Recent Advances in GNSS-RO Technology and Their Potential Impacts on Operational Weather Forecasting

Atmospheric profiles obtained using Global Navigation Satellite System Radio Occultation (GNSS-RO) measurements have become a vital observational dataset assimilated into numerical weather prediction (NWP) models for operational forecasts. Low-orbit earth (LEO) satellites equipped with GPS receivers take advantage of the optical effects introduced by the atmosphere on the radio signals transmitted by the GPS, and more recently, GNSS satellites. The accuracy, precision, and high vertical resolution of the measurements, as well as the global coverage provided by many satellite constellations, make them ideal for inclusion in NWP. In recent years, significant advances have been made in both GNSS receiver technology that have implications for GNSS-RO observations.

This talk outlines recent advances and explores their potential impacts on operational NWP capabilities. First, new GNSS constellations, including GLONASS, Galileo, and BeiDou, provide many more opportunities for GNSS-RO events with significant increase in sampling with global coverage. Also, the GPS satellites now include new, modernized civil signals that are being rolled out with each new block of GPS satellites. The next generation of GNSS receivers, such as the TriG receiver developed by the Jet Propulsion Laboratory, have the ability to receive many of the signals simultaneously. Additional advances, such as beam-steering technology and improved modeling for tracking, allow for enhanced signal to noise ratio, potentially resulting in more usable GNSS-RO profiles penetrating deeper into the troposphere. Finally, new missions offer improved global coverage and new opportunities to improve NWP. Polar orbiting satellites, like MetOp, complement the low latitude LEO coverage of constellations like COSMIC-2a. Research based missions, such as the Spanish low Earth orbiter for Earth Observation PAZ, explore the potential benefits of previously unutilized properties of the GNSS signals, e.g. the polarization, for new and expanded applications including detecting precipitation in addition to temperature profiles. It is expected that these advances in GNSS-RO will significantly improve the numerical weather forecasts.