Article (Scientific journals)
The GGCMI Phase 2 experiment: Global gridded crop model simulations under uniform changes in CO2, temperature, water, and nitrogen levels (protocol version 1.0)
Franke, J. A.; Müller, C.; Elliott, J. et al.
2020In Geoscientific Model Development, 13 (5), p. 2315-2336
Peer Reviewed verified by ORBi
 

Files


Full Text
gmd-13-2315-2020.pdf
Publisher postprint (10.04 MB)
Request a copy

All documents in ORBi are protected by a user license.

Send to



Details



Abstract :
[en] Concerns about food security under climate change motivate efforts to better understand future changes in crop yields. Process-based crop models, which represent plant physiological and soil processes, are necessary tools for this purpose since they allow representing future climate and management conditions not sampled in the historical record and new locations to which cultivation may shift. However, process-based crop models differ in many critical details, and their responses to different interacting factors remain only poorly understood. The Global Gridded Crop Model Intercomparison (GGCMI) Phase 2 experiment, an activity of the Agricultural Model Intercomparison and Improvement Project (AgMIP), is designed to provide a systematic parameter sweep focused on climate change factors and their interaction with overall soil fertility, to allow both evaluating model behavior and emulating model responses in impact assessment tools. In this paper we describe the GGCMI Phase 2 experimental protocol and its simulation data archive. A total of 12 crop models simulate five crops with systematic uniform perturbations of historical climate, varying CO2, temperature, water supply, and applied nitrogen ("CTWN") for rainfed and irrigated agriculture, and a second set of simulations represents a type of adaptation by allowing the adjustment of growing season length. We present some crop yield results to illustrate general characteristics of the simulations and potential uses of the GGCMI Phase 2 archive. For example, in cases without adaptation, modeled yields show robust decreases to warmer temperatures in almost all regions, with a nonlinear dependence that means yields in warmer baseline locations have greater temperature sensitivity. Inter-model uncertainty is qualitatively similar across all the four input dimensions but is largest in high-latitude regions where crops may be grown in the future. © Author(s) 2020.
Research center :
EC - European Commission
Disciplines :
Earth sciences & physical geography
Author, co-author :
Franke, J. A.;  Department of the Geophysical Sciences, University of Chicago, Chicago, IL, United States, Center for Robust Decision-making on Climate and Energy Policy (RDCEP), University of Chicago, Chicago, IL, United States
Müller, C.;  Potsdam Institute for Climate Impact Research, Leibniz Association, Potsdam, Germany
Elliott, J.;  Center for Robust Decision-making on Climate and Energy Policy (RDCEP), University of Chicago, Chicago, IL, United States, Department of Computer Science, University of Chicago, Chicago, IL, United States
Ruane, A. C.;  NASA, Goddard Institute for Space Studies, New York, NY, United States
Jägermeyr, J.;  Center for Robust Decision-making on Climate and Energy Policy (RDCEP), University of Chicago, Chicago, IL, United States, Potsdam Institute for Climate Impact Research, Leibniz Association, Potsdam, Germany, Department of Computer Science, University of Chicago, Chicago, IL, United States, NASA, Goddard Institute for Space Studies, New York, NY, United States
Balkovic, J.;  Ecosystem Services and Management Program, International Institute for Applied Systems Analysis, Laxenburg, Austria, Department of Soil Science, Faculty of Natural Sciences, Comenius University in Bratislava, Bratislava, Slovakia
Ciais, P.;  Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, Gif-sur-Yvette, France, Sino-French Institute of Earth System Sciences, College of Urban and Env. Sciences, Peking University, Beijing, China
Dury, Marie ;  Université de Liège - ULiège > Département d'astrophys., géophysique et océanographie (AGO) > Exotic
Falloon, P. D.;  Met Office Hadley Centre, Exeter, United Kingdom
Folberth, C.;  Ecosystem Services and Management Program, International Institute for Applied Systems Analysis, Laxenburg, Austria
François, Louis  ;  Université de Liège - ULiège > Département d'astrophys., géophysique et océanographie (AGO) > Modélisation du climat et des cycles biogéochimiques
Hank, T.;  Department of Geography, Ludwig-Maximilians-Universität München, Munich, Germany
Hoffmann, M.;  Georg-August-University Göttingen, Tropical Plant Production and Agricultural Systems Modeling, Göttingen, Germany, Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany
Izaurralde, R. C.;  Department of Geographical Sciences, University of Maryland, College Park, MD, United States, Texas Agrilife Research and Extension, Texas AandM University, Temple, TX, United States
Jacquemin, Ingrid ;  Université de Liège - ULiège > SPHERES
Jones, C.;  Department of Geographical Sciences, University of Maryland, College Park, MD, United States
Khabarov, N.;  Ecosystem Services and Management Program, International Institute for Applied Systems Analysis, Laxenburg, Austria
Koch, M.;  Georg-August-University Göttingen, Tropical Plant Production and Agricultural Systems Modeling, Göttingen, Germany
Li, M.;  Center for Robust Decision-making on Climate and Energy Policy (RDCEP), University of Chicago, Chicago, IL, United States, Department of Statistics, University of Chicago, Chicago, IL, United States
Liu, W.;  Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, Gif-sur-Yvette, France, EAWAG, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland
Olin, S.;  Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
Phillips, M.;  NASA, Goddard Institute for Space Studies, New York, NY, United States, Earth Institute Center for Climate Systems Research, Columbia University, New York, NY, United States
Pugh, T. A. M.;  School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, United Kingdom, Birmingham Institute of Forest Research, University of Birmingham, Birmingham, United Kingdom
Reddy, A.;  Department of Geographical Sciences, University of Maryland, College Park, MD, United States
Wang, X.;  Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, Gif-sur-Yvette, France, Sino-French Institute of Earth System Sciences, College of Urban and Env. Sciences, Peking University, Beijing, China
Williams, K.;  Met Office Hadley Centre, Exeter, United Kingdom, Global Systems Institute, University of Exeter, Laver Building, North Park Road, Exeter, EX4 4QE, United Kingdom
Zabel, F.;  Department of Geography, Ludwig-Maximilians-Universität München, Munich, Germany
Moyer, E. J.;  Department of the Geophysical Sciences, University of Chicago, Chicago, IL, United States, Center for Robust Decision-making on Climate and Energy Policy (RDCEP), University of Chicago, Chicago, IL, United States
More authors (18 more) Less
Language :
English
Title :
The GGCMI Phase 2 experiment: Global gridded crop model simulations under uniform changes in CO2, temperature, water, and nitrogen levels (protocol version 1.0)
Publication date :
2020
Journal title :
Geoscientific Model Development
ISSN :
1991-959X
eISSN :
1991-9603
Publisher :
Copernicus GmbH
Volume :
13
Issue :
5
Pages :
2315-2336
Peer reviewed :
Peer Reviewed verified by ORBi
Funders :
NSF - National Science Foundation [US-VA] [US-VA]
BMBF - Bundesministerium für Bildung und Forschung [DE]
NASA - National Aeronautics and Space Administration [US-DC] [US-DC]
CER - Conseil Européen de la Recherche [BE]
Newton Fund
Available on ORBi :
since 16 June 2020

Statistics


Number of views
71 (11 by ULiège)
Number of downloads
4 (4 by ULiège)

Scopus citations®
 
44
Scopus citations®
without self-citations
29
OpenCitations
 
21

Bibliography


Similar publications



Contact ORBi