How Does Assimilating a Large Commercial GNSS RO Dataset Impact HAFS Hurricane Forecasts? An Evaluation in Support of the ROMEX Experiment

Abstract. While Global Navigation Satellite System (GNSS) radio occultation (RO) data assimilation improves tropical cyclone (TC) intensity forecasts, the scaling of these impacts with RO observation volume remains unclear. This observing system experiment (OSE) study evaluates the impact of assimilating the large commercial GNSS RO profile dataset from the Radio Occultation Modeling Experiment (ROMEX) on 84 Hurricane Analysis and Forecast System (HAFS) model forecasts of four 2022 Atlantic hurricanes. The ROMEX dataset contains about 20,000 daily global Spire and PlanetiQ profiles, which is roughly triple the volume of government-provided RO data that the National Centers for Environmental Prediction (NCEP) assimilated operationally in 2022. Compared to a Control experiment that uses only operational RO data, assimilating ROMEX data together with operational RO profiles in HAFS yields ~ 5–15 % relative skill improvement in minimum central sea-level pressure (P_MIN) absolute intensity forecast errors in short-range forecasts, and it nearly eliminates a ~ 2–3 hPa P_MIN over-intensification bias in medium-to-long range forecasts. Additionally, ROMEX commercial RO data assimilation reduces HAFS temperature and water vapor errors in the middle-to-upper troposphere. A sensitivity experiment shows that lower-tropospheric RO data assimilated below the 5-km impact height provide a substantial contribution to ROMEX forecast improvements relative to Control. These results demonstrate that quadrupling the volume of assimilated GNSS RO data yields a meaningful positive impact on regional model TC forecasts.