English
 
Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

Global gridded crop models underestimate yield responses to droughts and heatwaves

Authors
/persons/resource/Stefanie.Heinicke

Heinicke,  Stefanie
Potsdam Institute for Climate Impact Research;

/persons/resource/Katja.Frieler

Frieler,  Katja
Potsdam Institute for Climate Impact Research;

/persons/resource/jonasjae

Jägermeyr,  Jonas
Potsdam Institute for Climate Impact Research;

/persons/resource/matthias.mengel

Mengel,  Matthias
Potsdam Institute for Climate Impact Research;

External Ressource
No external resources are shared
Fulltext (public)

26897oa.pdf
(Publisher version), 3MB

Supplementary Material (public)
There is no public supplementary material available
Citation

Heinicke, S., Frieler, K., Jägermeyr, J., Mengel, M. (2022): Global gridded crop models underestimate yield responses to droughts and heatwaves. - Environmental Research Letters, 17, 4, 044026.
https://doi.org/10.1088/1748-9326/ac592e


Cite as: https://publications.pik-potsdam.de/pubman/item/item_26897
Abstract
Extreme events can lead to crop yield declines, resulting in financial losses and threats to food security, and the frequency and intensity of such events is projected to increase. As global gridded crop models (GGCMs) are commonly used to assess climate change impacts on agricultural yields, there is a need to understand whether these models are able to reproduce the observed yield declines. We evaluated 13 GGCMs from the Inter-Sectoral Impact Model Intercomparison Project and compared observed and simulated impact of past droughts and heatwaves on yields for four crops (maize, rice, soy, wheat). We found that most models detect but underestimate the impact of droughts and heatwaves on yield. Specifically, the drought signal was detected by 12 of 13 models for maize and all models for wheat, while the heat signal was detected by eleven models for maize and six models for wheat. To investigate whether the difference between simulated and observed yield declines is due to a misrepresentation of simulated exposure to heat or water scarcity (i.e. misrepresentation of growing season), we analysed the relationship between average discrepancies between observed and simulated yield losses, and average simulated exposure to extreme weather conditions across all crop models. We found a positive correlation between simulated exposure to heat and model performance for heatwaves, but found no correlation for droughts. This suggests that there is a systematic underestimation of yield responses to heat and drought and not only a misrepresentation of exposure. Assuming that performance for the past indicates models' capacity to project future yield impacts, models likely underestimate future yield decline from climate change. High-quality temporally and spatially resolved observational data on growing seasons will be highly valuable to further improve crop models' capacity to adequately respond to extreme weather events.