A New Method for Radar Altimeter Sea State Bias Estimation Based on Crossover Data and Three-dimensional Nonparametric Model
JIANG Maofei①②③ XU Ke①② LIU Yalong④ WANG Lei①②
①(Key Laboratory of Microwave Remote Sensing, Chinese Academy of Sciences, Beijing 100190, China) ②(National Space Science Center, Chinese Academy of Sciences, Beijing 100190, China) ③(University of Chinese Academy of Sciences, Beijing 100049, China) ④(Yantai Marine Environmental Monitoring Center Station, State Oceanic Administration, Yantai 264000, China)
The Sea State Bias (SSB) is an important source of error in satellite altimetry. Operational SSB correction models are based on the altimeter-measured wind speed (U) and Significant Wave Height (SWH). This paper presents a new method to estimate the SSB from the crossover differences using a three-dimensional nonparametric model based on U, SWH, and the Mean Wave Period (MWP). Evaluated by the separate annual data sets from 2009 to 2011, the SSB values estimated with the presented method can decrease the variance of the crossover Sea Surface Height (SSH) differences by 1.64 cm2, or 1.28 cm RMS, and decrease the variance of the Sea Level Anomalies (SLA) by 0.92 cm2, or 0.96 cm RMS in comparison to the SSB values in the Geophysical Data Records (GDR) of Jason-2. It is of great significance for improving the precision of altimeter products.
蒋茂飞,许可,刘亚龙,王磊. 基于交叉点数据和三维非参数模型的雷达高度计海况偏差估计方法[J]. 电子与信息学报, 2016, 38(11): 2731-2738.
JIANG Maofei, XU Ke, LIU Yalong, WANG Lei. A New Method for Radar Altimeter Sea State Bias Estimation Based on Crossover Data and Three-dimensional Nonparametric Model. JEIT, 2016, 38(11): 2731-2738.
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