Coffee has proven to be highly sensitive to climate change. Because coffee plantations have a lifespan of about thirty years, the likely effects of future climates are already a concern. Forward-looking research on adaptation is therefore in high demand across the entire supply chain. In this paper we seek to project current and future climate suitability for coffee production (Coffea arabica and Coffea canephora) on a global scale. We used machine learning algorithms to derive functions of climatic suitability from a database of geo-referenced production locations. Use of several parameter combinations enhances the robustness of our analysis. The resulting multi-model ensemble suggests that higher temperatures may reduce yields of C. arabica, while C. canephora could suffer from increasing variability of intra-seasonal temperatures. Climate change will reduce the global area suitable for coffee by about 50 % across emission scenarios. Impacts are highest at low latitudes and low altitudes. Impacts at higher altitudes and higher latitudes are still negative but less pronounced. The world's dominant production regions in Brazil and Vietnam may experience substantial reductions in area available for coffee. Some regions in East Africa and Asia may become more suitable, but these are partially in forested areas, which could pose a challenge to mitigation efforts.
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