Articles | Volume 26, issue 14
https://doi.org/10.5194/hess-26-3847-2022
https://doi.org/10.5194/hess-26-3847-2022
Research article
 | 
22 Jul 2022
Research article |  | 22 Jul 2022

Comparison between canonical vine copulas and a meta-Gaussian model for forecasting agricultural drought over China

Haijiang Wu, Xiaoling Su, Vijay P. Singh, Te Zhang, Jixia Qi, and Shengzhi Huang

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Latest update: 24 Jul 2024
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Short summary
Agricultural drought forecasting lies at the core of overall drought risk management and is critical for food security and drought early warning. Using three-dimensional scenarios, we attempted to compare the agricultural drought forecast performance of a canonical vine copula (3C-vine) model and meta-Gaussian (MG) model over China. The findings show that the 3C-vine model exhibits more skill than the MG model when using 1– to 3-month lead times for forecasting agricultural drought.