Model simulation is an important way to study the effects of climate change on agriculture.Such assessment is subject to a range of uncertainties because of either incomplete knowledge or model technical uncertainties...Model simulation is an important way to study the effects of climate change on agriculture.Such assessment is subject to a range of uncertainties because of either incomplete knowledge or model technical uncertainties,impeding effective decision-making to climate change.On the basis of uncertainties in the impact assessment at different levels,this article systematically summarizes the sources and propagation of uncertainty in the assessment of the effect of climate change on agriculture in terms of the climate projection,the assessment process,and the crop models linking to climate models.Meanwhile,techniques and methods focusing on different levels and sources of uncertainty and uncertainty propagation are introduced,and shortcomings and insufficiencies in uncertainty processing are pointed out.Finally,in terms of how to accurately assess the effect of climate change on agriculture,improvements to further decrease potential uncertainty are suggested.展开更多
基金supported by the Global Change Global Research Key Project of the National Science Plan (2010CB951302)the National Natural Science Foundation of China (40771147)+1 种基金the Fund of the Key Laboratory of Agricultural Environment and Climate Change of the Ministry of Agriculture (2010)CAMS Basic Research Fund (2010Y004)
文摘Model simulation is an important way to study the effects of climate change on agriculture.Such assessment is subject to a range of uncertainties because of either incomplete knowledge or model technical uncertainties,impeding effective decision-making to climate change.On the basis of uncertainties in the impact assessment at different levels,this article systematically summarizes the sources and propagation of uncertainty in the assessment of the effect of climate change on agriculture in terms of the climate projection,the assessment process,and the crop models linking to climate models.Meanwhile,techniques and methods focusing on different levels and sources of uncertainty and uncertainty propagation are introduced,and shortcomings and insufficiencies in uncertainty processing are pointed out.Finally,in terms of how to accurately assess the effect of climate change on agriculture,improvements to further decrease potential uncertainty are suggested.