Climate Scenarios and Analyses for AgMIP Assessments.

Climate change presents a challenge to food security as changes in precipitation, temperature , and circulation patterns alter the climatic conditions upon which agricultural systems rely. Projections of future climate conditions are inherently uncertain owing to a lack of clarity on socio-economic development, greenhouse-gas emissions pathways, and complexities in modeling fundamental climate system components.

 The Agricultural Model Intercomparison and Improvement Project (AgMIP) climate-scenario-generation process was designed to satisfy a wide range of activities and participants, spanning many regions, disciplines, and temporal and spatial scales, to investigate the impact of climate change on food security. AgMIP’s integrated assessments require transparent methodologies that enable reproducible results and protocols accessible by many researchers. These methods and protocols must also be consistent (e.g. across regions) to allow for comparisons; must be practical and rapidly implementable; and must have clarity such that stakeholders and decision-makers may readily utilize the projected results, and uncertainties, in their assessments.

 The AgMIP climate scenario-generation process utilize a common data format that facilitates use of AgMIP information technology tools; assembles quality-controlled, historical climate datasets to calibrate agricultural models; analyzes historical data to identify trends and climate extremes; generates future climate scenarios that connect observations with changes in mean climate and climate variability from GCMs; and tracks how future agricultural projections are affected by various sources of uncertainty (e.g. in climate model projections).

Furthermore, the AgMIP climate team has also developed the Coordinated Climate-Crop Modeling Project (C3MP), in which all crop modelers are invited to run a set of common climate sensitivity experiments at sites where their models are already calibrated. C3MP has contributions representing over 18 crops, 56 countries, and 23 crop and grassland models. Preliminary results are shown to demonstrate the utility of this international effort, and the types of crop-specific, model-specific, and regional analyses that can be undertaken.