EGU25-15408, updated on 15 Mar 2025
https://doi.org/10.5194/egusphere-egu25-15408
EGU General Assembly 2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Poster | Tuesday, 29 Apr, 16:15–18:00 (CEST), Display time Tuesday, 29 Apr, 14:00–18:00
 
Hall X1, X1.111
New horizon of tropospheric studies using the next generation GNSS, Network of Satellite Constellations and AI
Witold Rohm1, Paweł Hordyniec1, Jan Kapłon1, Estera Trzcina1, Saeid Haji-Aghajany1, Peng Sun2, Longijang Li2, and Kefei Zhang2
Witold Rohm et al.
  • 1Institute of Geodesy and Geoinformatics, Wroclaw University of Environmental and Life Sciences, Wroclaw, Poland (witold.rohm@upwr.edu.pl)
  • 2School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China

We present a collaborative research project between Polish and Chinese scientists, supported by national research funding agencies, to advance GNSS remote sensing (RS) for atmospheric studies. Recent advancements in space technologies, artificial intelligence (AI), and information and communication technologies (ICT) have significantly enhanced our ability to observe, model, and predict atmospheric processes. AI-powered GNSS RS offers robust capabilities for acquiring essential atmospheric parameters, such as water vapor content and profiles, rain rates, wind speeds, and cloud composition.

This project focuses on bridging mathematical models, physical processes, and space- and ground-based observations to achieve the following objectives:

  • Data Fusion: Standardize and integrate GNSS RS measurements from ground- and space-based platforms.
  • Innovative Methods: Exploit advanced observation techniques, including signal polarimetry and reflectometry.
  • Network Integration: Harness the potential of multi-constellation satellite networks, including GNSS, LEO satellites, and Starlink-like constellations, for atmospheric studies.
  • AI-Driven Modeling: Develop seamless connections between GNSS observations and weather and climate models using AI and Digital Twin technologies to investigate interactive atmospheric mechanisms.

This research is supported by NCN project UMO-2023/48/Q/ST10/00278, fostering Polish-Chinese scientific collaboration.

How to cite: Rohm, W., Hordyniec, P., Kapłon, J., Trzcina, E., Haji-Aghajany, S., Sun, P., Li, L., and Zhang, K.: New horizon of tropospheric studies using the next generation GNSS, Network of Satellite Constellations and AI, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15408, https://doi.org/10.5194/egusphere-egu25-15408, 2025.