Articles | Volume 28, issue 2
Research article
31 Jan 2024
Research article |  | 31 Jan 2024

Simulating sub-hourly rainfall data for current and future periods using two statistical disaggregation models: case studies from Germany and South Korea

Ivan Vorobevskii, Jeongha Park, Dongkyun Kim, Klemens Barfus, and Rico Kronenberg


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2023-108', Anonymous Referee #1, 21 Jun 2023
    • AC1: 'Reply on RC1', Ivan Vorobevskii, 12 Sep 2023
  • RC2: 'Comment on hess-2023-108', Anonymous Referee #2, 18 Aug 2023
    • AC2: 'Reply on RC2', Ivan Vorobevskii, 12 Sep 2023

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) (24 Sep 2023) by Roberto Greco
AR by Ivan Vorobevskii on behalf of the Authors (20 Oct 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (03 Nov 2023) by Roberto Greco
RR by Anonymous Referee #2 (13 Nov 2023)
RR by Anonymous Referee #1 (06 Dec 2023)
ED: Publish subject to technical corrections (14 Dec 2023) by Roberto Greco
AR by Ivan Vorobevskii on behalf of the Authors (18 Dec 2023)  Manuscript 
Short summary
High-resolution precipitation data are often a “must” as input for hydrological and hydraulic models (i.e. urban drainage modelling). However, station or climate projection data usually do not provide the required (e.g. sub-hourly)  resolution. In the work, we present two new statistical models of different types to disaggregate precipitation from a daily to a 10  min scale. Both models were validated using radar data and then applied to climate models for 10 stations in Germany and South Korea.