Using Radio Occultation Data for Atmospheric Numerical Weather Prediction, Climate Sciences, and Atmospheric Studies: Recent Results from COSMIC-2 and Commercial RO Data at NESDIS/STAR

GNSS (Global Navigation Satellite System) Radio Occultation (RO) is one of the long-term core observables in NOAA. Similar to the NOAA Infrared (IR) and Microwave (WV), RO data collected from multiple RO missions (i.e., Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2) and NOAA-purchased Commercial RO data (i.e., Spire and PlanetiQ)) and partners’ missions (i.e., Metop -B,-C, and KOMPSAT-5, etc.), are assimilated into National Center for Environmental Prediction (NCEP) through their data assimilation system. The role of the STAR GNSS RO program is to fulfill NESDIS's need for in-house RO data processing, enterprise GNSS RO algorithm development, science development, support, archive, stewardship for the operational processing, user support, and science applications. We independently process the data to understand the data’s characteristics and assess their quality fully. In the past few years, we have developed the capability to use the raw RO measurements and satellite information to derive precise orbit determination (POD) for low Earth orbit (LEO) satellites, excess phase (L1 data), bending angles, refractivity, temperature and water vapor profiles (L2 data). We also released our processed data products from multiple RO missions to the RO and science communities at https://gpsmet.umd.edu/star_gnssro/download_star.html. We use two different processing approaches (the STAR ROPP inversion and STAR Full Spectrum Inversion) to derive the RO data products to demonstrate the structure uncertainty of each RO mission and identify the potential errors either in the processing or from the instruments.

In this study, we will present our analysis to answer the following questions:

1. Why did high SNR GNSS RO data not help improve the impacts on NWP, especially in the lower troposphere?
2. Why did the high SNR GNSS RO data not lead to enhanced retrieval results and smaller retrieval uncertainty?
3. Do Spire and COSMIC-2 data have an impact on tropical cyclone forecasts? and
4. Can we determine whether the RO data improves water vapor forecasts, especially in the lower troposphere?

The STAR RO derived RO products are used to not only generate the L1 and L2 we also generate the monthly mean climatology (MMC, L3) data products, including the global planetary boundary layer MMC, the temperature in the upper troposphere and low stratosphere (UTLS) MMC, and others. I will also highlight the current studies conducted at STAR using GNSS RO measurements for atmospheric applications and climate diagnostics and monitoring.

Disclaimer: The scientific results, conclusions, and views or opinions expressed herein are those of the author(s) and do not necessarily reflect those of NOAA or the Department of Commerce.