Articles | Volume 17, issue 4
Research article
26 Aug 2021
Research article |  | 26 Aug 2021

Can assimilation of satellite observations improve subsurface biological properties in a numerical model? A case study for the Gulf of Mexico

Bin Wang, Katja Fennel, and Liuqian Yu


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on os-2021-35', Anonymous Referee #1, 25 May 2021
  • RC2: 'Comment on os-2021-35', Anonymous Referee #2, 28 May 2021
  • RC3: 'Comment on os-2021-35', Anonymous Referee #3, 04 Jun 2021
  • RC4: 'Comment on os-2021-35', Anonymous Referee #4, 18 Jun 2021

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Bin Wang on behalf of the Authors (09 Jul 2021)  Author's response    Author's tracked changes    Manuscript
ED: Publish subject to technical corrections (27 Jul 2021) by Paolo Lazzari
AR by Bin Wang on behalf of the Authors (30 Jul 2021)  Author's response    Manuscript
Short summary
We demonstrate that even sparse BGC-Argo profiles can substantially improve biogeochemical prediction via a priori model tuning. By assimilating satellite surface chlorophyll and physical observations, subsurface distributions of physical properties and nutrients were improved immediately. The improvement of subsurface chlorophyll was modest initially but was greatly enhanced after adjusting the parameterization for light attenuation through further a priori tuning.