Impact of CYGNSS Data on Tropical Cyclone Analysis and Forecasts Using the Operational HWRF

The NASA CYclone Global Navigation Satellite System (CYGNSS), launched in December 2016, is a constellation of micro-satellites that utilizes reflected Global Positioning System (GPS) signals to retrieve ocean surface wind speed. The eight CYGNSS receivers are in a common, low-inclination angle orbit, resulting in more thorough spatial sampling and improved sampling intervals over tropical cyclones than is possible with current spaceborne scatterometer and passive microwave sensor platforms. Furthermore, CYGNSS retrieves wind speed under all precipitation conditions, and over a large range of wind speeds in and surrounding tropical cyclones. This study quantifies the impact of assimilating CYGNSS data on tropical cyclone analyses and forecasts, using a version of the 2017 operational Hurricane Weather and Research Forecast (HWRF) model. Using the Hybrid 3d-Variational/Ensemble Kalman Filter data assimilation system in the Gridpoint Statistical Interpolation (GSI) framework, the impacts of the CYGNSS data on 6-hourly analyses and 5-day HWRF forecasts of significant tropical cyclones will be quantified.