ENSO–climate fluctuation–crop yield early warning system—A case study in Jilin and Liaoning Province in Northeast China

• We firstly structure an early warning system of maize yield in China.
• The system simulates well the impact of each ENSO phase on maize yield.
• Significant difference in spatial response of maize yield is well presented.
• The study implies the potential usage of the system in other areas of China.

Crop yield is very sensitive to climate variability. The El Niño–Southern Oscillation (ENSO) is one of the most important contributors to global climate fluctuation, and therefore has a major impact on agricultural production. In this study, we structure an ENSO–climate fluctuation–crop yield early warning system to model the maize yield in Jilin and Liaoning Provinces in Northeast China. The system, which consists of a weather generator and a Model to capture the Crop Weather relationship over a Large Area (MCWLA), is not only capable of simulating the maize yield both at the provincial (regional) scale and the grid scale, but can also provide the exceedance probability of yield. Simulation results show maize yields in El Niño years to be higher on average than those in neutral years, while yields in La Niña years are the lowest. Spatially, the central part of the study area always shows a higher yield than other parts of the study, while yields in the northeast and northwest parts are relatively lower, no matter how high or low the exceedance probability and whatever the ENSO phase. Our study strongly implies that such a warning system shows considerable potential for application in other areas of China.