CropM: Understanding and Modelling Impacts of Climate Change on Crop Production

Frank Ewert, Reimund Rötter, Katharina Brüser


Key ambition:

To develop

  • a shared comprehensive information system on the impacts of climate change on European crop production and food security
  • first shared pan-continental assessments and tools
  • (Full) range of important crops and important crop rotations
  • Improved management and analysis of data
  • Model improvement (stresses and factors not yet accounted for)
  • Advanced scaling methods
  • Advanced link to farm and sector models
  • Comprehensive uncertainty assessment and reporting
  • To train integrative crop modeler
Data ... for better understanding and modelling climate change impact
  • Evaluation of data quality (platinum, gold, silver)
  • Quantify data gaps for modelling
  • Empirical analysis of crop responses to past climate variability and change
  • Observed adaptation options and their efficacy
  • Effect of extreme events (past analysis and projections)
  • Climate change scenarios
  • Concept for data management, data journal
  • Methodology & protocols for uncertainty analysis
  • Methodology for standardized model evaluation
  • Local-scale climate scenarios & uncertainties in climate projections
  • Basic methodology for probabilistic assessment of CC impacts using impact response surfaces
  • Methodology for probabilistic evaluation of alternative adaptation options 
Main aims in MACSUR2:
  • Improve crop model to better capture extremes
  • Complement knowledge from crop models with empirical crop-weather analysis
  • Consider management variables in simulations
  • Full range of methods for analysing uncertainty in climate impact assessments
  • Evaluate potential adaptation options
  • Contributing to cross-cutting issues and case studies.
  • Further the links with other modelling activities
  • Link local to European and global responses

Full Text:



Ewert F., van Bussel, L.G.J., Zhao, G., Hoffmann, H., Gaiser, T. … et al. (2015) Uncertainties in Scaling-up Crop Models for Large-area Climate-change Impact Assessments. In C. Rosenzweig and D. Hillel, editors. Handbook of Climate Change and Agroecosystems (in Press).

Eyshi Rezaei, E., S. Siebert, F. Ewert, 2015. Intensity of heat stress in winter wheat—phenology compensates for the adverse effect of global warming. Environmental Research Letters 10, 024012. DOI:10.1088/1748-9326/10/2/024012.

Kollas, C.… et al.(2015) Crop rotation modelling - a European model intercomparison. In review

Pirtioja, N et al (2015) A crop model ensemble analysis of temperature and precipitation effects on wheat yield across a European transect using impact response surfaces. Climate Research. (accepted)

Rötter, R., F. Tao, J. G. Höhn and T. Palosuo (2015) Use of crop simulation modelling to aid ideotype design of future cereal cultivars. Journal of Experimental Botany. doi:10.1093/jxb/erv098

Rötter, R. P. (2014). Agricultural Impacts: Robust uncertainty. Nature Climate Change, 4(4), 251-252. doi: 10.1038/nclimate2181

Trnka, M., Rötter, R. P., Ruiz-Ramos, M., Kersebaum, K. C., Olesen, J. E., Žalud, Z., & Semenov, M. A. (2014). Adverse weather conditions for European wheat production will become more frequent with climate change. Nature Climate Change, 4, 637–643. doi: 10.1038/nclimate2242

Zhao, G. …. et al (2015) The implication of irrigation in climate change impact assessment: a European wide study (in Review)

Zhao, G. …. et al (2015) Effect of weather data aggregation on regional crop simulation for different crops, production conditions and response variables. (in Review)

Previous issues and volumes can be found in the 'Archives' section.

You can refer to a paper published in this series in the following format Author (2013) Title. FACCE MACSUR Reports 2: D-C1.3, where "D-C1.3" is the article ID en lieu of page range.