Sensing the dynamics of severe weather using 4D GPS tomography in the Australian region
Creators: name: Manning, Toby
Publisher: name: RMIT University
Year: 2024

description: The dynamics of water vapour (WV) have a strong influence on weather and climate due to the large energy transfers in the hydrological processes. This particularly correlates to WV dynamics during the formation and lifecycle of severe mesoscale convective storm and precipitation systems. Contrary to its importance, WV remains poorly understood and inadequately measured both spatially and temporally, especially in Australia and the southern hemisphere where meteorological data are sparse. Ground-based and space-borne GPS (global positioning system) meteorology are currently regarded as leading atmospheric remote sensing instruments for numerical weather prediction (NWP) and climatology due to their high spatio-temporal resolutions, multiple observing platforms and continuous operability. The GPS signals are delayed and bent due to the refractive index of the ionosphere and troposphere. This tropospheric path delay can be separated into dry and wet integral components, with the latter proportional, using a scale factor, to the integrated precipitable water vapour (PWV) in the vertical column above the GPS stations. These wet delay measurements can also be combined using a network of GPS stations to resolve the spatial distribution of WV. This method is called GPS tomography, which is a promising and developing method of reconstructing dynamically changing four dimensional (4D) wet refractivity fields. This takes advantage of the high density and homogeneity of ground-based GPS Continuously Operating Reference Station (CORS) networks to provide accurately resolved WV profiles in space and time. A distinct trend between the 4D reconstructed wet refractivity fields using GPS tomography and the formation and lifecycle of severe storm and precipitation systems was found. Sharp gradients are evident up the vertical layers The dynamics of water vapour (WV) have a strong influence on weather and climate due to the large energy transfers in the hydrological processes. This particularly correlates to WV dynamics during the formation and lifecycle of severe mesoscale convective storm and precipitation systems. Contrary to its importance, WV remains poorly understood and inadequately measured both spatially and temporally, especially in Australia and the southern hemisphere where meteorological data are sparse. Ground-based and space-borne GPS (global positioning system) meteorology are currently regarded as leading atmospheric remote sensing instruments for numerical weather prediction (NWP) and climatology due to their high spatio-temporal resolutions, multiple observing platforms and continuous operability. The GPS signals are delayed and bent due to the refractive index of the ionosphere and troposphere. This tropospheric path delay can be separated into dry and wet integral components, with the latter proportional, using a scale factor, to the integrated precipitable water vapour (PWV) in the vertical column above the GPS stations. These wet delay measurements can also be combined using a network of GPS stations to resolve the spatial distribution of WV. This method is called GPS tomography, which is a promising and developing method of reconstructing dynamically changing four dimensional (4D) wet refractivity fields. This takes advantage of the high density and homogeneity of ground-based GPS Continuously Operating Reference Station (CORS) networks to provide accurately resolved WV profiles in space and time. A distinct trend between the 4D reconstructed wet refractivity fields using GPS tomography and the formation and lifecycle of severe storm and precipitation systems was found. Sharp gradients are evident up the vertical layers providing the wet refractivity trend of convection, with high gradient falls through the vertical layers after the storm system passed. Radiosonde is used as a reference to validate the GPS tomographic model with final accuracies of the March 2010 and January 2011 case studies presenting 8.58 and 9.36 ppm RMS errors, respectively. A wet refractivity index adopted for the GPS tomographic wet refractivity profiles showed an excessive increase above the planetary boundary layer as a response to the formation of a supercell thunderstorm. Finally, horizontal and vertical 2D cross sections, investigating the evolution of the March 2010 severe weather event concludes a high correlation between the highly dynamic spatial and temporal changes of wet refractivity, modelled using 4D GPS tomography with precipitation intensities measured using weather radars images. These gradient solutions from GPS tomography are able to identify the spatial and temporal structure of the mesoscale convective and stratiform processes during severe weather. Final investigations analyse the influence of additional observational methods introduced into the observation model of the GPS tomographic processing. This analysis is conducted during the formation and lifecycle of severe weather of the January 2011 case study. A statistical analysis compares additional observational methods including: radiosonde, synoptic weather station networks and GPS radio occultation and then the influence of all observation methods combined. The results are compared against radiosonde-derived wet refractivity estimates as the reference data to conclude RMS errors of 9.36, 8.03, 8.14, 8.56 and 7.57 ppm, respectively. These results have shown that the introduction of accurate additional information into the tomographic solution lead to a significant increase in accuracy and more robust results than the original method containing no additional data. These improvements are in the order of 14.29%, 13.09%, 8.57% and 19.15%, respectively. The major objectives of this research are satisfied by developing ground-based GPS meteorological platforms in the Australian region including the introduction of 4D tomographic reconstruction methods to the GPSnet. These developments are in view of assimilation methods for nowcasting and NWP to provide a more robust platform for early detection and prediction of severe weather and precipitation extremes. <br>