|Title:||Tropospheric parameter estimation based on GNSS tracking data of a fleet of trains||Other Titles:||Troposphärische Parameterbestimmung auf Basis von GNSS Messdaten von Zügen||Language:||English||Authors:||Aichinger-Rosenberger, Matthias||Qualification level:||Doctoral||Advisor:||Weber, Robert||Issue Date:||2021||Number of Pages:||187||Qualification level:||Doctoral||Abstract:||
Water vapour denotes one of the most important parameters utilized for describing the state and evolution of the atmosphere. Therefore, detailed knowledge of its distributionis of immense importance for weather forecasting. Furthermore, it is also the most effective greenhouse gas and highly variable in both space and time.Thus, it is obvious that high resolution observations are crucial for accurate precipitation forecasts,especially for short-term prediction of severe weather. Although not intentionally built for this purpose, Global Navigation Satellite Systems (GNSS) have proven to meet those requirements. The derivation of meteorological parameters from GNSS observations is based on the fact that electromagnetic signals are delayed when travelling through the atmosphere. Parametrisations of these delays, most prominently the Zenith Total Delay (ZTD) parameter, have been studied extensively and proven to provide substantial benefits for atmospheric research and especially Numerical Weather Prediction (NWP) model performance. Typically, regional/global networks of static reference stations are utilized to derive ZTD along with other parameters of interest in GNSS analysis (e.g.station coordinates). Results are used as a contributing data source for determining the initial conditions of NWP models, a process referred to as Data Assimilation (DA).This thesis goes beyond the approach outlined above, showing how reasonable tropospheric parameters can be derived from highly-kinematic, single-frequency (SF) GNSS data. This data was gathered on trains of the Austrian Federal Railways ( ̈OBB)and processed using the Precise Point Positioning (PPP) technique.The specialnature of the observations yields a number of additional challenges, from appropriatepre-processing and extended outlier detection, to advanced strategies in the PPPsetup and for usage in DA procedures. Furthermore, since only SF data is provided,the treatment of the ionosphere represents one of the major challenges of this study.Therefore different strategies have been investigated and shown to provide satisfactory results, suitable for ZTD estimation.Despite these challenging circumstances, reasonable results for ZTD estimates could be obtained for the analysed test cases investigating different PPP processing strategies.For validation of the results, comparisons with ZTD calculated using data from ERA5,the latest reanalys is of the European Centre for Medium-Range Weather Forecasts (ECMWF), were carried out. They yield very high correlation and an overall agreement from the low millimetre-range up to 5 centimetre, depending on solution and analysed travelling track. First tests of assimilation into a NWP model again show the reasonable quality of the results as between 30-100 % of the observations are accepted by the model. Furthermore guidelines to an operational processing and possible extensionsto advanced tropospheric parameters were outlined, in order to exploit the huge benefits (horizontal/temporal resolution) of this specific dataset for operational weather forecasting.
|Keywords:||Tropospärische Delays; Wettervorhersage
GNSS based Tropospheric Delays; Weather Forecast
|DOI:||10.34726/hss.2021.84161||Library ID:||AC16166233||Organisation:||E120 - Department für Geodäsie und Geoinformation||Publication Type:||Thesis
|Appears in Collections:||Thesis|
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checked on Jun 18, 2021
checked on Jun 18, 2021
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