Analysis of Climate Variability Trends and Local Perceptions in Kieni West Sub-County, Kenya

It is indisputable today that climate variability has taken place all over the world having huge impacts on ecosystems. Precipitation and rainfall are among the most notable changes of climate variability, majorly as a result of natural phenomena or anthropogenic activities contributing to global climatic extremes such as heatwaves, snow, droughts, and flooding. The aim of this study was to analyze trends of climate variability and local perceptions in Kieni West sub-county, Kenya. A mixed methods research design was employed where both quantitative and qualitative data were used. Gridded rainfall and temperature data was obtained from the Kenya Meteorological Department (KMD) for the period between 1988 and 2018. Mann-Kendall (MK) test statistic was used to detect climate trends in time series data and their statistical significance. Coefficient of Variation (CV) was employed to detect variations in seasonal rainfall both in short and long rain seasons. Pearson Coefficient of Correlation (r) was used to establish the relationship between rainfall and temperatures for the period 1988-2018. Quantitative data was analyzed using descriptive and inferential statistics whereas qualitative data was analyzed by establishing themes and patterns. Data presentation was done by use of figures, tables as well as narratives. The findings revealed that annual rainfall had been decreasing by 6.294mm/year (p > .05) while annual temperatures had been increasing significantly at 0.021oC/year (p < .05). Correlation analysis between annual rainfall and mean annual maximum temperatures revealed a weak negative correlation (r (29) = .23, p =.213) whereas there was an insignificant weak positive linear relationship between annual rainfall and mean annual minimum temperatures (r (29) = .08, p = .688). Additionally, Pearson’s correlation analysis revealed a non-significant small positive relationship between mean monthly rainfall and mean monthly maximum temperatures (r (10) = .27, p = .391) and a significant large positive correlation between mean monthly rainfall and mean monthly minimum temperatures (r (10) = .79, p =.002). The majority of respondents observed decreased rainfall (83%) and increased temperatures (71%) in the area. The study concludes that climate variability is taking place in Kieni West sub-county, Kenya