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Tom Pugh

Thomas Pugh

Senior lecturer

Tom Pugh

The Global Gridded Crop Model Intercomparison phase 1 simulation dataset

Author

  • 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
  • Stefan Olin
  • Thomas A.M. Pugh
  • Ashwan Reddy
  • Cynthia Rosenzweig
  • Alex C. Ruane
  • Gen Sakurai
  • Erwin Schmid
  • Rastislav Skalsky
  • Xuhui Wang
  • Allard de Wit
  • Hong Yang
Show all

Summary, in English

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.

Department/s

  • Dept of Physical Geography and Ecosystem Science
  • eSSENCE: The e-Science Collaboration
  • MERGE: ModElling the Regional and Global Earth system
  • BECC: Biodiversity and Ecosystem services in a Changing Climate

Publishing year

2019

Language

English

Publication/Series

Scientific Data

Volume

6

Issue

1

Document type

Journal article

Publisher

Nature Publishing Group

Topic

  • Physical Geography

Status

Published

ISBN/ISSN/Other

  • ISSN: 2052-4463