The Global Gridded Crop Model Intercomparison phase 1 simulation dataset

Research output: Contribution to journalArticle

Abstract

The Global Gridded Crop Model Intercomparison (GGCMI) phase 1 dataset of the Agricultural Model Intercomparison and Improvement Project (AgMIP) provides an unprecedentedly large dataset of crop model simulations covering the global ice-free land surface. The dataset consists of annual data fields at a spatial resolution of 0.5 arc-degree longitude and latitude. Fourteen crop modeling groups provided output for up to 11 historical input datasets spanning 1901 to 2012, and for up to three different management harmonization levels. Each group submitted data for up to 15 different crops and for up to 14 output variables. All simulations were conducted for purely rainfed and near-perfectly irrigated conditions on all land areas irrespective of whether the crop or irrigation system is currently used there. With the publication of the GGCMI phase 1 dataset we aim to promote further analyses and understanding of crop model performance, potential relationships between productivity and environmental impacts, and insights on how to further improve global gridded crop model frameworks. We describe dataset characteristics and individual model setup narratives.

Details

Authors
  • Christoph Müller
  • Joshua Elliott
  • David Kelly
  • Almut Arneth
  • Juraj Balkovic
  • Philippe Ciais
  • Delphine Deryng
  • Christian Folberth
  • Steven Hoek
  • Roberto C. Izaurralde
  • Curtis D. Jones
  • Nikolay Khabarov
  • Peter Lawrence
  • Wenfeng Liu
  • Thomas A.M. Pugh
  • Ashwan Reddy
  • Cynthia Rosenzweig
  • Alex C. Ruane
  • Gen Sakurai
  • Erwin Schmid
  • Rastislav Skalsky
  • Xuhui Wang
  • Allard de Wit
  • Hong Yang
Organisations
External organisations
  • Potsdam Institute for Climate Impact Research
  • University of Chicago
  • Karlsruhe Institute of Technology
  • International Institute for Applied Systems Analysis
  • Columbia University
  • Wageningen University
  • University of Maryland
  • Texas A and M University
  • National Center for Atmospheric Research
  • Eawag: Swiss Federal Institute of Aquatic Science and Technology
  • University of Birmingham
  • NASA Goddard Institute for Space Studies
  • Peking University
  • University of Basel
  • Comenius University
  • Laboratoire des Sciences du Climat et de l'Environnement
  • Institute for Agro-Environmental Sciences, NARO
  • University of Natural Resources and Life Sciences, Vienna
  • Soil Science and Conservation Research Institute, Slovakia
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Physical Geography
Original languageEnglish
Article number50
JournalScientific Data
Volume6
Issue number1
Publication statusPublished - 2019
Publication categoryResearch
Peer-reviewedYes