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.

Abstract: We compare 27 wheat models’ yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981-2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models’ climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R-2 <= 0.24) was found between the models’ sensitivities to interannual temperature variability and their response to long-term warming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts. Published by Elsevier Ltd.

Abstract: This review examines relevant impact assessments identified by a literature search from 1991to date. A bibliographic search was applied to the CAB Abstracts database with a given searchstring. Resultant papers were checked for relevance, based on expert judgment. This yielded 91 papers, which were subjected to further analysis. Firstly, publication intensity over time and distribution by geographic location and cereal crop were examined. Next, for a given crop, the assessments and their outcomes were grouped by type and number of the change variables considered – that is, effects of climate change only, elevated CO 2 and technological progress(improved breeds, management). Finally, separately for individual countries/subregions and Europe as a whole, we examined whether and to what extent study results have changed over time, for example become more positive/negative. Based on our sample, we found that publication intensity increased exponentially during thelast 4 years, the majority of studies are Europe-wide, but some concentrated on a few countries(Italy, Spain and UK), whereby studies on wheat are clearly most popular. Taking the factor of technological progress into account has an overruling influence on results. Finally, over time, projected yield impacts have become more negative. This is in line with finding from global analyses, as reflected by the most recent comparison of agricultural impact chapters, of the 4thand 5th Assessment Reports of Intergovernmental Panel on Climate Change, Working Group II.In the future, there is particular need to consider impacts under various incremental and transformational adaptation measures in more depth (e.g. their interconnections across scales)and with more breadth (e.g. anticipated new breeds). Follow-up reviews should also examine how projected impacts are changing with the new climate scenario data sets (CMIP5) and with improved impact models and assessment approaches.