Winter wheat is widely planted in China. The changes of winter wheat yield and quality are related to the food security of human society. Climate change has an important impact on the yield and quality of winter wheat. Diurnal temperature range (DTR) is an important factor affecting the yield and protein content of winter wheat. Furthermore, climate model is one of the main sources of error in crop model simulations of yields. Therefore, how to improve the accuracy of climate data has become an important concern for scholars.Previous model evaluations for the entire country or region cannot answer which model is suitable for the estimation of future winter wheat yield. Therefore, we evaluated the ability of climate models to simulate DTR within the range of winter wheat growing regions in China to identify the most suitable climate models for winter wheat yield and quality projections. The results show that CMIP6 models can basically reproduce the DTR of winter wheat-growing regions in China, but there are discrepancies in the simulations between nationwide and winter wheat-growing regions. EC-Earth3-Veg has the best simulation of climate DTR for wheat-growing regions (TS=0.848) and nationwide (TS=0.842), and ACCESS-CM2 has the strongest ability to simulate the annual growing season DTR (TS=0.46). In summary, in the estimation of future winter wheat yield, attention should be given to the selection of models suitable for the actual growing regions and the growing seasons of winter wheat.
Diurnal temperature range (DTR) is an important meteorological component affecting the yield and protein content of winter wheat. The accuracy of climate model simulations of DTR will directly affect the prediction of winter wheat yield and quality. Previous model evaluations for worldwide or nationwide cannot answer which model is suitable for the estimation of winter wheat yield. We evaluated the ability of the coupled model intercomparison project phase 6 (CMIP6) models to simulate DTR in the winter wheat growing regions of China using CN05 observations. The root mean square error (RMSE) and the interannual varibility skill score (IVS) were used to quantitatively evaluate the ability of models in simulating DTR spatial and temporal characteristics, and the comprehensive rating index (CRI) was used to determine the most suitable climate model for winter wheat. The results showed that the CMIP6 model can reproduce DTR in winter wheat growing regions. BCC-CSM2-MR simulations of DTR in the winter wheat growing season were more consistent with observations. EC-Earth3-Veg simulated the climatological DTR best in the wheat growing regions (RMSE=0.848). Meanwhile, the evaluation for climatological DTR in China is not applicable to the evaluation of DTR in winter wheat growing regions, and the evaluation for annual DTR is not a substitute for the evaluation for winter wheat growing season DTR. Our study highlights the importance of evaluating winter wheat growing regions' DTR, which can further improve the ability of CMIP6 models simulating DTR to serve the research of climate change impact on winter wheat yield.
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