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See detailAnalysis of GNSS sensed slant wet delay during severe weather events in central Europe
Hunegnaw, Addisu UL; Duman, Hüseyin; Elgered, Gunnar et al

Scientific Conference (2022, May 26)

Over the last few decades, anthropogenic greenhouse gas emissions have increased the frequency of climatological anomalies such as temperature, precipitation, and evapotranspiration. It is noticed that ... [more ▼]

Over the last few decades, anthropogenic greenhouse gas emissions have increased the frequency of climatological anomalies such as temperature, precipitation, and evapotranspiration. It is noticed that the frequency and severity of the intense precipitation signify a greater susceptibility to flash flooding. Flash flooding continues to be a major threat to European cities, with devastating mortality and considerable damage to urban infrastructure. As a result, accurate forecasting of future extreme precipitation events is critical for natural hazard mitigation. A network of ground-based GNSS receivers enables the measurement of integrated water vapour along slant pathways providing three-dimensional water vapour distributions. This study aims to demonstrate how GNSS sensing of the troposphere can be used to monitor the rapid and extreme weather events that occurred in central Europe in June 2013 and resulted in flash floods and property damage. We recovered one-way slant wet delay (SWD) by adding GNSS post-fit phase residuals, representing the troposphere's higher-order inhomogeneity. Nonetheless, noise in the GNSS phase observable caused by site-specific multipath can significantly affect the SWD from individual satellites. To overcome the problem, we employ a suitable averaging strategy for stacking post-fit phase residuals obtained from the PPP processing strategy to generate site-specific multipath corrections maps (MPS). The spatial stacking is carried out in congruent cells with an optimal resolution in elevation and azimuth at the local horizon but with decreasing azimuth resolution as the elevation angle increases. This permits an approximately equal number of observations allocated to each cell. The spatio-temporal fluctuations in the SWD as measured by GNSS closely mirrored the moisture field associated with severe weather events in central Europe, i.e., a brief rise prior to the main rain events, followed by a rapid decline once the storms passed. Furthermore, we validated the one-way SWD between ground-based water-vapour radiometry (WVR) and GNSS-derived SWD for different elevation angles. [less ▲]

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See detailMulti-GNSS Slant Wet Delay Retrieval Using Multipath Mitigation Maps
Hunegnaw, Addisu UL; Ejigu, Yohannes Getachew; Teferle, Felix Norman UL et al

Scientific Conference (2021, April 24)

The conventional Global Navigation Satellite System (GNSS) processing is typically contaminated with errors due to atmospheric variabilities, such as those associated with the mesoscale phenomena. These ... [more ▼]

The conventional Global Navigation Satellite System (GNSS) processing is typically contaminated with errors due to atmospheric variabilities, such as those associated with the mesoscale phenomena. These errors are manifested in the parameter estimates, including station coordinates and atmospheric products. To enhance the accuracy of these GNSS products further, a better understanding of the local-scale atmospheric variability is necessary. As part of multi-GNSS processing, station coordinates, carrier phase ambiguities, orbits, zenith total delay (ZTD) and horizontal gradients are the main parameters of interest. Here, ZTD is estimated as the average zenith delay along the line-of-sight to every observed GNSS satellite mapped to the vertical while the horizontal gradients are estimated in NS and EW directions and provide a means to partly account for the azimuthally inhomogeneous atmosphere. However, a better atmospheric description is possible by evaluating the slant path delay (SPD) or slant wet delay (SWD) along GNSS ray paths, which are not resolved by ordinary ZTD and gradient analysis. SWD is expected to provide better information about the inhomogeneous distribution of water vapour that is disregarded when retrieving ZTD and horizontal gradients. Usually, SWD cannot be estimated directly from GNSS processing as the number of unknown parameters exceeds the number of observations. Thus, SWD is generally calculated from ZTD for each satellite and may be dominated by un-modelled atmospheric delays, clock errors, unresolved carrier-phase ambiguities and near-surface multipath scattering. In this work, we have computed multipath maps by stacking individual post-fit carrier residuals incorporating the signals from four GNSS constellations, i.e. BeiDou, Galileo, Glonass and GPS. We have selected a subset of global International GNSS Service (IGS) stations capable of multi-GNSS observables located in different climatic zones. The multipath effects are reduced by subtracting the stacked multipath maps from the raw post-fit carrier phase residuals. We demonstrate that the multipath stacking technique results in significantly reduced variations in the one-way post-fit carrier phase residuals. This is particularly evident for lower elevation angles, thus, producing a retrieval method for SWD that is less affected by site-specific multipath effects. We show a positive impact on SWD estimation using our multipath maps during increased atmospheric inhomogeneity as induced by severe weather events. [less ▲]

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See detailMultipath Mitigation Maps feasibility and applicability as an International GNSS Service product
Hunegnaw, Addisu UL; Teferle, Felix Norman UL; Elgered, Gunnar et al

Scientific Conference (2020, December 17)

There have been many advances in the modeling of Global Navigation Satellite System (GNSS) observables when estimating position and other parameters of interest. Some of these bias models are related to ... [more ▼]

There have been many advances in the modeling of Global Navigation Satellite System (GNSS) observables when estimating position and other parameters of interest. Some of these bias models are related to improvements of reference frames, phase center offsets and variations of transmitter and receiver antennas, satellite orbits and clocks, and troposphere. Nonetheless, multipath remains for the most part an unmodelled source of error which causes range errors in the GNSS observations. The associated effects show highly localized features and have a different impact for each receiver and antenna. Multipath errors can propagate, can cause in-situ position biases and are also contributing to the prevalent draconitic harmonic signals. In order to mitigate the problem we generate site-specific corrections by employing a suitable averaging scheme for the stacking of carrier phase residuals. Our processing is based on globally distributed static multi-GNSS observations using several scientific GNSS software packages (Bernese GNSS Software, NAPEOS, GAMIT-GLOBK, and CSRS-PPP). Our multipath stacking maps (MPS) use the stacking of carrier phase residuals generated by variable azimuth cell size (congruent cells) and by allocating carrier phase residuals in each cell to generate the correction maps, unlike the standard fixed azimuth cell resolution approaches. This reduces the binning of fewer residuals at higher elevation angles. Before stacking, we also apply rigorous statistical outlier screening tests for each one-way post-fit carrier phase residual assigned to each of the congruent cells. We thus correct the multipath effects by subtracting the stacked multipath map from the post-fit carrier phase residual. Using this technique we produce a model available in the form of the Antenna Exchange (ANTEX) file format, that can potentially be implemented in routine GNSS analysis with no or little additional overhead for individual analysis centers (ACs). In this study, we assess the feasibility and applicability of the MPS maps as an International GNSS Service (IGS) product for routine GNSS analysis. We demonstrate the multipath stacking technique to result in a significant reduction of the variation in the one-way post-fit carrier phase residuals from multi-GNSS observations. [less ▲]

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