Visualization and analysis of GNSS radio occultation profiles

• Grant number: 20/09443-6
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: October 01, 2020
• End date: October 31, 2023
• Field of knowledge: Physical Sciences and Mathematics - Geosciences - Geodesy
• Principal Investigator: Daniele Barroca Marra Alves
• Grantee: Raphael Silva Nespolo
• Host Institution: Faculdade de Ciências e Tecnologia (FCT). Universidade Estadual Paulista (UNESP). Campus de Presidente Prudente. Presidente Prudente , SP, Brazil
• Associated scholarship(s): 22/14983-5 - Investigation of methods for validation of ionospheric profiles from radio occultation, BE.EP.IC

Abstract

Occultation is the phenomenon in which a celestial body ceases to be visible due to the superposition of another. The radio occultation (RO) technique has been widely applied with the use of stars and probes in order to investigate the atmosphere of other planets. The development of GNSS (Global Navigation Satellite System) and LEO (Low Earth Orbiting) satellites missions enabled the use of RO to explore and investigate the terrestrial atmosphere. RO considers that the signal transmitted by GNSS satellites is influenced by the atmosphere (neutral and ionised) effects when passing through it. This interaction, occurred with the signal propagation, allows the estimation of atmospheric refractive index and, using these values, it is possible to retrieve atmospheric profiles, such as humidity, pressure, temperature and electron density. Since the first RO mission, several other missions have been launched and their products made available. In this context, this project aims to investigate the profiles formats available at CDAAC (COSMIC Data Analysis and Archive Center), the center initially responsible for the COSMIC (Constellation Observing System for Meteorology, Ionosphere and Climate) mission, but which nowadays provides data from several missions. And, in addition, explore the options of visualizing and analyzing the atmospheric information from RO data, using comparisons between different missions or different data sources.