Assimilation of GPS radio occultation data with numerical weather prediction

Monitoring climate change is of great importance. The Earth’s climate is a dynamic system that is increasing influenced by human activity. Improvements to the forecasting accuracy of operational numerical weather prediction (NWP) systems and enhancements to the reliability of climate change analyses rely heavily on the availability of new technologies and new measurements. Due to its unprecedented high vertical resolution, degree of accuracy, global coverage ability and long term stability, GPS radio occultation (RO) has the capacity to complement other meteorological observation systems and significantly improve NWP forecast accuracy and global weather analyses.

The aim of this project is to investigate new methods for assimilating GPS RO data into NWP models for weather forecasting and climate monitoring. This study will explore new methodologies for improving the precision of temperature and moisture profiles in the troposphere. It will do this by using a combination of retrievals from GPS RO data and observations from high-resolution instruments such as the hyper-spectral Atmospheric Infrared Sounder (AIRS). The impact of different types of observations and their integration into global NWP forecast systems will be investigated within the context of one-dimensional three-dimensional and four-dimensional variational analysis frameworks.

The final aim of this project is to find the optimal combination of GPS RO data and remote sensing data required to precisely determine the atmospheric state thereby improving NWP and the accuracy of climate monitoring.

This is a joint research venture between the RMIT University SPACE Research Centre (Formally SPAN) and NOAA's World Data Centre for Meteorology.