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The Global Gridded Crop Model Intercomparison phase 1 simulation dataset.
Müller, Christoph; Elliott, Joshua; Kelly, David; Arneth, Almut; Balkovic, Juraj; Ciais, Philippe; Deryng, Delphine; Folberth, Christian; Hoek, Steven; Izaurralde, Roberto C; Jones, Curtis D; Khabarov, Nikolay; Lawrence, Peter; Liu, Wenfeng; Olin, Stefan; Pugh, Thomas A M; Reddy, Ashwan; Rosenzweig, Cynthia; Ruane, Alex C; Sakurai, Gen; Schmid, Erwin; Skalsky, Rastislav; Wang, Xuhui; de Wit, Allard; Yang, Hong.
Afiliação
  • Müller C; Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, 14473, Potsdam, Germany. Christoph.Mueller@pik-potsdam.de.
  • Elliott J; University of Chicago and ANL Computation Institute, Chicago, IL, 60637, USA.
  • Kelly D; University of Chicago and ANL Computation Institute, Chicago, IL, 60637, USA.
  • Arneth A; Karlsruhe Institute of Technology, IMK-IFU, 82467, Garmisch-Partenkirchen, Germany.
  • Balkovic J; Ecosystem Services and Management Program, International Institute for Applied Systems Analysis, 2361, Laxenburg, Austria.
  • Ciais P; Department of Soil Science, Comenius University in Bratislava, 842 15, Bratislava, Slovak Republic.
  • Deryng D; Laboratoire des Sciences du Climat et de l'Environnement, CEA CNRS UVSQ Orme des Merisiers, F-91191, Gif-sur-Yvette, France.
  • Folberth C; University of Chicago and ANL Computation Institute, Chicago, IL, 60637, USA.
  • Hoek S; Center for Climate Systems Research, Columbia University, New York, NY, 10025, USA.
  • Izaurralde RC; Ecosystem Services and Management Program, International Institute for Applied Systems Analysis, 2361, Laxenburg, Austria.
  • Jones CD; Department of Soil Science, Comenius University in Bratislava, 842 15, Bratislava, Slovak Republic.
  • Khabarov N; Earth Observation and Environmental Informatics, Alterra Wageningen University and Research Centre, 6708PB, Wageningen, Netherlands.
  • Lawrence P; Department of Geographical Sciences, University of Maryland, College Park, MD, 20742, USA.
  • Liu W; Texas AgriLife Research and Extension, Texas A&M University, Temple, TX, 76502, USA.
  • Olin S; Department of Geographical Sciences, University of Maryland, College Park, MD, 20742, USA.
  • Pugh TAM; Ecosystem Services and Management Program, International Institute for Applied Systems Analysis, 2361, Laxenburg, Austria.
  • Reddy A; Earth System Laboratory, National Center for Atmospheric Research, Boulder, CO, 80307, USA.
  • Rosenzweig C; Laboratoire des Sciences du Climat et de l'Environnement, CEA CNRS UVSQ Orme des Merisiers, F-91191, Gif-sur-Yvette, France.
  • Ruane AC; Eawag, Swiss Federal Institute of Aquatic Science and Technology, CH-8600, Duebendorf, Switzerland.
  • Sakurai G; Department of Physical Geography and Ecosystem Science, Lund University, 223 62, Lund, Sweden.
  • Schmid E; School of Geography, Earth & Environmental Science, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom.
  • Skalsky R; Birmingham Institute of Forest Research, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom.
  • Wang X; Department of Geographical Sciences, University of Maryland, College Park, MD, 20742, USA.
  • de Wit A; Center for Climate Systems Research, Columbia University, New York, NY, 10025, USA.
  • Yang H; National Aeronautics and Space Administration Goddard Institute for Space Studies, New York, NY, 10025, USA.
Sci Data ; 6(1): 50, 2019 May 08.
Article em En | MEDLINE | ID: mdl-31068583
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.

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Sci Data Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Alemanha

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Sci Data Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Alemanha