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This study investigates the spatial-temporal trends and variability of rainfall within East and South Africa (ESA) region. The newly available Climate Hazards group Infrared Precipitation with Stations (CHIRPS-v2) gridded data spanning 37 years (1981 to 2017) was validated against gauge observations (N = 4243) and utilised to map zones experiencing significant monotonic rainfall trends. Standardised annual rainfall anomalies revealed the spatial-temporal distribution of below and above normal rains that are associated with droughts and floods respectively. Results showed that CHIRPS-v2 data had a satisfactory skill to estimate monthly rainfall with Kling-Gupta efficiency (KGE = 0.68 and a high temporal agreement (r = 0.73) while also preserving total amount (β = 0.99) and variability (γ = 0.8). Two contiguous zones with significant increase in annual rainfall (3-15 mm year −1) occurred in Southwest Zambia and in Northern Lake Victoria Basin between Kenya and Uganda. The most significant decrease in annual rainfall (− 20 mm year −1) was recorded at Mount Kilimanjaro in Tanzania. Other significant decreases in annual rainfall ranging between − 4 and − 10 mm year −1 were observed in Southwest Tanzania, Central-South Kenya, Central Uganda and Western Rwanda. CHIRPS-v2 rainfall product provides reliable high spatial resolution information on amount of rainfall that can complement sparse rain gauge network in rain-fed agricultural systems in ESA region. The observed spatial-temporal trends and variability in rainfall are important basis for guiding targeting of appropriate adaptive measures across multiple sectors.

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This study carried out a local vulnerability assessment or measure to climate change in Baringo County. According to Posey (2009) most adaptive responses are made at the local level by resource managers, municipal planners, and individuals at the household level (household heads). As posted by Fazey et al. (2010) and Yoo et al. (2011) there has been relatively little attention given to how assessments can be conducted in ways that help build capacity for local communities to understand and find their own solutions to their problems. The study sought to address this empirical lacuna by conducting a household vulnerability assessment at the local community level with the focus n establishing household vulnerability among resident of Baringo County Kenya. The evaluation of vulnerability considered the following characteristics the scale of vulnerability. These characteristics conveyed information on diverse natural environments and heterogeneous socioeconomic structure at multiple scales which lacks in aggregate vulnerability indices. This was in line with Boyce (2003) who states that inequality aggravates environmental degradation, including climate change. The scale analysis of vulnerability took into account the bio-physical environmental difference of locations and the socioeconomic contextual differences at the local level. Heterogeneity of locations even within a country or specific region is often responsible for differential response (i.e. coping capability) to that hazard (Adger, (1999); Carina & Keskitalo, (2008) and Engle & Lemos, (2010). Therefore, this study established the scale of vulnerability by looking at the heterogeneity of socioeconomic contexts such as institutions, population, social network and culture, for this may affect the "local" vulnerability to climate change. The vulnerability assessment also involved tools and processes used to assess the vulnerability of a community and its natural resources to climate change. The approach as suggested by (