4DVAR assimilation of GNSS zenith path delays and precipitable water into a numerical weather prediction model WRF

Rohm, Witold; Guzikowski, Jakub; Wilgan, Karina; Kryza, Maciej

doi:https://doi.org/10.5194/amt-12-345-2019

Articles | Volume 12, issue 1

https://doi.org/10.5194/amt-12-345-2019

© Author(s) 2019. 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/amt-12-345-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 12, issue 1

Research article

|

18 Jan 2019

Research article |

| 18 Jan 2019

4DVAR assimilation of GNSS zenith path delays and precipitable water into a numerical weather prediction model WRF

Witold Rohm, Jakub Guzikowski, Karina Wilgan, and Maciej Kryza

Download

Final revised paper (published on 18 Jan 2019)
Preprint (discussion started on 17 Aug 2018)

Interactive discussion

Status: closed

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

- Printer-friendly version

- Supplement

RC1: 'Reviewers comments on paper', Anonymous Referee #1, 27 Aug 2018
- AC1: 'Response to the 1# Reviewer comments', Witold Rohm, 24 Nov 2018
RC2: 'Review: Witold Rohm et al. "4DVAR assimilation of GNSS zenith path delays and precipitable water into a numerical weather prediction model WRF"', Anonymous Referee #2, 13 Sep 2018
- AC2: 'Response to the 2# Reviewer comments', Witold Rohm, 24 Nov 2018

Peer-review completion

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

AR by Witold Rohm on behalf of the Authors (10 Dec 2018) Author's response Manuscript

ED: Publish as is (11 Dec 2018) by Jonathan Jones

AR by Witold Rohm on behalf of the Authors (21 Dec 2018) Author's response Manuscript

Short summary

Assimilation of satellite navigation data into a popular weather model is yet another example of how to turn non-meteorological data into valuable information about the current state of the troposphere. Results show that observations from ground-based GPS receivers can improve humidity and rain forecasts in most severe weather events. It is another reason to extend the adoption of GPS data into weather forecasting across Europe.