Segmented Parametric Estimates of the Sea State Bias for Radar Altimeters

2016 ◽  
Vol 4 (1) ◽  
pp. 10-15
Author(s):  
Guoshou Zhang ◽  
Hongli Miao ◽  
Guizhong Wang ◽  
Yingting Guo ◽  
Yujie Jing
Keyword(s):  
Sea State ◽  
Sea State Bias

scholarly journals Weakly nonlinear theory and sea state bias estimations

1999 ◽  
Vol 104 (C4) ◽  
pp. 7641-7647 ◽  
Author(s):  
Tanos Elfouhaily ◽  
Donald Thompson ◽  
Douglas Vandemark ◽  
Bertrand Chapron
Keyword(s):  
Nonlinear Theory ◽  
Sea State ◽  
Weakly Nonlinear ◽  
Weakly Nonlinear Theory ◽  
Sea State Bias

Improved Sea State Bias Estimation for Altimeter Reference Missions With Altimeter-Only Three-Parameter Models

2019 ◽  
Vol 57 (3) ◽  
pp. 1448-1462 ◽  
Author(s):  
Nelson Pires ◽  
M. Joana Fernandes ◽  
Christine Gommenginger ◽  
Remko Scharroo
Keyword(s):  
Bias Estimation ◽  
Sea State ◽  
Sea State Bias

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 ◽  
...  
Keyword(s):  
Sea Level ◽  
Radar Altimeter ◽  
Sea State ◽  
Sea State Bias ◽  
Nonparametric Estimates

scholarly journals Sea State Bias of ICESat in the Subarctic Seas

2018 ◽  
Vol 15 (8) ◽  
pp. 1144-1148 ◽  
Author(s):  
J. Morison ◽  
R. Kwok ◽  
S. Dickinson ◽  
D. Morison ◽  
C. Peralta-Ferriz ◽  
...  
Keyword(s):  
Sea State ◽  
Sea State Bias

scholarly journals Preliminary Evaluation and Correction of Sea Surface Height from Chinese Tiangong-2 Interferometric Imaging Radar Altimeter

2020 ◽  
Vol 12 (15) ◽  
pp. 2496
Author(s):  
Lin Ren ◽  
Jingsong Yang ◽  
Xiao Dong ◽  
Yunhua Zhang ◽  
Yongjun Jia
Keyword(s):  
Sea Surface Height ◽  
Sea Surface ◽  
Retrieval Algorithm ◽  
Preliminary Evaluation ◽  
Interferometric Imaging ◽  
Radar Altimeter ◽  
Sea State ◽  
Imaging Radar ◽  
Sea State Bias ◽  
Wide Swath

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.

Nonparametric Estimates of the Sea State Bias for the Jason-1 Radar Altimeter

2004 ◽  
Vol 27 (3-4) ◽  
pp. 453-481 ◽  
Author(s):  
SYLVIE LABROUE ◽  
PHILIPPE GASPAR ◽  
JOEL DORANDEU ◽  
OZ ZANIFé ◽  
F. MERTZ ◽  
...  
Keyword(s):  
Radar Altimeter ◽  
Sea State ◽  
Sea State Bias ◽  
Nonparametric Estimates

Validation of Sea Surface Wind Speeds from Satellite Altimeters and Relation to Sea State Bias

2018 ◽  
Vol 39 (2) ◽  
pp. 139-153 ◽  
Author(s):  
Do-Young Choi ◽  
◽  
Hye-Jin Woo ◽  
Kyung-Ae Park ◽  
Do-Seong Byun ◽  
...  
Keyword(s):  
Surface Wind ◽  
Sea Surface ◽  
Sea State ◽  
Wind Speeds ◽  
Sea Surface Wind ◽  
Sea State Bias
Sign in / Sign up

Export Citation Format

Share Document