Radio Occaultation Accuracy for Climate, Meteorology, and Space Weather

This project is part two of the NRFP round four project "Radio Occultation Accuracy for Climate, Meteorology, and Space Weather".

Aim of the project

This project aims to improve the long-term measurement accuracy of climate change, weather parameters and space weather using RO. The RO instrument measures the refraction angle of the GNSS signal as a function of altitude in the atmosphere.

Implementation

In part one, measurements from MetOp up to 85 kms altitude were studied. In the NRFP project, a simulation tool has been developed to model ionospheric disturbances. Ionospheric disturbances are consequences of solar activities and ionospheric conditions, i.e. space weather. Radio occultation measurements provided by MetOp satellites have global coverage and provide a large amount of data to investigate such a phenomenon. We are now finalizing the work packages in that part of the project by doing statistical evaluation and optimizing parameters in the simulation model. In part two we will continue where part one left off.

A natural continuation of this work is to extend the use of the simulation tool to perform a statistical analysis of ionospheric parameters. In recent years, there have been rapid developments in artificial intelligence (AI) and machine learning. Methods have been developed which are likely to be very well suited for applications in RO. A planned work package in NRFP-4 part two, is therefore to develop a machine learning algorithm trained to perform automatic detection of cases. The cases will then be compiled in the dataset that will be published for other researchers for reference.