Author
 |
BOOTE, K - University Of Florida |
|
ROSENZWEIG, C - National Aeronautics And Space Administration (NASA) |
|
JONES, J - University Of Florida |
|
Hatfield, Jerry |
|
RUANE, A - Columbia University |
|
THORBURN, P - Commonwealth Scientific And Industrial Research Organisation (CSIRO) |
|
ANTLE, J - Oregon State University |
|
NELSON, G - International Food Policy Researc Institute (IFPRI) |
|
PORTER, C - University Of Florida |
|
JANSSEN, S - Wageningen Agricultural University |
|
Submitted to: Meeting Abstract
Publication Type: Abstract Only Publication Acceptance Date: 4/2/2011 Publication Date: 4/21/2011 Citation: Boote, K.J., Rosenzweig, C., Jones, J.W., Hatfield, J.L., Ruane, A.C., Thorburn, P., Antle, J.M., Nelson, G.C., Porter, C., Janssen, S. 2011. The agricultural model intercomparison and improvement project (AgMIP) [abstract]. Biological Systems Simulations. CD-ROM. Interpretive Summary: Technical Abstract: The agricultural sector faces the challenge of increasing production to provide food security for the projected human population of 9 billion by mid-century, while protecting the environment and the functioning of its ecosystems. These challenges are compounded by the need to adapt to climate change, i.e., by taking advantage of potential benefits and by minimizing the potentially negative impacts to agricultural production. Crop models coupled with economic simulation models are proposed as a methodology to examine the impact of climate change on agriculture at regional and global scales. In addition to impact assessment, the same tools may be used to evaluate adaptation strategies (genetic, management, technology) for adaptation to climate change as well as mitigation strategies to minimize greenhouse gas emissions. Before undertaking such efforts on regional and global basis, it is important to organize and coordinate interested collaborators and to develop strategies for comparing and improving crop growth models against common data sets to evaluate crop model uncertainties and crop model reliabilities for predicting effects of climate change or adaptation and mitigation strategies. Just as the global circulation models have been subjected to intercomparison against each other, we propose that crop models also be intercompared, so we can determine uncertainties across multiple different crop models. The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a distributed simulation project for agricultural model intercomparison and future climate change assessments with open participation from multiple crop and economic modeling groups around the world. AgMIP research activities are organized under four project teams (Crop Modeling, Climate Scenarios, Economics, and Information Technologies), with guidance provided by a Leadership Team and a Steering Group. In addition, there are three cross-cutting themes – Representative Agricultural Pathways, Aggregation across Scales, and Uncertainty – which span the activities of all the teams. There are two primary tracks by which AgMIP will achieve its goals. Track 1 Model Intercomparison and Improvement is to conduct crop model intercomparisons and improvements using site-specific data to test accuracy and uncertainty of predicted crop yield response to climate. The second track is to use those models to conduct consistent multi-model assessments of climate change effects on local, regional, national, and global food production, food security, and poverty driven by climate change scenarios. Key elements of AgMIP include: 1) Crop Model Intercomparison and Improvement • Improve documentation, standardization and transparency of crop models and the data needed. • Compare performance of different crop models. • Better characterize the role of the direct effects of CO2 on crop yield and water use scaled to aggregated production estimates. • Improve crop model ability to simulate crop varietal performance. • Include the effects of extreme events in climate change projections. • Improve testing of agricultural adaptation to climate change. • Improve the representation of tropical region crops and geographic areas underrepresented in previous assessments. 2) Integrated Multi-Model Multiscale Assessment • Create rigorous methods of scaling and linking between climate, crop, and economic models from local to global applications. • Develop “Representative Agricultural Pathways” (RAPs) matching those developed by the global integrated assessment communities. • Generate and incorporate a wider spectrum of climate and economic scenario drivers to capture the range of plausible futures. • Better characterize important thresholds and inflection points in global agricultural production, relative to projected temperature and precipitation change. • Facilitate inter-compar |
