Key Research Papers
Explore the scientific foundation of GNSS meteorology—from the pioneering 1992 discovery to cutting-edge AI-based data assimilation. These peer-reviewed papers demonstrate why dense GNSS observations are transforming weather forecasting.
Generative Data Assimilation of Sparse Weather Station Observations at Kilometer Scales (2025)
Demonstrates AI-based diffusion model assimilation, showing how dense surface observations supercharge generative models. Extremely aligned with Skyfora's AI-based assimilation vision and represents where the field is heading.
Assimilation of GNSS Zenith Delays and Tropospheric Gradients (2025)
A sensitivity study utilizing sparse and dense station networks, demonstrating the value of high-density GNSS observations for weather forecasting.
Kilometer-Scale Convection Allowing Model Emulation using Generative Diffusion Modeling (2024)
Demonstrates that AI weather models now operate at km-scale resolution. Supports the narrative that next-generation AI models need dense humidity observations to reach their full potential.
Benchmark Campaign in Central Europe for Advanced GNSS Tropospheric Models (2016)
Shows that GNSS provides higher-resolution humidity structure than NWP models. Demonstrates gradients and tomography potential, supporting operational meteorology applications.
Precipitable Water Characteristics During the 2013 Colorado Flood (2013)
Uses 10 years of high-resolution GNSS precipitable water data showing record-breaking moisture anomalies preceded the catastrophic Colorado flood. Demonstrates GNSS capability for detecting rapid moisture surges and extreme-event precursors.
Integer Ambiguity Resolution on Undifferenced GPS Phase Measurements (2009)
Landmark paper establishing the PPP ambiguity resolution method for standalone receivers, enabling centimeter-level accuracy. Forms the technical foundation for modern high-accuracy GNSS infrastructure used in meteorology and climate monitoring.
A Near-Global, 2-Hourly Dataset of Atmospheric Precipitable Water from GPS (2007)
Shows global, climate-quality PWV datasets from GNSS with PWV derivation formulas. Demonstrates accuracy, stability, and climate applications. Critical to the "GNSS as an Essential Climate Variable" narrative.
GPS Meteorology: Remote Sensing of Atmospheric Water Vapor Using GPS (1992)
First-ever demonstration that GPS can retrieve atmospheric water vapor. Establishes the scientific legitimacy of GNSS meteorology. Highly cited and still referenced by all GNSS/NWP assimilation studies.