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<p>Integrated climate data and farmer perception studies are crucial to characterize the local microclimate, which directly affects smallholder agriculture. This study aimed to analyze climate variability and long-term trends in the South Wollo zone, Ethiopia, where information is scarce for informed decisions. Three meteorological stations’ rainfall and temperature data (1963–2020) were collected from national meteorology institutes, and 440 household survey data were collected from three districts using multistage sampling techniques. Qualitative data from key informant interviews (KIIS) and focus group discussions (FGDs) support the quantitative data. Climate patterns and trends were analyzed using descriptive statistics and Mann–Kendall and Sen’s slope estimator, respectively. Household data were analyzed using descriptive statistics, while KIIs and FGDs data were analyzed using narrations and thematic analysis. Rainfall trends significantly increased at Haik station during the <i>Kiremt</i> season (<i>p</i> = 0.03) ana Marye station during the <i>Belg</i> season (<i>p</i> = 0.05) at a 5% significance level, respectively, while a marginal decrease occurred at Haik station during the <i>Belg</i> season (<i>p</i> = 0.10) at a 10% significance level. Maximum temperature trends significantly increased at Haik station during the <i>Kiremt</i> season (<i>p</i> = 0.01) and at Worebabu station during the <i>Bega</i> season (<i>p</i> &lt; 0.01) at a 1% significance level, respectively. Marginal maximum temperature increases were observed at Worebabu station during the <i>Belg</i> season (<i>p</i> = 0.07) and at Haik station annually (<i>p</i> = 0.10) at a 10% significance level, respectively. In addition, about 66.3–77.9% and 65.3–75.9% of household respondents perceived trends and variabilities, respectively. Education, information, and availability of resources influence farmer perception. The study provides nuanced evidence for new entry points for informed decisions. Therefore, policymakers and agricultural extension offices should integrate scientific climate forecasts with local knowledge, while research institutes must accelerate the dissemination of climate-smart adaptation strategies for sustainable production.</p>

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Evidence of climate variability and long-term trends from meteorological station data and farmer perceptions in the South Wollo zone of northeastern Ethiopia

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月29日

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  • Tegegne Fentaw Shibeshi,
  • Fekadu Beyene Kenee,
  • Tewodros Tefera Amede,
  • Chanyalew Seyoum Aweke

摘要

Integrated climate data and farmer perception studies are crucial to characterize the local microclimate, which directly affects smallholder agriculture. This study aimed to analyze climate variability and long-term trends in the South Wollo zone, Ethiopia, where information is scarce for informed decisions. Three meteorological stations’ rainfall and temperature data (1963–2020) were collected from national meteorology institutes, and 440 household survey data were collected from three districts using multistage sampling techniques. Qualitative data from key informant interviews (KIIS) and focus group discussions (FGDs) support the quantitative data. Climate patterns and trends were analyzed using descriptive statistics and Mann–Kendall and Sen’s slope estimator, respectively. Household data were analyzed using descriptive statistics, while KIIs and FGDs data were analyzed using narrations and thematic analysis. Rainfall trends significantly increased at Haik station during the Kiremt season (p = 0.03) ana Marye station during the Belg season (p = 0.05) at a 5% significance level, respectively, while a marginal decrease occurred at Haik station during the Belg season (p = 0.10) at a 10% significance level. Maximum temperature trends significantly increased at Haik station during the Kiremt season (p = 0.01) and at Worebabu station during the Bega season (p < 0.01) at a 1% significance level, respectively. Marginal maximum temperature increases were observed at Worebabu station during the Belg season (p = 0.07) and at Haik station annually (p = 0.10) at a 10% significance level, respectively. In addition, about 66.3–77.9% and 65.3–75.9% of household respondents perceived trends and variabilities, respectively. Education, information, and availability of resources influence farmer perception. The study provides nuanced evidence for new entry points for informed decisions. Therefore, policymakers and agricultural extension offices should integrate scientific climate forecasts with local knowledge, while research institutes must accelerate the dissemination of climate-smart adaptation strategies for sustainable production.