首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Deriving Changjiang coastal zone wind from C-band SAR and its application to salinity simulation
Authors:Lihua Wang  Yunxuan Zhou  Jianrong Zhu  Fang Shen  Bo Tian
Institution:1. State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai, 200062, China
Abstract:Wind plays an important role in hydrodynamic processes such as the expansion of Changjiang (Yangtze) River Diluted Water (CDW), and shelf circulation in the Changjiang estuary. Thus, it is essential to include wind in the numerical simulation of these phenomena. Synthetic aperture radar (SAR) with high resolution and wide spatial coverage is valuable for measuring spatially inhomogeneous ocean surface wind fields. We have collected 87 ERS-2 SAR images with wind-induced streaks that cover the Changjiang coastal area, to verify and improve the validity of wind direction retrieval using the 2D fast Fourier transform method. We then used these wind directions as inputs to derive SAR wind speeds using the C-band model. To demonstrate the applicability of the algorithms, we validated the SAR-retrieved wind fields using QuikSCAT measurements and the atmospheric Weather Research Forecasting model. In general, we found good agreement between the datasets, indicating the reliability and applicability of SAR-retrieved algorithms under different atmospheric conditions. We investigated the main error sources of this process, and conducted sensitivity analyses to estimate the wind speed errors caused by the effect of speckle, uncertainties in wind direction, and inaccuracies in the normalized radar cross section. Finally, we used the SAR-retrieved wind fields to simulate the salinity distribution off the Changjiang estuary. The findings of this study will be valuable for wind resource assessment and the development of future numerical ocean models based on SAR images.
Keywords:synthetic aperture radar(SAR)  Changjiang estuary  fast Fourier transformation(FFT)  C-band model(CMOD)  weather research forecasting model(WRF)
本文献已被 CNKI 维普 SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号