Estimating the Impact of Global Navigation Satellite System Horizontal Delay Gradients in Variational Data Assimilation
1
GFZ German Research Centre for Geosciences, 14473 Potsdam, Germany
2
Geodetic Observatory Pecný, Research Institute of Geodesy, Topography and Cartography, Zdiby 250 66, Czech Republic
3
Department of Geoinformatics, VŠB – Technical University of Ostrava, Ostrava 708 33, Czech Republic
4
Institute of Geodesy and Geoinformation Science, Technical University of Berlin, 10623 Berlin, Germany
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(1), 41; https://doi.org/10.3390/rs11010041
Received: 26 November 2018 / Revised: 20 December 2018 / Accepted: 20 December 2018 / Published: 28 December 2018
(This article belongs to the Special Issue Selected Papers from IGL-1 2018 — First International Workshop on Innovating GNSS and LEO Occultations & Reflections for Weather, Climate and Space Weather)
We developed operators to assimilate Global Navigation Satellite System (GNSS) Zenith Total Delays (ZTDs) and horizontal delay gradients into a numerical weather model. In this study we experiment with refractivity fields derived from the Global Forecast System (GFS) available with a horizontal resolution of 0.5°. We begin our investigations with simulated observations. In essence, we extract the tropospheric parameters from the GFS analysis, add noise to mimic observation errors and assimilate the simulated observations into the GFS 24h forecast valid at the same time. We consider three scenarios: (1) the assimilation of ZTDs (2) the assimilation of horizontal delay gradients and (3) the assimilation of both ZTDs and horizontal delay gradients. The impact is measured by utilizing the refractivity fields. We find that the assimilation of the horizontal delay gradients in addition to the ZTDs improves the refractivity field around 800 hPa. When we consider a single station there is a clear improvement when horizontal delay gradients are assimilated in addition to the ZTDs because the horizontal delay gradients contain information that is not contained in the ZTDs. On the other hand, when we consider a dense station network there is not a significant improvement when horizontal delay gradients are assimilated in addition to the ZTDs because the horizontal delay gradients do not contain information that is not already contained in the ZTDs. Finally, we replace simulated by real observations, that is, tropospheric parameters from a Precise Point Positioning solution provided with the G-Nut/Tefnut software, in order to show that the GFS 24h forecast is indeed improved when GNSS horizontal delay gradients are assimilated in addition to GNSS ZTDs; for the considered station (Potsdam, Germany) and period (June and July, 2017) we find an improvement in the retrieved refractivity of up to 4%.
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
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MDPI and ACS Style
Zus, F.; Douša, J.; Kačmařík, M.; Václavovic, P.; Dick, G.; Wickert, J. Estimating the Impact of Global Navigation Satellite System Horizontal Delay Gradients in Variational Data Assimilation. Remote Sens. 2019, 11, 41.
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