scholarly journals Improving Nonparametric Estimates of the Sea State Bias in Radar Altimeter Measurements of Sea Level

2002 ◽  
Vol 19 (10) ◽  
pp. 1690-1707 ◽  
Author(s):  
Philippe Gaspar ◽  
Sylvie Labroue ◽  
Françoise Ogor ◽  
Guillaume Lafitte ◽  
Laurence Marchal ◽  
...  
2004 ◽  
Vol 27 (3-4) ◽  
pp. 453-481 ◽  
Author(s):  
SYLVIE LABROUE ◽  
PHILIPPE GASPAR ◽  
JOEL DORANDEU ◽  
OZ ZANIFé ◽  
F. MERTZ ◽  
...  

2020 ◽  
Vol 12 (15) ◽  
pp. 2496
Author(s):  
Lin Ren ◽  
Jingsong Yang ◽  
Xiao Dong ◽  
Yunhua Zhang ◽  
Yongjun Jia

In this study, we performed preliminary comparative evaluation and correction of two-dimensional sea surface height (SSH) data from the Chinese Tiangong-2 Interferometric Imaging Radar Altimeter (InIRA) with the goal of advancing its retrieval. Data from the InIRA were compared with one-dimensional SSH data from the traditional altimeters Jason-2, Saral/AltiKa, and Jason-3. Because the sea state bias (SSB) of distributed InIRA data has not yet been considered, consistency was maintained by neglecting the SSB for the traditional altimeters. The results of the comparisons show that the InIRA captures the same SSH trends as those obtained by traditional altimeters. However, there is a significant deviation between InIRA and traditional altimeter SSHs; consequently, systematic and parametric biases were analyzed. The parametric bias was found to be related to the incidence angles and a significant wave height. Upon correcting the two biases, the standard deviation significantly reduced to 8.1 cm. This value is slightly higher than those of traditional altimeters, which typically have a bias of ~7.0 cm. The results indicate that the InIRA is promising in providing a wide swath of SSH measurements. Moreover, we recommend that the InIRA retrieval algorithm should consider the two biases to improve SSH accuracy.


2017 ◽  
Vol 36 (9) ◽  
pp. 108-113 ◽  
Author(s):  
Hongli Miao ◽  
Yujie Jing ◽  
Yongjun Jia ◽  
Mingsen Lin ◽  
Guoshou Zhang ◽  
...  

Author(s):  
Yao Chen ◽  
Xiaoqing Wang ◽  
Mo Huang ◽  
Jin Feng ◽  
Haifeng Huang ◽  
...  

2019 ◽  
Vol 11 (10) ◽  
pp. 1176
Author(s):  
Yongcun Cheng ◽  
Qing Xu ◽  
Le Gao ◽  
Xiaofeng Li ◽  
Bin Zou ◽  
...  

Sea State Bias (SSB) contributes to global mean sea level variability and it needs cm-level range adjustment due to the instrumental drift over time. To investigate its variations and correct the global and regional sea level trend precisely, we calculate the temporal and spatial variability of the SSB correction in TOPEX, Jason-1, Jason-2 and Jason-3 missions, separately, as well as in the combined missions over the period 1993–2017. The long-term trend in global mean operational 2D non-parametric SSB correction is about −0.03 ± 0.03 mm/yr, which accounts for 1% of current global mean sea level change rate during 1993–2016. This correction contributes to sea level change rates of −1.27 ± 0.21 mm/yr and −0.26 ± 0.13 mm/yr in TOPEX-A and Jason-2 missions, respectively. The global mean SSB varies up to 7–10 mm during the very strong ENSO events in 1997–1998 and 2015–2016. Furthermore, the TOPEX SSB trend, which is consistent with recently reported sea level trend drift during 1993–1998, may leak into the determined global sea level trend in the period. Moreover, the Jason-1/2 zonal SSB variability is highly correlated with the significant wave height (SWH). On zonal average, SSB correction causes about 1% uncertainty in mean sea level trend. At high SWH regions, the uncertainties grow to 2–4% near the 50°N and 60°S bands. This should be considered in the study of regional sea level variability.


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