IGiG researchers reached another milestone in GNSS tomography research. In their quest for a high versatility model to picture vertical and horizontal variation of troposphere, they developed a unique way to divide the troposphere space above the GNSS receivers network into a mesh of irregular points. Something that was not done before as most of the models divide the space into a set of regular voxels. The flexible mesh is draped over the space based on the signal intersection density using clustering algorithms. This way the locations with higher density of GNSS signal are estimated with lower uncertainty, whereas areas space where the GNSS signal is not penetrating the troposphere is not artificially estimated. The method brought an important 10% increase in accuracy of the profiles and most importantly in the bottom part of the troposphere (0,5-2 km). We are expecting that this approach will have an even more positive impact on the combined ground and space based tomography retrievals.
Link to the Journal of Geodesy paper