Crop model improvement reduces the uncertainty of the response to temperature of multi-model ensembles
Andrea Maiorano
(1)
,
Pierre Martre
(1)
,
Senthold Asseng
(2)
,
Frank Ewert
(3)
,
Christoph Müller
(4)
,
Reimund P. Rotter
(5)
,
Alex C. Ruane
(6)
,
Mikhail A. Semenov
(7)
,
Daniel D. Wallach
(8)
,
Enli Wang
(9)
,
Phillip D. Alderman
(10)
,
Belay T. Kassie
(2)
,
Christian Biernath
(11)
,
Bruno Basso
(12)
,
Davide Cammarano
(2, 13)
,
Andrew J. Challinor
(14, 15)
,
Jordi Doltra
(16)
,
Benjamin Dumont
(17)
,
Ehsan Eyshi Rezaei
(3, 18)
,
Sebastian Gayler
(19)
,
Kurt Christian Kersebaum
(20)
,
Bruce A. Kimball
(21)
,
Ann-Kristin Koehler
(14)
,
Bin Liu
(22)
,
Garry O'Leary
(23)
,
Jørgen E. Olesen
(24)
,
Michael J. Ottman
(25)
,
Eckart Priesack
(11)
,
Matthew Reynolds
(10)
,
Pierre Stratonovitch
(7)
,
Thilo Streck
(19)
,
Peter J. Thorburn
(9)
,
Katharina Waha
(9, 4)
,
Gerard W. Wall
(21)
,
Jeffrey W. White
(26)
,
Zhigan Zhao
(9, 27)
,
Yan Zhu
(22)
1
LEPSE -
Écophysiologie des Plantes sous Stress environnementaux
2 UF|ABE - Department of Agricultural and Biological Engineering [Gainesville]
3 Institute of Crop Science and Resource Conservation [Bonn]
4 PIK - Potsdam Institute for Climate Impact Research
5 Environmental Impacts Group
6 GISS - NASA Goddard Institute for Space Studies
7 Computational and Systems Biology Department, Rothamsted Research
8 AGIR - AGroécologie, Innovations, teRritoires
9 CSIRO - Commonwealth Scientific and Industrial Research Organisation [Canberra]
10 CIMMYT - International Maize and Wheat Improvement Center
11 Institute of Biochemical Plant Pathology
12 Michigan State University [East Lansing]
13 The James Hutton Institute
14 University of Leeds
15 CGIAR-ESSP Program on Climate Change,Agriculture and Food Security
16 CIFA - Catabrian Agricultural Research and Training Center
17 Department of Geological Sciences and W. K. Kellogg Biological Station
18 Center for Development Research (ZEF)
19 Institute of Soil Science and Land Evaluation
20 ZALF - Leibniz-Zentrum für Agrarlandschaftsforschung
21 US Arid-Land Agricultural Research Center
22 NAU - Nanjing Agricultural University
23 Landscape & Water Sciences
24 Department of Agroecology
25 The School of Plant Sciences
26 USDA-ARS, Arid-Land Agricultural Research Center
27 CAU - China Agricultural University
2 UF|ABE - Department of Agricultural and Biological Engineering [Gainesville]
3 Institute of Crop Science and Resource Conservation [Bonn]
4 PIK - Potsdam Institute for Climate Impact Research
5 Environmental Impacts Group
6 GISS - NASA Goddard Institute for Space Studies
7 Computational and Systems Biology Department, Rothamsted Research
8 AGIR - AGroécologie, Innovations, teRritoires
9 CSIRO - Commonwealth Scientific and Industrial Research Organisation [Canberra]
10 CIMMYT - International Maize and Wheat Improvement Center
11 Institute of Biochemical Plant Pathology
12 Michigan State University [East Lansing]
13 The James Hutton Institute
14 University of Leeds
15 CGIAR-ESSP Program on Climate Change,Agriculture and Food Security
16 CIFA - Catabrian Agricultural Research and Training Center
17 Department of Geological Sciences and W. K. Kellogg Biological Station
18 Center for Development Research (ZEF)
19 Institute of Soil Science and Land Evaluation
20 ZALF - Leibniz-Zentrum für Agrarlandschaftsforschung
21 US Arid-Land Agricultural Research Center
22 NAU - Nanjing Agricultural University
23 Landscape & Water Sciences
24 Department of Agroecology
25 The School of Plant Sciences
26 USDA-ARS, Arid-Land Agricultural Research Center
27 CAU - China Agricultural University
Pierre Martre
- Fonction : Auteur
- PersonId : 183362
- IdHAL : pierre-martre
- ORCID : 0000-0002-7419-6558
- IdRef : 163589194
Frank Ewert
- Fonction : Auteur
- PersonId : 968227
Christoph Müller
- Fonction : Auteur
- PersonId : 772079
- ORCID : 0000-0003-2234-6902
Mikhail A. Semenov
- Fonction : Auteur
- PersonId : 774453
- ORCID : 0000-0002-1561-7113
Davide Cammarano
- Fonction : Auteur
- PersonId : 968228
Andrew J. Challinor
- Fonction : Auteur
- PersonId : 968229
Yan Zhu
- Fonction : Auteur
- PersonId : 768149
- ORCID : 0000-0001-7342-3782
- IdRef : 120749734
Résumé
To 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.