Development of the global maize yield model MATCRO-Maize version 1.0

Abstract. Process-based crop models combined with land surface models are useful tools for accurately quantifying the impacts of climate change on crops while considering the interactions between agricultural land and climate. MATCRO model is a process-based crop model initially developed for paddy rice, combined with a land surface model. We developed MATCRO-Maize as a new model for maize by incorporating leaf-level photosynthesis of C4 plants and adjusting crop-specific parameters into the original MATCRO model. MATCRO-Maize was evaluated at both a point scale and a global scale through comparisons with observational values. For global-scale simulations, the simulated yield showed statistically significant differences compared with Food and Agriculture Organization's FAOSTAT data at the country and global levels. Although the absolute value of the simulated yield tended to be overestimated, MATCRO-Maize reproduced spatial patterns with a correlation coefficient (COR) of 0.58 (p value < 0.01) for the 30-year average yield comparison of the top 20 maize-producing countries. In addition, the comparisons of the interannual variability derived from detrended deviation were statistically significant for the total global yield (COR of 0.55 with p value < 0.01) and for half of the top 20 countries (COR of 0.64–0.90 with p value < 0.001 for 6 countries; COR of 0.50–0.51 with p value < 0.01 for 2 countries; COR of 0.48–0.55 with p value < 0.05 for 2 countries), which are comparable with those of other global crop models. One of the reasons for this overestimation could be related to the strong model response to nitrogen fertilizer observed in MATCRO-Maize. With experimental field data under more comprehensive conditions, improvements in the functions of nitrogen fertilizer in the model would be needed to simulate the maize yield more accurately.