Articles | Volume 26, issue 14
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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Cited articles

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Aas, K., Czado, C., Frigessi, A., and Bakken, H.: Pair-copula constructions of multiple dependence, Insur. Math. Econ., 44, 182–198,, 2009. 
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Bell, B., Hersbach, H., Berrisford, P., Dahlgren, P., Horányi, A., Muñoz Sabater, J., Nicolas, J., Radu, R., Schepers, D., Simmons, A., Soci, C., and Thépaut, J.-N.: ERA5 monthly averaged data on single levels from 1950 to 1978 (preliminary version). Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set],!/dataset/reanalysis-era5-single-levels-monthly-means-preliminary-back-extension?tab=overview (last access: 14 May 2022), 2020. 
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.