GNSS ground-based tomography: state-of-the-art and technological challenges

Global navigation satellite system (GNSS) meteorology is utilized in predicting and monitoring extreme weather events using tropospheric products like precipitable water vapour for horizontal 2D detail and water vapour density profiles for 3D detail. In water vapour (WV) tomography, the slant delays from GNSS observations are used to model 4D variations of wet refractivity in the atmosphere above the study area. We present a comprehensive review on the evolution of GNSS WV tomography since its inception, the current state of the art, the challenges faced by the meteorology community, and a qualitative analysis of various techniques used in the process. With the growing infrastructure of meteorologically oriented GNSS station networks as well as increasing utilization of multi-source earth observation datasets powered with machine learning tools, GNSS tomography has shown improvements in producing accurate WV profiles. These new improvements have created the need for conducting multi-factor canonical analyses to understand the efficiency of these well-established methods in controlling the accuracy of the output field.