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1. Estimating Individual Radio Occultation Uncertainties Using the Observations and Environmental Parameters

   https://doi.org/10.1175/JTECH-D-23-0029.1  

   Sjoberg, Jeremiah; Anthes, Richard; Zhang, Hailing (November 2023, Journal of Atmospheric and Oceanic Technology)

   Abstract Estimation of uncertainties (random error statistics) of radio occultation (RO) observations is important for their effective assimilation in numerical weather prediction (NWP) models. Average uncertainties can be estimated for large samples of RO observations and these statistics may be used for specifying the observation errors in NWP data assimilation. However, the uncertainties of individual RO observations vary, and so using average uncertainty estimates will overestimate the uncertainties of some observations and underestimate those of others, reducing their overall effectiveness in the assimilation. Several parameters associated with RO observations or their atmospheric environments have been proposed to estimate individual RO errors. These include the standard deviation of bending angle (BA) departures from either climatology in the upper stratosphere and lower mesosphere (STDV) or the sample mean between 40 and 60 km (STD4060), the local spectral width (LSW), and the magnitude of the horizontal gradient of refractivity (|∇_HN|). In this paper we show how the uncertainties of two RO datasets, COSMIC-2 and Spire BA, as well as their combination, vary with these parameters. We find that the uncertainties are highly correlated with STDV and STD4060 in the stratosphere, and with LSW and |∇_HN| in the lower troposphere. These results suggest a hybrid error model for individual BA observations that uses an average statistical model of RO errors modified by STDV or STD4060 above 30 km, and LSW or |∇_HN| below 8 km. Significance StatementThese results contribute to the understanding of the sources of uncertainties in radio occultation observations. They could be used to improve the effectiveness of these observations in their assimilation into numerical weather prediction and reanalysis models by improving the estimation of their observational errors. 

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2. The Impact of Assimilating GNSS-RO Observations on HAFS Tropical Cyclone Forecasts from the 2022 Atlantic Hurricane Season

   https://doi.org/10.1175/WAF-D-25-0045.1  

   Johnston, Benjamin R; Cucurull, Lidia; Anthes, Richard; Mueller, Michael J; Lim, Agnes_H N (December 2025, Weather and Forecasting)

   Abstract Global Navigation Satellite System radio occultation (GNSS-RO) data have become an essential part of observational assimilation in numerical weather prediction (NWP) models due to their high accuracy and precision, insensitivity to clouds and precipitation, high vertical resolution, and a considerable increase in sampling density in recent years. Their impact has been demonstrated in many global models, as well as in several regional models. In this study, we show the impact of assimilating GNSS-RO bending angle (BA) observations on 10 tropical cyclone (TC) forecasts from the 2022 Atlantic hurricane season using the Hurricane Analysis and Forecast System (HAFS) model. Our evaluation shows that track forecasts are improved considerably (∼15%–20%) after assimilating RO BAs, mainly through global model forecasts as initial and boundary conditions for HAFS, and these improvements are especially evident at longer forecast lead times. A case study of Hurricane Ian, a category 5 hurricane, which made landfall along the western Florida coast, showed greatly improved landfall prediction 3–5 days before landfall after assimilating RO BAs due to improved forecasts of the synoptic-scale steering flow over the region. Further study after adding many additional commercial RO profiles for assimilation through the Radio Occultation Modeling Experiment (ROMEX) showed 25%–30% improvements to TC intensity forecasts at longer lead times, albeit utilizing fewer TCs in the sample. For example, Hurricane Ian showed HAFS accurately forecasting maximum wind speeds, including its rapid intensification, 2–4 days in advance due to the improved representation of midlevel moisture in the vicinity of Ian. These results emphasize the benefits that RO can provide to both TC track and intensity forecasts. Significance StatementThe purpose of this study is to understand how utilizing larger numbers (relative to what is operationally available) of radio occultation (RO) satellite observations in a hurricane model can impact tropical cyclone forecasts. It is important to determine the value of these additional data for possible commercial RO data purchases as well as developing future RO satellite missions. Our results show improvements to both track and intensity forecasts for tropical cyclones after using these additional data in the model. 

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3. Radio Occultation Modeling Experiment (ROMEX): Determining the impact of radio occultation observations on numerical weather prediction

   https://doi.org/10.1175/BAMS-D-23-0326.1  

   Anthes, Richard A; Marquardt, Christian; Ruston, Benjamin; Shao, Hui (June 2024, Bulletin of the American Meteorological Society)

   Abstract The international radio occultation (RO) community is conducting a collaborative effort to explore the impact of a large number of RO observations on numerical weather prediction (NWP). This effort, the Radio Occultation Modeling Experiment (ROMEX), has been endorsed by the International Radio Occultation Working Group, a scientific working group under the auspices of the Coordination Group for Meteorological Satellites (CGMS). ROMEX seeks to inform strategies for future RO missions and acquisitions. ROMEX is planned to consist of at least one three-month period during which all available RO data are collected, processed, archived, and made available to the global community free of charge for research and testing. Although the primary purpose is to test the impact of varying numbers of RO observations on NWP, the three months of RO observations during the first ROMEX period (ROMEX-1, September-November 2022) will be a rich data set for research on many atmospheric phenomena. The RO data providers have sent their data to EUMETSAT for processing. The total number of RO profiles averages between 30,000 and 40,000 per day for ROMEX-1. The processed data (phase, bending angle, refractivity, temperature, and water vapor) will be distributed to ROMEX participants by the Radio Occultation Meteorology Satellite Applications Facility (ROM SAF). The data will also be processed independently by the UCAR COSMIC Data Analysis and Archive Center (CDAAC) and available via ROM SAF. The data are freely available to all participants who agree to the conditions that the providers be acknowledged and the data are not used for commercial or operational purposes. 

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4. Sub‐Seasonal Impact of GNSS Radio Occultation Data

   https://doi.org/10.1029/2025GL116068  

   Lonitz, K; Vitart, F; Healy, S B; Fu, Qiang (November 2025, Geophysical Research Letters)

   Abstract This study investigates for the first time whether the assimilation of the Global Navigation Satellite System Radio occultation (GNSS‐RO) data has a significant impact on the European Centre for Medium‐Range Weather Forecasts sub‐seasonal forecasts. The impact was measured by running two large sets of 32‐day ensemble re‐forecasts over the extended winter periods from 2020 to 2023 which were initialized from an analysis with or without GNSS‐RO assimilated. Results indicate a difference of 4 m/s in zonal wind at the equator in the two analyses and a statistically significant improvement in the reforecast skill scores up to week 4 in the stratosphere, particularly over the Tropics when assimilating GNSS‐RO. The impact in the troposphere is generally negligible. However, the amplitude of the Madden Julian Oscillation (MJO) is significantly stronger during the first 2 weeks when the reforecasts are initialized from the analysis with GNSS‐RO assimilated, suggesting a potential link between MJO prediction and the initialization of the stratosphere. 

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5. Evaluation of biases and uncertainties in ROMEX radio occultation observations

   https://doi.org/10.5194/egusphere-2025-2089  

   Anthes, Richard; Sjoberg, Jeremiah; Starr, Jon; Zeng, Zhen (May 2025, EGUsphere)

   Abstract. The Radio Occultation Modeling EXperiment (ROMEX) is an international collaboration to test the impact of varying numbers of radio occultation (RO) profiles in operational numerical weather prediction (NWP) models. An average of 35,000 RO profiles per day for September–November 2022 from 13 different missions are being used in experiments at major NWP centers. This paper evaluates properties of ROMEX data, with emphasis on the three largest datasets: COSMIC-2 (C2), Spire, and Yunyao. The penetration rates (percent of profiles reaching different levels above the surface) of most of the ROMEX datasets are similar, with more than 80 % of all occultations reaching 2 km or lower and more than 50 % reaching 1 km or lower. The relative uncertainties of the C2, Spire, and Yunyao bending angles and refractivities are estimated using the three-cornered hat method. They are similar on the average in the region of overlap (45° S–45° N). Larger uncertainties occur in the tropics compared to higher latitudes below 20 km. Relatively small variations in longitude exist. The assimilation of ROMEX data caused small degradations in biases in several NWP models. We investigate biases in the observations by comparing them to each other and to models. C2 bending angles appear to be biased by about +0.1–0.15 % compared to Spire and other ROMEX data. These apparent biases, some of which are representativeness or sampling differences, are caused by the different orbits of C2 and other ROMEX missions around the non-spherical Earth and the associated varying radii of curvature (radius of a sphere that best fits the Earth’s surface curvature at a given location and orientation of the RO occultation plane and is used in the RO BA retrievals). 

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