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

Download

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2021-599', Anonymous Referee #1, 28 Dec 2021
    • AC1: 'Reply on RC1', Haijiang Wu, 08 Jan 2022
  • RC2: 'Comment on hess-2021-599', Anonymous Referee #2, 24 Mar 2022
    • AC2: 'Reply on RC2', Haijiang Wu, 02 Apr 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
ED: Reconsider after major revisions (further review by editor and referees) (09 Apr 2022) by Carlo De Michele
AR by Haijiang Wu on behalf of the Authors (19 Apr 2022)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (04 May 2022) by Carlo De Michele
RR by Mohammad Nazeri Tahroudi (11 May 2022)
RR by Anonymous Referee #2 (18 May 2022)
ED: Publish subject to minor revisions (review by editor) (12 Jun 2022) by Carlo De Michele
AR by Haijiang Wu on behalf of the Authors (14 Jun 2022)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (06 Jul 2022) by Carlo De Michele
AR by Haijiang Wu on behalf of the Authors (07 Jul 2022)
Download
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.