@article{fdi:010065439,
  title = {{E}mulating maize yields from global gridded crop models using statistical estimates},
  author = {{B}lanc, {E}. and {S}ultan, {B}enjamin},
  editor = {},
  language = {{ENG}},
  abstract = {{T}his study estimates statistical models emulating maize yield responses to changes in temperature and precipitation simulated by global gridded crop models. {W}e use the unique and newly released {I}nter-{S}ectoral {I}mpact {M}odel {I}ntercomparison {P}roject {F}ast {T}rack ensemble of global gridded crop model simulations to build a panel of annual maize yields simulations from five crop models and corresponding monthly weather variables for over a century. {T}his dataset is then used to estimate statistical relationship between yields and weather variables for each crop model. {T}he statistical models are able to closely replicate both in- and out-of-sample maize yields projected by the crop models. {T}his study therefore provides simple tools to predict gridded changes in maize yields due to climate change at the global level. {B}y emulating crop yields for several models, the tools will be useful for climate change impact assessments and facilitate evaluation of crop model uncertainty.},
  keywords = {{C}rop yields ; {C}rop model ; {S}tatistical model ; {C}limate change ; {M}aize},
  booktitle = {},
  journal = {{A}gricultural and {F}orest {M}eteorology},
  volume = {214},
  numero = {},
  pages = {134--147},
  ISSN = {0168-1923},
  year = {2015},
  DOI = {10.1016/j.agrformet.2015.08.256},
  URL = {https://www.documentation.ird.fr/hor/fdi:010065439},
}