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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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AMT | Articles | Volume 12, issue 9
Atmos. Meas. Tech., 12, 4829–4848, 2019
https://doi.org/10.5194/amt-12-4829-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue: Advanced Global Navigation Satellite Systems tropospheric...

Atmos. Meas. Tech., 12, 4829–4848, 2019
https://doi.org/10.5194/amt-12-4829-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 10 Sep 2019

Research article | 10 Sep 2019

Assimilation of GNSS tomography products into the Weather Research and Forecasting model using radio occultation data assimilation operator

Natalia Hanna et al.
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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer review completion
AR: Author's response | RR: Referee report | ED: Editor decision
AR by Natalia Hanna on behalf of the Authors (18 Jun 2019)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (11 Jul 2019) by Eric Pottiaux
RR by Anonymous Referee #1 (29 Jul 2019)
RR by Anonymous Referee #3 (13 Aug 2019)
ED: Publish subject to minor revisions (review by editor) (13 Aug 2019) by Eric Pottiaux
AR by Natalia Hanna on behalf of the Authors (16 Aug 2019)  Author's response    Manuscript
ED: Publish as is (21 Aug 2019) by Eric Pottiaux
Publications Copernicus
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Short summary
In the study, the potential of GNSS tomography as an important supplementary data source for numerical weather prediction models was examined. We used two GNSS tomography models (TUW, WUELS) in different configurations. The GNSS tomography outputs were assimilated into the WRF model using a radio occultation observations operator (non-standard approach). Promising results show improvement in the weather forecasting of relative humidity and temperature during heavy-precipitation events.
In the study, the potential of GNSS tomography as an important supplementary data source for...
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