Assessing the Accuracy of ECMWF Operational Atmospheric Forecasts with Tropospheric Delays from Ray Tracing

This study presents a comprehensive global accuracy assessment of the medium-range (up to 15 days) forecast pressure-level data generated by the physics-based Integrated Forecast System (IFS) and the newly operational, data-driven Artificial Intelligence Forecasting System (AIFS) from the European Centre for Medium-Range Weather Forecasts (ECMWF) based on the radio wave signal delays during propagation through the troposphere. Troposphere signal path delays are calculated using the software package Ankara Ray-tracing Tools (ART). This newly developed troposphere ray-tracing software package integrates hydrostatic and wet refractivities along the ray path of a radio wave signal using an approximation of a two-dimensional piecewise-linear ray path. Along with the IFS and AIFS pressure-level data, the AIFS/IFS combination generated and appended in this study is used to compute 62 forecast runs for each of the January and August 2025 monthly periods. Each run includes 6-hourly forecast steps over 15 days and is initialized twice daily at 0 and 12 UT throughout January and August 2025. These forecasts cover 52 globally distributed Global Navigation Satellite Systems (GNSS) stations operated by the International GNSS Service (IGS). The forecast zenith delay accuracies were systematically evaluated using the root mean square (RMS) and bias error metrics with respect to the IGS troposphere product and the ECMWF Operational Analysis data as robust validation benchmarks. In addition to the Vienna Mapping Functions 3 (VMF3) troposphere delay product, the empirical troposphere delay models Global Pressure and Temperature 3 (GPT3) and the model utilized by satellite-based augmentation systems (SBAS, e.g., WAAS and EGNOS) GNSS receivers are incorporated into the assessments. Both IFS and AIFS models exhibit exceptional short-range capabilities, keeping global zenith total delay errors (RMS relative to IGS) below 2 cm up to a 2-day lead time. However, a critical performance crossover occurs between the 10-day and 11-day forecasting horizons, where the forecast accuracy of both IFS and AIFS declines below the threshold of the GPT3 model, whose zenith total delay RMS across all stations with respect to the IGS troposphere product is found to be about 4 cm. The findings of this study offer crucial insights for improving the accuracy of real-time satellite navigation, climate monitoring, and satellite-based high-precision positioning applications.