Articles | Volume 16, issue 13
Development and technical paper
06 Jul 2023
Development and technical paper |  | 06 Jul 2023

Data assimilation sensitivity experiments in the East Auckland Current system using 4D-Var

Rafael Santana, Helen Macdonald, Joanne O'Callaghan, Brian Powell, Sarah Wakes, and Sutara H. Suanda


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CEC1: 'Comment on gmd-2022-270', Astrid Kerkweg, 28 Nov 2022
    • AC1: 'Reply on CEC1', Rafael Santana, 29 Nov 2022
  • RC1: 'Comment on gmd-2022-270', Srinivasa Ramanujam Kannan, 22 Dec 2022
    • AC2: 'Reply on RC1', Rafael Santana, 24 Apr 2023
  • RC2: 'Comment on gmd-2022-270', Anonymous Referee #2, 26 Jan 2023
    • AC3: 'Reply on RC2', Rafael Santana, 24 Apr 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Rafael Santana on behalf of the Authors (24 Apr 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (03 May 2023) by Deepak Subramani
RR by Anonymous Referee #2 (16 May 2023)
ED: Publish subject to minor revisions (review by editor) (17 May 2023) by Deepak Subramani
AR by Rafael Santana on behalf of the Authors (24 May 2023)  Author's tracked changes   Manuscript 
EF by Sarah Buchmann (26 May 2023)  Author's response 
ED: Publish as is (31 May 2023) by Deepak Subramani
AR by Rafael Santana on behalf of the Authors (01 Jun 2023)
Short summary
We show the importance of assimilating subsurface temperature and velocity data in a model of the East Auckland Current. Assimilation of velocity increased the representation of large oceanic vortexes. Assimilation of temperature is needed to correctly simulate temperatures around 100 m depth, which is the most difficult region to simulate in ocean models. Our simulations showed improved results in comparison to the US Navy global model and highlight the importance of regional models.