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The response of coffee (Coffea arabica L.) agronomical performance to changes in climate and atmospheric carbon dioxide concentration ([CO₂]) is uncertain. Improving our understanding of potential responses of the coffee plant to these changes while taking into consideration agricultural management is required for identifying best-bet adaptation strategies. A mechanistic crop modelling approach enables the inclusion of a wide range of prior knowledge and an evaluation of assumptions. We adapt a model by connecting it to spatially variable soil and climate data, by which we are able to calculate yield of rain-fed coffee on a daily time-step. The model takes account of variation in microclimate and water use as influenced by shade trees. The approach is exemplified at two East African sites with distinctly different climates (Mt. Elgon, Uganda, and Mt. Kilimanjaro, Tanzania) using a global sensitivity analysis for …