Using estimated radiation in crop models amplified the negative impacts of climate variability on maize and winter wheat yields in China

Abstract

As a main tool for climate variability impact studies on agriculture, crop models are widely used for agricultural assessments. However, the accuracy of input data like radiation data fundamentally affects the reliability of the crop model outputs. In previous studies, estimated radiation was commonly used due to the scarcity of directly measured radiation, which introduced errors into the assessment results. In this study, by assuming the measured radiation data as the true values, we used four sources of estimated solar radiation values to analyze the underlying errors in the results based on estimated solar radiation. The results showed that the total estimated radiation during the crop growing season is all higher than the measured radiation, especially for winter wheat (6.6%∼14.8% for maize, and 18.7%∼34.0% for winter wheat). When using estimated radiation as input data, regardless of the source, the crop model overestimated the simulated crop yields for maize (13.8%∼23.6%) and winter wheat (37.3%∼65.4%) in China. The amplitude of such overestimation was relatively greater in the south than in the north, and relatively greater for winter wheat than for maize. As compared to using the measured radiation, the negative impact of climate variability on simulated crop yield was exaggerated when using estimated radiation except for reanalysis datasets (1.6%∼4% for maize, and 4.2%∼6.3% for winter wheat). Our study results provide scientific evidence of the importance of using accurate radiation data in agricultural impact analyses, and the previous related results may need to be re-evaluated.