Reference : Crop model improvement reduces the uncertainty of the response to temperature of mult...
Scientific journals : Article
Life sciences : Environmental sciences & ecology
Engineering, computing & technology : Computer science
Life sciences : Agriculture & agronomy
Crop model improvement reduces the uncertainty of the response to temperature of multi-model ensembles
Maiorano, Andrea [> >]
Martre, Pierre [> >]
Asseng, Senthold [> >]
Ewert, Frank [> >]
Müller, Christoph [> >]
Rötter, Reimund P. [> >]
Ruane, Alex C. [> >]
Semenov, Mikhail A. [> >]
Wallach, Daniel [> >]
Wang, Enli [> >]
Alderman, Phillip D. [> >]
Kassie, Belay T. [> >]
Biernath, Christian [> >]
Basso, Bruno [> >]
Cammarano, Davide [> >]
Challinor, Andrew J. [> >]
Doltra, Jordi [> >]
Dumont, Benjamin mailto [Université de Liège > Agronomie, Bio-ingénierie et Chimie (AgroBioChem) > Phytotechnie des régions tempérées > >]
Rezaei, Ehsan Eyshi [> >]
Gayler, Sebastian [> >]
Kersebaum, Kurt Christian [> >]
Kimball, Bruce A. [> >]
Koehler, Ann-Kristin [> >]
Liu, Bing [> >]
O’Leary, Garry J. [> >]
Olesen, Jørgen E. [> >]
Ottman, Michael J. [> >]
Priesack, Eckart [> >]
Reynolds, Matthew [> >]
Stratonovitch, Pierre [> >]
Streck, Thilo [> >]
Thorburn, Peter J. [> >]
Waha, Katharina [> >]
Wall, Gerard W. [> >]
White, Jeffrey W. [> >]
Zhao, Zhigan [> >]
Zhu, Yan [> >]
Field Crops Research
Elsevier Science
In press
Yes (verified by ORBi)
[en] Impact uncertainty
[en] o improve climate change impact estimates and to quantify their uncertainty, multi-model ensembles (MMEs) have been suggested. Model improvements can improve the accuracy of simulations and reduce the uncertainty of climate change impact assessments. Furthermore, they can reduce the number of models needed in a MME. Herein, 15 wheat growth models of a larger MME were improved through re-parameterization and/or incorporating or modifying heat stress effects on phenology, leaf growth and senescence, biomass growth, and grain number and size using detailed field experimental data from the USDA Hot Serial Cereal experiment (calibration data set). Simulation results from before and after model improvement were then evaluated with independent field experiments from a CIMMYT world-wide field trial network (evaluation data set). Model improvements decreased the variation (10th to 90th model ensemble percentile range) of grain yields simulated by the MME on average by 39% in the calibration data set and by 26% in the independent evaluation data set for crops grown in mean seasonal temperatures >24 °C. MME mean squared error in simulating grain yield decreased by 37%. A reduction in MME uncertainty range by 27% increased MME prediction skills by 47%. Results suggest that the mean level of variation observed in field experiments and used as a benchmark can be reached with half the number of models in the MME. Improving crop models is therefore important to increase the certainty of model-based impact assessments and allow more practical, i.e. smaller MMEs to be used effectively.
UE - Union Européenne ; INRA - Institut National de la Recherche Agronomique ; IFPRI - International Food Policy Research Institute ; BMBF - Federal Ministry of Education and Research ; Federal Ministry of Economic Co-operation and Development ; CSIRO - Commonwealth Scientific and Industrial Research Organisation
AgreenSkills fellowship grant agreement no. PCOFUND-GA-2010-267196; AAFCCE - Adaptation of Agriculture and Forests to Climate Change. FACCE JPI MACSUR project (031A103B); FACCE MACSUR project (031A103B); PARI Project; Advancing crop yield while reducing the use of water andnitrogen Project; KULUNDA project(01LL0905L); MACMIT project (01LN1317A); FACCE MACSUR project; CCAFS - CGIAR Research Program on ClimateChange, Agriculture, and Food Security; Helmholtz project ‘REKLIM-Regional Climate Change:Causes and Effects; 20:20Wheat Programme
CIMMYT - International Maize and Wheat Improvement Center
Researchers ; Professionals ; Students
The final version of the article can be accessed at following URL :
FP7 ; 609405 - COFUNDPOSTDOCDTU - HC Ørsted Postdoc, cofunded by Marie Curie Actions

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