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Climate suitability is important for coffee (Coffea arabica L.) production in climate variability-prone regions like Ethiopia. The aim of this study was to assess the current and future climate suitability for the species in the Jimma zone under moderate (RCP4.5) and worst (RCP8.5) climate change scenarios. Field surveys and Worldclim and Paleoclim databases were used to capture 224 C. arabica species' location points and 9 bioclimatic data, respectively. The MaxEnt model with integration of ArcGis was used to simulate and characterize these data. The diagnostic outcome of the model showed that the anticipated climate change will increase the areas of suitability in the first and third coffee sub-zones, while there will be a decrease in the second sub-zone. Net suitability under the RCP4.5 would be decreased by 4.75 and 6.09% in the 2050s and 2070s, respectively. Indeed, under the RCP8.5, total suitability will be expected to be increased by 2.52% and 2.25% in the 2050s and 2070s, respectively. For the 2050s and 2070s, the suitability gap between RCP4.5 and RCP8.5 was estimated to be 401 km 2 and 1567 km 2 , respectively. To summarize, with the exemption of RCP 8.5 within the 2070s, the suitability would be improved and come up short in all circumstances. To keep Arabica coffee in its original habitat, we suggest that the entire climate change adjustment procedures that are prearranged under the RCP4.5 ought to be executed to sustain the crop trees in its origin. Otherwise, moving the crop plant from impeded areas to suitable ones is crucial., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Climate extremes are becoming more prevalent and hazardous as global climate change increases. The purpose of this study was to find out how often severe rainfall and temperature events occur, as well as the study area's spatial vulnerability indexes to extremes of both indices. Thirty years of daily rainfall and temperature data from 10 national meteorological stations were used. Four rainfall and eight temperature extremes were extracted using Climpact2 software tools. These variables were calculated for standardized anomaly and vulnerability indices and mapped using ArcMap. The results showed that the spatial variation of climatic extremes in the study area was significantly varied. Avery high rainfall (R95P) and extremely high rainfall (R99P) were widely experienced in the study area's west-south, but in the southeast, similar trends were rare. R95P had a statistically significant growing trend, but R99P did not. The warmest night temperature (TNx) event was widely observed in the east, southeast, and northwest, but the coldest night temperature (TNn) was only found in the eastern part. Extremely cold daytime temperatures (TXn) were more prevalent in the south and southeast of the study area, whereas extremely warm daytime temperatures (TXx) were more prevalent in the north. The number of dry spells (CDD), R95P, R99P, cold spells at night (TN10P), warm spells at night (TN90P), cold spells during the day (TX10P), and warm spells during the day (TX10P) frequency bell curves were skewed to the left side of the histogram. This suggests that the distribution of the variables was not symmetrical due to the fact that the negative anomaly frequencies of the variables were higher than the positive ones. The results of the spatial vulnerability study show that all provinces were vulnerable to the combined effects of climatic extremes, with scores ranging from 0.20 to 0.8, with none of them vulnerable and extremely vulnerable areas. Omo-Nada and Chora-Botor were particularly sensitive to climate change with an average score of 0.61. Only 12 of the 27 severe climate indexes were taken into account in this study, and the remaining 15 extreme indices will have to be investigated further., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)