Data assimilation of GNSS zenith total delays from a Nordic processing centre

Lindskog, Magnus; Ridal, Martin; Thorsteinsson, Sigurdur; Ning, Tong

doi:https://doi.org/10.5194/acp-17-13983-2017

Articles | Volume 17, issue 22

https://doi.org/10.5194/acp-17-13983-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Advanced Global Navigation Satellite Systems tropospheric...

https://doi.org/10.5194/acp-17-13983-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 17, issue 22

Research article

|

24 Nov 2017

Research article |

| 24 Nov 2017

Data assimilation of GNSS zenith total delays from a Nordic processing centre

Magnus Lindskog, Martin Ridal, Sigurdur Thorsteinsson, and Tong Ning

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Final revised paper (published on 24 Nov 2017)
Preprint (discussion started on 01 Aug 2017)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Review of Lindskog et al acp-2017-567', Anonymous Referee #1, 08 Aug 2017
- AC1: 'Response to Reviewer I comments', Magnus Lindskog, 05 Sep 2017
RC2: 'Review of acp-2017-567: Data assimilation of GNSS Zenith Total Delays from a Nordic processing centre, by Magnus Lindskog, Martin Ridal, Sigurdur Thorsteinsson, and Tong Ning', Anonymous Referee #2, 11 Aug 2017
- AC2: 'Response to Reviewer II comments', Magnus Lindskog, 05 Sep 2017

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Magnus Lindskog on behalf of the Authors (27 Sep 2017) Manuscript

ED: Publish as is (11 Oct 2017) by Jonathan Jones

AR by Magnus Lindskog on behalf of the Authors (11 Oct 2017) Manuscript

Short summary

Atmospheric moisture-related information obtained from Global Navigation Satellite System (GNSS) observations from ground-based receiver stations of the Nordic GNSS Analysis Centre (NGAA) has been used within a state-of-the-art kilometre-scale numerical weather prediction system. The sensitivity of results to aspects of the data processing, observation density, bias-correction and data assimilation has been investigated. Results show a benefit on forecast quality of using GNSS ZTD.