Articles | Volume 31, issue 1
Research article
21 Feb 2024
Research article |  | 21 Feb 2024

Extraction of periodic signals in Global Navigation Satellite System (GNSS) vertical coordinate time series using the adaptive ensemble empirical modal decomposition method

Weiwei Li and Jing Guo


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on npg-2023-23', Anonymous Referee #1, 19 Nov 2023
    • AC1: 'Reply on RC1', Weiwei Li, 19 Dec 2023
  • RC2: 'Comment on npg-2023-23', Anonymous Referee #2, 27 Nov 2023
    • AC2: 'Reply on RC2', Weiwei Li, 19 Dec 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Weiwei Li on behalf of the Authors (20 Dec 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (29 Dec 2023) by Norbert Marwan
RR by Anonymous Referee #2 (06 Jan 2024)
ED: Publish subject to technical corrections (08 Jan 2024) by Norbert Marwan
AR by Weiwei Li on behalf of the Authors (13 Jan 2024)  Manuscript 
Short summary
Improper handling of missing data and offsets will affect the accuracy of a signal of interest. The trend in GNSS belonging to GLOSS is key to getting the absolute sea level. However, this is affected by the periodic signals that are included. Although adaptive EEMD is capable of extracting periodic signals, missing data and offsets are ignored in previous work. Meanwhile, the time-varying periodic characteristics derived by adaptive EEMD are more conducive to analyzing the driving factors.