Abstract
Understanding household perceptions of climate change and determinants of such perceptions are important for planning community/household based climate change mitigation and adaptation strategies. In this study, herding/farming households’ perceptions were studied and compared with recorded trends of extreme rainfall and temperature indicators from nearby weather stations across three eco-environments (pastoral, agro-pastoral and mixed crop-livestock highland system) in Ethiopia. Factors influencing household perceptions were assessed using a multinomial logit model. Results indicated that the majority of households (52.5-98.8%) across the three eco-environments perceived increasing numbers of extreme warm days and warm nights and decreasing numbers of extreme cool days and cool nights. In most cases, the household perceptions agreed with the recorded extreme temperature trends. Household perceptions of the studied extreme events were significantly affected by literacy, eco-environment, contact with the agricultural extension service, and presence of relief aid. We conclude that policy programs that enhance the literacy level of household and strengthen eco-environment-based extension services may increase the level of awareness and understanding of climate change by households which could help them to better adapt to climate change. Key words: Determinant, Ethiopia, household, perception, rainfall, season, temperature.
Highlights
Climate change as a reality has been increasingly recognized with the advent of a growing number of scientific studies (Henry, 2000; Thornton et al, 2006; Trenberth et al, 2007)
The perceptions were in line with recorded significant increasing trends in warm days (WD) and warm nights (WN) across seasons
The decreasing trends from observed data were significant only for the major and small rainy seasons but were broadly in line with the decreasing trends in cool days (CD) and cool nights (CN) perceived by the household
Summary
Climate change as a reality has been increasingly recognized with the advent of a growing number of scientific studies (Henry, 2000; Thornton et al, 2006; Trenberth et al, 2007). Analysis of weather monitoring station data is a primary source of evidence (Trenberth et al, 2007). In Sub-Saharan Africa, scientific studies based on station data lag behind other parts of the world mainly because of low station density, lack of data continuity and heterogeneity in the quality of records (Seleshi and Zanke, 2004).
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