Abstract On the basis of the output of 3 General Circulation Models (GISS, GFDL, and UKMO GCMs), combined with the local current daily weather data from 1961 to 2000 (Baseline) at 19 sites and the 3 hypotheses about increase in climatic variability (CV) in the future, 9 scenarios of (CC+ΔCV) involving both climate change (CC) and its variability (ΔCV) were generated at the 19 sites in 3 agro-ecological zones in Northeast China using the Weather Generator WGEN as a tool. Four crop models, SOYGRO, CERES-Maize, CERES-Wheat, and CERES-Rice in DSSAT, were used as effect models and their parameter modification, validation, and sensitivity analyses were carried out using the baseline weather, statistical yield data of the 4 crops, and the local typical soil data. When running the effect models under both baseline and various (CC+ΔCV) scenarios, with the comparison between the simulated outputs, the potential impacts of changes in both climate and its variability on regional food production with a doubling of CO2 were assessed. The results showed that the 4 effect models were available in the 3 agro-ecological zones and could be used as tools in climate impact studies. Generally, climate change would be favorable for soybean [Glycine max (L.) Merr.] and rice (Oryza sativa L.) productions in the studied regions, especially in the Northern Cold Zone and Eastern Wet Zone. In contrast, it was unfavorable for maize (Zea mays L.) and spring wheat (Triticum aestivum L.) productions. Particularly, the maize yields would reduce significantly under all scenarios. With the increase of CV, the rainfed crops, such as soybean, maize, and spring wheat, were negatively affected in decreases of yield and yield stability, whereas, the irrigated rice was in less influence.
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