Comparisons between GAMIT-derived Zenith Tropospheric Delay (ZTD) values from AWS and GNSS met sensor values

Precise estimation of Zenith Tropospheric Delay (ZTD) is crucial for improving the accuracy of data from Continuously Operating Reference Stations (CORS), particularly in applications requiring high-precision GNSS positioning. This study focuses on evaluating various ZTD models to identify the most accurate approach for mitigating atmospheric delays in CORS data. The research compares ZTD values derived from Automatic Weather Stations (AWS), GNSS meteorological sensors, and temperature-pressure-humidity-based models calculated using the GAMIT software with reference values obtained from co-located weather stations and global atmospheric models.

The methodology involves processing GNSS observations from selected CORS sites using multiple ZTD estimation models, including empirical approaches. The accuracy of these models is assessed using key performance metrics such as root mean square error (RMSE), mean bias, and correlation with actual weather conditions.

Preliminary results indicate that empirical models show better consistency in stable atmospheric conditions. Additionally, comparisons between GAMIT-derived ZTD values and those from AWS and GNSS met sensors reveal insights into the reliability and precision of each data source under different atmospheric conditions.

The study highlights that precise ZTD estimation is essential for reducing atmospheric errors in CORS data, thereby enhancing GNSS-based applications such as geodesy, surveying, and real-time positioning. The research concludes that combining inputs from various meteorological data sources offers the best accuracy across diverse CORS networks, particularly in regions with varying climatic conditions and atmospheric dynamics.