Articles | Volume 19, issue 17
https://doi.org/10.5194/amt-19-5553-2026
https://doi.org/10.5194/amt-19-5553-2026
Research article
 | 
31 Aug 2026
Research article |  | 31 Aug 2026

Impact of high-volume GNSS Radio Occultation data on the Navy's global numerical weather prediction

Hui W. Christophersen, Benjamin Ruston, and Dan Tyndall

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Cited articles

Anthes, R. A., Marquardt, C., Ruston, B., and Shao, H.: Radio Occultation Modeling Experiment (ROMEX): Determining the Impact of Radio Occultation Observations on Numerical Weather Prediction, B. Am. Meteorol. Soc., E1552–E1568, 2024. 
Aparicio, J. and Deblonde, G.: Impact of the assimilation of CHAMP refractivity profiles in Environment Canada global forecasts, Mon. Weather Rev., 136, 257–275, https://doi.org/10.1175/2007MWR1951.1, 2008. 
Baker, N., Rosmond, T., Hoppel, K., Pauley, P., Ruston, B., and Swadley, S.: The assimilation of water vapor information from satellite observations and the choice of the analysis variable, 17th Conference on Satellite Meteorology and Oceanography, Annapolis, MD, https://ams.confex.com/ams/17Air17Sat9Coas/techprogram/paper_174905.htm (last access: 2 August 2026), 2017. 
Baker, N. L., Pauley, P. M., Stone, R. E., and Langland, R. H.: Interpretation of forecast sensitivity observation impact in data denial experiments, in: Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications, vol. IV, Springer, Berlin, Germany, 2022, https://doi.org/10.1007/978-3-030-77722-7, 2022. 
Bowler, N. E., Zhang, H., Anlauf, H., Aparicio, J. M., Christophersen, H. W., Kim, E.-H., Li, X., Liu, Y., Lonitz, K., Murakami, Y., Raspaud, D., and Ruston, B.: Intercomparison of GNSS-RO Quality Control Checks in NWP. Part I: Survey of Methods, J. Atmos. Ocean. Tech., 43, 701–712, 2026. 
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Short summary
This study examined whether adding large volumes of satellite-based atmospheric data can improve weather forecasts in a Navy model. Using a series of controlled experiments, we tested different ways of incorporating the data. Simply adding it introduced biases, but adjusting how the data were used led to clear improvements. All missions contributed positively, with Spire providing the largest total benefit and COSMIC-2 the highest impact per observation.
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