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Title:

Evaluation of crop model prediction and uncertainty using Bayesian parameter estimation and Bayesian model averaging

Document type:
Zeitschriftenaufsatz
Author(s):
Gao, Yujing; Wallach, Daniel; Hasegawa, Toshihiro; Tang, Liang; Zhang, Ruoyang; Asseng, Senthold; Kahveci, Tamer; Liu, Leilei; He, Jianqiang; Hoogenboom, Gerrit
Abstract:
A recent trend in crop modeling has been the use of multi-model ensembles (MMEs) for impact assessment, especially as it relates to climate change. Studies have shown that, compared to individual models, the mean or median of a MME is a better predictor that is more accurate in making predictions and capable of providing model uncertainty information. In previous studies that used MMEs, each individual model was assigned an equal weight by simply averaging the predictions over all the models. He...     »
Keywords:
Crop models, Multi-model ensemble, MCMC, Reliability diagram, Model weighting
Journal title:
Agricultural and Forest Meteorology
Year:
2021
Journal volume:
311
Pages contribution:
108686
Fulltext / DOI:
doi:https://doi.org/10.1016/j.agrformet.2021.108686
WWW:
https://www.sciencedirect.com/science/article/pii/S0168192321003725
Print-ISSN:
0168-1923
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