Comparison of advanced troposphere models for aiding reduction of PPP convergence time in Australia

This paper first analyses the precision of tropospheric zenith total delay (ZTD) values obtained from the empirical models GPT2 and GPT2w, and the numerical weather models (NWM) from Australian Bureau of Meteorology (BoM), and European Centre for Medium-Range Weather Forecasts (ECMWF). Comparison of these ZTD values with IGS ZTD product at four sites showed that the ZTDs from NWM datasets were more precise than the empirical models. The ZTD from BoM data gave the best results, with mean errors between -0.034 m to 0.029 m and standard deviations better than 0.045 m. Next, the PPP convergence time and achievable accuracy using the BoM NWM constrained ZTD by including them as pseudo-observations with a pre-set precision was compared to the case of estimating the troposphere. This resulted in a slight enhancement in convergence time, and improvements in vertical positioning accuracy was found at all the four tested sites at 0.036–0.058 m after 2 min, 0.023–0.038 m after 3 min and 0.013–0.020 m after 5 min of PPP initialisation

Validation of a New Model for the Estimation of Residual Tropospheric Delay Error Under Extreme Weather Conditions

The electromagnetic signals of the Global Navigation Satellite Systems (GNSS) satellites suffer delays while propagating through the troposphere. The tropospheric delay is a significant systematic error of GNSS positioning. For safety-of-life applications of positioning many systematic error effects are either mitigated or eliminated in the positioning solution. Space based augmentation systems provide corrections for the orbital and satellite clock error, the ionospheric effects, etc. Moreover advanced GNSS provide dual frequency code observations for civilian users to eliminate the ionospheric delays caused by the electron content of the upper atmosphere. Nevertheless tropospheric delays are still taken into account using empirical models.For safety-of-life applications besides the accuracy of the positioning, the integrity of the positioning service is an important factor, too. The integrity information includes the maximal positioning error at an extremely rare probability level, called protection level to ensure highly reliable position solution in the aviation. The Radio Technical Commission for Aeronautics Minimum Operational Performance Standard (RTCA MOPS) recommends 0.12 m as the maximum zenith tropospheric error in terms of standard deviation. Previous studies show that this recommendation seems to be too conservative leading to a lower service availability. Therefore a more realistic integrity model has to be derived for the estimation of maximal residual tropospheric delay error.In the recent years many advanced empirical tropospheric delay models have been formulated compared to the one recommended by the RTCA. Recently new integrity models have been derived for estimating the maximum residual tropospheric delay error using numerical weather models under real extreme weather.The aim of this paper is to study the reliability of these models conditions. In order to achieve this, high-resolution numerical weather models were ray-traced using an improved ray-tracing algorithm to evaluate the slant and zenith tropospheric delays with the geographical resolution of 0.1° × 0.1°

Tropospheric delay performance for GNSS integrated water vapor estimation by using GPT2w model, ECMWF's IFS operational model and in situ meteorological data

Tropospheric delay comprises one of the most important error sources in satellite navigation and is caused when radio signals broadcasted by GPS satellites propagate into the atmosphere. It is usually projected onto zenith direction by using mapping functions named as Zenith Tropospheric Delay (ZTD). ZTD is described as the sum of the Zenith Hydrostatic Delay (ZHD) and the Zenith Wet Delay (ZWD) and with the aid of surface pressure and temperature the integrated water vapor can be estimated. The main objective of this study is to evaluate the tropospheric delay performance for GNSS integrated water vapor estimation by using GPT2w model, ECMWF's IFS (ECMWF stands for the European Centre for Medium-Range Weather Forecasts) reanalysis model and ground meteorological data from two stations of the permanent network of Cyprus and Greece. The period from 27 May to 3 June 2018 is characterized by two different synoptic conditions: high pressure with fair weather in central Mediterranean (Greece), on the one hand, and high instability over the upper levels of the atmosphere that resulted in thunderstorms inland and mountainous areas during midday over the Eastern Mediterranean (Cyprus), on the other hand. In general, the results show that both the empirical blind model GPT2w and the ECMWF (IFS) operational model perform well in particular over Nicosia when used for the retrieval of Integrated Water Vapor (IWV) from GNSS measurements, although appreciable deviations were observed between ECMWF (IFS)-retrieved IWV and the one retrieved from GNSS observations by using meteorological measurements. A sharp increase of IWV prior to the abrupt rainfall events during noon on 30 and 31 May over Nicosia was also found.</p

Estimating integrated water vapor trends from VLBI, GPS,and numerical weather models: sensitivity totropospheric parameterization

©2018. American Geophysical UnionIn this study, we estimate integrated water vapor (IWV) trends from very long baseline interferometry (VLBI) and global navigation satellite systems (GNSS) data analysis, as well as from numerical weather models (NWMs). We study the impact of modeling and parameterization of the tropospheric delay from VLBI on IWV trends. We address the impact of the meteorological data source utilized to model the hydrostatic delay and the thermal deformation of antennas, as well as the mapping functions employed to project zenith delays to arbitrary directions. To do so, we derive a new mapping function, called Potsdam mapping functions based on NWM data and a new empirical model, GFZ‐PT. GFZ‐PT differs from previous realizations as it describes diurnal and subdiurnal in addition to long‐wavelength variations, it provides harmonic functions of ray tracing‐derived gradients, and it features robustly estimated rates. We find that alternating the mapping functions in VLBI data analysis yields no statistically significant differences in the IWV rates, whereas alternating the meteorological data source distorts the trends significantly. Moreover, we explore methods to extract IWV given a NWM. The rigorously estimated IWV rates from the different VLBI setups, GNSS, and ERA‐Interim are intercompared, and a good agreement is found. We find a quite good agreement comparing ERA‐Interim to VLBI and GNSS, separately, at the level of 75%.DFG, 255986470, GGOS-SIM-2: Simulation des "Global Geodetic Observing System

Modelling atmospheric wet refractivity profile using ground and space-based global positioning system

Precise measurement of atmospheric water vapour has been very challenging due to some limitations of the conventional meteorological systems. Hence, there is a need for Global Positioning System (GPS) for meteorology or GPS meteorology. Therefore, the ground-based GPS meteorology and the space-based GPS Radio Occultation (GPS RO) techniques have been used. The major challenges of groundbased GPS meteorology approach include the lack of surface meteorological data collocating with the location of the ground-based GPS receivers as well as its inability to profile the atmosphere. Whereas the GPS RO technique has a problem of generating profile for the lower tropospheric region which holds the largest amount of water vapour. This research investigates an approach for estimating wet refractivity profile using GPS data. Three specific objectives were set for the study which was conducted in three phases. The first objective assessed GPS Integrated Water Vapour (GPS IWV) in which GPS IWV from interpolated meteorological data and the applicability of Global Pressure and Temperature (GPT2w) model for GPS meteorology was evaluated. The results revealed that the GPS IWV from Automatic Weather Station (AWS) presents good correlation with the radiosonde IWV, the standard deviation of the biases vary spatially from 3.162kg/m2 to 3.878 kg/m2. The actual influence of the errors of GPT2w meteorological parameters on GPT2w-based GPS IWV lies between 2kg/m2 and 3kg/m2, translating to an average relative accuracy of 1.2%. Meanwhile, the sensitivity of the GPS RO data to equatorial water vapour trend was evaluated to achieve second objective. It was found that the GPS RO IWV is highly comparable with the ground-based GPS IWV, having average bias of 1.8kg/m2. Finally, a methodology for GPS wet refractivity retrieval was developed towards achieving the third objective of this research. The Modified Single Exponential Function (MSEF) model for retrieving wet refractivity profile from ground-based GPS Zenith Wet Delay (ZWD) was realised. The output validation using profile from radiosonde and GPS RO observations showed high correlation in each case. In order to improve the performance of the MSEF model, an approach for integrating the ground-based and the space-based GPS data (GIWRef) was formulated. The GIWRef profile is highly correlated with the GPS RO profile, which showed an average improvement of 41% over the initial MSEF method with average correlation coefficient of 0.99. It can be concluded from the foregoing results of the study that the MSEF and GIWREF concepts developed in this work, presents a potential for augmenting weather forecasting and monitoring water vapour system

Tropospheric delays in ground-based GNSS Multipath Reflectometry – experimental evidence from coastal sites

Recent studies have demonstrated the utility of ground based GNSS Multipath Reflectometry (GNSS-MR) for sea level studies. Typical root-mean-square (RMS) differences of GNSS-MR derived sea level time series with respect to nearby tide gauges are on the order of 6 – 40 cm, sufficiently accurate to estimate tidal and secular sea level variations but are possibly biased due to delay of the signal through the troposphere. In this study we investigate the tropospheric effect from more than 20 GNSS coastal sites located from several meters up to 280 m above sea level. We find a bias in the estimated heights that is elevation and height dependent and can reach orders of 1 m for a 90 m site. Without correcting for tropospheric delay we find that GNSS-MR estimated tidal coefficients will be smaller than their true amplitudes by around 2% while phases seem unaffected. Correcting for the tropospheric delay also improves levelling results as a function of reflector height. Correcting for the tropospheric delay in GNSS-MR for sea level studies is therefore highly recommended for all sites no matter the height of the antenna above the sea surface as it manifests as a scale error

Constructing a precipitable water vapor map from regional GNSS network observations without collocated meteorological data for weather forecasting

Surface pressure (Ps) and weighted mean temperature (Tm) are two necessary variables for the accurate retrieval of precipitable water vapor (PWV) from Global Navigation Satellite System (GNSS) zenith total delay (ZTD) estimates. The lack of Ps or Tm information is a concern for those GNSS sites that are not collocated with meteorological sensors. This paper investigates an alternative method of inferring accurate Ps and Tm at the GNSS station using nearby synoptic observations. Ps and Tm obtained at the nearby synoptic sites are interpolated onto the location of the GNSS station by performing both vertical and horizontal adjustments, in which the parameters involved in Ps and Tm calculation are estimated from ERA-Interim reanalysis profiles. In addition, we present a method of constructing high-quality PWV maps through vertical reduction and horizontal interpolation of the retrieved GNSS PWVs. To evaluate the performances of the Ps and Tm retrieval, and the PWV map construction, GNSS data collected from 58 stations of the Hunan GNSS network and synoptic observations from 20 nearby sites in 2015 were processed to extract the PWV so as to subsequently generate the PWV maps. The retrieved Ps and Tm and constructed PWV maps were assessed by the results derived from radiosonde and the ERA-Interim reanalysis. The results show that (1) accuracies of Ps and Tm derived by synoptic interpolation are within the range of 1.7–3.0&thinsp;hPa and 2.5–3.0&thinsp;K, respectively, which are much better than the GPT2w model; (2) the constructed PWV maps have good agreements with radiosonde and ERA-Interim reanalysis data with the overall accuracy being better than 3&thinsp;mm; and (3) PWV maps can well reveal the moisture advection, transportation and convergence during heavy rainfall.</p

Tropospheric delay in microwave propagation in Nigeria

Satellite communication systems suffer from the systematic error of tropospheric delay. Accurate estimation of this delay is essential for communication budget and planning. This study investigates the tropospheric delay in three Nigeria cities: Abuja, Lagos, Port-Harcourt using two different models (Saastominen and Hopfield). Three year atmospheric data for surface pressure, relative humidity and temperature obtained at 5-mins interval were acquired from the Tropospheric Data Acquisition Network (TRODAN) archives. Computed radio refractivity values showed distinct seasonal dependence in Abuja with low and high values during the dry and wet season respectively. The Hopfield model predicts higher hydrostatic delay values than the Saastominen model. In the non-hydrostatic delay, the two models converge to a single values at high temperature. Theorems were proposed with proofs to explain the relationship observed between the two models