Ground-based GNSS ZTD/IWV estimation system for numerical weather prediction in challenging weather conditions

Abstract The Global Navigation Satellite Systems (GNSS) are one of the very few tools that can provide continuous, unbiased, precise and robust atmosphere condition information. The extensive research of GNSS space-based segment (e.g. available precise, real-time satellite orbits and clocks), unlimited access to the ground-based Continuously Operating Reference Stations (CORS) GNSS networks along with the well established data processing methods provides an unprecedented opportunity to study the environmental impacts on the GNSS signal propagation. GNSS measurements have been successfully used in precise positioning, tectonic plate monitoring, ionosphere studies and troposphere monitoring. However all GNSS signals recorded on the ground by CORS are subject to ionosphere delay, troposphere delay, multipath and signal strength loss. Nowadays, the GNSS signal delays are gradually incorporated into the numerical weather prediction (NWP) models. Usually the Zenith Total Delay (ZTD) or Integrated Water Vapour (IWV) have been considered as an important source of water vapour contents and assimilated into the NWP models. However, successful assimilation of these products requires strict accuracy assessment, especially in the challenging severe weather conditions. In this study a number of GNSS signal processing strategies have been verified to obtain the best possible estimates of troposphere delays using a selection of International GNSS Service (IGS) orbit and clock products. Three different severe weather events (severe storm, flash flooding, flooding) have been investigated in this paper. The strategies considered are; 1) Double Differenced (DD) network solution with shortest baselines, 2) DD network solution with longest baselines, 3) DD baseline-by-baseline solution (tested but not considered), 4) Zero Differenced (ZD) Precise Point Positioning (PPP) based on ambiguity float solutions, all with precise orbits and clocks, and real time clocks and predicted orbits. The quality of the estimates obtained has been evaluated against radiosonde measurements, Automatic Weather Station (AWS) observations, NWP (assimilation step without ground-based GNSS data) and ZTD estimates from the well established IGS processing centre, the Center of Orbit Determination in Europe (CODE). It shows that the ZTD and IWV estimates from the DD short baseline solution are robust with usually a very small bias (− 2.7 to − 0.8 mm) and errors of less than 10 mm (7.6–8.5) (ZTD) or 3 mm (2.6–2.7) (IWV). The DD short baseline network solution was found to be the most reliable method in the considered case studies, regardless of the type of orbits and clocks applied.