Detecting Severe Weather using GPS Tomography: An Australian Case Study

Abstract

The dynamics of water vapour (WV) has a strong influence on the formation and lifecycle of severe mesoscale convective storm systems due to the large energy transfers in the hydrological processes. Contrary to its importance WV remains poorly understood and inadequately measured both spatially and temporally, especially in the southern hemisphere where meteorological data are sparse. GPS meteorology is currently one of the most important atmospheric remote sensing instruments for meteorology and climatology due to its high spatial and temporal resolutions. Kalman filtering based GPS tomography is a promising method of reconstructing dynamically changing four dimensional (4D) wet refractivity fields. This method takes advantage of the high density and homogeneity of ground-based GPS Continuously Operating Reference Station (CORS) networks. Ground-based GPS tomography has the potential to utilize the dense groundbased infrastructure in Australia providing wet refractivity field solutions at a high spatial and temporal resolution to improve early detection and prediction of severe weather. This research presents a case study based on the analysis of an extreme convective super cell storm in the Victorian region during March 2010 using GPS tomography and the most advanced state-wide CORS network – GPSnet in Australia. Integrated Precipitable Water Vapour (PWV) estimates derived for the MOBS GPS CORS station confirmed high time resolution as well as sensitivity to incoming severe weather. A wet refractivity index adopted for GPS tomographic wet refractivity profiles shows an excessive increase as a response to supercell thunderstorm formation. Finally a 2D cross section mapping over the lifecycle of this severe weather event concludes a correlation between the highly dynamic spatial and temporal changes of wet refractivity modelled using 4D GPS tomography with precipitation intensities measured using weather radars.