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Global Gridded Crop Model Evaluation: Benchmarking, Skills, Deficiencies and Implications.Crop models are increasingly used to simulate crop yields at the global scale, but so far there is no general framework on how to assess model performance. Here we evaluate the simulation results of 14 global gridded crop modeling groups that have contributed historic crop yield simulations for maize, wheat, rice and soybean to the Global Gridded Crop Model Intercomparison (GGCMI) of the Agricultural Model Intercomparison and Improvement Project (AgMIP). Simulation results are compared to reference data at global, national and grid cell scales and we evaluate model performance with respect to time series correlation, spatial correlation and mean bias. We find that global gridded crop models (GGCMs) show mixed skill in reproducing time series correlations or spatial patterns at the different spatial scales. Generally, maize, wheat and soybean simulations of many GGCMs are capable of reproducing larger parts of observed temporal variability (time series correlation coefficients (r) of up to 0.888 for maize, 0.673 for wheat and 0.643 for soybean at the global scale) but rice yield variability cannot be well reproduced by most models. Yield variability can be well reproduced for most major producing countries by many GGCMs and for all countries by at least some. A comparison with gridded yield data and a statistical analysis of the effects of weather variability on yield variability shows that the ensemble of GGCMs can explain more of the yield variability than an ensemble of regression models for maize and soybean, but not for wheat and rice. We identify future research needs in global gridded crop modeling and for all individual crop modeling groups. In the absence of a purely observation-based benchmark for model evaluation, we propose that the best performing crop model per crop and region establishes the benchmark for all others, and modelers are encouraged to investigate how crop model performance can be increased. We make our evaluation system accessible to all crop modelers so that other modeling groups can also test their model performance against the reference data and the GGCMI benchmark.
Document ID
20170003517
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
Authors
Muller, Christoph
(Potsdam-Inst. fuer Klimafolgenforschung Potsdam, Germany)
Elliott, Joshua
(Columbia Univ. New York, NY, United States)
Chryssanthacopoulos, James
(Columbia Univ. New York, NY, United States)
Arneth, Almut
(Karlsruhe Inst. of Technology Germany)
Balkovic, Juraj
(Comenius Univ. Bratislava, Czechoslovakia)
Ciais, Philippe
(Laboratoire des Sciences du Climat et de l'Environnement Gif-sur-Yvette, France)
Deryng, Delphine
(Columbia Univ. New York, NY, United States)
Folberth, Christian
(Laboratoire des Sciences du Climat et de l'Environnement Gif-sur-Yvette, France)
Glotter, Michael
(Chicago Univ. Chicago, IL, United States)
Hoek, Steven
(Wageningen Univ. Wageningen, Netherlands)
Iizumi, Toshichika
(National Agriculture and Food Research Organization Tsukuba, Japan)
Izaurralde, Roberto C.
(Texas A&M Univ. Temple, TX, United States)
Jones, Curtis
(Maryland Univ. College Park, MD, United States)
Khabarov, Nikolay
(International Inst. for Applied Systems Analysis Laxenburg, Austria)
Lawrence, Peter
(National Center for Atmospheric Research Boulder, CO, United States)
Liu, Wenfeng
(Swiss Federal Inst. of Aquatic Science and Technology Dubendorf, Switzerland)
Olin, Stefan
(Lund Univ. Sweden)
Pugh, Thomas A. M.
(Birmingham Univ. United Kingdom)
Ray, Deepak K.
(Minnesota Univ. Saint Paul, MN, United States)
Reddy, Ashwan
(Maryland Univ. College Park, MD, United States)
Rosenzweig, Cynthia
(NASA Goddard Inst. for Space Studies New York, NY United States)
Ruane, Alex C.
(NASA Goddard Inst. for Space Studies New York, NY United States)
Sakurai, Gen
(National Agriculture and Food Research Organization Tsukuba, Japan)
Schmid, Erwin
(University for Natural Resources and Applied Life Sciences Vienna, Austria)
Skalsky, Rastislav
(International Inst. for Applied Systems Analysis Laxenburg, Austria)
Date Acquired
April 17, 2017
Publication Date
April 4, 2017
Publication Information
Publication: Geoscientific Model Development
Publisher: Copernicus Publications
Volume: 10
Issue: 4
ISSN: 1991-9603
Subject Category
Meteorology And Climatology
Statistics And Probability
Report/Patent Number
GSFC-E-DAA-TN41474
Distribution Limits
Public
Copyright
Other
Keywords
wheat
performance
crop models
global gridded crop model
rice
crop yield simulations
soybean
maize

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