Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1111/gcb.14019 |
Contribution of crop model structure, parameters and climate projections to uncertainty in climate change impact assessments | |
Tao, Fulu1; Roetter, Reimund P.2,3; Palosuo, Taru1; Hernandez Diaz-Ambrona, Carlos Gregorio4; Ines Minguez, M.4; Semenov, Mikhail A.5; Kersebaum, Kurt Christian6; Nendel, Claas6; Specka, Xenia6; Hoffmann, Holger7; Ewert, Frank6,7; Dambreville, Anaelle8; Martre, Pierre8; Rodriguez, Lucia4; Ruiz-Ramos, Margarita4; Gaiser, Thomas7; Hohn, Jukka G.1; Salo, Tapio1; Ferrise, Roberto9; Bindi, Marco9; Cammarano, Davide10; Schulman, Alan H.1,11,12 | |
2018-03-01 | |
发表期刊 | GLOBAL CHANGE BIOLOGY |
ISSN | 1354-1013 |
EISSN | 1365-2486 |
出版年 | 2018 |
卷号 | 24期号:3页码:1291-1307 |
文章类型 | Article |
语种 | 英语 |
国家 | Finland; Germany; Spain; England; France; Italy; Scotland |
英文摘要 | Climate change impact assessments are plagued with uncertainties from many sources, such as climate projections or the inadequacies in structure and parameters of the impact model. Previous studies tried to account for the uncertainty from one or two of these. Here, we developed a triple-ensemble probabilistic assessment using seven crop models, multiple sets of model parameters and eight contrasting climate projections together to comprehensively account for uncertainties from these three important sources. We demonstrated the approach in assessing climate change impact on barley growth and yield at Jokioinen, Finland in the Boreal climatic zone and Lleida, Spain in the Mediterranean climatic zone, for the 2050s. We further quantified and compared the contribution of crop model structure, crop model parameters and climate projections to the total variance of ensemble output using Analysis of Variance (ANOVA). Based on the triple-ensemble probabilistic assessment, the median of simulated yield change was -4% and +16%, and the probability of decreasing yield was 63% and 31% in the 2050s, at Jokioinen and Lleida, respectively, relative to 1981-2010. The contribution of crop model structure to the total variance of ensemble output was larger than that from downscaled climate projections and model parameters. The relative contribution of crop model parameters and downscaled climate projections to the total variance of ensemble output varied greatly among the seven crop models and between the two sites. The contribution of downscaled climate projections was on average larger than that of crop model parameters. This information on the uncertainty from different sources can be quite useful for model users to decide where to put the most effort when preparing or choosing models or parameters for impact analyses. We concluded that the triple-ensemble probabilistic approach that accounts for the uncertainties from multiple important sources provide more comprehensive information for quantifying uncertainties in climate change impact assessments as compared to the conventional approaches that are deterministic or only account for the uncertainties from one or two of the uncertainty sources. |
英文关键词 | barley climate change Europe impact super-ensemble uncertainty |
领域 | 气候变化 ; 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000425396700035 |
WOS关键词 | NITROGEN DYNAMICS ; SIMULATION-MODELS ; YIELD ; RICE ; WEATHER ; GROWTH ; MAIZE ; PRODUCTIVITY ; TEMPERATURE ; CALIBRATION |
WOS类目 | Biodiversity Conservation ; Ecology ; Environmental Sciences |
WOS研究方向 | Biodiversity & Conservation ; Environmental Sciences & Ecology |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/17047 |
专题 | 气候变化 资源环境科学 |
作者单位 | 1.Nat Resources Inst Finland Luke, Helsinki, Finland; 2.Georg August Univ Gottingen, Dept Crop Sci, Trop Plant Prod & Agr Syst Modelling TROPAGS, Gottingen, Germany; 3.Georg August Univ Gottingen, Ctr Biodivers & Sustainable Land Use CBL, Gottingen, Germany; 4.Univ Madrid, AgSyst CEIGRAM Res Ctr Agr & Environm Risk Manage, Madrid, Spain; 5.Rothamsted Res, Harpenden, Herts, England; 6.Leibniz Ctr Agr Landscape Res, Inst Landscape Syst Anal, Muncheberg, Germany; 7.Univ Bonn, Crop Sci Grp, INRES, Bonn, Germany; 8.INRA, UMR LEPSE, Montpellier, France; 9.Univ Florence, Dept Agrifood Prod & Environm Sci, Florence, Italy; 10.James Hutton Inst, Dundee, Scotland; 11.Univ Helsinki, Inst Biotechnol, Helsinki, Finland; 12.Univ Helsinki, Viikki Plant Sci Ctr, Helsinki, Finland |
推荐引用方式 GB/T 7714 | Tao, Fulu,Roetter, Reimund P.,Palosuo, Taru,et al. Contribution of crop model structure, parameters and climate projections to uncertainty in climate change impact assessments[J]. GLOBAL CHANGE BIOLOGY,2018,24(3):1291-1307. |
APA | Tao, Fulu.,Roetter, Reimund P..,Palosuo, Taru.,Hernandez Diaz-Ambrona, Carlos Gregorio.,Ines Minguez, M..,...&Schulman, Alan H..(2018).Contribution of crop model structure, parameters and climate projections to uncertainty in climate change impact assessments.GLOBAL CHANGE BIOLOGY,24(3),1291-1307. |
MLA | Tao, Fulu,et al."Contribution of crop model structure, parameters and climate projections to uncertainty in climate change impact assessments".GLOBAL CHANGE BIOLOGY 24.3(2018):1291-1307. |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论