分类： 地球科学 >> 空间物理学 提交时间： 2017-03-10
摘要： With a standard deviation as large as 2 cm, the sea state bias (SSB) has become the dominant source of error in satellite altimetry. The operational SSB correction models are two-dimensional (2-D) empirical (parametric or nonparametric) models based on the altimeter-measured wind speed (U) and significant wave height (SWH). However, these 2-D SSB models cannot entirely parameterize the range bias variability. The SSB uncertainty may be lowered through improved SSB models including additional measurable or predictable correlatives. This paper presents a method to estimate the SSB from crossover differences by using a three-dimensional (3-D) nonparametric model. The model is based on U, SWH from Jason-2 altimeter ocean observations, and the mean wave period from the European Centre for Medium-Range Weather Forecasts reanalysis project ERA-Interim (The SSB model developed with the method presented in this paper is called “3-D SSB model” and the SSB estimated with the 3-D SSB model is called “3-D SSB estimate”). Simulations indicate that the wave period can greatly affect the SSB. Evaluated by the separate annual datasets from 2009 to 2011, the 3-D SSB estimates can increase the explained variance by 1.32 cm2, or 1.15-cm RMS relative to the traditional 2-D SSB estimates based on U and SWH. Spatial evaluation of improvement shows that the 3-D SSB estimates are better than the traditional 2-D SSB estimates at all latitudes. The enhancement from 2-D to 3-D SSB estimates is of great significance to improve the precision of the altimeter product.[COMP]: Please set math TYPE gin the sentence below (40) as per the authors PDF.
分类： 地球科学 >> 空间物理学 提交时间： 2017-03-10
摘要： The sea state bias (SSB) has become the dominant source of error in satellite altimetry. The operational SSB correction models are two-dimensional (2-D) nonparametric models based on the wind speed (U) and the significant wave height (SWH) that can be directly measured by the altimeters. This paper estimates the sea state bias of HY-2A radar altimeter using a three-dimensional (3-D) nonparametric model based on SWH from HY-2A interim geophysical dataset records (IGDR), U and the mean wave period (MWP) from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis project ERA-Interim. The 3-D SSB estimates can increase the explained variance by 1.72 cm2, or 1.31 cm RMS relative to the traditional 2-D SSB estimates based on U and SWH. �2016 IEEE.
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