Impact of CYGNSS Ocean Surface Wind Speeds on Analysis and Forecasts of Hurricane Harvey and Irma (2017) with HWRF model

The launch of NASA Cyclone Global Navigation Satellite System (CYGNSS) offers a useful source of ocean surface wind data. Specifically, owing to its ability to obtain wind speeds over the inner-core regions of tropical cyclones and mesoscale convective systems, CYGNSS retrieved wind speeds can be available under all precipitation conditions and over the full dynamic range. Thus, they provide a unique dataset for improving tropical cyclone track and intensity prediction.This presentation reports current research progress on evaluating impacts of CYGNSS ocean surface winds on hurricane track and intensity forecasts with NCEP operational Hurricane Weather Research and Forecasting (HWRF) model and the GSI-based three-dimensional variational-ensemble hybrid data assimilation system. Specifically, influences of assimilation of CYGNSS retrieved wind speeds on numerical simulations of two notable hurricanes, Harvey and Irma in 2017 hurricane season are evaluated. Results show either positive and neutral impacts of CYGNSS data on prediction of these two hurricanes before they made landfalls in the US. Specifically, with the assimilation of CYGNSS, notable positive impacts are found in predicting the track of Hurricane Irma and Intensity of Hurricane Harvey at some of the forecast lead times. The maximum track error reduction could be as much as 30%, even when all other available conventional, satellite, and radar data were assimilated altogether. Additional data assimilation experiments are performed with the sensitivity of the analysis and forecast to data quality control and different strategies of assimilation. Results will be presented at the conference.