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Crop models capture the impacts of climate variability on corn yield
Author(s) -
Niyogi Dev,
Liu Xing,
Andresen Jeff,
Song Yang,
Jain Atul K.,
Kellner Olivia,
Takle Eugene S.,
Doering Otto C.
Publication year - 2015
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1002/2015gl063841
Subject(s) - crop , crop yield , yield (engineering) , environmental science , climate model , climatology , el niño southern oscillation , climate change , crop simulation model , agronomy , geology , ecology , biology , materials science , metallurgy
Abstract We investigate the ability of three different crop models of varying complexity for capturing El Niño–Southern Oscillation‐based climate variability impacts on the U.S. Corn Belt (1981–2010). Results indicate that crop models, irrespective of their complexity, are able to capture the impacts of climate variability on yield. Multiple‐model ensemble analysis provides best results. There was no significant difference between using on‐site and gridded meteorological data sets to drive the models. These results highlight the ability of using simpler crop models and gridded regional data sets for crop‐climate assessments.