The GGCMI Phase 2 emulators: global gridded crop model responses to changes in CO2 temperature, water, and nitrogen (version 1.0) - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Geoscientific Model Development Année : 2020

The GGCMI Phase 2 emulators: global gridded crop model responses to changes in CO2 temperature, water, and nitrogen (version 1.0)

James Franke
  • Fonction : Auteur
Christoph Müller
Joshua Elliott
  • Fonction : Auteur
Alex Ruane
  • Fonction : Auteur
Jonas Jägermeyr
  • Fonction : Auteur
Abigail Snyder
  • Fonction : Auteur
Marie Dury
  • Fonction : Auteur
Pete Falloon
  • Fonction : Auteur
Christian Folberth
Louis François
  • Fonction : Auteur
Tobias Hank
  • Fonction : Auteur
R. Cesar Izaurralde
  • Fonction : Auteur
Ingrid Jacquemin
  • Fonction : Auteur
Curtis Jones
  • Fonction : Auteur
Michelle Li
  • Fonction : Auteur
Stefan Olin
Meridel Phillips
  • Fonction : Auteur
Thomas Pugh
  • Fonction : Auteur
Ashwan Reddy
  • Fonction : Auteur
Karina Williams
  • Fonction : Auteur
Ziwei Wang
  • Fonction : Auteur
Florian Zabel
  • Fonction : Auteur
Elisabeth Moyer
  • Fonction : Auteur

Résumé

Statistical emulation allows combining advantageous features of statistical and process-based crop models for understanding the effects of future climate changes on crop yields. We describe here the development of emulators for nine process-based crop models and five crops using output from the Global Gridded Model Intercomparison Project (GGCMI) Phase 2. The GGCMI Phase 2 experiment is designed with the explicit goal of producing a structured training dataset for emulator development that samples across four dimensions relevant to crop yields: atmospheric carbon dioxide (CO 2) concentrations, temperature, water supply , and nitrogen inputs (CTWN). Simulations are run under two different adaptation assumptions: that growing seasons shorten in warmer climates, and that cultivar choice allows growing seasons to remain fixed. The dataset allows emulating the climatological-mean yield response of all models with a simple polynomial in mean growing-season values. Climatological-mean yields are a central metric in climate change impact analysis; we show here that they can be captured without relying on interannual variations. In general , emulation errors are negligible relative to differences across crop models or even across climate model scenarios; errors become significant only in some marginal lands where crops are not currently grown. We demonstrate that the resulting GGCMI emulators can reproduce yields under realistic future climate simulations, even though the GGCMI Phase 2 dataset is constructed with uniform CTWN offsets, suggesting that the effects of changes in temperature and precipitation distributions are small relative to those of changing means. The resulting emulators therefore capture relevant crop model responses in a lightweight, computationally tractable form, providing a tool that can facilitate model comparison , diagnosis of interacting factors affecting yields, and integrated assessment of climate impacts.
Fichier principal
Vignette du fichier
gmd-13-3995-2020.pdf (6.3 Mo) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte
Loading...

Dates et versions

hal-02968695 , version 1 (19-10-2020)

Identifiants

Citer

James Franke, Christoph Müller, Joshua Elliott, Alex Ruane, Jonas Jägermeyr, et al.. The GGCMI Phase 2 emulators: global gridded crop model responses to changes in CO2 temperature, water, and nitrogen (version 1.0). Geoscientific Model Development, 2020, 13 (9), pp.3995-4018. ⟨10.5194/gmd-13-3995-2020⟩. ⟨hal-02968695⟩
36 Consultations
25 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More