| Author |
Title |
Year |
Publication |
Volume |
Pages |
| Sanna, M.; Bellocchi, G.; Fumagalli, M.; Acutis, M. |
A new method for analysing the interrelationship between performance indicators with an application to agrometeorological models |
2015 |
Environmental Modelling & Software |
73 |
286-304 |
| Wallach, D.; Mearns, L.O.; Ruane, A.C.; Rötter, R.P.; Asseng, S. |
Lessons from climate modeling on the design and use of ensembles for crop modeling |
2016 |
Climatic Change |
139 |
551-564 |
| Schauberger, B.; Rolinski, S.; Müller, C. |
A network-based approach for semi-quantitative knowledge mining and its application to yield variability |
2016 |
Environmental Research Letters |
11 |
123001 |
| Zhang, S.; Tao, F.; Zhang, Z. |
Uncertainty from model structure is larger than that from model parameters in simulating rice phenology in China |
2017 |
European Journal of Agronomy |
87 |
30-39 |
| 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. |
Contribution of crop model structure, parameters and climate projections to uncertainty in climate change impact assessments |
2018 |
Global Change Biology |
24 |
1291-1307 |
