全球变暗是气候变化的重要趋势之一。全球变暗表现为到达地面的太阳总辐射减少和其中散射辐射比例增加。太阳辐射减少对作物产量有负面影响，散射辐射比例增加则对作物有肥效作用，但目前尚不清楚两者对作物产量的综合影响。作物生长模型是评估全球变暗对作物影响的工具。但现有作物生长模型没有考虑散射辐射比例增加对作物生理过程和产量的影响，不能准确评估不同程度的全球变暗对作物生产力的影响。针对这些问题，本项目以水稻为研究对象，通过设置同一太阳总辐射水平下不同程度散射辐射比例增加以及同一散射辐射水平下不同程度太阳总辐射减少的处理试验，定量分析太阳总辐射减少的负面作用和散射辐射比例增加的肥效作用对水稻生长和产量的综合影响，建立全球变暗背景下太阳辐射变化对水稻生产力综合影响模拟模型，为准确评估全球变暗对水稻产量的影响提供可靠的模型工具。本项目的研究结果可以为作物生产应对气候变化和保障我国粮食安全提供重要科学依据。

Global dimming is one of the important trends of climate change. Under global dimming is characterized with reduction in incident global radiation and increase of its proportion of diffuse radiation. Reduction in incident global radiation has negative impacts on crop growth and yield while the increase of proportion of diffuse radiation has fertilization effects on crop growth and yield. Under fifferent digree of global dimming conditions, how those negative and position impacts will ultimately affect crop productivity is the essential question to quantitatively evaluate the impacts of global dimming on crop productivity. The existing crop models, however, cannot be directly used to evaluate the impacts of dimming on crop productivity since they do not take into account the impacts of low light conditions and different proportion of diffuse radiation on crop growth processes. The objective of this research is to develop a model to predict the impacts of changed incident solar radiation on rice crop productivity under different degree of global dimming conditions. For this purpose, open field experiments with different levels of incident global radiation and proportion of diffuse radiation will be conducted to investigate the response of rice crop to changed incident solar radiation under different degree of global dimming conditions. The impacts of different levels of incident global radiation and the proportion of diffuse radiation on crop growth processes will be quantified based on the open field experimental data. A model for predicting the impacts of changed incident solar radiation on rice crop productivity will be developed by integrating those quantitative relationships into an existing rice growth simulation model. The results of this project will not only provide an effective tool for quantitatively evaluating the impacts of different degree of global dimming on crop productivity, but also decision support for crop production mitigating climate change and food security.