Agricultural productivity in Sub-Saharan Africa (SSA) is low due to poor natural resource management and limited capacities to adapt to adverse weather, climate variability, and extreme events. A particular challenge is the lack of high-quality climate observation data, required for analysing trends, validating regional climate models and as input for impact models. These are used to support managing environmental resources and mitigating effects of extreme climate events. Besides, there are significant inconsistencies in existing field-based meteorological datasets. This is largely due to the limited number of measuring stations, the time resolution and duration of the series, and inadequate data management.
Therefore, this project aims to synthesize climate data from global and regional climate models, remote sensing, and meteorological stations. Statistical downscaling will be employed to obtain regional climatic information. The study will provide a consolidated high-quality long-term series of climate datasets for Sub-Saharan Africa. These can serve as an input for climate projections, impact assessment, and sector modelling. Regionally downscaled, synthesised data will allow for an assessment of the impacts of climate change and extreme events on the regional soil-water budget.