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

摘要

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.%海况偏差(Sea State Bias,SSB)是雷达高度计测量海面高度的重要误差源.目前,业务化运行的雷达高度计的海况偏差校正都是采用基于风速(U)和有效波高(SWH)的2维经验模型方法,其海况偏差校正不确定度约为2 cm.该文提出一种基于交叉点数据和3维非参数模型的海况偏差估计方法,该方法利用星下交叉点数据,采用基于U,SWH以及平均波周期(MWP)的3维非参数模型进行海况偏差估计.该文利用这种估计方法对Jason-2卫星雷达高度计2009~2011年3年的数据进行了处理,将处理结果与Jason-2卫星高度计的地球物理数据集(Geophysical Data Records,GDR)中的海况偏差校正项进行对比,结果表明该文提出的海况偏差估计方法平均能降低1.64 cm2的交叉点海面高度不符值的方差和0.92 cm2的沿轨海面高度异常值的方差,分别对应于1.28 cm和0.96 cm的均方根(RMS)海面高度,这对于提高高度计数据产品的精度具有重要意义.