New South Wales Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga, New South Wales, Australia.
Gulbali Institute for Agriculture, Water and Environment, Charles Sturt University, Wagga Wagga, New South Wales, Australia.
Nat Food. 2024 Jul;5(7):550-556. doi: 10.1038/s43016-024-01014-w. Epub 2024 Jul 15.
Both climate and impact models are essential for understanding and quantifying the impact of climate change on agricultural productivity. Multi-model ensembles have highlighted considerable uncertainties in these assessments, yet a systematic approach to quantify these uncertainties is lacking. We propose a standardized approach to attribute uncertainties in multi-model ensemble studies, based on insights from the Agricultural Model Intercomparison and Improvement Project. We find that crop model processes are the primary source of uncertainty in agricultural projections (over 50%), excluding unquantified hidden uncertainty that is not explicitly measured within the analyses. We propose multidimensional pathways to reduce uncertainty in climate change impact assessments.
气候和影响模型对于理解和量化气候变化对农业生产力的影响都至关重要。多模式集合突出了这些评估中的相当大的不确定性，但缺乏对这些不确定性进行量化的系统方法。我们提出了一种基于农业模型比较和改进项目的见解的标准化方法来确定多模式集合研究中的不确定性。我们发现，作物模型过程是农业预测中不确定性的主要来源（超过 50%），不包括在分析中没有明确测量的未量化的隐藏不确定性。我们提出了多维途径来减少气候变化影响评估中的不确定性。
