Assimilation of CYGNSS satellite-derived ocean surface winds and surface heat fluxes into NCEP HAFS system

Hurricane forecasts, especially predicting hurricane rapid intensification and intensity change, have been a challenge in research and operation. This is largely due to a lack of observations over the ocean and our inability to obtain inner-core observations. The Cyclone Global Navigation Satellite System (CYGNSS) is a passive remote sensing satellite constellation that can obtain inner-core observations from tropical cyclones. This study examines the effects of assimilating NASA CYGNSS satellite-derived ocean surface winds and surface heat fluxes into NCEP's operational Hurricane Analysis and Forecast System (HAFS) using the operational Gridpoint Statistical Interpolation (GSI)-based four-dimensional ensemble-variational (4DEnVAR) data assimilation system. Prior research has shown that assimilating CYGNSS ocean surface winds into the hurricane weather research and forecasting (HWRF) model improves hurricane inner-core structure and wind field, thereby positively influencing both track and intensity forecasts. This study will transition CYGNSS ocean surface wind data assimilation from HWRF to HAFS. In addition, new development will be conducted to assimilate CYGNSS satellite-derived surface heat fluxes. The effects of assimilating ocean surface winds and surface heat fluxes will be examined together and separately. The National Hurricane Center (NHC) best-track data and available satellite and radar data will be used to verify the impact of assimilation experiments. Ultimately, we will analyze the numerical results to understand the role of surface heat fluxes and ocean surface winds on tropical cyclone evolution and intensity changes.