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See detailOn the Application of Multipath Stacking Maps for Improved Severe Weather Tracking and Low-cost Antenna Calibration
Teferle, Felix Norman UL; Hunegnaw, Addisu UL; Duman, Hüseyin et al

Presentation (2022, July 07)

Modern cities all over the world are now more susceptible to flash floods as a result of a rise in the frequency and severity of meteorological events with significant precipitation. For minimizing the ... [more ▼]

Modern cities all over the world are now more susceptible to flash floods as a result of a rise in the frequency and severity of meteorological events with significant precipitation. For minimizing the risks due to these hydro-meteorological hazards, reliable fore- and now-casting of severe precipitation has become essential. Water vapor can be measured along slant paths by network of ground-based GNSS stations, providing real-time, three-dimensional (3D) distributions of vapor concentrations at an affordable cost. Consequently, these data provide an invaluable additional source of knowledge for monitoring and predicting events with flash flood potential. But site-specific multipath (MP) effects at GNSS stations do affect incoming signals, particularly at low elevations, as is widely known. The bulk of GNSS products for meteorology up to now are based on estimates of ordinary zenith total delay and horizontal gradients with little sensitivity to azimuthal variations, thus these products may not be best suited for estimating 3D distributions of water vapor during storm events. Using slant delays directly, can overcome this lack of azimuthal information. However, at low elevations, this approach is more susceptible to multipath errors. A thunderstorm event which occurred over Turkey and adjacent countries on July 27, 2017, resulting in flash floods and severe infrastructure damage, is used as an example to explore the effects of multipath-corrected slant wet delay (SWD) estimations on monitoring extreme weather events. To reconstruct the one-way SWD, we first added phase residuals derived from the GNSS one-way post-fit observations, which represent the anisotropic component of the SWD. This can also be interpreted as a higher order inhomogeneity component, which is not resolved by ordinary zenith or gradient products. For the generation of site-specific MP correction maps, we stacked the post-fit residuals derived from our Precise Point Positioning (PPP) processing strategy because the MP errors in the GNSS phase observables can adversely impact the SWD along the direction of individual satellites. The spatial stacking was performed in congruent cells as a function of elevation and azimuth. This enables each cell to receive roughly the same number of residuals, providing a better stacking result. The stacking of residuals for a single cell over several days allows the detection and reduction of systematic errors; random errors are minimal because the averaging is done over a suitably sufficient chosen time span. Finally, the one-way SWD were enhanced by applying these MP correction maps for the analysis of the meteorological event. Our study revealed that the anisotropic component contributed up to 11% of one-way SWD estimates. Furthermore, the spatio-temporal changes in SWD as derived from GNSS closely matched the moisture field from the ERA5 re-analysis linked to this weather event. As it turns out, the MP correction maps may also provide a “kind of calibration” for uncalibrated or low-cost GNSS antennas, even for those in mobile phones, as these devices are highly susceptible to MP errors. In turn, this would allow the application of low-cost sensors to accurately estimate SWD for severe weather monitoring in urban regions. [less ▲]

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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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