Location: Soil, Water & Air Resources ResearchTitle: The agricultural model intercomparison and improvement project (AgMIP): Protocols and pilot studies) Author
Submitted to: Agriculture and Forest Meterology
Publication Type: Peer reviewed journal
Publication Acceptance Date: 9/1/2012
Publication Date: 1/10/2013
Citation: Rosenzweig, C., Jones, J.W., Hatfield, J.L., Ruane, A.C., Boote, K.J., Thorburn, P., Antle, J.M., Nelson, G.C., Porter, C., Janssen, S., Asseng, S., Basso, B., Ewert, F., Wallach, D., Baigorria, G., Winter, J.M. 2013. The agricultural model intercomparison and improvement project (AgMIP): Protocols and pilot studies. Agriculture and Forest Meterology. 170:166-182. Interpretive Summary: Climate impacts on crop production around the world will offer a challenge to meet the food production requirements necessary to meet food security goals. A project was developed to intercompare both crop production and economic models available from the research community around the world. The agricultural model intercomparison project was designed to compare crop models across a range of growing conditions and climates and then incorporate climate scenarios into these models to assess the future impacts of climate change on food production. A similar approach is being undertaken for the economic models to assess the national and international economic impacts of changes in food production scenarios. Intercomparison of crop models requires the assembly of existing data sets on crop growth from various soils, climates, and crops and these are being assembled into a data base for use by the worldwide modeling community. These efforts will benefit science in being able to provide a robust assessment of the future impacts of climate change on agricultural production. This information will benefit both the science and policy community by having this analysis for the major food crops around the world.
Technical Abstract: The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a distributed climate-scenario simulation research activity for historical period model intercomparison and future climate change conditions with participation of multiple crop and agricultural economic model groups around the world. Analyses of the agricultural impacts of climate variability and change require a transdisciplinary effort to consistently link state-of-the-art climate scenarios to process-based crop models, with results aggregated as inputs to economic models to determine changes in comparative advantage, trading opportunities, regional vulnerabilities, and potential adaptation strategies in the agricultural sector. The goals of AgMIP are to improve substantially the characterization of risk of hunger and world food security due to climate change and to enhance adaptation capacity in both developing and developed countries. Climate scenario, crop model, economics, and information technologies protocols are presented to guide AgMIP research activities around the world, along with research initiatives for cross-cutting themes that address representative agricultural pathways, aggregation across scales, and uncertainty. Research activities organized by geographic region and specific crops are described. Example results demonstrate AgMIP’s role in assessing climate impacts with explicit representation of uncertainties in climate scenarios and simulations using crop and economic models. First, an intercomparison of wheat model simulations near Obregón, Mexico, revealed inter-model differences in yield sensitivity to [CO2] that held approximately steady as concentrations rose, while model uncertainty increased with rising temperatures. Wheat model simulations of 2050s yield changes project a slight decline in yields, however they were more sensitive to the selection of crop model than to the selection of global climate model, emissions scenario, or climate scenario downscaling method. Second, a comparison between national-scale economic simulations and regional economic simulations revealed a large sensitivity in projected yield changes to the simulations’ resolved scales. Finally, the complexity of a unified AgMIP is underscored through an examination of the many connected models required to assess global agricultural impacts.