The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a major international collaborative effort to improve the state of agricultural simulation and to understand climate impacts on the agricultural sector at global and regional scales.
AgMIP Indo-Gangetic Basin Research Team （2016.12.20）
The Indo-Gangetic Basin research team is one of seven regional research teams across Africa and Southern Asia working to provide scientifically rigorous and relevant agricultural information to stakeholders and decision makers. These Regional Research Teams, following the Agricultural Model Intercomparison and Improvement Project (AgMIP) Protocols for Regional Integrated Assessments, are at the forefront of agricultural research.
AgMIP Regional Research Teams in Sub-Saharan Africa and South Asia have been using a new tool to help them streamline their workflow and use the power of cloud computing. This new tool named FACE-IT is an open, interactive, online platform that enables users to access data; easily build and run workflows; and analyze, visualize, and share results.
FACE-IT accomplishes these goals by building and integrating a number of really awesome web-based software tools to enable researchers to easily develop data manipulation and analysis applications, apply those apps to their own data and to data provided by others, link multiple apps into data analysis pipelines, and share such pipelines with their collaborators and community.
This new video about FACE-IT explains the concept and interface in more detail. To learn more visit here.
VIDEO – THE BENEFITS OF CO-DEVELOPING RESEARCH （2016.8.12）
Since 2012, The Agricultural Model Intercomparison and Improvement Project (AgMIP) Regional Research Teams in Sub-Saharan Africa and South Asia have been conducting assessments of the impacts of variable and changing climate on regional food security. These integrated assessments feature an interdisciplinary approach that link climate, crop, livestock, and economic models to simulate agricultural productivity, rural income, and poverty rates.
Fundamental to the AgMIP Regional Integrated Assessment approach is the co-development of research that incorporates knowledge from local stakeholders. Stakeholder engagement cannot wait until after the research has been completed. Instead, it is an ongoing discussion that occurs throughout the research process where stakeholder knowledge and input assist scientists in producing outputs that are relevant to decision-makers.
In June 2015 over 80 scientists from 24 countries attended the Agricultural Model Intercomparison and Improvement Project (AgMIP) Regional Fundamentals Workshop in Victoria Falls, Zimbabwe. The participants included members of AgMIP Regional Research Teams from institutions in Sub-Saharan Africa and South Asia who, along with AgMIP leaders, have been co-developing protocols to assess the impacts of climate change on regional food security.
This video features five women scientists who attended the workshop as members of their Regional Research Teams. All five women hold important positions on their teams and are critical for the success of the project. The goal of the video was to listen to them describe in their own words the challenges they face, culturally or institutionally, in their pursuit of a career in the sciences.
Cheryl Porter gives an overview of AgMIP RIA crop modeling process and how FACE-IT can help.
FACE-IT demo 2014-11-21: The AgMIP RIA Use Case （2014.11.21）
Cheryl Porter provides an overview of the AgMIP RIA use case, the challenges faced by the regional assessment teams, and how FACE-IT may help provide solutions.
Predicting climate’s impact on food supply（2013.5.22）
Models used around the world to predict agricultural output, the economics of the food supply and climate change don’t all speak the same language. What are the best ways to project how climate will affect our ability to produce enough food for a growing population? Alex Ruane of the Center for Climate Systems Research and the NASA-Goddard Institute for Space Studies explains the Agricultural Model Intercomparison.