably affected the physical and functional properties of the microencapsulated bioactive product. Similar trends were also observed on the antioxidant activities of the microencapsulates. The best encapsulation efficiency and TPC were obtained at the optimum spray drying process conditions: MD:HP ratio, core: coating ratio and inlet air temperature were: 9:1, 1:6 and 140 °C, respectively; with the predictive values of 87.8% for encapsulation efficiency and 103.55 mg GAE/g micro for TPC. [ABSTRACT FROM AUTHOR]

Surface incoming shortwave (solar) radiation data are an important component of many scientific analyses, but direct measurements are not commonly available. Estimates can be obtained from gridded meteorological analysis or reanalysis systems, such as the Global Data Assimilation Systems (GDAS) and Modern Era Retrospective Reanalysis System (MERRA-2), or calculated using empirical models dependent on meteorological variables such as air temperature. The purpose of this analysis was to compare multiple methods for estimating daily shortwave radiation in a tropical highland environment in Ethiopia. Direct solar radiation outputs of GDAS and MERRA-2, topographically corrected outputs of the two analysis systems, and empirically estimated solar radiation values calculated with the systems’ air temperature data were compared to see which produced the most reliable radiation values. GDAS appeared to underestimate the seasonal variability, resulting in low correlation (R2) with in situ data and large mean bias error (MBE). In comparison, MERRA-2 did not underestimate variability, but produced larger bias than the empirical model estimates. There was an improvement in correlation and reduction in MBE when using the GDAS air temperature predictions in the empirical model, but the opposite was true for MERRA-2. The empirical model using station air temperature data (stationT) produced the highest correlation across all four stations, with best performance at the lower elevation sites. The direct shortwave radiation outputs of MERRA-2 produced comparable correlation values, with larger R2 at stations at higher elevation. Topography possibly influenced these results, as MERRA-2 performed comparably to stationT at the stations in moderate terrain, but not in steeper terrain. This work can serve as a starting point for analyses in other tropical highland regions, where continuous in situ solar radiation data are rarely available. [ABSTRACT FROM AUTHOR]

ABSTRACT Ethiopia has wide eco-environmental diversity ranging from extreme heat at one of the lowest places in the world to one of the coolest summits in Africa. Associated with this environmental diversity and climate change, climatic extremes are expected to change over time and also vary across eco-environments in the country. This study was conducted to examine the trends of past precipitation and temperature extremes over three eco-environments in Ethiopia. The study involved analysis of 20 extreme indices computed from daily temperature and precipitation data spanning over 42 years (1967-2008). The climate data were obtained from 11 stations selected from three major eco-environments (pastoral, agropastoral and highland). The results indicated positive trends for maximum value of the maximum temperature ( TXx), warm days ( TX90p), warm nights ( TN90p) and warm spell duration indicators ( WSDI) and negative trends for cool days ( TX10p), cool nights ( TN10p) and cold spell duration indicators ( CSDI) in more than 8 of the 11 stations studied. However, most of the trends were not significant at many of the stations and the significant trends were not uniquely differentiated by eco-environments. Unlike temperature extremes, precipitation extreme trends showed high variability among nearby stations within eco-environments and were not significant at many of the stations studied. It is concluded that trends of temperature and precipitation extremes vary considerably among stations located within a given eco-environment indicating that the response of local climate to global warming could be different in physiographically diverse regions. [ABSTRACT FROM AUTHOR]

Accurate estimation of evapotranspiration (ET) is essential in water resources management and hydrological practices. Estimation of ET in areas, where adequate meteorological data are not available, is one of the challenges faced by water resource managers. Hence, a simplified approach, which is less data intensive, is crucial. The FAO-56 Penman-Monteith (FAO-56 PM) is a sole global standard method, but it requires numerous weather data for the estimation of reference ET. A new simple temperature method is developed, which uses only maximum temperature data to estimate ET. Ten class I weather stations data were collected from the National Meteorological Agency of Ethiopia. This method was compared with the global standard PM method, the observed Piche evaporimeter data, and the well-known Hargreaves (HAR) temperature method. The coefficient of determination ( R2) of the new method was as high as 0.74, 0.75, and 0.91, when compared with that of PM reference evapotranspiration (ETo), Piche evaporimeter data, and HAR methods, respectively. The annual average R2 over the ten stations when compared with PM, Piche, and HAR methods were 0.65, 0.67, and 0.84, respectively. The Nash-Sutcliff efficiency of the new method compared with that of PM was as high as 0.67. The method was able to estimate daily ET with an average root mean square error and an average absolute mean error of 0.59 and 0.47 mm, respectively, from the PM ETo method. The method was also tested in dry and wet seasons and found to perform well in both seasons. The average R2 of the new method with the HAR method was 0.82 and 0.84 in dry and wet seasons, respectively. During validation, the average R2 and Nash-Sutcliff values when compared with Piche evaporation were 0.67 and 0.51, respectively. The method could be used for the estimation of daily ETo where there are insufficient data. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]