ASKNE NORDIUS MODEL ACCURATION ANALYSIS OF GPS - PWV OBSERVATION IN INDONESIA

• Main Author: Novia Taryuni, Ika
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/73392
• Institution: Institut Teknologi Bandung

<p align="justify">The propagation of GPS satellite signals to observer receivers on the earth's surface will pass through the layers of the atmosphere, especially the troposphere, and ionosphere. The effect of the troposphere on the GNSS signal creates a measurement delay (tropospheric delay) which causes a bias in the GPS distance measurement results. Therefore, to get the absolute position, a refraction correction is needed. There are several ways to correct this bias, one of which is by using the global modelling method. The purpose of this research is to identify and determine the characteristics of the troposphere in Indonesia using long-term GNSS data (2010 – 2020). Based on previous modelling, it was found that the Askne & Nordius model is a global model which currently can represent the characteristics of the troposphere well. The data used is Zenith Tropospheric Delay (ZTD) data which is processed into Precipitable Water Vapor (PWV) data for 11 years from 10 CORS BIG stations across Indonesia. The Askne & Nordius global model was used to determine the accuracy of this model for tropospheric characteristics in Indonesia, and then a correlation calculation was performed to compare the estimated PWV data with the GNSS model using the Pearson, Kendall Rank, and Spearman correlation methods. Based on the calculation results, the correlation value of each station is low, which means that all stations have their uniqueness and are not affected by other stations. In addition, calculations were carried out using the Lomb Spectral method to determine the characteristics of the troposphere in Indonesia. Each station in East and West Indonesia is unique and not affected by one another. Many things affect these differences, including the location and condition of stations, ENSO events, and monsoons, as well as other factors that affect the characteristics of the troposphere in Indonesia.