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The purpose of this paper is to investigate the patterns and trends of drought incidence in north east highlands of Ethiopia using monthly rainfall record for the period 1984-2014.

Standard precipitation index and Mann – Kendal test were used to analyze drought incident and trends of drought occurrences, respectively. The spatial extent of droughts in the study area has been interpolated by inverse distance weighted method using the spatial analyst tool of ArcGIS.

Most of the studied stations experienced drought episodes in 1984, 1987/1988, 1992/1993, 1999, 2003/2004 and 2007/2008 which were among the worst drought years in the history of Ethiopia. The year 1984 was the most drastic and distinct-wide extreme drought episode in all studied stations. The Mann–Kendal test shows an increasing tendencies of drought at three-month (spring) timescale at all stations though significant (p < 0.05) only at Mekaneselam and decreasing tendencies at three-month (summer) and 12-month timescales at all stations. The frequency of total drought was the highest in central and north parts of the region in all study seasons.

This detail drought characterization can be used as bench mark to take comprehensive drought management measures such as early warning system, preparation and contingency planning, climate change adaptation programs.

This study aims to analyze the temperature variability and change for the past 30 years (1990–2019) and the future 60 years (2030s, 2050s and 2070s) in Wolaita Zone and the surroundings, in Southern Ethiopia.

The temperature (maximum and minimum) data of the past 30 years (1990–2019) of ten meteorological stations and the future (2021–2080) data of regional climate models (RCMs) under two representative concentration pathways (RCP4.5 and RCP8.5) were used in this study. The accuracy of RCMs in representing observed temperature data was evaluated against mean absolute error, root-mean-square error, percent bias, Nash–Sutcliffe measure of efficiency, index of agreement (d) and coefficient of determination (R²). The temperature variability was analyzed using the coefficient of variation, and the trend was determined using the Mann–Kendall trend and Sen’s slope tests.

The results indicate that the past maximum (Tmax) and minimum (Tmin) temperatures showed low variability (CV = 4.3%) with consistently increasing trends. Similarly, Tmax and Tmin are projected to have low variability in the future years, with upward trends. The Tmax and Tmin are projected to deviate by 0.7°C–1.2°C, 1.3°C–2.2°C and 1.5°C–3.2°C by 2030s, 2050s and 2070s, respectively, under RCP4.5 and RCP8.5, from the baseline. Thus, it can be concluded that temperature has low variability in all periods, with consistently increasing trends. The increasing temperature could have been affecting agricultural production systems in Southern Ethiopia.

This research did not remove the uncertainties of models (inherited errors of models) in future temperature projections. However, this study did not have any limitation. Therefore, individuals or organizations working on agricultural productivity, food security and sustainable development can use the results and recommendations.

The globe has been warming due to the increasing temperature; as a result, many adaptation and mitigation measures have been suggested globally and nationally (IPCC, 2021). FAO (2017) indicates that the level of vulnerability to the impacts of climate change varies with geographic location, economy and demography; the adaptation measures need to be local. The detailed information on temperature variability and change in the past and future helps to understand the associated negative impacts on agriculture, hydrology, biodiversity, environment and human well-being, among others.

The projected future climate pattern helps the country devise proactive adaptation and mitigation measures for the associated damages at different levels (from local to national). This could improve the resilience of farmers and the country to climate change impacts. This contributes to achieving sustainable development goals (e.g. no poverty, zero hunger and climate action). This is because the agriculture sector in Ethiopia accounts for 80% of employment, 33% of the gross domestic product and 76% of exports (EPRSS, 2023).

Temperature is one of the major climate elements affecting agricultural production in rain-fed production systems. Despite this, past studies in Southern Ethiopia considered only the past temperature but not the future climate. Thus, generating detailed information about past and future temperatures is very important to take proactive adaptation measures for reducing climate-associated damages in the agriculture sector in Ethiopia.

As climate change shocks and stresses increasingly affect urban areas in developing countries, resilience is imperative for the purposes of preparation, recovery and adaptation. This study aims to investigate demographic characteristics and social networks that influence the household capacity to prepare, recover and adapt when faced with prolonged droughts or erratic rainfall events in Mbale municipality in Eastern Uganda.

A cross-sectional research design was used to elicit subjective opinions. Previous studies indicate the importance of subjective approaches for measuring social resilience but their use has not been well explored in the context of quantifying urban resilience to climate change shocks and stresses. This study uses 389 structured household interviews to capture demographic characteristics, social networks and resilience capacities. Descriptive and inferential statistics were used for analysis.

The ability of low-income households to meet their daily expenditure needs, household size, and networks with relatives and non government organizations (NGOs) were significant determinants of preparedness, recovery and adaptation to prolonged droughts or erratic rainfall events.

The results imply that policymakers and practitioners have an important role vis-à-vis encouraging activities that boost the ability of households to meet their daily expenditure needs, promoting small household size and reinforcing social networks that enhance household resilience.

Even the low-income households are substantially more likely to prepare for and recover from prolonged droughts or erratic rainfall events if they can meet their daily expenditure needs. This finding is noteworthy because the poorest in society are generally the most vulnerable to hazards.