3D ground and space-based ray tracing tomography model – methodology and implementation

One of the indispensable elements of high-resolution weather forecast systems is the provision of reliable initial conditions using observations. Among the methods for collecting meteorological data, besides the quality of measurements, their time and space variability play a crucial role. Hence, GNSS observations stand out as stable, bias-free alternatives for weather stations, radiosondes, or microwave satellites.

Current studies of GNSS observations in weather forecasting give promising results. However, the observations themselves are subject to errors due to their geometry, mainly caused by insufficient vertical and horizontal resolution. Therefore, applying them in an operational forecasting model is challenging. A possible way to solve this is to integrate space and ground-based observations into one tomography model.

The solution should be able to detect local, extreme weather phenomena with repeatable uncertainty and high numerical stability. Hence, we propose a precise 3D ray tracing solution for effective simulations of the ray path between the GNSS satellite and the GNSS receiver (Low Earth Orbiting LEO satellite), along with the ground receiver. Although, the combination of these results in one computationally efficient and stable model is a complex task.

The following step is the 3D ray tracing simulation integration into a modified TOMO2 operator dedicated to the tomography of 3D wet refractivity fields. The ray tracing module collects information on ray points’ refractivity and distance traversed in models’ voxels along the ray path. Then delivers it to mutual observational matrices for ground- and space-based simulations. 

This study focuses on the methodology of integrated tomography modeling.  Results are compared to the ground-based only GNSS tomography solution and validated with radiosondes profiles. The case studies are based on severe weather events in Poland with RO data delivered by SPIRE company and GNSS ground-based observations produced by UPWr. Numerical Weather Model input comes from European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5.