Determining the 4D dynamics of wet refractivity using GPS tomography
in the Australian region
chapter
posted on 2024-10-30, 20:43authored byToby Manning, Witold Rohm, Kefei ZhangKefei Zhang, Fabian Hunter, Charlie Wang
The Earth's climate and weather is a highly dynamic and complex system. Monitoring and predicting meteorological conditions with a high accuracy and reliability is, therefore, a challenging task. Water vapour (WV) has a strong influence on the Earth's climate and weather due to the large energy transfers in the hydrological process. However, it remains poorly understood and inadequately measured both spatially and temporally, especially in Australia and the southern hemisphere. Four dimensional (4D) WV fields may be reconstructed using a tomographic inversion method that takes advantage of the high density of ground-based GPS Continue Operating Reference Station (CORS) networks. Recent development in GNSS tomography technique based on the dense Australian national positioning infrastructure has the potential to provide near real time 4D WV solutions at a high spatial and temporal resolution for numerical weather prediction, severe weather monitoring and precise positioning. This paper presents a preliminary study using the most advanced state CORS network-GPSnet as a test bed and introduces 4D GPS tomography in Australia and evaluates different parameters for voxel and height resolution and the influence of a priori data through simulations in a controlled field. Preliminary analyses of a real data campaign using a priori information are presented. These preliminary results conclude that the most optimal setup for GNSS tomography models in Victoria is: 55 km horizontal resolution and 15 vertical layers with a smaller spacing in the lower troposphere and a larger spacing towards the tropopause. Further analysis will be undertaken to optimize the parameter settings for real data processing. The initial investigation into real data analysis has concluded an overall RMS error of 5.8 ppm with respect to the operational Australian NumericalWeather Prediction (NWP) model for 1 day.