Climate extreme events have been observed more frequently since the 1970s throughout Ethiopia, which adversely affects the socio-economic development of the country, as its economy depends on agriculture, which, in turn, relies heavily on annual and seasonal rainfall. Climate extremes studies conducted in Ethiopia are mainly limited to a specific location or watershed, making it difficult to have insights at the national level. The present study thus aims to examine the observed climate extreme events in Ethiopia at both station and agro-ecological zone (AEZ) levels. Daily rainfall and temperature data for 47 and 37 stations, respectively (1986 up to 2020), were obtained from the National Meteorology Agency (NMA). The Modified Mann–Kendall (MMK) trend test and the Theil–Sen slope estimator were employed to estimate the trends in rainfall and temperature extremes. This study examines trends of 13 temperature and 10 rainfall extreme indices using RClimDex in R software. The results revealed that most of the extreme rainfall indices showed a positive trend in the majority of the climate stations. For example, an increase in consecutive dry days (CDD), very heavy rainfall days (R20), number of heavy rainfall days (R10) and consecutive wet days (CWD) were exhibited in most climate stations. In relation to AEZs, the greater number of extreme rainfall indices illustrated an upward trend in cool and sub-humid, cool and humid, and cool and moist AEZs, a declining trend in hot arid AEZ, and equal proportions of increasing and decreasing trends in warm semi-arid AEZs. Concerning extreme temperature indices, the result indicated an increasing trend of warm temperature extreme indices and a downward trend of cold temperature extreme indices in most of the climate stations, indicating the overall warming and dryness trends in the country. With reference to AEZs, an overall warming was exhibited in all AEZs, except in the hot arid AEZ. The observed trends in the rainfall and temperature extremes will have tremendous direct and indirect impacts on agriculture, water resources, health, and other sectors in the country. Therefore, the findings suggest the need for identifying and developing climate change adaptation strategies to minimize the ill effects of these extreme climate events on the social, economic, and developmental sectors.

In the tropics, extreme weather associated with global climate teleconnections can have an outsized impact on food security. In Ethiopia, the El Niño Southern Oscillation (ENSO) is frequently linked to drought-induced food insecurity. Many projections hold that El Niño events will become more frequent or more intense under climate change, suggesting that El Niño associated droughts may become more destructive. Agricultural vulnerability to extremes under climate change, however, is a function of exposure, sensitivity, and adaptive capacity. Sensitivity, in this context, can depend on subseasonal distribution of rainfall. This paper investigates crop sensitivity to sub-seasonal rainfall variability under climate change in a food insecure area of the Ethiopian highlands through analysis of process-oriented crop model results for the years 1981-2100 driven by 14 GCMs chosen for the ability to represent ENSO and rainfall characteristics of the study area. Further, adaptive capacity in the region is investigated with in-depth interviews and focus groups concerning the 2015 strong El Niño event. Crop model results for sorghum highlight that exposure and sensitivity to sub-seasonal extremes of low rainfall can diverge significantly from sorghum's response to seasonal drought. Even though climate change will bring generally warmer and wetter seasons to the study area, there is an increased occurrence of sub-seasonal failure of rains early in the rainy season which will likely have negative impacts on sorghum yield. In-depth interviews show that biophysical constraints significantly reduce farmer adaptive capacity to this type of sub-seasonal extreme. This work highlights the need to consider sub-seasonal weather when assessing climate change threats to agriculture, particularly for subsistence farmers in the developing world.

Effective nutrient management is essential for boosting maize yield and quality and tackling factors that limit or reduce productivity. The Crop Environment Resource Synthesis (CERES)-Maize model embedded in the Decision Support Systems for Agrotechnology Transfer (DSSAT) cropping system model (CSM), known for its accurate predictions, serves as a valuable tool for guiding agricultural decisions, particularly in nutrient management, offering an efficient alternative to traditional long term field trials. This systematic review consolidates the current knowledge on nutrient management practices for maize using the CERES-Maize (DSSAT) model, providing insights that benefit researchers, agronomists, policymakers, and farmers. By leveraging crop system, soil carbon and nitrogen, and daily water balance models with crop/land management options, the model accurately predicts the effect of agricultural practices on crop growth, yield, and environmental impacts. This enables the evaluation of diverse management strategies to improve productivity and sustainability.

Tropical highland environments present substantial challenges for climate projections due to sparse observations, significant local heterogeneity and inconsistent performance of global climate models (GCMs). Moreover, these areas are often densely populated, with agriculture‐based livelihoods sensitive to transient climate extremes not always included in available climate projections. In this context, we present an analysis of observed and projected trends in temperature and precipitation extremes across agroecosystems (AESs) in the northwest Ethiopian Highlands, to provide more relevant information for adaptation. Limited observational networks are supplemented with a satellite‐station hybrid product, and trends are calculated locally and summarized at the adaptation‐relevant unit of the AES. Projections are then presented from GCM realizations with divergent climate projections, and results are interpreted in the context of agricultural climate sensitivities. Trends in temperature extremes (1981–2016) are typically consistent across sites and AES, but with different implications for agricultural activities in the other AES. Trends in temperature extremes from GCM projected data also generally have the same sign as the observed trends. For precipitation extremes, there is greater site‐to‐site variability. Summarized by AES, however, there is a clear tendency towards reduced precipitation, associated with decreases in wet extremes and a tendency towards temporally clustered wet and dry days. Over the retrospective analysis period, neither of the two analysed GCMs captures these trends. Future projections from both GCMs include significant wetting and an increase in precipitation extremes across AES. However, given the lack of agreement between GCMs and observations with respect to trends in recent decades, the reliability of these projections is questionable. The present study is consistent with the “East Africa Paradox” that observations show drying in summer season rainfall while GCMs project wetting. This has an expression in summertime Ethiopian rain that has not received significant attention in previous studies.

Potato (Solanum tuberosum L.) is an important tuber crop that is highly affected by poor soil fertility and nutrient disparities. Nutrient depletion due to intensive monocropping and poor soil management practices is a serious problem in Ethiopia, including in northwestern areas. Therefore, an experiment was conducted in the East Gojjam zone of northwestern Ethiopia to evaluate the influence of phosphorus and potassium fertilizer rates on potato tuber production. Three phosphorus levels (0, 34.5, and 69kg/ha⁻¹) and four potassium levels (0, 100, 200, and 300kg/ha⁻¹) were set out in a factorial arrangement and replicated three times using a randomized complete block design. Data on growth and quality parameters, as well as plant tissue analysis results, were collected. According to the results, the main effects of phosphorus and potassium fertilizer rates statistically affected growth components. The combined effects of phosphorus and potassium fertilizers had a significant influence on quality components (tuber size distribution). Similarly, the interaction effects of phosphorus and potassium fertilizer rates gave the highest response in all nutrient use efficiency parameters. The combined application of 34.5kgP₂O₅ and 200kgK₂O fertilizers resulted in the highest medium (28.32 ton/ha⁻¹) and large-sized (20.0 ton/ha⁻¹) tuber yields. The interaction effect of 34.5kgP₂O₅ with 100kgK₂O ha⁻¹ yielded the highest agronomic and recovery efficiency values. Hence, a combination of 34.5kgP₂O₅ ha⁻¹ and 200kgK₂O ha⁻¹ fertilizer rates can be recommended for the optimal production of potato in the northwestern area.