The practice of modeling biomass yields on the basis of deterministic point values aggregated over space and time obscures important risks associated with large-scale biofuel use, particularly risks related to drought-induced yield reductions that may become increasingly frequent under a changing climate. Using switchgrass as a case study, this work quantifies the variability in expected yields over time and space through switchgrass growth modeling under historical and simulated future weather. The predicted switchgrass yields across the United States range from about 12 to 19 Mg/ha, and the 80% confidence intervals range from 20 to 60% of the mean. Average yields are predicted to decrease with increased temperatures and weather variability induced by climate change. Feedstock yield variability needs to be a central part of modeling to ensure that policy makers acknowledge risks to energy supplies and develop strategies or contingency plans that mitigate those risks.