Estimation of neutral atmosphere parameters from GNSS positioning signals: Modeling and analysis using meteorological in situ and radiosonde data

• Grant number: 25/07321-4
• Support Opportunities: Scholarships abroad - Research Internship - Master's degree
• Start date: September 01, 2025
• End date: November 30, 2025
• Field of knowledge: Physical Sciences and Mathematics - Geosciences - Geodesy
• Principal Investigator: Daniele Barroca Marra Alves
• Grantee: Afonso Marques Albuquerque
• Supervisor: Johannes Bohm
• Host Institution: Faculdade de Ciências e Tecnologia (FCT). Universidade Estadual Paulista (UNESP). Campus de Presidente Prudente. Presidente Prudente , SP, Brazil
• Institution abroad: Vienna University of Technology (TU Wien), Austria
• Associated to the scholarship: 23/14739-0 - Improvement of GNSS-PWV Estimation in the Occurrence of Precipitation Events, BP.MS

Abstract

The signals of Global Navigation Satellite Systems (GNSS) are influenced by several error sources, with neutrospheric delay being one of the most significant, reaching meter level at the zenith. The zenithal total delay (ZTD), resulting from the interaction of GNSS signals with dry gases (hydrostatic delay) and water vapor (non-hydrostatic delay) in the neutrosphere, affects positioning accuracy, making its modeling essential for high-precision applications. Furthermore, studies on ZTD not only improve error modeling in GNSS positioning but also contribute to the acquisition of water vapor data in the neutrosphere, using the non-hydrostatic delay to obtain Precipitable Water Vapor (PWV), which represents the amount of water vapor that could potentially precipitate in millimeters, transforming ZTD into valuable information for meteorology. In this context, this project aims to investigate and test advanced neutrospheric delay modeling techniques in Precise Point Positioning (PPP) using the raPPPid and BNC software to estimate ZTD and PWV in post-processing and under nowcasting conditions. In this study, we also intend to evaluate the ZTD data from Austria compared to ZTD obtained for Brazilian stations, considering Brazilian climatology. Additionally, we will compare PWV-GNSS estimates with PWV obtained from radiosonde data during extreme precipitation events. Finally, this project aims to acquire knowledge at a leading research institution, contributing to advancements in ZTD and PWV modelling, as well as further research in climatology and meteorology. (AU)