Articles | Volume 14, issue 10
Atmos. Meas. Tech., 14, 6379–6394, 2021
https://doi.org/10.5194/amt-14-6379-2021
Atmos. Meas. Tech., 14, 6379–6394, 2021
https://doi.org/10.5194/amt-14-6379-2021

Research article 01 Oct 2021

Research article | 01 Oct 2021

A new zenith hydrostatic delay model for real-time retrievals of GNSS-PWV

Longjiang Li et al.

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2021-113', Anonymous Referee #1, 19 Jun 2021
    • AC1: 'Reply on RC1', Longjiang Li, 11 Aug 2021
    • AC3: 'Reply on RC1', Longjiang Li, 11 Aug 2021
  • RC2: 'Comment on amt-2021-113', Anonymous Referee #2, 18 Jul 2021
    • AC2: 'Reply on RC2', Longjiang Li, 11 Aug 2021
    • AC4: 'Reply on RC2', Longjiang Li, 11 Aug 2021

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Anna Wenzel on behalf of the Authors (13 Aug 2021)  Author's response
ED: Referee Nomination & Report Request started (22 Aug 2021) by Roeland Van Malderen
RR by Anonymous Referee #2 (23 Aug 2021)
ED: Publish as is (31 Aug 2021) by Roeland Van Malderen
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Short summary
The zenith hydrostatic delay (ZHD) derived from blind models are of low accuracy, especially in mid- and high-latitude regions. To address this issue, the ratio of the ZHD to zenith total delay (ZTD) is firstly investigated; then, based on the relationship between the ZHD and ZTD, a new ZHD model was developed using the back propagation artificial neural network (BP-ANN) method which took the ZTD as an input variable. The model outperforms blind models.