Articles | Volume 22, issue 1
Nat. Hazards Earth Syst. Sci., 22, 23–40, 2022
https://doi.org/10.5194/nhess-22-23-2022
Nat. Hazards Earth Syst. Sci., 22, 23–40, 2022
https://doi.org/10.5194/nhess-22-23-2022
Research article
05 Jan 2022
Research article | 05 Jan 2022

Evaluation of Mei-yu heavy-rainfall quantitative precipitation forecasts in Taiwan by a cloud-resolving model for three seasons of 2012–2014

Chung-Chieh Wang et al.

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2020-397', Anonymous Referee #1, 15 Mar 2021
  • CC1: 'Comment on nhess-2020-397', G. T.-J. Chen, 19 Mar 2021
  • RC2: 'Comment on nhess-2020-397', Anonymous Referee #2, 16 Jul 2021

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (further review by editor and referees) (03 Sep 2021) by Joaquim G. Pinto
AR by Pi-Yu Chuang on behalf of the Authors (06 Sep 2021)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (07 Sep 2021) by Joaquim G. Pinto
RR by Anonymous Referee #1 (17 Sep 2021)
RR by Anonymous Referee #2 (22 Sep 2021)
ED: Reconsider after major revisions (further review by editor and referees) (04 Oct 2021) by Joaquim G. Pinto
AR by Pi-Yu Chuang on behalf of the Authors (10 Oct 2021)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (13 Oct 2021) by Joaquim G. Pinto
RR by Anonymous Referee #2 (28 Oct 2021)
ED: Publish subject to minor revisions (review by editor) (15 Nov 2021) by Joaquim G. Pinto
AR by Pi-Yu Chuang on behalf of the Authors (16 Nov 2021)  Author's response    Author's tracked changes    Manuscript
ED: Publish as is (22 Nov 2021) by Joaquim G. Pinto
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Short summary
This study indicated that the Cloud-Resolving Storm Simulator (CReSS) model significantly improved heavy-rainfall quantitative precipitation forecasts in the Taiwan Mei-yu season. At high resolution, the model has higher threat scores and is more skillful in predicting larger rainfall events compared to smaller ones. And the strength of the model mainly lies in the topographic rainfall rather than less predictable and migratory events due to nonlinearity.
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