Abstract As global climate change intensifies, hurricane‐induced storm surges are becoming more frequent and severe. While Global Navigation Satellite System‐Interferometric Reflectometry (GNSS‐IR) is widely used to monitor sea level variations, its capability to detect rapid and extreme events remains limited. We propose a short‐time feature extraction GNSS‐IR strategy constrained by astronomical tidal models. By analyzing the continuity and stability of spectral reflections, the method identifies coherent signals from transient sea level changes and effectively addresses the typical 10–20 min temporal bias introduced by the static‐surface assumption. Validation results show that the method achieves a long‐term monitoring accuracy of 4.6 cm over 1 year, and maintains a stable accuracy of approximately 10 cm during storm surges. It also achieves 4.0 cm accuracy over 12‐hr period and enables short‐term sea level prediction with an accuracy of 7 cm. These findings highlight the potential of near‐shore GNSS‐IR to strengthen tide gauge networks and marine assessments.
Chang et al. (Fri,) studied this question.