Coordinated evaporative demand and precipitation maximize rainfed maize and soybean crop yields in the USA

Abstract To understand how climate change affects crop yields, we need to identify the climatic indices that best predict yields. Grain yields are most often predicted using precipitation and temperature in statistical models, assuming linear dependences. However, soil water availability is more influential for plant growth than temperature, there ecophysiological evidence of intermediate yield maximizing conditions. Using rainfed maize soybean 1970–2010 across USA, tested whether aridity index, is, ratio potential evapotranspiration seasonal totals a proxy availability, better predicts growing season total, average their interaction. We also non‐monotonic responses allowing yield‐maximizing The index alone explained 77% 72% variability, compared with 78% 73% by Yield were non‐monotonic, maximized at as well 0.79 0.98 soybean. increased faster conditions show could both increase decrease depending on come closer or deviate from future. In counties, during 1970–2010, lower higher those suggesting will reduce