缩小尺度
气候变化
种植
环境科学
气候学
气候模式
作物产量
不确定度分析
产量(工程)
基线(sea)
作物
大气环流模式
农业
地理
数学
农学
统计
生态学
海洋学
地质学
生物
考古
冶金
材料科学
作者
Bin Wang,Puyu Feng,De Li Liu,Garry J. O’Leary,Ian Macadam,Cathy Waters,Senthold Asseng,Annette Cowie,Tengcong Jiang,Dengpan Xiao,Hongyan Ruan,Jianqiang He,Qiang Yu
出处
期刊:Nature food
[Nature Portfolio]
日期:2020-11-02
卷期号:1 (11): 720-728
被引量:108
标识
DOI:10.1038/s43016-020-00181-w
摘要
Understanding sources of uncertainty in climate–crop modelling is critical for informing adaptation strategies for cropping systems. An understanding of the major sources of uncertainty in yield change is needed to develop strategies to reduce the total uncertainty. Here, we simulated rain-fed wheat cropping at four representative locations in China and Australia using eight crop models, 32 global climate models (GCMs) and two climate downscaling methods, to investigate sources of uncertainty in yield response to climate change. We partitioned the total uncertainty into sources caused by GCMs, crop models, climate scenarios and the interactions between these three. Generally, the contributions to uncertainty were broadly similar in the two downscaling methods. The dominant source of uncertainty is GCMs in Australia, whereas in China it is crop models. This difference is largely due to uncertainty in GCM-projected future rainfall change across locations. Our findings highlight the site-specific sources of uncertainty, which should be one step towards understanding uncertainties for more robust climate–crop modelling.
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