Parameterization-induced uncertainties and impacts of crop management harmonization in a global gridded crop model ensemble

Christian Folberth (1) , Joshua Elliott (2) , Christoph Müller (3) , Juraj Balkovič (4) , James Chryssanthacopoulos (5) , Roberto Izaurralde , Curtis Jones (6) , Nikolay Khabarov (7) , Wenfeng Liu , Ashwan Reddy (6) , Erwin Schmid (8) , Rastislav Skalsky (9) , Hong Yang , Almut Arneth (10) , Philippe Ciais (11, 12) , Delphine Deryng (13) , Peter Lawrence (14) , Stefan Olin (15) , Thomas A.M. Pugh (16) , Alex Ruane (17) , Xuhui Wang (18)

1 Department of Geography
2 University of Chicago
3 PIK - Potsdam Institute for Climate Impact Research
4 Ecosystem Services and Management Program
5 CCSR - Center for Climate Systems Research [New York]
6 Department of Geographical Sciences [College Park]
7 IIASA - International Institute for Applied Systems Analysis [Laxenburg]
8 BOKU - Universität für Bodenkultur Wien = University of Natural Resources and Life [Vienne, Autriche]
9 Soil Science and Conservation Research Institute
10 IMK-IFU - Institut für Meteorologie und Klimaforschung - Atmosphärische Umweltforschung
11 LSCE - Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette]
12 ICOS-ATC - ICOS-ATC
13 Tyndall Centre for Climate Change Research
14 GIMAP - Groupe Immunité des Muqueuses et Agents Pathogènes
15 Department of Physical Geography and Ecosystem Science
16 IMK - Institute for Meteorology and Climate Research
17 GISS - NASA Goddard Institute for Space Studies
18 LMD - Laboratoire de Météorologie Dynamique (UMR 8539)

Global gridded crop models (GGCMs) combine agronomic or plant growth models with gridded spatial input data to estimate spatially explicit crop yields and agricultural externali-ties at the global scale. Differences in GGCM outputs arise from the use of different biophys-ical models, setups, and input data. GGCM ensembles are frequently employed to bracket uncertainties in impact studies without investigating the causes of divergence in outputs. This study explores differences in maize yield estimates from five GGCMs based on the public domain field-scale model Environmental Policy Integrated Climate (EPIC) that participate in the AgMIP Global Gridded Crop Model Intercomparison initiative. Albeit using the same crop model, the GGCMs differ in model version, input data, management assumptions , parameterization, and selection of subroutines affecting crop yield estimates via culti-var distributions, soil attributes, and hydrology among others. The analyses reveal inter-annual yield variability and absolute yield levels in the EPIC-based GGCMs to be highly sensitive to soil parameterization and crop management. All GGCMs show an intermediate PLOS ONE | https://doi.org/10.1371/journal.pone.

Domaines: Océan, Atmosphère; Interfaces continentales, environnement

Christian Folberth, Joshua Elliott, Christoph Müller, Juraj Balkovič, James Chryssanthacopoulos, et al.. Parameterization-induced uncertainties and impacts of crop management harmonization in a global gridded crop model ensemble. PLoS ONE, 2019, 14 (9), pp.e0221862. ⟨10.1371/journal.pone.0221862⟩. ⟨hal-02899801⟩