Accurate weather forecasting is vital for various industries, including utilities, agriculture, transport, construction, and disaster risk management. The World Bank estimates that these weather-sensitive industries could potentially benefit by approximately €160 billion annually from improved forecasting. Weather's impact is increasing due to climate change, creating demand for advanced weather monitoring solutions from public and private sectors.
Private weather companies face challenges due to the high cost of weather observation infrastructure, relying heavily on public agencies' data. Quality and coverage vary by region, hindering comprehensive forecasting. However, the growing global network of 5G base stations offers an untapped opportunity. Equipped with dual-band GNSS receivers, they capture navigation signal delays caused by atmospheric interference, which can be processed for precise weather forecasting.
Unlike traditional methods, GNSS signals can be captured from multiple directions, enabling volumetric estimation of atmospheric conditions. During the project, Skyfora advanced its WeatherCTScan software to process GNSS signal delays and integrate them with external weather datasets, producing 3D atmospheric tomography models. These models were validated against real-world and synthetic data, demonstrating significantly improved accuracy and resolution compared to baseline approaches.
The system was able to extract humidity, temperature, pressure, and wind fields, providing more granular forecasts for pilot users. The results confirmed measurable forecast improvements, showing how GNSS-based tomography can enhance both public safety applications and industry-specific planning.
These validated outcomes provide a foundation for future integration into public warning systems and tailored forecasting services for weather-sensitive industries, supporting both societal resilience and commercial adoption.
