Downscaling climate change information using an ensemble of regional climate models for agricultural planning: a case study of Tana River County, Kenya

Abstract

The truncated ecosystems of the Tana River County are highly vulnerable to climate change and variability due to their low adaptive capacities and high dependence on climate sensitive resources. Inadequacy of long term climate information is a serious constraint for long-term planning for enhanced food security and minimization of the adverse impacts of climate change and variability. This study was motivated by the need to downscale climate information using modelling procedures based on Regional Climate Models (RCMs). The objectives of the study revolved around evaluations of the performance of Coordinated Regional Climate Downscaling Experiment (CORDEX) RCMs in simulating rainfall and temperature conditions and use of these data sets in projecting future climate change scenarios and their implications on agricultural productivity and related resources. Assessments and validation tests were run to authenticate the plausibility of CORDEX RCMs and the relevance of historical climate data in evaluations of the impact of climate change and variability on agricultural productivity. Agricultural data (crops and livestock) for more than 20 years collected from the Ministry of Agriculture, Livestock and Fisheries (MALF) departments in Tana River County were utilized in the study. The gross yield of five widely grown crops in the region comprising of maize, green grams, rice, cassava and mangoes was collated. Livestock population data for specific livestock species was used. Subjective sampling was applied for three focused group discussions conducted. Bi-variate correlations and simple linear regressions were used to investigate crop/livestock production and rainfall relationships. Combination of dynamical and statistical downscaling approaches were used in RCMs evaluation and projecting the future climate scenarios for Tana River County. RCMs simulated above 84% observed climatology in Tana River County making them valuable tools for agricultural production planning. The ensemble model had better agreement with ground data observations than individual models. Seasonal rainfall variability was of the order of 70% during short and long rains making rainfed agriculture unreliable. Crop yields showed low correlations with March-May (MAM) seasonal rainfall (r = 0.3) as compared with OctoberDecember (OND) season (r = 0.55). Seasonal rainfall explained 8% of the variation in maize yields and 40-56% in livestock numbers. The OND season is more reliable for agricultural production activities in the region. A warming trend in the region of 3.0 to 3.5oC under RCP4.5/8.5 scenarios is projected by the middle of 21st century. A warming climate in the region will negatively impact food production, water availability and livelihood systems in the region.