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.

Our early studies were conducted by using the NCEP GSI-based 3DEnVAR data assimilation system. 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 into the mesoscale community WRF model. Results with Hurricane Ida indicated that: 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.

Recent studies have been conducted with the NCEP Hurricane Analysis and Forecast System (HAFS). In addition to assimilating TROPICS-derived L2 retrieved products, efforts have been started to assimilate TROPICS satellite radiances. Recent results and updates will be included in the presentation.