Spatially explicit modelling of extreme weather and climate events hot spots for cumulative climate change in Uganda

Abstract

The reality of climate change continues to influence the intensity and frequency of extreme weather events such as heat waves, droughts, floods, and landslides. The impacts of the cumulative interplay of these extreme weather and climate events variation continue to perturb governments causing a scramble into formation of mitigation policies. However, national scale composites of climate hotspots remain a bottle neck to this policy formation. This paper therefore, modelled the spatially explicit extreme weather and climate events indicators into a Uganda-national extreme weather and climate events composite hotspot indicator model. The hotspot model was mapped into decomposable sub-indicators based on the Geon concept. A spatial indicator framework was developed through literature review and expert knowledge. The resulting indicators were weighted using Principal Component Analysis (PCA) /factor analysis and then normalized. They were aggregated using Multi Criteria Decision Analysis (MCDA) tools in an Object Based Image Analysis (OBIA) environment. Sensitivity analysis was carried out to ascertain the influence and significance of the indicators in the resultant model. A cumulative climate change index model was hence analysed and mapped. The mapping provides spatially explicit information regarding climate extremes at national scale, consequently addressing its growing demand among public and private institutions. Further research, into the complex interactions of cumulative climatic factors and external components like ecological systems and anthropogenic biomes will go a long way in boosting climate information. This coupled with easy access to open web availability; if adopted, will readily inform national climate change policy at national level and greatly improve decision making within development sectors, hence mitigating the advance effects of climate change.