Impact of GNSS RO data on the prediction of atmospheric river events: A ROMEX experiment

Lin, H., Kuo, Y., Zhang, H., Braun, J. J., Liu, Z.. (2026). Impact of GNSS RO data on the prediction of atmospheric river events: A ROMEX experiment. Weather and Forecasting, doi:https://doi.org/10.1175/waf-d-25-0151.1

Title Impact of GNSS RO data on the prediction of atmospheric river events: A ROMEX experiment
Genre Article
Author(s) Hsiao-Chun Lin, Ying-Hwa Kuo, Hailing Zhang, John J. Braun, Zhiquan Liu
Abstract The assimilation of Global Navigation Satellite Systems (GNSS) radio occultation (RO) data has been shown to improve the prediction of atmospheric rivers (ARs), which are key drivers of heavy precipitation along the U.S. West Coast. This study builds on prior research by evaluating the impact of the Radio Occultation Modeling Experiment (ROMEX) dataset, which provides approximately 36 000 RO profiles per day, tripling the volume of the current operational RO dataset. Using the Weather Research and Forecasting Data Assimilation (WRFDA) system, we assimilate GNSS RO observations for the primary AR event that took place between 29 and 31 October 2022, as well as a preceding AR event. Results show that the denser RO dataset improves forecasts of the large-scale atmospheric state in the lower troposphere, integrated vapor transport (IVT), AR duration, the timing of peak moisture transport, and quantitative precipitation. These improvements showcase the value of increased RO data for better characterizing AR structure and improving its prediction.
Publication Title Weather and Forecasting
Publication Date Mar 1, 2026
Publisher's Version of Record https://doi.org/10.1175/waf-d-25-0151.1
OpenSky Citable URL https://n2t.net/ark:/85065/d7z60tkf
OpenSky Listing View on OpenSky
MMM Affiliations PARC

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