Joint Assimilation of TROPICS and CYGNSS Satellite Data for Improved Numerical Prediction of Tropical Cyclones

Recent NASA Smallsats missions, namely Cyclone Global Navigation Satellite System (CYGNSS) and Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS), are dedicated to enhancing tropical cyclone prediction through observations of the cyclone's inner core and environment. Through advanced data assimilation methods and state-of-the-art numerical weather prediction models, this study conducts comprehensive numerical simulations and data assimilation experiments to assess the impact of CYGNSS and TROPICS data on predicting tropical cyclones.

Using the NCEP GSI-based 3DEnVAR data assimilation system, recent numerical experiments have demonstrated positive effects on tropical cyclone prediction by assimilating TROPICS Pathfinder satellite-derived temperature and moisture profiles, as well as CYGNSS-derived ocean surface winds. Compared to control simulations that only assimilate conventional observations, the inclusion of CYGNSS ocean surface winds in the data assimilation system improves the hurricane's inner-core structure and enhances the surface fluxes associated with tropical cyclones. Meanwhile, the incorporation of TROPICS temperature profiles significantly impacts hurricane track prediction, while the TROPICS moisture profile notably influences the structure of precipitation. Remarkably, combining both CYGNSS and TROPICS data in data assimilation results in the most accurate prediction of tropical cyclones.

During the presentation, detailed results from Hurricane Ida (2021) and recent hurricanes will be emphasized, along with the recent progress made with updated TROPICS data products. The error characteristics of the data, their influence on data assimilation results, and strategies for optimal assimilation of both types of satellite data will be discussed.