Ocean surface wind vectors (OVW) from scatterometers have been proved to be of great benefit to marine weather analysis and numerical model prediction. Conventional single-frequency scatterometers are capable to measure substantially accurate wind fields in clear atmospheric conditions, whereas winds obtained in marine extreme weather conditions are not so satisfying due to the high wind speed saturation effect and the rain perturbation. Therefore, a dualfrequency wind field measuring radar (WIFIR) to be onboard FengYun-3E is being predesigned to obtain relatively accurate wind fields in all weather conditions, which will compensate for the single-frequency shortcomings. The purpose of this study was to investigate the potential ability of WIFIR to measure OVW in tropical cyclones. A high-fidelity forward model was developed to simulate the sea surface normalize radar cross sections (NRCS) measured by WIFIR. The wind and rain rate fields used to drive the model are generated by UWNMS cloud model for Hurricane Ivan in 2004. High-wind GMFs and a theoretical rain model, which includes attenuation and volume scattering effect, have been utilized to describe the forward model. Based on the simulation results, the impact of rain on radar measurements and a dual-frequency retrieval algorithm were studied. The dual-frequency method was shown to have the ability to obtain information of rain rates up to 30mm/hr, and acquire more accurate wind vectors than single-frequency measurements. This method will be more effective to improve wind retrieval accuracy in tropical cyclones with the synchronous observation of microwave humidity sounder (MWHS) aboard FY-3 satellite.

Date Published: 19 November 2014
PDF: 7 pages
Proc. SPIE 9264, Earth Observing Missions and Sensors: Development, Implementation, and Characterization III, 92641G (19 November 2014); doi: 10.1117/12.2068803

Published in SPIE Proceedings Vol. 9264:
Earth Observing Missions and Sensors: Development, Implementation, and Characterization III
Xiaoxiong Xiong; Haruhisa Shimoda, Editor(s)