7A.4 Assimilation of CYGNSS Ocean Surface Wind Speeds with NCEP GSI-based Ensemble-Variational Data Assimilation Systems for Improved Numerical Simulations of Tropical Cyclones and Convective Systems

Tuesday, 17 April 2018: 2:15 PM
Masters E (Sawgrass Marriott)
Zhiqiang Cui, Univ. of Utah, Salt Lake City, UT; and Z. Pu, V. Tallapragada, C. Ruf, and R. Atlas

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 core regions of tropical cyclones and mesoscale convective systems, CYGNSS provides unique data for improving tropical convective weather prediction. This presentation reports recent research progress on evaluating impacts of CYGNSS ocean surface winds on hurricane and tropical weather forecasting within NCEP operational Hurricane Weather Research and Forecasting (HWRF) model and the Global Forecast System (GFS) model. The NCEP operational gridpoint statistical interpolation (GSI)-based hybrid 3D-EnVar, and 4D-EnVar data assimilation systems are used. Case studies with the tropial cyclone cases in 2017 hurricane seaon with HWRF model and tropical convection cases with GFS model will be presented. The data impacts, issues related to data quality control, and strategies of the proper assimilation of the data will be addressed.
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