The Agricultural Model Intercomparison and Improvement Project (AgMIP): Protocols and pilot studies
- Publication date
- Publisher
- 'Elsevier BV'
Abstract
The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a major international effort linking the climate, crop, and economic modeling communities with cutting-edge information technology
to produce improved crop and economic models and the next generation of climate impact projections for
the agricultural sector. The goals of AgMIP are to improve substantially the characterization of world food
security due to climate change and to enhance adaptation capacity in both developing and developed
countries. Analyses of the agricultural impacts of climate variability and change require a transdisciplinary
effort to consistently link state-of-the-art climate scenarios to crop and economic models. Crop
model outputs are aggregated as inputs to regional and global economic models to determine regional
vulnerabilities, changes in comparative advantage, price effects, and potential adaptation strategies in
the agricultural sector. Climate, Crop Modeling, Economics, and Information Technology Team Protocols
are presented to guide coordinated climate, crop modeling, economics, and information technology
research activities around the world, along with AgMIP Cross-Cutting Themes that address uncertainty,
aggregation and scaling, and the development of Representative Agricultural Pathways (RAPs) to enable
testing of climate change adaptations in the context of other regional and global trends. The organization
of research activities by geographic region and specific crops is described, along with project milestones.
Pilot results demonstrate AgMIP’s role in assessing climate impacts with explicit representation of
uncertainties in climate scenarios and simulations using crop and economic models. An intercomparison
of wheat model simulations near Obregón, Mexico reveals inter-model differences in yield sensitivity to
[CO₂] with model uncertainty holding approximately steady as concentrations rise, while uncertainty
related to choice of crop model increases with rising temperatures. Wheat model simulations with midcentury
climate scenarios project a slight decline in absolute yields that is more sensitive to selection of
crop model than to global climate model, emissions scenario, or climate scenario downscaling method. A
comparison of regional and national-scale economic simulations finds a large sensitivity of projected yield
changes to the simulations’ resolved scales. Finally, a global economic model intercomparison example
demonstrates that improvements in the understanding of agriculture futures arise from integration of
the range of uncertainty in crop, climate, and economic modeling results in multi-model assessments.
© 2012 Published by Elsevier B.V.This is the publisher’s final pdf. The published article is copyrighted by Elsevier and can be found at: http://www.elsevier.com/KEYWORDS: Intercomparison, Food security, Risk, Climate change, Uncertainty, Economic models, Agriculture, Crop models, Adaptatio