Ewert, F., Rötter, R. P., Bindi, M., Webber, H., Trnka, M., Kersebaum, K. C., et al. (2015). Crop modelling for integrated assessment of risk to food production from climate change. Env. Model. Softw., 72, 287–303.
Abstract: The complexity of risks posed by climate change and possible adaptations for crop production has called for integrated assessment and modelling (IAM) approaches linking biophysical and economic models. This paper attempts to provide an overview of the present state of crop modelling to assess climate change risks to food production and to which extent crop models comply with IAM demands. Considerable progress has been made in modelling effects of climate variables, where crop models best satisfy IAM demands. Demands are partly satisfied for simulating commonly required assessment variables. However, progress on the number of simulated crops, uncertainty propagation related to model parameters and structure, adaptations and scaling are less advanced and lagging behind IAM demands. The limitations are considered substantial and apply to a different extent to all crop models. Overcoming these limitations will require joint efforts, and consideration of novel modelling approaches.
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Cammarano, D., Rötter, P., Ewert, F., Palosuo, T., Bindi, M., Kersebaum, K. C., et al. (2013). Challenges for Agro-Ecosystem Modelling in Climate Change Risk Assessment for major European Crops and Farming systems. (pp. 555–564).
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Nendel, C., Ewert, F., Rötter, R. P., Rosenzweig, C., Jones, J. W., Hatfield, J. L., et al. (2013). Addressing challenges and uncertainties for, the use of agro-ecosystem models to, assess climate change impact and food security across scales..
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Janssen, S. (2015). Inventory of data and data sharing mechanism for model linking and scaling exercises (Vol. 6).
Abstract: This deliverable lays out the work as done as part of MACSUR CropM on ‘Inventory of data and data sharing mechanism for model linking and scaling exercises’. In summary not much work was done, as it was found that there was not real demand for the activity in this task. The task in itself was servicing the other work as part of MACSUR, and as the service was not in demand, it was decided to take a low profile and wait for specific requests by partners for data in relation to model linking and upscaling. No Label
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Janssen, S., Houtkamp, J., De Groot, H., & Schils, R. (2015). Online web tool for data visualization (Vol. 6).
Abstract: This deliverable lays out the work as done as part of MACSUR CropM on data, with the focus on providing a web tool for visualization of model output. It was decided early on that not a specific MACSUR web tool would be developed as part of MACSUR for phase 1, and mostly results would be visualized in other available tools, such as the Global Yield Gap Atlas, which are recognised resources for visualizations. Only in relationship to the MACSUR Geonetwork data catalog hosted at Aarhus University some developments where started. Operationally speaking, most data was still being generated during phase 1, so there was not enough to visualize on specific websites and partners did not commit financial resources to their development, and only in kind was available. No Label
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