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See detailOn Improving Slant Wet delays for Tracking Severe Weather Events: An evaluation During Two Storms in Europe
Teferle, Felix Norman UL; Hunegnaw, Addisu UL; Duman, Huseyin et al

Scientific Conference (2022, December 14)

Climate change has led to an increase in the frequency and severity of weather events with intense precipitation and, subsequently, a greater susceptibility of communities around the world to flash ... [more ▼]

Climate change has led to an increase in the frequency and severity of weather events with intense precipitation and, subsequently, a greater susceptibility of communities around the world to flash flooding. Networks of ground-based Global Navigation Satellite System (GNSS) stations enable the measurement of integrated water vapor along slant pathways, providing three-dimensional (3D) water vapor distributions at low-cost and in real-time. This makes these data a valuable complementary source of information for tracking storm events and predicting their paths. However, it is well established that residual modelling errors and multipath (MP) effects at GNSS stations do impact incoming signals, especially at low elevations and during storms when the atmospheric conditions change rapidly. Until now, the bulk of GNSS products for meteorology are estimates of the more conventional zenith total delays and horizontal gradients, but these products may not be most appropriate for determining 3D distributions of water vapor during convective storm events. In this study we investigate the impact of residual-phase-corrected and multipath-corrected slant wet delay (SWD) estimates on tracking extreme weather events using two events in Europe that led to flooding, damage to property and loss of life. We employed Precise Point Positioning (PPP) with integer ambiguity resolution to generate station-specific MP correction maps. The spatial stacking was 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. In our analysis we recovered the one-way SWD by adding GNSS post-fit phase residuals, representing the non-isotropic component of the SWD, i.e., the higher-order inhomogeneity. Using the derived MP maps in a final step, the one-way SWD were improved to employ them for the analysis of the weather event. Moreover, we validated the SWD between ground-based water-vapor radiometry and GNSS-derived SWD for different elevation angles. Furthermore, the spatio-temporal fluctuations in the SWD as measured by GNSS closely mirrored the moisture field from the ERA5 re-analysis associated with this severe weather event [less ▲]

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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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See detailCross-Evaluation of Surface Meteorological Data and GNSS-derived Water Vapor with Re-analysis Information for South Georgia Island, South Atlantic Ocean
Erkihune, Eshetu Nega UL; Teferle, Felix Norman UL; Hunegnaw, Addisu UL et al

Poster (2020, December 11)

As one of the most important components of the global hydrologic cycle, atmospheric water vapor shows significant variability in both space and time over a large range of scales. This variability results ... [more ▼]

As one of the most important components of the global hydrologic cycle, atmospheric water vapor shows significant variability in both space and time over a large range of scales. This variability results from the interactions of many different factors, including topography and the presence of specific atmospheric processes. One of the key regions for affecting global climatic variations lies in the sub-Antarctic zone over the Southern Ocean with its Antarctic Circumpolar Current and the associated Antarctic Convergence. There, in this cold and maritime region, lies South Georgia Island with its weather and climate being largely affected by both the dominating ocean currents and the strong east ward blowing winds in this zone. While the island forms an important outpost for various surface observations in this largely under-sampled and extremely remote region, it also forms a barrier for these winds due to its high topography, which, in turn, leads to various local meteorological phenomena, such as foehn winds. Surface meteorological data have been available for several stations near King Edward Point (KEP) on South Georgia for much of the 20th century. Since 2013 and 2014, Global Navigation Satellite System (GNSS) data have been available at five locations around the periphery of the island and during a few months in 2016 also radiosonde data have been collected at KEP. This study aims at investigating the consistency between the different surface meteorological data sets such as temperature, pressure and wind direction/speed that have been collected at KEP and a nearby GNSS station on Brown Mountain (BMT) for which we also compare the precipitable water vapor estimates. A cross-evaluation of these data sets with model values from the ERA-Interim re-analyses is carried out to further investigate the performance of both instruments and models. Overall, our preliminary results show high consistency between the surface meteorological observations and the re-analysis model values. It was our main objective to investigate the homogeneity and accuracy of the BMT observation time series through cross-evaluation with the series of the official WMO station at KEP. Air temperature and pressure at both sites from observation and model data are strongly correlated at hourly intervals, reaching correlation coefficients in the range of 0.966 - 0.968 for the former data set. The difference temperature time series shows seasonal variations but no obvious steps. The difference pressure time series is flat, also indicating no discontinuities. A cross-evaluation of the wind observations shows the distinct directional feature at KEP for a station in a valley where the winds are funneled through the valley. For BMT the wind observations confirm the main directions of winds but also show the openness of the station from all directions. The observations of temperature, pressure, humidity and GNSS-derived PWV clearly show the signatures of the frequent foehn events. [less ▲]

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See detailTest
Erkihune, Eshetu Nega UL; Teferle, Felix Norman UL; Hunegnaw, Addisu UL et al

Poster (2020, December 11)

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See detailComparative Analysis of Real-Time Precise Point Positioning Zenith Total Delay Estimates
Ahmed, Furqan UL; Vaclavovic, Pavel; Teferle, Felix Norman UL et al

in GPS Solutions (2014)

The continuous evolution of global navigation satellite systems (GNSS) meteorology has led to an increased use of associated observations for operational modern low-latency numerical weather prediction ... [more ▼]

The continuous evolution of global navigation satellite systems (GNSS) meteorology has led to an increased use of associated observations for operational modern low-latency numerical weather prediction (NWP) models, which assimilate GNSS-derived zenith total delay (ZTD) estimates. The development of NWP models with faster assimilation cycles, e.g., 1-h assimilation cycle in the rapid update cycle NWP model, has increased the interest of the meteorological community toward sub-hour ZTD estimates. The suitability of real-time ZTD estimates obtained from three different precise point positioning software packages has been assessed by comparing them with the state-of-the-art IGS final troposphere product as well as collocated radiosonde (RS) observations. The ZTD estimates obtained by BNC2.7 show a mean bias of 0.21 cm, and those obtained by the G-Nut/Tefnut software library show a mean bias of 1.09 cm to the IGS final troposphere product. In comparison with the RS-based ZTD, the BNC2.7 solutions show mean biases between 1 and 2 cm, whereas the G-Nut/Tefnut solutions show mean biases between 2 and 3 cm with the RS-based ZTD, and the ambiguity float and ambiguity fixed solutions obtained by PPPWizard have mean biases between 6 and 7 cm with the references. The large biases in the time series from PPP-Wizard are due to the fact that this software has been developed for kinematic applications and hence does not apply receiver antenna eccentricity and phase center offset (PCO) corrections on the observations. Application of the eccentricity and PCO corrections to the a priori coordinates has resulted in a 66 % reduction of bias in the PPP-Wizard solutions. The biases are found to be stable over the whole period of the comparison, which are criteria (rather than the magnitude of the bias) for the suitability of ZTD estimates for use in NWP nowcasting. A millimeter-level impact on the ZTD estimates has also been observed in relation to ambiguity resolution. As a result of a comparison with the established user requirements for NWP nowcasting, it was found that both the GNut/Tefnut solutions and one of the BNC2.7 solutions meet the threshold requirements, whereas one of the BNC2.7 solution and both the PPPWizard solutions currently exceed this threshold. [less ▲]

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See detailComparative Analysis of Real-Time Precise Point Positioning Zenith Total Delay Estimates
Ahmed, Furqan UL; Vaclavovic, Pavel; Teferle, Felix Norman UL et al

Poster (2013, December 13)

The use of observations from Global Navigation Satellite Systems (GNSS) in operational meteorology is increasing worldwide due to the continuous evolution of GNSS. The assimilation of near real-time (NRT ... [more ▼]

The use of observations from Global Navigation Satellite Systems (GNSS) in operational meteorology is increasing worldwide due to the continuous evolution of GNSS. The assimilation of near real-time (NRT) GNSS-derived zenith total delay (ZTD) estimates into local, regional and global scale numerical weather prediction (NWP) models is now in operation at a number of meteorological institutions. The development of NWP models with high update cycles for nowcasting and monitoring of extreme weather events in recent years, requires the estimation of ZTD with minimal latencies, i.e. from 5 to 10 minutes, while maintaining an adequate level of accuracy for these. The availability of real-time (RT) observations and products from the IGS RT service and associated analysis centers make it possible to compute precise point positioning (PPP) solutions in RT, which provide ZTD along with position estimates. This study presents a comparison of the RT ZTD estimates from three different PPP software packages (G-Nut/Tefnut, BNC2.7 and PPP-Wizard) to the state-of-the-art IGS Final Troposphere Product employing PPP in the Bernese GPS Software. Overall, the ZTD time series obtained by the software packages agree fairly well with the estimates following the variations of the other solutions, but showing various biases with the reference. After correction of these the RMS differences are at the order of 0.01 m. The application of PPP ambiguity resolution in one solution or the use of different RT product streams shows little impact on the ZTD estimates. [less ▲]

Detailed reference viewed: 182 (10 UL)