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Haas, E.; R. Kiese; Klatt, S.; Hoffmann, H.; Zhao, G.; Ewert, F.; J. Constantin; Raynal, H.; Coucheney, E.; Lewan, E.; Sosa, C.; Dechow, R.; Grosz, B.; Eckersten, H.; Gaiser, T.; Kuhnert, M.; Smith, P.; Kersebaum, K.C.; C. Nendel; Specka, X.; Wang, E.; Zhao, Z.; Weihermüller, L. |
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Title |
Responses of soil nitrous oxide emissions and nitrate leaching on climate, soil and management input data aggregation: a biogeochemistry model ensemble study |
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Conference Article |
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2016 |
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Berlin (Germany) |
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poster |
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International Crop Modelling Symposium iCROPM 2016, 2016-05-15 to 2016-05-17, Berlin, Germany |
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MA @ admin @ |
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4907 |
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Hoffmann, H.; Zhao, G.; Asseng, S.A.U.-,; Bindi, M.; Cammarano, D.; Constantin, J.; Coucheney, E.; Dechow, R.; Doro, L.; Eckersten, H.; Gaiser, T.; Grosz, B.; Haas, E.; Kassie, B.; Kersebaum, K.C.; Kiese, R.; Klatt, S.; Kuhnert, M.; Lewan, E.; Moriondo, M.; Nendel, C.; Raynal, H.; Roggero, P.P.; Rötter, R.; Siebert, S.; Sosa, C.; Specka, X.; Tao, F.; Teixeira, E.; Trombi, G.; Yeluripati, J.; Vanuytrecht, E.; Wallach, D.; Wang, E.; Weihermüller, L.; Zhao, Z.; Ewert, F. |
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Analysing data aggregation effects on large-scale yield simulations |
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Conference Article |
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2016 |
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Berlin (Germany) |
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International Crop Modelling Symposium iCROPM 2016, 2016-05-15 to 2016-05-17, Berlin, Germany |
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MA @ admin @ |
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4923 |
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Hoffmann, H.; Gang, Z.; Van Bussel, L.G.J.; Enders, A.; Specka, X.; Sosa, C.; Yeluripati, J.; Tao, F.; Constantin, J.; Casellas, E.; Teixeira, E.; Grosz, B.; Doro, L.; Zhao, Z.; Nendel, C.; Kiese, R.; Raynal, H.; Eckersten, H.; Klatt, S.; Edwin, H.; Wang, E.; Kuhnert, M.; Lewan, E.; Bach, M.; Kersebaum, K.-C.; Rötter, R.; Roggero, P.P.; Wallach, D.; Krauss, G.; Siebert, S.; Gaiser, T.; Ewert, F. |
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Sensitivity of crop models to spatial aggregation of soil and climate data |
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2014 |
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Annual conference of the German/Austrian Agronomical Society & Max-Eyth-Society IS - |
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MA @ admin @ |
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5041 |
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Tao, F.; Roetter, R.P.; Palosuo, T.; Hernandez Diaz-Ambrona, C.G.; Ines Minguez, M.; Semenov, M.A.; Kersebaum, K.C.; Nendel, C.; Specka, X.; Hoffmann, H.; Ewert, F.; Dambreville, A.; Martre, P.; Rodriguez, L.; Ruiz-Ramos, M.; Gaiser, T.; Hohn, J.G.; Salo, T.; Ferrise, R.; Bindi, M.; Cammarano, D.; Schulman, A.H. |
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Title |
Contribution of crop model structure, parameters and climate projections to uncertainty in climate change impact assessments |
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Journal Article |
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2018 |
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Global Change Biology |
Abbreviated Journal |
Glob. Chang. Biol. |
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24 |
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3 |
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1291-1307 |
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Keywords |
barley; climate change; Europe; impact; super-ensemble; uncertainty; Nitrogen Dynamics; Multimodel Ensembles; Simulation-Models; Change; Scenarios; Yield; Rice; Weather; Growth; Wheat; Maize |
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Abstract |
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. |
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2018-03-08 |
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English |
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1354-1013 |
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CropM, ft_macsur |
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MA @ admin @ |
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5194 |
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Author |
Klatt, S.; Haas, E.; Hoffmann, H.; Zhao, G.; Van Bussel, L.G.J.; Enders, A.; Gaiser, T.; Ewert, F.; Teixeira, E.; Kiese, R.; Doro, L.; Specka, X.; Nendel, C.; Kersebaum, K.-C.; Sosa, C.; Lewan, E.; Eckersten, H.; Gebbert, S.; Dechow, R.; Grosz, B.; Bach, M.; Yeluripati, J.; Tao, F.; Constantin, J.; Raynal, H.; Wallach, D.; Kuhnert, M. |
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Title |
Responses of soil N2O emissions and nitrate leaching on climate input data aggregation: a biogeochemistry model ensemble study |
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Conference Article |
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2014 |
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CropM International Symposium and Workshop |
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CropM International Symposium and Workshop, 2014-02-10 to 2014-02-12, Oslo, Norway |
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MA @ admin @ |
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5042 |
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