Articles | Volume 30, issue 1
Research article
07 Feb 2023
Research article |  | 07 Feb 2023

Extending ensemble Kalman filter algorithms to assimilate observations with an unknown time offset

Elia Gorokhovsky and Jeffrey L. Anderson


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-536', Anonymous Referee #1, 16 Aug 2022
  • RC2: 'Comment on egusphere-2022-536', Anonymous Referee #2, 20 Aug 2022
  • AC1: 'Comment on egusphere-2022-536', Elia Gorokhovsky, 19 Oct 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Elia Gorokhovsky on behalf of the Authors (19 Oct 2022)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (17 Nov 2022) by Amit Apte
RR by Anonymous Referee #1 (23 Nov 2022)
RR by Anonymous Referee #2 (12 Dec 2022)
ED: Publish subject to technical corrections (09 Jan 2023) by Amit Apte
AR by Elia Gorokhovsky on behalf of the Authors (15 Jan 2023)  Author's response   Manuscript 
Short summary
Older observations of the Earth system sometimes lack information about the time they were taken, posing problems for analyses of past climate. To begin to ameliorate this problem, we propose new methods of varying complexity, including methods to estimate the distribution of the offsets between true and reported observation times. The most successful method accounts for the nonlinearity in the system, but even the less expensive ones can improve data assimilation in the presence of time error.